nodeAgg.c

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/*-------------------------------------------------------------------------
 *
 * nodeAgg.c
 *    Routines to handle aggregate nodes.
 *
 *    ExecAgg normally evaluates each aggregate in the following steps:
 *
 *       transvalue = initcond
 *       foreach input_tuple do
 *          transvalue = transfunc(transvalue, input_value(s))
 *       result = finalfunc(transvalue, direct_argument(s))
 *
 *    If a finalfunc is not supplied then the result is just the ending
 *    value of transvalue.
 *
 *    Other behaviors can be selected by the "aggsplit" mode, which exists
 *    to support partial aggregation.  It is possible to:
 *    * Skip running the finalfunc, so that the output is always the
 *    final transvalue state.
 *    * Substitute the combinefunc for the transfunc, so that transvalue
 *    states (propagated up from a child partial-aggregation step) are merged
 *    rather than processing raw input rows.  (The statements below about
 *    the transfunc apply equally to the combinefunc, when it's selected.)
 *    * Apply the serializefunc to the output values (this only makes sense
 *    when skipping the finalfunc, since the serializefunc works on the
 *    transvalue data type).
 *    * Apply the deserializefunc to the input values (this only makes sense
 *    when using the combinefunc, for similar reasons).
 *    It is the planner's responsibility to connect up Agg nodes using these
 *    alternate behaviors in a way that makes sense, with partial aggregation
 *    results being fed to nodes that expect them.
 *
 *    If a normal aggregate call specifies DISTINCT or ORDER BY, we sort the
 *    input tuples and eliminate duplicates (if required) before performing
 *    the above-depicted process.  (However, we don't do that for ordered-set
 *    aggregates; their "ORDER BY" inputs are ordinary aggregate arguments
 *    so far as this module is concerned.)  Note that partial aggregation
 *    is not supported in these cases, since we couldn't ensure global
 *    ordering or distinctness of the inputs.
 *
 *    If transfunc is marked "strict" in pg_proc and initcond is NULL,
 *    then the first non-NULL input_value is assigned directly to transvalue,
 *    and transfunc isn't applied until the second non-NULL input_value.
 *    The agg's first input type and transtype must be the same in this case!
 *
 *    If transfunc is marked "strict" then NULL input_values are skipped,
 *    keeping the previous transvalue.  If transfunc is not strict then it
 *    is called for every input tuple and must deal with NULL initcond
 *    or NULL input_values for itself.
 *
 *    If finalfunc is marked "strict" then it is not called when the
 *    ending transvalue is NULL, instead a NULL result is created
 *    automatically (this is just the usual handling of strict functions,
 *    of course).  A non-strict finalfunc can make its own choice of
 *    what to return for a NULL ending transvalue.
 *
 *    Ordered-set aggregates are treated specially in one other way: we
 *    evaluate any "direct" arguments and pass them to the finalfunc along
 *    with the transition value.
 *
 *    A finalfunc can have additional arguments beyond the transvalue and
 *    any "direct" arguments, corresponding to the input arguments of the
 *    aggregate.  These are always just passed as NULL.  Such arguments may be
 *    needed to allow resolution of a polymorphic aggregate's result type.
 *
 *    We compute aggregate input expressions and run the transition functions
 *    in a temporary econtext (aggstate->tmpcontext).  This is reset at least
 *    once per input tuple, so when the transvalue datatype is
 *    pass-by-reference, we have to be careful to copy it into a longer-lived
 *    memory context, and free the prior value to avoid memory leakage.  We
 *    store transvalues in another set of econtexts, aggstate->aggcontexts
 *    (one per grouping set, see below), which are also used for the hashtable
 *    structures in AGG_HASHED mode.  These econtexts are rescanned, not just
 *    reset, at group boundaries so that aggregate transition functions can
 *    register shutdown callbacks via AggRegisterCallback.
 *
 *    The node's regular econtext (aggstate->ss.ps.ps_ExprContext) is used to
 *    run finalize functions and compute the output tuple; this context can be
 *    reset once per output tuple.
 *
 *    The executor's AggState node is passed as the fmgr "context" value in
 *    all transfunc and finalfunc calls.  It is not recommended that the
 *    transition functions look at the AggState node directly, but they can
 *    use AggCheckCallContext() to verify that they are being called by
 *    nodeAgg.c (and not as ordinary SQL functions).  The main reason a
 *    transition function might want to know this is so that it can avoid
 *    palloc'ing a fixed-size pass-by-ref transition value on every call:
 *    it can instead just scribble on and return its left input.  Ordinarily
 *    it is completely forbidden for functions to modify pass-by-ref inputs,
 *    but in the aggregate case we know the left input is either the initial
 *    transition value or a previous function result, and in either case its
 *    value need not be preserved.  See int8inc() for an example.  Notice that
 *    the EEOP_AGG_PLAIN_TRANS step is coded to avoid a data copy step when
 *    the previous transition value pointer is returned.  It is also possible
 *    to avoid repeated data copying when the transition value is an expanded
 *    object: to do that, the transition function must take care to return
 *    an expanded object that is in a child context of the memory context
 *    returned by AggCheckCallContext().  Also, some transition functions want
 *    to store working state in addition to the nominal transition value; they
 *    can use the memory context returned by AggCheckCallContext() to do that.
 *
 *    Note: AggCheckCallContext() is available as of PostgreSQL 9.0.  The
 *    AggState is available as context in earlier releases (back to 8.1),
 *    but direct examination of the node is needed to use it before 9.0.
 *
 *    As of 9.4, aggregate transition functions can also use AggGetAggref()
 *    to get hold of the Aggref expression node for their aggregate call.
 *    This is mainly intended for ordered-set aggregates, which are not
 *    supported as window functions.  (A regular aggregate function would
 *    need some fallback logic to use this, since there's no Aggref node
 *    for a window function.)
 *
 *    Grouping sets:
 *
 *    A list of grouping sets which is structurally equivalent to a ROLLUP
 *    clause (e.g. (a,b,c), (a,b), (a)) can be processed in a single pass over
 *    ordered data.  We do this by keeping a separate set of transition values
 *    for each grouping set being concurrently processed; for each input tuple
 *    we update them all, and on group boundaries we reset those states
 *    (starting at the front of the list) whose grouping values have changed
 *    (the list of grouping sets is ordered from most specific to least
 *    specific).
 *
 *    Where more complex grouping sets are used, we break them down into
 *    "phases", where each phase has a different sort order (except phase 0
 *    which is reserved for hashing).  During each phase but the last, the
 *    input tuples are additionally stored in a tuplesort which is keyed to the
 *    next phase's sort order; during each phase but the first, the input
 *    tuples are drawn from the previously sorted data.  (The sorting of the
 *    data for the first phase is handled by the planner, as it might be
 *    satisfied by underlying nodes.)
 *
 *    Hashing can be mixed with sorted grouping.  To do this, we have an
 *    AGG_MIXED strategy that populates the hashtables during the first sorted
 *    phase, and switches to reading them out after completing all sort phases.
 *    We can also support AGG_HASHED with multiple hash tables and no sorting
 *    at all.
 *
 *    From the perspective of aggregate transition and final functions, the
 *    only issue regarding grouping sets is this: a single call site (flinfo)
 *    of an aggregate function may be used for updating several different
 *    transition values in turn. So the function must not cache in the flinfo
 *    anything which logically belongs as part of the transition value (most
 *    importantly, the memory context in which the transition value exists).
 *    The support API functions (AggCheckCallContext, AggRegisterCallback) are
 *    sensitive to the grouping set for which the aggregate function is
 *    currently being called.
 *
 *    Plan structure:
 *
 *    What we get from the planner is actually one "real" Agg node which is
 *    part of the plan tree proper, but which optionally has an additional list
 *    of Agg nodes hung off the side via the "chain" field.  This is because an
 *    Agg node happens to be a convenient representation of all the data we
 *    need for grouping sets.
 *
 *    For many purposes, we treat the "real" node as if it were just the first
 *    node in the chain.  The chain must be ordered such that hashed entries
 *    come before sorted/plain entries; the real node is marked AGG_MIXED if
 *    there are both types present (in which case the real node describes one
 *    of the hashed groupings, other AGG_HASHED nodes may optionally follow in
 *    the chain, followed in turn by AGG_SORTED or (one) AGG_PLAIN node).  If
 *    the real node is marked AGG_HASHED or AGG_SORTED, then all the chained
 *    nodes must be of the same type; if it is AGG_PLAIN, there can be no
 *    chained nodes.
 *
 *    We collect all hashed nodes into a single "phase", numbered 0, and create
 *    a sorted phase (numbered 1..n) for each AGG_SORTED or AGG_PLAIN node.
 *    Phase 0 is allocated even if there are no hashes, but remains unused in
 *    that case.
 *
 *    AGG_HASHED nodes actually refer to only a single grouping set each,
 *    because for each hashed grouping we need a separate grpColIdx and
 *    numGroups estimate.  AGG_SORTED nodes represent a "rollup", a list of
 *    grouping sets that share a sort order.  Each AGG_SORTED node other than
 *    the first one has an associated Sort node which describes the sort order
 *    to be used; the first sorted node takes its input from the outer subtree,
 *    which the planner has already arranged to provide ordered data.
 *
 *    Memory and ExprContext usage:
 *
 *    Because we're accumulating aggregate values across input rows, we need to
 *    use more memory contexts than just simple input/output tuple contexts.
 *    In fact, for a rollup, we need a separate context for each grouping set
 *    so that we can reset the inner (finer-grained) aggregates on their group
 *    boundaries while continuing to accumulate values for outer
 *    (coarser-grained) groupings.  On top of this, we might be simultaneously
 *    populating hashtables; however, we only need one context for all the
 *    hashtables.
 *
 *    So we create an array, aggcontexts, with an ExprContext for each grouping
 *    set in the largest rollup that we're going to process, and use the
 *    per-tuple memory context of those ExprContexts to store the aggregate
 *    transition values.  hashcontext is the single context created to support
 *    all hash tables.
 *
 *    Spilling To Disk
 *
 *    When performing hash aggregation, if the hash table memory exceeds the
 *    limit (see hash_agg_check_limits()), we enter "spill mode". In spill
 *    mode, we advance the transition states only for groups already in the
 *    hash table. For tuples that would need to create a new hash table
 *    entries (and initialize new transition states), we instead spill them to
 *    disk to be processed later. The tuples are spilled in a partitioned
 *    manner, so that subsequent batches are smaller and less likely to exceed
 *    hash_mem (if a batch does exceed hash_mem, it must be spilled
 *    recursively).
 *
 *    Spilled data is written to logical tapes. These provide better control
 *    over memory usage, disk space, and the number of files than if we were
 *    to use a BufFile for each spill.  We don't know the number of tapes needed
 *    at the start of the algorithm (because it can recurse), so a tape set is
 *    allocated at the beginning, and individual tapes are created as needed.
 *    As a particular tape is read, logtape.c recycles its disk space. When a
 *    tape is read to completion, it is destroyed entirely.
 *
 *    Tapes' buffers can take up substantial memory when many tapes are open at
 *    once. We only need one tape open at a time in read mode (using a buffer
 *    that's a multiple of BLCKSZ); but we need one tape open in write mode (each
 *    requiring a buffer of size BLCKSZ) for each partition.
 *
 *    Note that it's possible for transition states to start small but then
 *    grow very large; for instance in the case of ARRAY_AGG. In such cases,
 *    it's still possible to significantly exceed hash_mem. We try to avoid
 *    this situation by estimating what will fit in the available memory, and
 *    imposing a limit on the number of groups separately from the amount of
 *    memory consumed.
 *
 *    Transition / Combine function invocation:
 *
 *    For performance reasons transition functions, including combine
 *    functions, aren't invoked one-by-one from nodeAgg.c after computing
 *    arguments using the expression evaluation engine. Instead
 *    ExecBuildAggTrans() builds one large expression that does both argument
 *    evaluation and transition function invocation. That avoids performance
 *    issues due to repeated uses of expression evaluation, complications due
 *    to filter expressions having to be evaluated early, and allows to JIT
 *    the entire expression into one native function.
 *
 * Portions Copyright (c) 1996-2026, PostgreSQL Global Development Group
 * Portions Copyright (c) 1994, Regents of the University of California
 *
 * IDENTIFICATION
 *    src/backend/executor/nodeAgg.c
 *
 *-------------------------------------------------------------------------
 */
 
#include "postgres.h"
 
#include "access/htup_details.h"
#include "access/parallel.h"
#include "catalog/objectaccess.h"
#include "catalog/pg_aggregate.h"
#include "catalog/pg_proc.h"
#include "catalog/pg_type.h"
#include "common/hashfn.h"
#include "executor/execExpr.h"
#include "executor/executor.h"
#include "executor/nodeAgg.h"
#include "lib/hyperloglog.h"
#include "miscadmin.h"
#include "nodes/nodeFuncs.h"
#include "optimizer/optimizer.h"
#include "parser/parse_agg.h"
#include "parser/parse_coerce.h"
#include "utils/acl.h"
#include "utils/builtins.h"
#include "utils/datum.h"
#include "utils/expandeddatum.h"
#include "utils/injection_point.h"
#include "utils/logtape.h"
#include "utils/lsyscache.h"
#include "utils/memutils.h"
#include "utils/memutils_memorychunk.h"
#include "utils/syscache.h"
#include "utils/tuplesort.h"
 
/*
 * Control how many partitions are created when spilling HashAgg to
 * disk.
 *
 * HASHAGG_PARTITION_FACTOR is multiplied by the estimated number of
 * partitions needed such that each partition will fit in memory. The factor
 * is set higher than one because there's not a high cost to having a few too
 * many partitions, and it makes it less likely that a partition will need to
 * be spilled recursively. Another benefit of having more, smaller partitions
 * is that small hash tables may perform better than large ones due to memory
 * caching effects.
 *
 * We also specify a min and max number of partitions per spill. Too few might
 * mean a lot of wasted I/O from repeated spilling of the same tuples. Too
 * many will result in lots of memory wasted buffering the spill files (which
 * could instead be spent on a larger hash table).
 */
#define HASHAGG_PARTITION_FACTOR 1.50
#define HASHAGG_MIN_PARTITIONS 4
#define HASHAGG_MAX_PARTITIONS 1024
 
/*
 * For reading from tapes, the buffer size must be a multiple of
 * BLCKSZ. Larger values help when reading from multiple tapes concurrently,
 * but that doesn't happen in HashAgg, so we simply use BLCKSZ. Writing to a
 * tape always uses a buffer of size BLCKSZ.
 */
#define HASHAGG_READ_BUFFER_SIZE BLCKSZ
#define HASHAGG_WRITE_BUFFER_SIZE BLCKSZ
 
/*
 * HyperLogLog is used for estimating the cardinality of the spilled tuples in
 * a given partition. 5 bits corresponds to a size of about 32 bytes and a
 * worst-case error of around 18%. That's effective enough to choose a
 * reasonable number of partitions when recursing.
 */
#define HASHAGG_HLL_BIT_WIDTH 5
 
/*
 * Assume the palloc overhead always uses sizeof(MemoryChunk) bytes.
 */
#define CHUNKHDRSZ sizeof(MemoryChunk)
 
/*
 * Represents partitioned spill data for a single hashtable. Contains the
 * necessary information to route tuples to the correct partition, and to
 * transform the spilled data into new batches.
 *
 * The high bits are used for partition selection (when recursing, we ignore
 * the bits that have already been used for partition selection at an earlier
 * level).
 */
typedef struct HashAggSpill
{
    int         npartitions;    /* number of partitions */
    LogicalTape **partitions;   /* spill partition tapes */
    int64      *ntuples;        /* number of tuples in each partition */
    uint32      mask;           /* mask to find partition from hash value */
    int         shift;          /* after masking, shift by this amount */
    hyperLogLogState *hll_card; /* cardinality estimate for contents */
} HashAggSpill;
 
/*
 * Represents work to be done for one pass of hash aggregation (with only one
 * grouping set).
 *
 * Also tracks the bits of the hash already used for partition selection by
 * earlier iterations, so that this batch can use new bits. If all bits have
 * already been used, no partitioning will be done (any spilled data will go
 * to a single output tape).
 */
typedef struct HashAggBatch
{
    int         setno;          /* grouping set */
    int         used_bits;      /* number of bits of hash already used */
    LogicalTape *input_tape;    /* input partition tape */
    int64       input_tuples;   /* number of tuples in this batch */
    double      input_card;     /* estimated group cardinality */
} HashAggBatch;
 
/* used to find referenced colnos */
typedef struct FindColsContext
{
    bool        is_aggref;      /* is under an aggref */
    Bitmapset  *aggregated;     /* column references under an aggref */
    Bitmapset  *unaggregated;   /* other column references */
} FindColsContext;
 
static void select_current_set(AggState *aggstate, int setno, bool is_hash);
static void initialize_phase(AggState *aggstate, int newphase);
static TupleTableSlot *fetch_input_tuple(AggState *aggstate);
static void initialize_aggregates(AggState *aggstate,
                                  AggStatePerGroup *pergroups,
                                  int numReset);
static void advance_transition_function(AggState *aggstate,
                                        AggStatePerTrans pertrans,
                                        AggStatePerGroup pergroupstate);
static void advance_aggregates(AggState *aggstate);
static void process_ordered_aggregate_single(AggState *aggstate,
                                             AggStatePerTrans pertrans,
                                             AggStatePerGroup pergroupstate);
static void process_ordered_aggregate_multi(AggState *aggstate,
                                            AggStatePerTrans pertrans,
                                            AggStatePerGroup pergroupstate);
static void finalize_aggregate(AggState *aggstate,
                               AggStatePerAgg peragg,
                               AggStatePerGroup pergroupstate,
                               Datum *resultVal, bool *resultIsNull);
static void finalize_partialaggregate(AggState *aggstate,
                                      AggStatePerAgg peragg,
                                      AggStatePerGroup pergroupstate,
                                      Datum *resultVal, bool *resultIsNull);
static inline void prepare_hash_slot(AggStatePerHash perhash,
                                     TupleTableSlot *inputslot,
                                     TupleTableSlot *hashslot);
static void prepare_projection_slot(AggState *aggstate,
                                    TupleTableSlot *slot,
                                    int currentSet);
static void finalize_aggregates(AggState *aggstate,
                                AggStatePerAgg peraggs,
                                AggStatePerGroup pergroup);
static TupleTableSlot *project_aggregates(AggState *aggstate);
static void find_cols(AggState *aggstate, Bitmapset **aggregated,
                      Bitmapset **unaggregated);
static bool find_cols_walker(Node *node, FindColsContext *context);
static void build_hash_tables(AggState *aggstate);
static void build_hash_table(AggState *aggstate, int setno, double nbuckets);
static void hashagg_recompile_expressions(AggState *aggstate, bool minslot,
                                          bool nullcheck);
static void hash_create_memory(AggState *aggstate);
static double hash_choose_num_buckets(double hashentrysize,
                                      double ngroups, Size memory);
static int  hash_choose_num_partitions(double input_groups,
                                       double hashentrysize,
                                       int used_bits,
                                       int *log2_npartitions);
static void initialize_hash_entry(AggState *aggstate,
                                  TupleHashTable hashtable,
                                  TupleHashEntry entry);
static void lookup_hash_entries(AggState *aggstate);
static TupleTableSlot *agg_retrieve_direct(AggState *aggstate);
static void agg_fill_hash_table(AggState *aggstate);
static bool agg_refill_hash_table(AggState *aggstate);
static TupleTableSlot *agg_retrieve_hash_table(AggState *aggstate);
static TupleTableSlot *agg_retrieve_hash_table_in_memory(AggState *aggstate);
static void hash_agg_check_limits(AggState *aggstate);
static void hash_agg_enter_spill_mode(AggState *aggstate);
static void hash_agg_update_metrics(AggState *aggstate, bool from_tape,
                                    int npartitions);
static void hashagg_finish_initial_spills(AggState *aggstate);
static void hashagg_reset_spill_state(AggState *aggstate);
static HashAggBatch *hashagg_batch_new(LogicalTape *input_tape, int setno,
                                       int64 input_tuples, double input_card,
                                       int used_bits);
static MinimalTuple hashagg_batch_read(HashAggBatch *batch, uint32 *hashp);
static void hashagg_spill_init(HashAggSpill *spill, LogicalTapeSet *tapeset,
                               int used_bits, double input_groups,
                               double hashentrysize);
static Size hashagg_spill_tuple(AggState *aggstate, HashAggSpill *spill,
                                TupleTableSlot *inputslot, uint32 hash);
static void hashagg_spill_finish(AggState *aggstate, HashAggSpill *spill,
                                 int setno);
static Datum GetAggInitVal(Datum textInitVal, Oid transtype);
static void build_pertrans_for_aggref(AggStatePerTrans pertrans,
                                      AggState *aggstate, EState *estate,
                                      Aggref *aggref, Oid transfn_oid,
                                      Oid aggtranstype, Oid aggserialfn,
                                      Oid aggdeserialfn, Datum initValue,
                                      bool initValueIsNull, Oid *inputTypes,
                                      int numArguments);
 
 
/*
 * Select the current grouping set; affects current_set and
 * curaggcontext.
 */
static void
select_current_set(AggState *aggstate, int setno, bool is_hash)
{
    /*
     * When changing this, also adapt ExecAggPlainTransByVal() and
     * ExecAggPlainTransByRef().
     */
    if (is_hash)
        aggstate->curaggcontext = aggstate->hashcontext;
    else
        aggstate->curaggcontext = aggstate->aggcontexts[setno];
 
    aggstate->current_set = setno;
}
 
/*
 * Switch to phase "newphase", which must either be 0 or 1 (to reset) or
 * current_phase + 1. Juggle the tuplesorts accordingly.
 *
 * Phase 0 is for hashing, which we currently handle last in the AGG_MIXED
 * case, so when entering phase 0, all we need to do is drop open sorts.
 */
static void
initialize_phase(AggState *aggstate, int newphase)
{
    Assert(newphase <= 1 || newphase == aggstate->current_phase + 1);
 
    /*
     * Whatever the previous state, we're now done with whatever input
     * tuplesort was in use.
     */
    if (aggstate->sort_in)
    {
        tuplesort_end(aggstate->sort_in);
        aggstate->sort_in = NULL;
    }
 
    if (newphase <= 1)
    {
        /*
         * Discard any existing output tuplesort.
         */
        if (aggstate->sort_out)
        {
            tuplesort_end(aggstate->sort_out);
            aggstate->sort_out = NULL;
        }
    }
    else
    {
        /*
         * The old output tuplesort becomes the new input one, and this is the
         * right time to actually sort it.
         */
        aggstate->sort_in = aggstate->sort_out;
        aggstate->sort_out = NULL;
        Assert(aggstate->sort_in);
        tuplesort_performsort(aggstate->sort_in);
    }
 
    /*
     * If this isn't the last phase, we need to sort appropriately for the
     * next phase in sequence.
     */
    if (newphase > 0 && newphase < aggstate->numphases - 1)
    {
        Sort       *sortnode = aggstate->phases[newphase + 1].sortnode;
        PlanState  *outerNode = outerPlanState(aggstate);
        TupleDesc   tupDesc = ExecGetResultType(outerNode);
 
        aggstate->sort_out = tuplesort_begin_heap(tupDesc,
                                                  sortnode->numCols,
                                                  sortnode->sortColIdx,
                                                  sortnode->sortOperators,
                                                  sortnode->collations,
                                                  sortnode->nullsFirst,
                                                  work_mem,
                                                  NULL, TUPLESORT_NONE);
    }
 
    aggstate->current_phase = newphase;
    aggstate->phase = &aggstate->phases[newphase];
}
 
/*
 * Fetch a tuple from either the outer plan (for phase 1) or from the sorter
 * populated by the previous phase.  Copy it to the sorter for the next phase
 * if any.
 *
 * Callers cannot rely on memory for tuple in returned slot remaining valid
 * past any subsequently fetched tuple.
 */
static TupleTableSlot *
fetch_input_tuple(AggState *aggstate)
{
    TupleTableSlot *slot;
 
    if (aggstate->sort_in)
    {
        /* make sure we check for interrupts in either path through here */
        CHECK_FOR_INTERRUPTS();
        if (!tuplesort_gettupleslot(aggstate->sort_in, true, false,
                                    aggstate->sort_slot, NULL))
            return NULL;
        slot = aggstate->sort_slot;
    }
    else
        slot = ExecProcNode(outerPlanState(aggstate));
 
    if (!TupIsNull(slot) && aggstate->sort_out)
        tuplesort_puttupleslot(aggstate->sort_out, slot);
 
    return slot;
}
 
/*
 * (Re)Initialize an individual aggregate.
 *
 * This function handles only one grouping set, already set in
 * aggstate->current_set.
 *
 * When called, CurrentMemoryContext should be the per-query context.
 */
static void
initialize_aggregate(AggState *aggstate, AggStatePerTrans pertrans,
                     AggStatePerGroup pergroupstate)
{
    /*
     * Start a fresh sort operation for each DISTINCT/ORDER BY aggregate.
     */
    if (pertrans->aggsortrequired)
    {
        /*
         * In case of rescan, maybe there could be an uncompleted sort
         * operation?  Clean it up if so.
         */
        if (pertrans->sortstates[aggstate->current_set])
            tuplesort_end(pertrans->sortstates[aggstate->current_set]);
 
 
        /*
         * We use a plain Datum sorter when there's a single input column;
         * otherwise sort the full tuple.  (See comments for
         * process_ordered_aggregate_single.)
         */
        if (pertrans->numInputs == 1)
        {
            Form_pg_attribute attr = TupleDescAttr(pertrans->sortdesc, 0);
 
            pertrans->sortstates[aggstate->current_set] =
                tuplesort_begin_datum(attr->atttypid,
                                      pertrans->sortOperators[0],
                                      pertrans->sortCollations[0],
                                      pertrans->sortNullsFirst[0],
                                      work_mem, NULL, TUPLESORT_NONE);
        }
        else
            pertrans->sortstates[aggstate->current_set] =
                tuplesort_begin_heap(pertrans->sortdesc,
                                     pertrans->numSortCols,
                                     pertrans->sortColIdx,
                                     pertrans->sortOperators,
                                     pertrans->sortCollations,
                                     pertrans->sortNullsFirst,
                                     work_mem, NULL, TUPLESORT_NONE);
    }
 
    /*
     * (Re)set transValue to the initial value.
     *
     * Note that when the initial value is pass-by-ref, we must copy it (into
     * the aggcontext) since we will pfree the transValue later.
     */
    if (pertrans->initValueIsNull)
        pergroupstate->transValue = pertrans->initValue;
    else
    {
        MemoryContext oldContext;
 
        oldContext = MemoryContextSwitchTo(aggstate->curaggcontext->ecxt_per_tuple_memory);
        pergroupstate->transValue = datumCopy(pertrans->initValue,
                                              pertrans->transtypeByVal,
                                              pertrans->transtypeLen);
        MemoryContextSwitchTo(oldContext);
    }
    pergroupstate->transValueIsNull = pertrans->initValueIsNull;
 
    /*
     * If the initial value for the transition state doesn't exist in the
     * pg_aggregate table then we will let the first non-NULL value returned
     * from the outer procNode become the initial value. (This is useful for
     * aggregates like max() and min().) The noTransValue flag signals that we
     * still need to do this.
     */
    pergroupstate->noTransValue = pertrans->initValueIsNull;
}
 
/*
 * Initialize all aggregate transition states for a new group of input values.
 *
 * If there are multiple grouping sets, we initialize only the first numReset
 * of them (the grouping sets are ordered so that the most specific one, which
 * is reset most often, is first). As a convenience, if numReset is 0, we
 * reinitialize all sets.
 *
 * NB: This cannot be used for hash aggregates, as for those the grouping set
 * number has to be specified from further up.
 *
 * When called, CurrentMemoryContext should be the per-query context.
 */
static void
initialize_aggregates(AggState *aggstate,
                      AggStatePerGroup *pergroups,
                      int numReset)
{
    int         transno;
    int         numGroupingSets = Max(aggstate->phase->numsets, 1);
    int         setno = 0;
    int         numTrans = aggstate->numtrans;
    AggStatePerTrans transstates = aggstate->pertrans;
 
    if (numReset == 0)
        numReset = numGroupingSets;
 
    for (setno = 0; setno < numReset; setno++)
    {
        AggStatePerGroup pergroup = pergroups[setno];
 
        select_current_set(aggstate, setno, false);
 
        for (transno = 0; transno < numTrans; transno++)
        {
            AggStatePerTrans pertrans = &transstates[transno];
            AggStatePerGroup pergroupstate = &pergroup[transno];
 
            initialize_aggregate(aggstate, pertrans, pergroupstate);
        }
    }
}
 
/*
 * Given new input value(s), advance the transition function of one aggregate
 * state within one grouping set only (already set in aggstate->current_set)
 *
 * The new values (and null flags) have been preloaded into argument positions
 * 1 and up in pertrans->transfn_fcinfo, so that we needn't copy them again to
 * pass to the transition function.  We also expect that the static fields of
 * the fcinfo are already initialized; that was done by ExecInitAgg().
 *
 * It doesn't matter which memory context this is called in.
 */
static void
advance_transition_function(AggState *aggstate,
                            AggStatePerTrans pertrans,
                            AggStatePerGroup pergroupstate)
{
    FunctionCallInfo fcinfo = pertrans->transfn_fcinfo;
    MemoryContext oldContext;
    Datum       newVal;
 
    if (pertrans->transfn.fn_strict)
    {
        /*
         * For a strict transfn, nothing happens when there's a NULL input; we
         * just keep the prior transValue.
         */
        int         numTransInputs = pertrans->numTransInputs;
        int         i;
 
        for (i = 1; i <= numTransInputs; i++)
        {
            if (fcinfo->args[i].isnull)
                return;
        }
        if (pergroupstate->noTransValue)
        {
            /*
             * transValue has not been initialized. This is the first non-NULL
             * input value. We use it as the initial value for transValue. (We
             * already checked that the agg's input type is binary-compatible
             * with its transtype, so straight copy here is OK.)
             *
             * We must copy the datum into aggcontext if it is pass-by-ref. We
             * do not need to pfree the old transValue, since it's NULL.
             */
            oldContext = MemoryContextSwitchTo(aggstate->curaggcontext->ecxt_per_tuple_memory);
            pergroupstate->transValue = datumCopy(fcinfo->args[1].value,
                                                  pertrans->transtypeByVal,
                                                  pertrans->transtypeLen);
            pergroupstate->transValueIsNull = false;
            pergroupstate->noTransValue = false;
            MemoryContextSwitchTo(oldContext);
            return;
        }
        if (pergroupstate->transValueIsNull)
        {
            /*
             * Don't call a strict function with NULL inputs.  Note it is
             * possible to get here despite the above tests, if the transfn is
             * strict *and* returned a NULL on a prior cycle. If that happens
             * we will propagate the NULL all the way to the end.
             */
            return;
        }
    }
 
    /* We run the transition functions in per-input-tuple memory context */
    oldContext = MemoryContextSwitchTo(aggstate->tmpcontext->ecxt_per_tuple_memory);
 
    /* set up aggstate->curpertrans for AggGetAggref() */
    aggstate->curpertrans = pertrans;
 
    /*
     * OK to call the transition function
     */
    fcinfo->args[0].value = pergroupstate->transValue;
    fcinfo->args[0].isnull = pergroupstate->transValueIsNull;
    fcinfo->isnull = false;     /* just in case transfn doesn't set it */
 
    newVal = FunctionCallInvoke(fcinfo);
 
    aggstate->curpertrans = NULL;
 
    /*
     * If pass-by-ref datatype, must copy the new value into aggcontext and
     * free the prior transValue.  But if transfn returned a pointer to its
     * first input, we don't need to do anything.
     *
     * It's safe to compare newVal with pergroup->transValue without regard
     * for either being NULL, because ExecAggCopyTransValue takes care to set
     * transValue to 0 when NULL. Otherwise we could end up accidentally not
     * reparenting, when the transValue has the same numerical value as
     * newValue, despite being NULL.  This is a somewhat hot path, making it
     * undesirable to instead solve this with another branch for the common
     * case of the transition function returning its (modified) input
     * argument.
     */
    if (!pertrans->transtypeByVal &&
        DatumGetPointer(newVal) != DatumGetPointer(pergroupstate->transValue))
        newVal = ExecAggCopyTransValue(aggstate, pertrans,
                                       newVal, fcinfo->isnull,
                                       pergroupstate->transValue,
                                       pergroupstate->transValueIsNull);
 
    pergroupstate->transValue = newVal;
    pergroupstate->transValueIsNull = fcinfo->isnull;
 
    MemoryContextSwitchTo(oldContext);
}
 
/*
 * Advance each aggregate transition state for one input tuple.  The input
 * tuple has been stored in tmpcontext->ecxt_outertuple, so that it is
 * accessible to ExecEvalExpr.
 *
 * We have two sets of transition states to handle: one for sorted aggregation
 * and one for hashed; we do them both here, to avoid multiple evaluation of
 * the inputs.
 *
 * When called, CurrentMemoryContext should be the per-query context.
 */
static void
advance_aggregates(AggState *aggstate)
{
    ExecEvalExprNoReturnSwitchContext(aggstate->phase->evaltrans,
                                      aggstate->tmpcontext);
}
 
/*
 * Run the transition function for a DISTINCT or ORDER BY aggregate
 * with only one input.  This is called after we have completed
 * entering all the input values into the sort object.  We complete the
 * sort, read out the values in sorted order, and run the transition
 * function on each value (applying DISTINCT if appropriate).
 *
 * Note that the strictness of the transition function was checked when
 * entering the values into the sort, so we don't check it again here;
 * we just apply standard SQL DISTINCT logic.
 *
 * The one-input case is handled separately from the multi-input case
 * for performance reasons: for single by-value inputs, such as the
 * common case of count(distinct id), the tuplesort_getdatum code path
 * is around 300% faster.  (The speedup for by-reference types is less
 * but still noticeable.)
 *
 * This function handles only one grouping set (already set in
 * aggstate->current_set).
 *
 * When called, CurrentMemoryContext should be the per-query context.
 */
static void
process_ordered_aggregate_single(AggState *aggstate,
                                 AggStatePerTrans pertrans,
                                 AggStatePerGroup pergroupstate)
{
    Datum       oldVal = (Datum) 0;
    bool        oldIsNull = true;
    bool        haveOldVal = false;
    MemoryContext workcontext = aggstate->tmpcontext->ecxt_per_tuple_memory;
    MemoryContext oldContext;
    bool        isDistinct = (pertrans->numDistinctCols > 0);
    Datum       newAbbrevVal = (Datum) 0;
    Datum       oldAbbrevVal = (Datum) 0;
    FunctionCallInfo fcinfo = pertrans->transfn_fcinfo;
    Datum      *newVal;
    bool       *isNull;
 
    Assert(pertrans->numDistinctCols < 2);
 
    tuplesort_performsort(pertrans->sortstates[aggstate->current_set]);
 
    /* Load the column into argument 1 (arg 0 will be transition value) */
    newVal = &fcinfo->args[1].value;
    isNull = &fcinfo->args[1].isnull;
 
    /*
     * Note: if input type is pass-by-ref, the datums returned by the sort are
     * freshly palloc'd in the per-query context, so we must be careful to
     * pfree them when they are no longer needed.
     */
 
    while (tuplesort_getdatum(pertrans->sortstates[aggstate->current_set],
                              true, false, newVal, isNull, &newAbbrevVal))
    {
        /*
         * Clear and select the working context for evaluation of the equality
         * function and transition function.
         */
        MemoryContextReset(workcontext);
        oldContext = MemoryContextSwitchTo(workcontext);
 
        /*
         * If DISTINCT mode, and not distinct from prior, skip it.
         */
        if (isDistinct &&
            haveOldVal &&
            ((oldIsNull && *isNull) ||
             (!oldIsNull && !*isNull &&
              oldAbbrevVal == newAbbrevVal &&
              DatumGetBool(FunctionCall2Coll(&pertrans->equalfnOne,
                                             pertrans->aggCollation,
                                             oldVal, *newVal)))))
        {
            MemoryContextSwitchTo(oldContext);
            continue;
        }
        else
        {
            advance_transition_function(aggstate, pertrans, pergroupstate);
 
            MemoryContextSwitchTo(oldContext);
 
            /*
             * Forget the old value, if any, and remember the new one for
             * subsequent equality checks.
             */
            if (!pertrans->inputtypeByVal)
            {
                if (!oldIsNull)
                    pfree(DatumGetPointer(oldVal));
                if (!*isNull)
                    oldVal = datumCopy(*newVal, pertrans->inputtypeByVal,
                                       pertrans->inputtypeLen);
            }
            else
                oldVal = *newVal;
            oldAbbrevVal = newAbbrevVal;
            oldIsNull = *isNull;
            haveOldVal = true;
        }
    }
 
    if (!oldIsNull && !pertrans->inputtypeByVal)
        pfree(DatumGetPointer(oldVal));
 
    tuplesort_end(pertrans->sortstates[aggstate->current_set]);
    pertrans->sortstates[aggstate->current_set] = NULL;
}
 
/*
 * Run the transition function for a DISTINCT or ORDER BY aggregate
 * with more than one input.  This is called after we have completed
 * entering all the input values into the sort object.  We complete the
 * sort, read out the values in sorted order, and run the transition
 * function on each value (applying DISTINCT if appropriate).
 *
 * This function handles only one grouping set (already set in
 * aggstate->current_set).
 *
 * When called, CurrentMemoryContext should be the per-query context.
 */
static void
process_ordered_aggregate_multi(AggState *aggstate,
                                AggStatePerTrans pertrans,
                                AggStatePerGroup pergroupstate)
{
    ExprContext *tmpcontext = aggstate->tmpcontext;
    FunctionCallInfo fcinfo = pertrans->transfn_fcinfo;
    TupleTableSlot *slot1 = pertrans->sortslot;
    TupleTableSlot *slot2 = pertrans->uniqslot;
    int         numTransInputs = pertrans->numTransInputs;
    int         numDistinctCols = pertrans->numDistinctCols;
    Datum       newAbbrevVal = (Datum) 0;
    Datum       oldAbbrevVal = (Datum) 0;
    bool        haveOldValue = false;
    TupleTableSlot *save = aggstate->tmpcontext->ecxt_outertuple;
    int         i;
 
    tuplesort_performsort(pertrans->sortstates[aggstate->current_set]);
 
    ExecClearTuple(slot1);
    if (slot2)
        ExecClearTuple(slot2);
 
    while (tuplesort_gettupleslot(pertrans->sortstates[aggstate->current_set],
                                  true, true, slot1, &newAbbrevVal))
    {
        CHECK_FOR_INTERRUPTS();
 
        tmpcontext->ecxt_outertuple = slot1;
        tmpcontext->ecxt_innertuple = slot2;
 
        if (numDistinctCols == 0 ||
            !haveOldValue ||
            newAbbrevVal != oldAbbrevVal ||
            !ExecQual(pertrans->equalfnMulti, tmpcontext))
        {
            /*
             * Extract the first numTransInputs columns as datums to pass to
             * the transfn.
             */
            slot_getsomeattrs(slot1, numTransInputs);
 
            /* Load values into fcinfo */
            /* Start from 1, since the 0th arg will be the transition value */
            for (i = 0; i < numTransInputs; i++)
            {
                fcinfo->args[i + 1].value = slot1->tts_values[i];
                fcinfo->args[i + 1].isnull = slot1->tts_isnull[i];
            }
 
            advance_transition_function(aggstate, pertrans, pergroupstate);
 
            if (numDistinctCols > 0)
            {
                /* swap the slot pointers to retain the current tuple */
                TupleTableSlot *tmpslot = slot2;
 
                slot2 = slot1;
                slot1 = tmpslot;
                /* avoid ExecQual() calls by reusing abbreviated keys */
                oldAbbrevVal = newAbbrevVal;
                haveOldValue = true;
            }
        }
 
        /* Reset context each time */
        ResetExprContext(tmpcontext);
 
        ExecClearTuple(slot1);
    }
 
    if (slot2)
        ExecClearTuple(slot2);
 
    tuplesort_end(pertrans->sortstates[aggstate->current_set]);
    pertrans->sortstates[aggstate->current_set] = NULL;
 
    /* restore previous slot, potentially in use for grouping sets */
    tmpcontext->ecxt_outertuple = save;
}
 
/*
 * Compute the final value of one aggregate.
 *
 * This function handles only one grouping set (already set in
 * aggstate->current_set).
 *
 * The finalfn will be run, and the result delivered, in the
 * output-tuple context; caller's CurrentMemoryContext does not matter.
 * (But note that in some cases, such as when there is no finalfn, the
 * result might be a pointer to or into the agg's transition value.)
 *
 * The finalfn uses the state as set in the transno.  This also might be
 * being used by another aggregate function, so it's important that we do
 * nothing destructive here.  Moreover, the aggregate's final value might
 * get used in multiple places, so we mustn't return a R/W expanded datum.
 */
static void
finalize_aggregate(AggState *aggstate,
                   AggStatePerAgg peragg,
                   AggStatePerGroup pergroupstate,
                   Datum *resultVal, bool *resultIsNull)
{
    LOCAL_FCINFO(fcinfo, FUNC_MAX_ARGS);
    bool        anynull = false;
    MemoryContext oldContext;
    int         i;
    ListCell   *lc;
    AggStatePerTrans pertrans = &aggstate->pertrans[peragg->transno];
 
    oldContext = MemoryContextSwitchTo(aggstate->ss.ps.ps_ExprContext->ecxt_per_tuple_memory);
 
    /*
     * Evaluate any direct arguments.  We do this even if there's no finalfn
     * (which is unlikely anyway), so that side-effects happen as expected.
     * The direct arguments go into arg positions 1 and up, leaving position 0
     * for the transition state value.
     */
    i = 1;
    foreach(lc, peragg->aggdirectargs)
    {
        ExprState  *expr = (ExprState *) lfirst(lc);
 
        fcinfo->args[i].value = ExecEvalExpr(expr,
                                             aggstate->ss.ps.ps_ExprContext,
                                             &fcinfo->args[i].isnull);
        anynull |= fcinfo->args[i].isnull;
        i++;
    }
 
    /*
     * Apply the agg's finalfn if one is provided, else return transValue.
     */
    if (OidIsValid(peragg->finalfn_oid))
    {
        int         numFinalArgs = peragg->numFinalArgs;
 
        /* set up aggstate->curperagg for AggGetAggref() */
        aggstate->curperagg = peragg;
 
        InitFunctionCallInfoData(*fcinfo, &peragg->finalfn,
                                 numFinalArgs,
                                 pertrans->aggCollation,
                                 (Node *) aggstate, NULL);
 
        /* Fill in the transition state value */
        fcinfo->args[0].value =
            MakeExpandedObjectReadOnly(pergroupstate->transValue,
                                       pergroupstate->transValueIsNull,
                                       pertrans->transtypeLen);
        fcinfo->args[0].isnull = pergroupstate->transValueIsNull;
        anynull |= pergroupstate->transValueIsNull;
 
        /* Fill any remaining argument positions with nulls */
        for (; i < numFinalArgs; i++)
        {
            fcinfo->args[i].value = (Datum) 0;
            fcinfo->args[i].isnull = true;
            anynull = true;
        }
 
        if (fcinfo->flinfo->fn_strict && anynull)
        {
            /* don't call a strict function with NULL inputs */
            *resultVal = (Datum) 0;
            *resultIsNull = true;
        }
        else
        {
            Datum       result;
 
            result = FunctionCallInvoke(fcinfo);
            *resultIsNull = fcinfo->isnull;
            *resultVal = MakeExpandedObjectReadOnly(result,
                                                    fcinfo->isnull,
                                                    peragg->resulttypeLen);
        }
        aggstate->curperagg = NULL;
    }
    else
    {
        *resultVal =
            MakeExpandedObjectReadOnly(pergroupstate->transValue,
                                       pergroupstate->transValueIsNull,
                                       pertrans->transtypeLen);
        *resultIsNull = pergroupstate->transValueIsNull;
    }
 
    MemoryContextSwitchTo(oldContext);
}
 
/*
 * Compute the output value of one partial aggregate.
 *
 * The serialization function will be run, and the result delivered, in the
 * output-tuple context; caller's CurrentMemoryContext does not matter.
 */
static void
finalize_partialaggregate(AggState *aggstate,
                          AggStatePerAgg peragg,
                          AggStatePerGroup pergroupstate,
                          Datum *resultVal, bool *resultIsNull)
{
    AggStatePerTrans pertrans = &aggstate->pertrans[peragg->transno];
    MemoryContext oldContext;
 
    oldContext = MemoryContextSwitchTo(aggstate->ss.ps.ps_ExprContext->ecxt_per_tuple_memory);
 
    /*
     * serialfn_oid will be set if we must serialize the transvalue before
     * returning it
     */
    if (OidIsValid(pertrans->serialfn_oid))
    {
        /* Don't call a strict serialization function with NULL input. */
        if (pertrans->serialfn.fn_strict && pergroupstate->transValueIsNull)
        {
            *resultVal = (Datum) 0;
            *resultIsNull = true;
        }
        else
        {
            FunctionCallInfo fcinfo = pertrans->serialfn_fcinfo;
            Datum       result;
 
            fcinfo->args[0].value =
                MakeExpandedObjectReadOnly(pergroupstate->transValue,
                                           pergroupstate->transValueIsNull,
                                           pertrans->transtypeLen);
            fcinfo->args[0].isnull = pergroupstate->transValueIsNull;
            fcinfo->isnull = false;
 
            result = FunctionCallInvoke(fcinfo);
            *resultIsNull = fcinfo->isnull;
            *resultVal = MakeExpandedObjectReadOnly(result,
                                                    fcinfo->isnull,
                                                    peragg->resulttypeLen);
        }
    }
    else
    {
        *resultVal =
            MakeExpandedObjectReadOnly(pergroupstate->transValue,
                                       pergroupstate->transValueIsNull,
                                       pertrans->transtypeLen);
        *resultIsNull = pergroupstate->transValueIsNull;
    }
 
    MemoryContextSwitchTo(oldContext);
}
 
/*
 * Extract the attributes that make up the grouping key into the
 * hashslot. This is necessary to compute the hash or perform a lookup.
 */
static inline void
prepare_hash_slot(AggStatePerHash perhash,
                  TupleTableSlot *inputslot,
                  TupleTableSlot *hashslot)
{
    int         i;
 
    /* transfer just the needed columns into hashslot */
    slot_getsomeattrs(inputslot, perhash->largestGrpColIdx);
    ExecClearTuple(hashslot);
 
    for (i = 0; i < perhash->numhashGrpCols; i++)
    {
        int         varNumber = perhash->hashGrpColIdxInput[i] - 1;
 
        hashslot->tts_values[i] = inputslot->tts_values[varNumber];
        hashslot->tts_isnull[i] = inputslot->tts_isnull[varNumber];
    }
    ExecStoreVirtualTuple(hashslot);
}
 
/*
 * Prepare to finalize and project based on the specified representative tuple
 * slot and grouping set.
 *
 * In the specified tuple slot, force to null all attributes that should be
 * read as null in the context of the current grouping set.  Also stash the
 * current group bitmap where GroupingExpr can get at it.
 *
 * This relies on three conditions:
 *
 * 1) Nothing is ever going to try and extract the whole tuple from this slot,
 * only reference it in evaluations, which will only access individual
 * attributes.
 *
 * 2) No system columns are going to need to be nulled. (If a system column is
 * referenced in a group clause, it is actually projected in the outer plan
 * tlist.)
 *
 * 3) Within a given phase, we never need to recover the value of an attribute
 * once it has been set to null.
 *
 * Poking into the slot this way is a bit ugly, but the consensus is that the
 * alternative was worse.
 */
static void
prepare_projection_slot(AggState *aggstate, TupleTableSlot *slot, int currentSet)
{
    if (aggstate->phase->grouped_cols)
    {
        Bitmapset  *grouped_cols = aggstate->phase->grouped_cols[currentSet];
 
        aggstate->grouped_cols = grouped_cols;
 
        if (TTS_EMPTY(slot))
        {
            /*
             * Force all values to be NULL if working on an empty input tuple
             * (i.e. an empty grouping set for which no input rows were
             * supplied).
             */
            ExecStoreAllNullTuple(slot);
        }
        else if (aggstate->all_grouped_cols)
        {
            ListCell   *lc;
 
            /* all_grouped_cols is arranged in desc order */
            slot_getsomeattrs(slot, linitial_int(aggstate->all_grouped_cols));
 
            foreach(lc, aggstate->all_grouped_cols)
            {
                int         attnum = lfirst_int(lc);
 
                if (!bms_is_member(attnum, grouped_cols))
                    slot->tts_isnull[attnum - 1] = true;
            }
        }
    }
}
 
/*
 * Compute the final value of all aggregates for one group.
 *
 * This function handles only one grouping set at a time, which the caller must
 * have selected.  It's also the caller's responsibility to adjust the supplied
 * pergroup parameter to point to the current set's transvalues.
 *
 * Results are stored in the output econtext aggvalues/aggnulls.
 */
static void
finalize_aggregates(AggState *aggstate,
                    AggStatePerAgg peraggs,
                    AggStatePerGroup pergroup)
{
    ExprContext *econtext = aggstate->ss.ps.ps_ExprContext;
    Datum      *aggvalues = econtext->ecxt_aggvalues;
    bool       *aggnulls = econtext->ecxt_aggnulls;
    int         aggno;
 
    /*
     * If there were any DISTINCT and/or ORDER BY aggregates, sort their
     * inputs and run the transition functions.
     */
    for (int transno = 0; transno < aggstate->numtrans; transno++)
    {
        AggStatePerTrans pertrans = &aggstate->pertrans[transno];
        AggStatePerGroup pergroupstate;
 
        pergroupstate = &pergroup[transno];
 
        if (pertrans->aggsortrequired)
        {
            Assert(aggstate->aggstrategy != AGG_HASHED &&
                   aggstate->aggstrategy != AGG_MIXED);
 
            if (pertrans->numInputs == 1)
                process_ordered_aggregate_single(aggstate,
                                                 pertrans,
                                                 pergroupstate);
            else
                process_ordered_aggregate_multi(aggstate,
                                                pertrans,
                                                pergroupstate);
        }
        else if (pertrans->numDistinctCols > 0 && pertrans->haslast)
        {
            pertrans->haslast = false;
 
            if (pertrans->numDistinctCols == 1)
            {
                if (!pertrans->inputtypeByVal && !pertrans->lastisnull)
                    pfree(DatumGetPointer(pertrans->lastdatum));
 
                pertrans->lastisnull = false;
                pertrans->lastdatum = (Datum) 0;
            }
            else
                ExecClearTuple(pertrans->uniqslot);
        }
    }
 
    /*
     * Run the final functions.
     */
    for (aggno = 0; aggno < aggstate->numaggs; aggno++)
    {
        AggStatePerAgg peragg = &peraggs[aggno];
        int         transno = peragg->transno;
        AggStatePerGroup pergroupstate;
 
        pergroupstate = &pergroup[transno];
 
        if (DO_AGGSPLIT_SKIPFINAL(aggstate->aggsplit))
            finalize_partialaggregate(aggstate, peragg, pergroupstate,
                                      &aggvalues[aggno], &aggnulls[aggno]);
        else
            finalize_aggregate(aggstate, peragg, pergroupstate,
                               &aggvalues[aggno], &aggnulls[aggno]);
    }
}
 
/*
 * Project the result of a group (whose aggs have already been calculated by
 * finalize_aggregates). Returns the result slot, or NULL if no row is
 * projected (suppressed by qual).
 */
static TupleTableSlot *
project_aggregates(AggState *aggstate)
{
    ExprContext *econtext = aggstate->ss.ps.ps_ExprContext;
 
    /*
     * Check the qual (HAVING clause); if the group does not match, ignore it.
     */
    if (ExecQual(aggstate->ss.ps.qual, econtext))
    {
        /*
         * Form and return projection tuple using the aggregate results and
         * the representative input tuple.
         */
        return ExecProject(aggstate->ss.ps.ps_ProjInfo);
    }
    else
        InstrCountFiltered1(aggstate, 1);
 
    return NULL;
}
 
/*
 * Find input-tuple columns that are needed, dividing them into
 * aggregated and unaggregated sets.
 */
static void
find_cols(AggState *aggstate, Bitmapset **aggregated, Bitmapset **unaggregated)
{
    Agg        *agg = (Agg *) aggstate->ss.ps.plan;
    FindColsContext context;
 
    context.is_aggref = false;
    context.aggregated = NULL;
    context.unaggregated = NULL;
 
    /* Examine tlist and quals */
    (void) find_cols_walker((Node *) agg->plan.targetlist, &context);
    (void) find_cols_walker((Node *) agg->plan.qual, &context);
 
    /* In some cases, grouping columns will not appear in the tlist */
    for (int i = 0; i < agg->numCols; i++)
        context.unaggregated = bms_add_member(context.unaggregated,
                                              agg->grpColIdx[i]);
 
    *aggregated = context.aggregated;
    *unaggregated = context.unaggregated;
}
 
static bool
find_cols_walker(Node *node, FindColsContext *context)
{
    if (node == NULL)
        return false;
    if (IsA(node, Var))
    {
        Var        *var = (Var *) node;
 
        /* setrefs.c should have set the varno to OUTER_VAR */
        Assert(var->varno == OUTER_VAR);
        Assert(var->varlevelsup == 0);
        if (context->is_aggref)
            context->aggregated = bms_add_member(context->aggregated,
                                                 var->varattno);
        else
            context->unaggregated = bms_add_member(context->unaggregated,
                                                   var->varattno);
        return false;
    }
    if (IsA(node, Aggref))
    {
        Assert(!context->is_aggref);
        context->is_aggref = true;
        expression_tree_walker(node, find_cols_walker, context);
        context->is_aggref = false;
        return false;
    }
    return expression_tree_walker(node, find_cols_walker, context);
}
 
/*
 * (Re-)initialize the hash table(s) to empty.
 *
 * To implement hashed aggregation, we need a hashtable that stores a
 * representative tuple and an array of AggStatePerGroup structs for each
 * distinct set of GROUP BY column values.  We compute the hash key from the
 * GROUP BY columns.  The per-group data is allocated in initialize_hash_entry(),
 * for each entry.
 *
 * We have a separate hashtable and associated perhash data structure for each
 * grouping set for which we're doing hashing.
 *
 * The contents of the hash tables live in the aggstate's hash_tuplescxt
 * memory context (there is only one of these for all tables together, since
 * they are all reset at the same time).
 */
static void
build_hash_tables(AggState *aggstate)
{
    int         setno;
 
    for (setno = 0; setno < aggstate->num_hashes; ++setno)
    {
        AggStatePerHash perhash = &aggstate->perhash[setno];
        double      nbuckets;
        Size        memory;
 
        if (perhash->hashtable != NULL)
        {
            ResetTupleHashTable(perhash->hashtable);
            continue;
        }
 
        memory = aggstate->hash_mem_limit / aggstate->num_hashes;
 
        /* choose reasonable number of buckets per hashtable */
        nbuckets = hash_choose_num_buckets(aggstate->hashentrysize,
                                           perhash->aggnode->numGroups,
                                           memory);
 
#ifdef USE_INJECTION_POINTS
        if (IS_INJECTION_POINT_ATTACHED("hash-aggregate-oversize-table"))
        {
            nbuckets = memory / TupleHashEntrySize();
            INJECTION_POINT_CACHED("hash-aggregate-oversize-table", NULL);
        }
#endif
 
        build_hash_table(aggstate, setno, nbuckets);
    }
 
    aggstate->hash_ngroups_current = 0;
}
 
/*
 * Build a single hashtable for this grouping set.
 */
static void
build_hash_table(AggState *aggstate, int setno, double nbuckets)
{
    AggStatePerHash perhash = &aggstate->perhash[setno];
    MemoryContext metacxt = aggstate->hash_metacxt;
    MemoryContext tuplescxt = aggstate->hash_tuplescxt;
    MemoryContext tmpcxt = aggstate->tmpcontext->ecxt_per_tuple_memory;
    Size        additionalsize;
 
    Assert(aggstate->aggstrategy == AGG_HASHED ||
           aggstate->aggstrategy == AGG_MIXED);
 
    /*
     * Used to make sure initial hash table allocation does not exceed
     * hash_mem. Note that the estimate does not include space for
     * pass-by-reference transition data values, nor for the representative
     * tuple of each group.
     */
    additionalsize = aggstate->numtrans * sizeof(AggStatePerGroupData);
 
    perhash->hashtable = BuildTupleHashTable(&aggstate->ss.ps,
                                             perhash->hashslot->tts_tupleDescriptor,
                                             perhash->hashslot->tts_ops,
                                             perhash->numCols,
                                             perhash->hashGrpColIdxHash,
                                             perhash->eqfuncoids,
                                             perhash->hashfunctions,
                                             perhash->aggnode->grpCollations,
                                             nbuckets,
                                             additionalsize,
                                             metacxt,
                                             tuplescxt,
                                             tmpcxt,
                                             DO_AGGSPLIT_SKIPFINAL(aggstate->aggsplit));
}
 
/*
 * Compute columns that actually need to be stored in hashtable entries.  The
 * incoming tuples from the child plan node will contain grouping columns,
 * other columns referenced in our targetlist and qual, columns used to
 * compute the aggregate functions, and perhaps just junk columns we don't use
 * at all.  Only columns of the first two types need to be stored in the
 * hashtable, and getting rid of the others can make the table entries
 * significantly smaller.  The hashtable only contains the relevant columns,
 * and is packed/unpacked in lookup_hash_entries() / agg_retrieve_hash_table()
 * into the format of the normal input descriptor.
 *
 * Additional columns, in addition to the columns grouped by, come from two
 * sources: Firstly functionally dependent columns that we don't need to group
 * by themselves, and secondly ctids for row-marks.
 *
 * To eliminate duplicates, we build a bitmapset of the needed columns, and
 * then build an array of the columns included in the hashtable. We might
 * still have duplicates if the passed-in grpColIdx has them, which can happen
 * in edge cases from semijoins/distinct; these can't always be removed,
 * because it's not certain that the duplicate cols will be using the same
 * hash function.
 *
 * Note that the array is preserved over ExecReScanAgg, so we allocate it in
 * the per-query context (unlike the hash table itself).
 */
static void
find_hash_columns(AggState *aggstate)
{
    Bitmapset  *base_colnos;
    Bitmapset  *aggregated_colnos;
    TupleDesc   scanDesc = aggstate->ss.ss_ScanTupleSlot->tts_tupleDescriptor;
    List       *outerTlist = outerPlanState(aggstate)->plan->targetlist;
    int         numHashes = aggstate->num_hashes;
    EState     *estate = aggstate->ss.ps.state;
    int         j;
 
    /* Find Vars that will be needed in tlist and qual */
    find_cols(aggstate, &aggregated_colnos, &base_colnos);
    aggstate->colnos_needed = bms_union(base_colnos, aggregated_colnos);
    aggstate->max_colno_needed = 0;
    aggstate->all_cols_needed = true;
 
    for (int i = 0; i < scanDesc->natts; i++)
    {
        int         colno = i + 1;
 
        if (bms_is_member(colno, aggstate->colnos_needed))
            aggstate->max_colno_needed = colno;
        else
            aggstate->all_cols_needed = false;
    }
 
    for (j = 0; j < numHashes; ++j)
    {
        AggStatePerHash perhash = &aggstate->perhash[j];
        Bitmapset  *colnos = bms_copy(base_colnos);
        AttrNumber *grpColIdx = perhash->aggnode->grpColIdx;
        List       *hashTlist = NIL;
        TupleDesc   hashDesc;
        int         maxCols;
        int         i;
 
        perhash->largestGrpColIdx = 0;
 
        /*
         * If we're doing grouping sets, then some Vars might be referenced in
         * tlist/qual for the benefit of other grouping sets, but not needed
         * when hashing; i.e. prepare_projection_slot will null them out, so
         * there'd be no point storing them.  Use prepare_projection_slot's
         * logic to determine which.
         */
        if (aggstate->phases[0].grouped_cols)
        {
            Bitmapset  *grouped_cols = aggstate->phases[0].grouped_cols[j];
            ListCell   *lc;
 
            foreach(lc, aggstate->all_grouped_cols)
            {
                int         attnum = lfirst_int(lc);
 
                if (!bms_is_member(attnum, grouped_cols))
                    colnos = bms_del_member(colnos, attnum);
            }
        }
 
        /*
         * Compute maximum number of input columns accounting for possible
         * duplications in the grpColIdx array, which can happen in some edge
         * cases where HashAggregate was generated as part of a semijoin or a
         * DISTINCT.
         */
        maxCols = bms_num_members(colnos) + perhash->numCols;
 
        perhash->hashGrpColIdxInput =
            palloc(maxCols * sizeof(AttrNumber));
        perhash->hashGrpColIdxHash =
            palloc(perhash->numCols * sizeof(AttrNumber));
 
        /* Add all the grouping columns to colnos */
        for (i = 0; i < perhash->numCols; i++)
            colnos = bms_add_member(colnos, grpColIdx[i]);
 
        /*
         * First build mapping for columns directly hashed. These are the
         * first, because they'll be accessed when computing hash values and
         * comparing tuples for exact matches. We also build simple mapping
         * for execGrouping, so it knows where to find the to-be-hashed /
         * compared columns in the input.
         */
        for (i = 0; i < perhash->numCols; i++)
        {
            perhash->hashGrpColIdxInput[i] = grpColIdx[i];
            perhash->hashGrpColIdxHash[i] = i + 1;
            perhash->numhashGrpCols++;
            /* delete already mapped columns */
            colnos = bms_del_member(colnos, grpColIdx[i]);
        }
 
        /* and add the remaining columns */
        i = -1;
        while ((i = bms_next_member(colnos, i)) >= 0)
        {
            perhash->hashGrpColIdxInput[perhash->numhashGrpCols] = i;
            perhash->numhashGrpCols++;
        }
 
        /* and build a tuple descriptor for the hashtable */
        for (i = 0; i < perhash->numhashGrpCols; i++)
        {
            int         varNumber = perhash->hashGrpColIdxInput[i] - 1;
 
            hashTlist = lappend(hashTlist, list_nth(outerTlist, varNumber));
            perhash->largestGrpColIdx =
                Max(varNumber + 1, perhash->largestGrpColIdx);
        }
 
        hashDesc = ExecTypeFromTL(hashTlist);
 
        execTuplesHashPrepare(perhash->numCols,
                              perhash->aggnode->grpOperators,
                              &perhash->eqfuncoids,
                              &perhash->hashfunctions);
        perhash->hashslot =
            ExecAllocTableSlot(&estate->es_tupleTable, hashDesc,
                               &TTSOpsMinimalTuple);
 
        list_free(hashTlist);
        bms_free(colnos);
    }
 
    bms_free(base_colnos);
}
 
/*
 * Estimate per-hash-table-entry overhead.
 */
Size
hash_agg_entry_size(int numTrans, Size tupleWidth, Size transitionSpace)
{
    Size        tupleChunkSize;
    Size        pergroupChunkSize;
    Size        transitionChunkSize;
    Size        tupleSize = (MAXALIGN(SizeofMinimalTupleHeader) +
                             tupleWidth);
    Size        pergroupSize = numTrans * sizeof(AggStatePerGroupData);
 
    /*
     * Entries use the Bump allocator, so the chunk sizes are the same as the
     * requested sizes.
     */
    tupleChunkSize = MAXALIGN(tupleSize);
    pergroupChunkSize = pergroupSize;
 
    /*
     * Transition values use AllocSet, which has a chunk header and also uses
     * power-of-two allocations.
     */
    if (transitionSpace > 0)
        transitionChunkSize = CHUNKHDRSZ + pg_nextpower2_size_t(transitionSpace);
    else
        transitionChunkSize = 0;
 
    return
        TupleHashEntrySize() +
        tupleChunkSize +
        pergroupChunkSize +
        transitionChunkSize;
}
 
/*
 * hashagg_recompile_expressions()
 *
 * Identifies the right phase, compiles the right expression given the
 * arguments, and then sets phase->evalfunc to that expression.
 *
 * Different versions of the compiled expression are needed depending on
 * whether hash aggregation has spilled or not, and whether it's reading from
 * the outer plan or a tape. Before spilling to disk, the expression reads
 * from the outer plan and does not need to perform a NULL check. After
 * HashAgg begins to spill, new groups will not be created in the hash table,
 * and the AggStatePerGroup array may be NULL; therefore we need to add a null
 * pointer check to the expression. Then, when reading spilled data from a
 * tape, we change the outer slot type to be a fixed minimal tuple slot.
 *
 * It would be wasteful to recompile every time, so cache the compiled
 * expressions in the AggStatePerPhase, and reuse when appropriate.
 */
static void
hashagg_recompile_expressions(AggState *aggstate, bool minslot, bool nullcheck)
{
    AggStatePerPhase phase;
    int         i = minslot ? 1 : 0;
    int         j = nullcheck ? 1 : 0;
 
    Assert(aggstate->aggstrategy == AGG_HASHED ||
           aggstate->aggstrategy == AGG_MIXED);
 
    if (aggstate->aggstrategy == AGG_HASHED)
        phase = &aggstate->phases[0];
    else                        /* AGG_MIXED */
        phase = &aggstate->phases[1];
 
    if (phase->evaltrans_cache[i][j] == NULL)
    {
        const TupleTableSlotOps *outerops = aggstate->ss.ps.outerops;
        bool        outerfixed = aggstate->ss.ps.outeropsfixed;
        bool        dohash = true;
        bool        dosort = false;
 
        /*
         * If minslot is true, that means we are processing a spilled batch
         * (inside agg_refill_hash_table()), and we must not advance the
         * sorted grouping sets.
         */
        if (aggstate->aggstrategy == AGG_MIXED && !minslot)
            dosort = true;
 
        /* temporarily change the outerops while compiling the expression */
        if (minslot)
        {
            aggstate->ss.ps.outerops = &TTSOpsMinimalTuple;
            aggstate->ss.ps.outeropsfixed = true;
        }
 
        phase->evaltrans_cache[i][j] = ExecBuildAggTrans(aggstate, phase,
                                                         dosort, dohash,
                                                         nullcheck);
 
        /* change back */
        aggstate->ss.ps.outerops = outerops;
        aggstate->ss.ps.outeropsfixed = outerfixed;
    }
 
    phase->evaltrans = phase->evaltrans_cache[i][j];
}
 
/*
 * Set limits that trigger spilling to avoid exceeding hash_mem. Consider the
 * number of partitions we expect to create (if we do spill).
 *
 * There are two limits: a memory limit, and also an ngroups limit. The
 * ngroups limit becomes important when we expect transition values to grow
 * substantially larger than the initial value.
 */
void
hash_agg_set_limits(double hashentrysize, double input_groups, int used_bits,
                    Size *mem_limit, uint64 *ngroups_limit,
                    int *num_partitions)
{
    int         npartitions;
    Size        partition_mem;
    Size        hash_mem_limit = get_hash_memory_limit();
 
    /* if not expected to spill, use all of hash_mem */
    if (input_groups * hashentrysize <= hash_mem_limit)
    {
        if (num_partitions != NULL)
            *num_partitions = 0;
        *mem_limit = hash_mem_limit;
        *ngroups_limit = hash_mem_limit / hashentrysize;
        return;
    }
 
    /*
     * Calculate expected memory requirements for spilling, which is the size
     * of the buffers needed for all the tapes that need to be open at once.
     * Then, subtract that from the memory available for holding hash tables.
     */
    npartitions = hash_choose_num_partitions(input_groups,
                                             hashentrysize,
                                             used_bits,
                                             NULL);
    if (num_partitions != NULL)
        *num_partitions = npartitions;
 
    partition_mem =
        HASHAGG_READ_BUFFER_SIZE +
        HASHAGG_WRITE_BUFFER_SIZE * npartitions;
 
    /*
     * Don't set the limit below 3/4 of hash_mem. In that case, we are at the
     * minimum number of partitions, so we aren't going to dramatically exceed
     * work mem anyway.
     */
    if (hash_mem_limit > 4 * partition_mem)
        *mem_limit = hash_mem_limit - partition_mem;
    else
        *mem_limit = hash_mem_limit * 0.75;
 
    if (*mem_limit > hashentrysize)
        *ngroups_limit = *mem_limit / hashentrysize;
    else
        *ngroups_limit = 1;
}
 
/*
 * hash_agg_check_limits
 *
 * After adding a new group to the hash table, check whether we need to enter
 * spill mode. Allocations may happen without adding new groups (for instance,
 * if the transition state size grows), so this check is imperfect.
 */
static void
hash_agg_check_limits(AggState *aggstate)
{
    uint64      ngroups = aggstate->hash_ngroups_current;
    Size        meta_mem = MemoryContextMemAllocated(aggstate->hash_metacxt,
                                                     true);
    Size        entry_mem = MemoryContextMemAllocated(aggstate->hash_tuplescxt,
                                                      true);
    Size        tval_mem = MemoryContextMemAllocated(aggstate->hashcontext->ecxt_per_tuple_memory,
                                                     true);
    Size        total_mem = meta_mem + entry_mem + tval_mem;
    bool        do_spill = false;
 
#ifdef USE_INJECTION_POINTS
    if (ngroups >= 1000)
    {
        if (IS_INJECTION_POINT_ATTACHED("hash-aggregate-spill-1000"))
        {
            do_spill = true;
            INJECTION_POINT_CACHED("hash-aggregate-spill-1000", NULL);
        }
    }
#endif
 
    /*
     * Don't spill unless there's at least one group in the hash table so we
     * can be sure to make progress even in edge cases.
     */
    if (aggstate->hash_ngroups_current > 0 &&
        (total_mem > aggstate->hash_mem_limit ||
         ngroups > aggstate->hash_ngroups_limit))
    {
        do_spill = true;
    }
 
    if (do_spill)
        hash_agg_enter_spill_mode(aggstate);
}
 
/*
 * Enter "spill mode", meaning that no new groups are added to any of the hash
 * tables. Tuples that would create a new group are instead spilled, and
 * processed later.
 */
static void
hash_agg_enter_spill_mode(AggState *aggstate)
{
    INJECTION_POINT("hash-aggregate-enter-spill-mode", NULL);
    aggstate->hash_spill_mode = true;
    hashagg_recompile_expressions(aggstate, aggstate->table_filled, true);
 
    if (!aggstate->hash_ever_spilled)
    {
        Assert(aggstate->hash_tapeset == NULL);
        Assert(aggstate->hash_spills == NULL);
 
        aggstate->hash_ever_spilled = true;
 
        aggstate->hash_tapeset = LogicalTapeSetCreate(true, NULL, -1);
 
        aggstate->hash_spills = palloc_array(HashAggSpill, aggstate->num_hashes);
 
        for (int setno = 0; setno < aggstate->num_hashes; setno++)
        {
            AggStatePerHash perhash = &aggstate->perhash[setno];
            HashAggSpill *spill = &aggstate->hash_spills[setno];
 
            hashagg_spill_init(spill, aggstate->hash_tapeset, 0,
                               perhash->aggnode->numGroups,
                               aggstate->hashentrysize);
        }
    }
}
 
/*
 * Update metrics after filling the hash table.
 *
 * If reading from the outer plan, from_tape should be false; if reading from
 * another tape, from_tape should be true.
 */
static void
hash_agg_update_metrics(AggState *aggstate, bool from_tape, int npartitions)
{
    Size        meta_mem;
    Size        entry_mem;
    Size        hashkey_mem;
    Size        buffer_mem;
    Size        total_mem;
 
    if (aggstate->aggstrategy != AGG_MIXED &&
        aggstate->aggstrategy != AGG_HASHED)
        return;
 
    /* memory for the hash table itself */
    meta_mem = MemoryContextMemAllocated(aggstate->hash_metacxt, true);
 
    /* memory for hash entries */
    entry_mem = MemoryContextMemAllocated(aggstate->hash_tuplescxt, true);
 
    /* memory for byref transition states */
    hashkey_mem = MemoryContextMemAllocated(aggstate->hashcontext->ecxt_per_tuple_memory, true);
 
    /* memory for read/write tape buffers, if spilled */
    buffer_mem = npartitions * HASHAGG_WRITE_BUFFER_SIZE;
    if (from_tape)
        buffer_mem += HASHAGG_READ_BUFFER_SIZE;
 
    /* update peak mem */
    total_mem = meta_mem + entry_mem + hashkey_mem + buffer_mem;
    if (total_mem > aggstate->hash_mem_peak)
        aggstate->hash_mem_peak = total_mem;
 
    /* update disk usage */
    if (aggstate->hash_tapeset != NULL)
    {
        uint64      disk_used = LogicalTapeSetBlocks(aggstate->hash_tapeset) * (BLCKSZ / 1024);
 
        if (aggstate->hash_disk_used < disk_used)
            aggstate->hash_disk_used = disk_used;
    }
 
    /* update hashentrysize estimate based on contents */
    if (aggstate->hash_ngroups_current > 0)
    {
        aggstate->hashentrysize =
            TupleHashEntrySize() +
            (hashkey_mem / (double) aggstate->hash_ngroups_current);
    }
}
 
/*
 * Create memory contexts used for hash aggregation.
 */
static void
hash_create_memory(AggState *aggstate)
{
    Size        maxBlockSize = ALLOCSET_DEFAULT_MAXSIZE;
 
    /*
     * The hashcontext's per-tuple memory will be used for byref transition
     * values and returned by AggCheckCallContext().
     */
    aggstate->hashcontext = CreateWorkExprContext(aggstate->ss.ps.state);
 
    /*
     * The meta context will be used for the bucket array of
     * TupleHashEntryData (or arrays, in the case of grouping sets). As the
     * hash table grows, the bucket array will double in size and the old one
     * will be freed, so an AllocSet is appropriate. For large bucket arrays,
     * the large allocation path will be used, so it's not worth worrying
     * about wasting space due to power-of-two allocations.
     */
    aggstate->hash_metacxt = AllocSetContextCreate(aggstate->ss.ps.state->es_query_cxt,
                                                   "HashAgg meta context",
                                                   ALLOCSET_DEFAULT_SIZES);
 
    /*
     * The hash entries themselves, which include the grouping key
     * (firstTuple) and pergroup data, are stored in the table context. The
     * bump allocator can be used because the entries are not freed until the
     * entire hash table is reset. The bump allocator is faster for
     * allocations and avoids wasting space on the chunk header or
     * power-of-two allocations.
     *
     * Like CreateWorkExprContext(), use smaller sizings for smaller work_mem,
     * to avoid large jumps in memory usage.
     */
 
    /*
     * Like CreateWorkExprContext(), use smaller sizings for smaller work_mem,
     * to avoid large jumps in memory usage.
     */
    maxBlockSize = pg_prevpower2_size_t(work_mem * (Size) 1024 / 16);
 
    /* But no bigger than ALLOCSET_DEFAULT_MAXSIZE */
    maxBlockSize = Min(maxBlockSize, ALLOCSET_DEFAULT_MAXSIZE);
 
    /* and no smaller than ALLOCSET_DEFAULT_INITSIZE */
    maxBlockSize = Max(maxBlockSize, ALLOCSET_DEFAULT_INITSIZE);
 
    aggstate->hash_tuplescxt = BumpContextCreate(aggstate->ss.ps.state->es_query_cxt,
                                                 "HashAgg hashed tuples",
                                                 ALLOCSET_DEFAULT_MINSIZE,
                                                 ALLOCSET_DEFAULT_INITSIZE,
                                                 maxBlockSize);
 
}
 
/*
 * Choose a reasonable number of buckets for the initial hash table size.
 */
static double
hash_choose_num_buckets(double hashentrysize, double ngroups, Size memory)
{
    double      max_nbuckets;
    double      nbuckets = ngroups;
 
    max_nbuckets = memory / hashentrysize;
 
    /*
     * Underestimating is better than overestimating. Too many buckets crowd
     * out space for group keys and transition state values.
     */
    max_nbuckets /= 2;
 
    if (nbuckets > max_nbuckets)
        nbuckets = max_nbuckets;
 
    /*
     * BuildTupleHashTable will clamp any obviously-insane result, so we don't
     * need to be too careful here.
     */
    return nbuckets;
}
 
/*
 * Determine the number of partitions to create when spilling, which will
 * always be a power of two. If log2_npartitions is non-NULL, set
 * *log2_npartitions to the log2() of the number of partitions.
 */
static int
hash_choose_num_partitions(double input_groups, double hashentrysize,
                           int used_bits, int *log2_npartitions)
{
    Size        hash_mem_limit = get_hash_memory_limit();
    double      partition_limit;
    double      mem_wanted;
    double      dpartitions;
    int         npartitions;
    int         partition_bits;
 
    /*
     * Avoid creating so many partitions that the memory requirements of the
     * open partition files are greater than 1/4 of hash_mem.
     */
    partition_limit =
        (hash_mem_limit * 0.25 - HASHAGG_READ_BUFFER_SIZE) /
        HASHAGG_WRITE_BUFFER_SIZE;
 
    mem_wanted = HASHAGG_PARTITION_FACTOR * input_groups * hashentrysize;
 
    /* make enough partitions so that each one is likely to fit in memory */
    dpartitions = 1 + (mem_wanted / hash_mem_limit);
 
    if (dpartitions > partition_limit)
        dpartitions = partition_limit;
 
    if (dpartitions < HASHAGG_MIN_PARTITIONS)
        dpartitions = HASHAGG_MIN_PARTITIONS;
    if (dpartitions > HASHAGG_MAX_PARTITIONS)
        dpartitions = HASHAGG_MAX_PARTITIONS;
 
    /* HASHAGG_MAX_PARTITIONS limit makes this safe */
    npartitions = (int) dpartitions;
 
    /* ceil(log2(npartitions)) */
    partition_bits = pg_ceil_log2_32(npartitions);
 
    /* make sure that we don't exhaust the hash bits */
    if (partition_bits + used_bits >= 32)
        partition_bits = 32 - used_bits;
 
    if (log2_npartitions != NULL)
        *log2_npartitions = partition_bits;
 
    /* number of partitions will be a power of two */
    npartitions = 1 << partition_bits;
 
    return npartitions;
}
 
/*
 * Initialize a freshly-created TupleHashEntry.
 */
static void
initialize_hash_entry(AggState *aggstate, TupleHashTable hashtable,
                      TupleHashEntry entry)
{
    AggStatePerGroup pergroup;
    int         transno;
 
    aggstate->hash_ngroups_current++;
    hash_agg_check_limits(aggstate);
 
    /* no need to allocate or initialize per-group state */
    if (aggstate->numtrans == 0)
        return;
 
    pergroup = (AggStatePerGroup) TupleHashEntryGetAdditional(hashtable, entry);
 
    /*
     * Initialize aggregates for new tuple group, lookup_hash_entries()
     * already has selected the relevant grouping set.
     */
    for (transno = 0; transno < aggstate->numtrans; transno++)
    {
        AggStatePerTrans pertrans = &aggstate->pertrans[transno];
        AggStatePerGroup pergroupstate = &pergroup[transno];
 
        initialize_aggregate(aggstate, pertrans, pergroupstate);
    }
}
 
/*
 * Look up hash entries for the current tuple in all hashed grouping sets.
 *
 * Some entries may be left NULL if we are in "spill mode". The same tuple
 * will belong to different groups for each grouping set, so may match a group
 * already in memory for one set and match a group not in memory for another
 * set. When in "spill mode", the tuple will be spilled for each grouping set
 * where it doesn't match a group in memory.
 *
 * NB: It's possible to spill the same tuple for several different grouping
 * sets. This may seem wasteful, but it's actually a trade-off: if we spill
 * the tuple multiple times for multiple grouping sets, it can be partitioned
 * for each grouping set, making the refilling of the hash table very
 * efficient.
 */
static void
lookup_hash_entries(AggState *aggstate)
{
    AggStatePerGroup *pergroup = aggstate->hash_pergroup;
    TupleTableSlot *outerslot = aggstate->tmpcontext->ecxt_outertuple;
    int         setno;
 
    for (setno = 0; setno < aggstate->num_hashes; setno++)
    {
        AggStatePerHash perhash = &aggstate->perhash[setno];
        TupleHashTable hashtable = perhash->hashtable;
        TupleTableSlot *hashslot = perhash->hashslot;
        TupleHashEntry entry;
        uint32      hash;
        bool        isnew = false;
        bool       *p_isnew;
 
        /* if hash table already spilled, don't create new entries */
        p_isnew = aggstate->hash_spill_mode ? NULL : &isnew;
 
        select_current_set(aggstate, setno, true);
        prepare_hash_slot(perhash,
                          outerslot,
                          hashslot);
 
        entry = LookupTupleHashEntry(hashtable, hashslot,
                                     p_isnew, &hash);
 
        if (entry != NULL)
        {
            if (isnew)
                initialize_hash_entry(aggstate, hashtable, entry);
            pergroup[setno] = TupleHashEntryGetAdditional(hashtable, entry);
        }
        else
        {
            HashAggSpill *spill = &aggstate->hash_spills[setno];
            TupleTableSlot *slot = aggstate->tmpcontext->ecxt_outertuple;
 
            if (spill->partitions == NULL)
                hashagg_spill_init(spill, aggstate->hash_tapeset, 0,
                                   perhash->aggnode->numGroups,
                                   aggstate->hashentrysize);
 
            hashagg_spill_tuple(aggstate, spill, slot, hash);
            pergroup[setno] = NULL;
        }
    }
}
 
/*
 * ExecAgg -
 *
 *    ExecAgg receives tuples from its outer subplan and aggregates over
 *    the appropriate attribute for each aggregate function use (Aggref
 *    node) appearing in the targetlist or qual of the node.  The number
 *    of tuples to aggregate over depends on whether grouped or plain
 *    aggregation is selected.  In grouped aggregation, we produce a result
 *    row for each group; in plain aggregation there's a single result row
 *    for the whole query.  In either case, the value of each aggregate is
 *    stored in the expression context to be used when ExecProject evaluates
 *    the result tuple.
 */
static TupleTableSlot *
ExecAgg(PlanState *pstate)
{
    AggState   *node = castNode(AggState, pstate);
    TupleTableSlot *result = NULL;
 
    CHECK_FOR_INTERRUPTS();
 
    if (!node->agg_done)
    {
        /* Dispatch based on strategy */
        switch (node->phase->aggstrategy)
        {
            case AGG_HASHED:
                if (!node->table_filled)
                    agg_fill_hash_table(node);
                /* FALLTHROUGH */
            case AGG_MIXED:
                result = agg_retrieve_hash_table(node);
                break;
            case AGG_PLAIN:
            case AGG_SORTED:
                result = agg_retrieve_direct(node);
                break;
        }
 
        if (!TupIsNull(result))
            return result;
    }
 
    return NULL;
}
 
/*
 * ExecAgg for non-hashed case
 */
static TupleTableSlot *
agg_retrieve_direct(AggState *aggstate)
{
    Agg        *node = aggstate->phase->aggnode;
    ExprContext *econtext;
    ExprContext *tmpcontext;
    AggStatePerAgg peragg;
    AggStatePerGroup *pergroups;
    TupleTableSlot *outerslot;
    TupleTableSlot *firstSlot;
    TupleTableSlot *result;
    bool        hasGroupingSets = aggstate->phase->numsets > 0;
    int         numGroupingSets = Max(aggstate->phase->numsets, 1);
    int         currentSet;
    int         nextSetSize;
    int         numReset;
    int         i;
 
    /*
     * get state info from node
     *
     * econtext is the per-output-tuple expression context
     *
     * tmpcontext is the per-input-tuple expression context
     */
    econtext = aggstate->ss.ps.ps_ExprContext;
    tmpcontext = aggstate->tmpcontext;
 
    peragg = aggstate->peragg;
    pergroups = aggstate->pergroups;
    firstSlot = aggstate->ss.ss_ScanTupleSlot;
 
    /*
     * We loop retrieving groups until we find one matching
     * aggstate->ss.ps.qual
     *
     * For grouping sets, we have the invariant that aggstate->projected_set
     * is either -1 (initial call) or the index (starting from 0) in
     * gset_lengths for the group we just completed (either by projecting a
     * row or by discarding it in the qual).
     */
    while (!aggstate->agg_done)
    {
        /*
         * Clear the per-output-tuple context for each group, as well as
         * aggcontext (which contains any pass-by-ref transvalues of the old
         * group).  Some aggregate functions store working state in child
         * contexts; those now get reset automatically without us needing to
         * do anything special.
         *
         * We use ReScanExprContext not just ResetExprContext because we want
         * any registered shutdown callbacks to be called.  That allows
         * aggregate functions to ensure they've cleaned up any non-memory
         * resources.
         */
        ReScanExprContext(econtext);
 
        /*
         * Determine how many grouping sets need to be reset at this boundary.
         */
        if (aggstate->projected_set >= 0 &&
            aggstate->projected_set < numGroupingSets)
            numReset = aggstate->projected_set + 1;
        else
            numReset = numGroupingSets;
 
        /*
         * numReset can change on a phase boundary, but that's OK; we want to
         * reset the contexts used in _this_ phase, and later, after possibly
         * changing phase, initialize the right number of aggregates for the
         * _new_ phase.
         */
 
        for (i = 0; i < numReset; i++)
        {
            ReScanExprContext(aggstate->aggcontexts[i]);
        }
 
        /*
         * Check if input is complete and there are no more groups to project
         * in this phase; move to next phase or mark as done.
         */
        if (aggstate->input_done == true &&
            aggstate->projected_set >= (numGroupingSets - 1))
        {
            if (aggstate->current_phase < aggstate->numphases - 1)
            {
                initialize_phase(aggstate, aggstate->current_phase + 1);
                aggstate->input_done = false;
                aggstate->projected_set = -1;
                numGroupingSets = Max(aggstate->phase->numsets, 1);
                node = aggstate->phase->aggnode;
                numReset = numGroupingSets;
            }
            else if (aggstate->aggstrategy == AGG_MIXED)
            {
                /*
                 * Mixed mode; we've output all the grouped stuff and have
                 * full hashtables, so switch to outputting those.
                 */
                initialize_phase(aggstate, 0);
                aggstate->table_filled = true;
                ResetTupleHashIterator(aggstate->perhash[0].hashtable,
                                       &aggstate->perhash[0].hashiter);
                select_current_set(aggstate, 0, true);
                return agg_retrieve_hash_table(aggstate);
            }
            else
            {
                aggstate->agg_done = true;
                break;
            }
        }
 
        /*
         * Get the number of columns in the next grouping set after the last
         * projected one (if any). This is the number of columns to compare to
         * see if we reached the boundary of that set too.
         */
        if (aggstate->projected_set >= 0 &&
            aggstate->projected_set < (numGroupingSets - 1))
            nextSetSize = aggstate->phase->gset_lengths[aggstate->projected_set + 1];
        else
            nextSetSize = 0;
 
        /*----------
         * If a subgroup for the current grouping set is present, project it.
         *
         * We have a new group if:
         *  - we're out of input but haven't projected all grouping sets
         *    (checked above)
         * OR
         *    - we already projected a row that wasn't from the last grouping
         *      set
         *    AND
         *    - the next grouping set has at least one grouping column (since
         *      empty grouping sets project only once input is exhausted)
         *    AND
         *    - the previous and pending rows differ on the grouping columns
         *      of the next grouping set
         *----------
         */
        tmpcontext->ecxt_innertuple = econtext->ecxt_outertuple;
        if (aggstate->input_done ||
            (node->aggstrategy != AGG_PLAIN &&
             aggstate->projected_set != -1 &&
             aggstate->projected_set < (numGroupingSets - 1) &&
             nextSetSize > 0 &&
             !ExecQualAndReset(aggstate->phase->eqfunctions[nextSetSize - 1],
                               tmpcontext)))
        {
            aggstate->projected_set += 1;
 
            Assert(aggstate->projected_set < numGroupingSets);
            Assert(nextSetSize > 0 || aggstate->input_done);
        }
        else
        {
            /*
             * We no longer care what group we just projected, the next
             * projection will always be the first (or only) grouping set
             * (unless the input proves to be empty).
             */
            aggstate->projected_set = 0;
 
            /*
             * If we don't already have the first tuple of the new group,
             * fetch it from the outer plan.
             */
            if (aggstate->grp_firstTuple == NULL)
            {
                outerslot = fetch_input_tuple(aggstate);
                if (!TupIsNull(outerslot))
                {
                    /*
                     * Make a copy of the first input tuple; we will use this
                     * for comparisons (in group mode) and for projection.
                     */
                    aggstate->grp_firstTuple = ExecCopySlotHeapTuple(outerslot);
                }
                else
                {
                    /* outer plan produced no tuples at all */
                    if (hasGroupingSets)
                    {
                        /*
                         * If there was no input at all, we need to project
                         * rows only if there are grouping sets of size 0.
                         * Note that this implies that there can't be any
                         * references to ungrouped Vars, which would otherwise
                         * cause issues with the empty output slot.
                         *
                         * XXX: This is no longer true, we currently deal with
                         * this in finalize_aggregates().
                         */
                        aggstate->input_done = true;
 
                        while (aggstate->phase->gset_lengths[aggstate->projected_set] > 0)
                        {
                            aggstate->projected_set += 1;
                            if (aggstate->projected_set >= numGroupingSets)
                            {
                                /*
                                 * We can't set agg_done here because we might
                                 * have more phases to do, even though the
                                 * input is empty. So we need to restart the
                                 * whole outer loop.
                                 */
                                break;
                            }
                        }
 
                        if (aggstate->projected_set >= numGroupingSets)
                            continue;
                    }
                    else
                    {
                        aggstate->agg_done = true;
                        /* If we are grouping, we should produce no tuples too */
                        if (node->aggstrategy != AGG_PLAIN)
                            return NULL;
                    }
                }
            }
 
            /*
             * Initialize working state for a new input tuple group.
             */
            initialize_aggregates(aggstate, pergroups, numReset);
 
            if (aggstate->grp_firstTuple != NULL)
            {
                /*
                 * Store the copied first input tuple in the tuple table slot
                 * reserved for it.  The tuple will be deleted when it is
                 * cleared from the slot.
                 */
                ExecForceStoreHeapTuple(aggstate->grp_firstTuple,
                                        firstSlot, true);
                aggstate->grp_firstTuple = NULL;    /* don't keep two pointers */
 
                /* set up for first advance_aggregates call */
                tmpcontext->ecxt_outertuple = firstSlot;
 
                /*
                 * Process each outer-plan tuple, and then fetch the next one,
                 * until we exhaust the outer plan or cross a group boundary.
                 */
                for (;;)
                {
                    /*
                     * During phase 1 only of a mixed agg, we need to update
                     * hashtables as well in advance_aggregates.
                     */
                    if (aggstate->aggstrategy == AGG_MIXED &&
                        aggstate->current_phase == 1)
                    {
                        lookup_hash_entries(aggstate);
                    }
 
                    /* Advance the aggregates (or combine functions) */
                    advance_aggregates(aggstate);
 
                    /* Reset per-input-tuple context after each tuple */
                    ResetExprContext(tmpcontext);
 
                    outerslot = fetch_input_tuple(aggstate);
                    if (TupIsNull(outerslot))
                    {
                        /* no more outer-plan tuples available */
 
                        /* if we built hash tables, finalize any spills */
                        if (aggstate->aggstrategy == AGG_MIXED &&
                            aggstate->current_phase == 1)
                            hashagg_finish_initial_spills(aggstate);
 
                        if (hasGroupingSets)
                        {
                            aggstate->input_done = true;
                            break;
                        }
                        else
                        {
                            aggstate->agg_done = true;
                            break;
                        }
                    }
                    /* set up for next advance_aggregates call */
                    tmpcontext->ecxt_outertuple = outerslot;
 
                    /*
                     * If we are grouping, check whether we've crossed a group
                     * boundary.
                     */
                    if (node->aggstrategy != AGG_PLAIN && node->numCols > 0)
                    {
                        tmpcontext->ecxt_innertuple = firstSlot;
                        if (!ExecQual(aggstate->phase->eqfunctions[node->numCols - 1],
                                      tmpcontext))
                        {
                            aggstate->grp_firstTuple = ExecCopySlotHeapTuple(outerslot);
                            break;
                        }
                    }
                }
            }
 
            /*
             * Use the representative input tuple for any references to
             * non-aggregated input columns in aggregate direct args, the node
             * qual, and the tlist.  (If we are not grouping, and there are no
             * input rows at all, we will come here with an empty firstSlot
             * ... but if not grouping, there can't be any references to
             * non-aggregated input columns, so no problem.)
             */
            econtext->ecxt_outertuple = firstSlot;
        }
 
        Assert(aggstate->projected_set >= 0);
 
        currentSet = aggstate->projected_set;
 
        prepare_projection_slot(aggstate, econtext->ecxt_outertuple, currentSet);
 
        select_current_set(aggstate, currentSet, false);
 
        finalize_aggregates(aggstate,
                            peragg,
                            pergroups[currentSet]);
 
        /*
         * If there's no row to project right now, we must continue rather
         * than returning a null since there might be more groups.
         */
        result = project_aggregates(aggstate);
        if (result)
            return result;
    }
 
    /* No more groups */
    return NULL;
}
 
/*
 * ExecAgg for hashed case: read input and build hash table
 */
static void
agg_fill_hash_table(AggState *aggstate)
{
    TupleTableSlot *outerslot;
    ExprContext *tmpcontext = aggstate->tmpcontext;
 
    /*
     * Process each outer-plan tuple, and then fetch the next one, until we
     * exhaust the outer plan.
     */
    for (;;)
    {
        outerslot = fetch_input_tuple(aggstate);
        if (TupIsNull(outerslot))
            break;
 
        /* set up for lookup_hash_entries and advance_aggregates */
        tmpcontext->ecxt_outertuple = outerslot;
 
        /* Find or build hashtable entries */
        lookup_hash_entries(aggstate);
 
        /* Advance the aggregates (or combine functions) */
        advance_aggregates(aggstate);
 
        /*
         * Reset per-input-tuple context after each tuple, but note that the
         * hash lookups do this too
         */
        ResetExprContext(aggstate->tmpcontext);
    }
 
    /* finalize spills, if any */
    hashagg_finish_initial_spills(aggstate);
 
    aggstate->table_filled = true;
    /* Initialize to walk the first hash table */
    select_current_set(aggstate, 0, true);
    ResetTupleHashIterator(aggstate->perhash[0].hashtable,
                           &aggstate->perhash[0].hashiter);
}
 
/*
 * If any data was spilled during hash aggregation, reset the hash table and
 * reprocess one batch of spilled data. After reprocessing a batch, the hash
 * table will again contain data, ready to be consumed by
 * agg_retrieve_hash_table_in_memory().
 *
 * Should only be called after all in memory hash table entries have been
 * finalized and emitted.
 *
 * Return false when input is exhausted and there's no more work to be done;
 * otherwise return true.
 */
static bool
agg_refill_hash_table(AggState *aggstate)
{
    HashAggBatch *batch;
    AggStatePerHash perhash;
    HashAggSpill spill;
    LogicalTapeSet *tapeset = aggstate->hash_tapeset;
    bool        spill_initialized = false;
 
    if (aggstate->hash_batches == NIL)
        return false;
 
    /* hash_batches is a stack, with the top item at the end of the list */
    batch = llast(aggstate->hash_batches);
    aggstate->hash_batches = list_delete_last(aggstate->hash_batches);
 
    hash_agg_set_limits(aggstate->hashentrysize, batch->input_card,
                        batch->used_bits, &aggstate->hash_mem_limit,
                        &aggstate->hash_ngroups_limit, NULL);
 
    /*
     * Each batch only processes one grouping set; set the rest to NULL so
     * that advance_aggregates() knows to ignore them. We don't touch
     * pergroups for sorted grouping sets here, because they will be needed if
     * we rescan later. The expressions for sorted grouping sets will not be
     * evaluated after we recompile anyway.
     */
    MemSet(aggstate->hash_pergroup, 0,
           sizeof(AggStatePerGroup) * aggstate->num_hashes);
 
    /* free memory and reset hash tables */
    ReScanExprContext(aggstate->hashcontext);
    for (int setno = 0; setno < aggstate->num_hashes; setno++)
        ResetTupleHashTable(aggstate->perhash[setno].hashtable);
 
    aggstate->hash_ngroups_current = 0;
 
    /*
     * In AGG_MIXED mode, hash aggregation happens in phase 1 and the output
     * happens in phase 0. So, we switch to phase 1 when processing a batch,
     * and back to phase 0 after the batch is done.
     */
    Assert(aggstate->current_phase == 0);
    if (aggstate->phase->aggstrategy == AGG_MIXED)
    {
        aggstate->current_phase = 1;
        aggstate->phase = &aggstate->phases[aggstate->current_phase];
    }
 
    select_current_set(aggstate, batch->setno, true);
 
    perhash = &aggstate->perhash[aggstate->current_set];
 
    /*
     * Spilled tuples are always read back as MinimalTuples, which may be
     * different from the outer plan, so recompile the aggregate expressions.
     *
     * We still need the NULL check, because we are only processing one
     * grouping set at a time and the rest will be NULL.
     */
    hashagg_recompile_expressions(aggstate, true, true);
 
    INJECTION_POINT("hash-aggregate-process-batch", NULL);
    for (;;)
    {
        TupleTableSlot *spillslot = aggstate->hash_spill_rslot;
        TupleTableSlot *hashslot = perhash->hashslot;
        TupleHashTable hashtable = perhash->hashtable;
        TupleHashEntry entry;
        MinimalTuple tuple;
        uint32      hash;
        bool        isnew = false;
        bool       *p_isnew = aggstate->hash_spill_mode ? NULL : &isnew;
 
        CHECK_FOR_INTERRUPTS();
 
        tuple = hashagg_batch_read(batch, &hash);
        if (tuple == NULL)
            break;
 
        ExecStoreMinimalTuple(tuple, spillslot, true);
        aggstate->tmpcontext->ecxt_outertuple = spillslot;
 
        prepare_hash_slot(perhash,
                          aggstate->tmpcontext->ecxt_outertuple,
                          hashslot);
        entry = LookupTupleHashEntryHash(hashtable, hashslot,
                                         p_isnew, hash);
 
        if (entry != NULL)
        {
            if (isnew)
                initialize_hash_entry(aggstate, hashtable, entry);
            aggstate->hash_pergroup[batch->setno] = TupleHashEntryGetAdditional(hashtable, entry);
            advance_aggregates(aggstate);
        }
        else
        {
            if (!spill_initialized)
            {
                /*
                 * Avoid initializing the spill until we actually need it so
                 * that we don't assign tapes that will never be used.
                 */
                spill_initialized = true;
                hashagg_spill_init(&spill, tapeset, batch->used_bits,
                                   batch->input_card, aggstate->hashentrysize);
            }
            /* no memory for a new group, spill */
            hashagg_spill_tuple(aggstate, &spill, spillslot, hash);
 
            aggstate->hash_pergroup[batch->setno] = NULL;
        }
 
        /*
         * Reset per-input-tuple context after each tuple, but note that the
         * hash lookups do this too
         */
        ResetExprContext(aggstate->tmpcontext);
    }
 
    LogicalTapeClose(batch->input_tape);
 
    /* change back to phase 0 */
    aggstate->current_phase = 0;
    aggstate->phase = &aggstate->phases[aggstate->current_phase];
 
    if (spill_initialized)
    {
        hashagg_spill_finish(aggstate, &spill, batch->setno);
        hash_agg_update_metrics(aggstate, true, spill.npartitions);
    }
    else
        hash_agg_update_metrics(aggstate, true, 0);
 
    aggstate->hash_spill_mode = false;
 
    /* prepare to walk the first hash table */
    select_current_set(aggstate, batch->setno, true);
    ResetTupleHashIterator(aggstate->perhash[batch->setno].hashtable,
                           &aggstate->perhash[batch->setno].hashiter);
 
    pfree(batch);
 
    return true;
}
 
/*
 * ExecAgg for hashed case: retrieving groups from hash table
 *
 * After exhausting in-memory tuples, also try refilling the hash table using
 * previously-spilled tuples. Only returns NULL after all in-memory and
 * spilled tuples are exhausted.
 */
static TupleTableSlot *
agg_retrieve_hash_table(AggState *aggstate)
{
    TupleTableSlot *result = NULL;
 
    while (result == NULL)
    {
        result = agg_retrieve_hash_table_in_memory(aggstate);
        if (result == NULL)
        {
            if (!agg_refill_hash_table(aggstate))
            {
                aggstate->agg_done = true;
                break;
            }
        }
    }
 
    return result;
}
 
/*
 * Retrieve the groups from the in-memory hash tables without considering any
 * spilled tuples.
 */
static TupleTableSlot *
agg_retrieve_hash_table_in_memory(AggState *aggstate)
{
    ExprContext *econtext;
    AggStatePerAgg peragg;
    AggStatePerGroup pergroup;
    TupleHashEntry entry;
    TupleTableSlot *firstSlot;
    TupleTableSlot *result;
    AggStatePerHash perhash;
 
    /*
     * get state info from node.
     *
     * econtext is the per-output-tuple expression context.
     */
    econtext = aggstate->ss.ps.ps_ExprContext;
    peragg = aggstate->peragg;
    firstSlot = aggstate->ss.ss_ScanTupleSlot;
 
    /*
     * Note that perhash (and therefore anything accessed through it) can
     * change inside the loop, as we change between grouping sets.
     */
    perhash = &aggstate->perhash[aggstate->current_set];
 
    /*
     * We loop retrieving groups until we find one satisfying
     * aggstate->ss.ps.qual
     */
    for (;;)
    {
        TupleTableSlot *hashslot = perhash->hashslot;
        TupleHashTable hashtable = perhash->hashtable;
        int         i;
 
        CHECK_FOR_INTERRUPTS();
 
        /*
         * Find the next entry in the hash table
         */
        entry = ScanTupleHashTable(hashtable, &perhash->hashiter);
        if (entry == NULL)
        {
            int         nextset = aggstate->current_set + 1;
 
            if (nextset < aggstate->num_hashes)
            {
                /*
                 * Switch to next grouping set, reinitialize, and restart the
                 * loop.
                 */
                select_current_set(aggstate, nextset, true);
 
                perhash = &aggstate->perhash[aggstate->current_set];
 
                ResetTupleHashIterator(perhash->hashtable, &perhash->hashiter);
 
                continue;
            }
            else
            {
                return NULL;
            }
        }
 
        /*
         * Clear the per-output-tuple context for each group
         *
         * We intentionally don't use ReScanExprContext here; if any aggs have
         * registered shutdown callbacks, they mustn't be called yet, since we
         * might not be done with that agg.
         */
        ResetExprContext(econtext);
 
        /*
         * Transform representative tuple back into one with the right
         * columns.
         */
        ExecStoreMinimalTuple(TupleHashEntryGetTuple(entry), hashslot, false);
        slot_getallattrs(hashslot);
 
        ExecClearTuple(firstSlot);
        memset(firstSlot->tts_isnull, true,
               firstSlot->tts_tupleDescriptor->natts * sizeof(bool));
 
        for (i = 0; i < perhash->numhashGrpCols; i++)
        {
            int         varNumber = perhash->hashGrpColIdxInput[i] - 1;
 
            firstSlot->tts_values[varNumber] = hashslot->tts_values[i];
            firstSlot->tts_isnull[varNumber] = hashslot->tts_isnull[i];
        }
        ExecStoreVirtualTuple(firstSlot);
 
        pergroup = (AggStatePerGroup) TupleHashEntryGetAdditional(hashtable, entry);
 
        /*
         * Use the representative input tuple for any references to
         * non-aggregated input columns in the qual and tlist.
         */
        econtext->ecxt_outertuple = firstSlot;
 
        prepare_projection_slot(aggstate,
                                econtext->ecxt_outertuple,
                                aggstate->current_set);
 
        finalize_aggregates(aggstate, peragg, pergroup);
 
        result = project_aggregates(aggstate);
        if (result)
            return result;
    }
 
    /* No more groups */
    return NULL;
}
 
/*
 * hashagg_spill_init
 *
 * Called after we determined that spilling is necessary. Chooses the number
 * of partitions to create, and initializes them.
 */
static void
hashagg_spill_init(HashAggSpill *spill, LogicalTapeSet *tapeset, int used_bits,
                   double input_groups, double hashentrysize)
{
    int         npartitions;
    int         partition_bits;
 
    npartitions = hash_choose_num_partitions(input_groups, hashentrysize,
                                             used_bits, &partition_bits);
 
#ifdef USE_INJECTION_POINTS
    if (IS_INJECTION_POINT_ATTACHED("hash-aggregate-single-partition"))
    {
        npartitions = 1;
        partition_bits = 0;
        INJECTION_POINT_CACHED("hash-aggregate-single-partition", NULL);
    }
#endif
 
    spill->partitions = palloc0_array(LogicalTape *, npartitions);
    spill->ntuples = palloc0_array(int64, npartitions);
    spill->hll_card = palloc0_array(hyperLogLogState, npartitions);
 
    for (int i = 0; i < npartitions; i++)
        spill->partitions[i] = LogicalTapeCreate(tapeset);
 
    spill->shift = 32 - used_bits - partition_bits;
    if (spill->shift < 32)
        spill->mask = (npartitions - 1) << spill->shift;
    else
        spill->mask = 0;
    spill->npartitions = npartitions;
 
    for (int i = 0; i < npartitions; i++)
        initHyperLogLog(&spill->hll_card[i], HASHAGG_HLL_BIT_WIDTH);
}
 
/*
 * hashagg_spill_tuple
 *
 * No room for new groups in the hash table. Save for later in the appropriate
 * partition.
 */
static Size
hashagg_spill_tuple(AggState *aggstate, HashAggSpill *spill,
                    TupleTableSlot *inputslot, uint32 hash)
{
    TupleTableSlot *spillslot;
    int         partition;
    MinimalTuple tuple;
    LogicalTape *tape;
    int         total_written = 0;
    bool        shouldFree;
 
    Assert(spill->partitions != NULL);
 
    /* spill only attributes that we actually need */
    if (!aggstate->all_cols_needed)
    {
        spillslot = aggstate->hash_spill_wslot;
        slot_getsomeattrs(inputslot, aggstate->max_colno_needed);
        ExecClearTuple(spillslot);
        for (int i = 0; i < spillslot->tts_tupleDescriptor->natts; i++)
        {
            if (bms_is_member(i + 1, aggstate->colnos_needed))
            {
                spillslot->tts_values[i] = inputslot->tts_values[i];
                spillslot->tts_isnull[i] = inputslot->tts_isnull[i];
            }
            else
                spillslot->tts_isnull[i] = true;
        }
        ExecStoreVirtualTuple(spillslot);
    }
    else
        spillslot = inputslot;
 
    tuple = ExecFetchSlotMinimalTuple(spillslot, &shouldFree);
 
    if (spill->shift < 32)
        partition = (hash & spill->mask) >> spill->shift;
    else
        partition = 0;
 
    spill->ntuples[partition]++;
 
    /*
     * All hash values destined for a given partition have some bits in
     * common, which causes bad HLL cardinality estimates. Hash the hash to
     * get a more uniform distribution.
     */
    addHyperLogLog(&spill->hll_card[partition], hash_bytes_uint32(hash));
 
    tape = spill->partitions[partition];
 
    LogicalTapeWrite(tape, &hash, sizeof(uint32));
    total_written += sizeof(uint32);
 
    LogicalTapeWrite(tape, tuple, tuple->t_len);
    total_written += tuple->t_len;
 
    if (shouldFree)
        pfree(tuple);
 
    return total_written;
}
 
/*
 * hashagg_batch_new
 *
 * Construct a HashAggBatch item, which represents one iteration of HashAgg to
 * be done.
 */
static HashAggBatch *
hashagg_batch_new(LogicalTape *input_tape, int setno,
                  int64 input_tuples, double input_card, int used_bits)
{
    HashAggBatch *batch = palloc0_object(HashAggBatch);
 
    batch->setno = setno;
    batch->used_bits = used_bits;
    batch->input_tape = input_tape;
    batch->input_tuples = input_tuples;
    batch->input_card = input_card;
 
    return batch;
}
 
/*
 * hashagg_batch_read
 *      read the next tuple from a batch's tape.  Return NULL if no more.
 */
static MinimalTuple
hashagg_batch_read(HashAggBatch *batch, uint32 *hashp)
{
    LogicalTape *tape = batch->input_tape;
    MinimalTuple tuple;
    uint32      t_len;
    size_t      nread;
    uint32      hash;
 
    nread = LogicalTapeRead(tape, &hash, sizeof(uint32));
    if (nread == 0)
        return NULL;
    if (nread != sizeof(uint32))
        ereport(ERROR,
                (errcode_for_file_access(),
                 errmsg_internal("unexpected EOF for tape %p: requested %zu bytes, read %zu bytes",
                                 tape, sizeof(uint32), nread)));
    if (hashp != NULL)
        *hashp = hash;
 
    nread = LogicalTapeRead(tape, &t_len, sizeof(t_len));
    if (nread != sizeof(uint32))
        ereport(ERROR,
                (errcode_for_file_access(),
                 errmsg_internal("unexpected EOF for tape %p: requested %zu bytes, read %zu bytes",
                                 tape, sizeof(uint32), nread)));
 
    tuple = (MinimalTuple) palloc(t_len);
    tuple->t_len = t_len;
 
    nread = LogicalTapeRead(tape,
                            (char *) tuple + sizeof(uint32),
                            t_len - sizeof(uint32));
    if (nread != t_len - sizeof(uint32))
        ereport(ERROR,
                (errcode_for_file_access(),
                 errmsg_internal("unexpected EOF for tape %p: requested %zu bytes, read %zu bytes",
                                 tape, t_len - sizeof(uint32), nread)));
 
    return tuple;
}
 
/*
 * hashagg_finish_initial_spills
 *
 * After a HashAggBatch has been processed, it may have spilled tuples to
 * disk. If so, turn the spilled partitions into new batches that must later
 * be executed.
 */
static void
hashagg_finish_initial_spills(AggState *aggstate)
{
    int         setno;
    int         total_npartitions = 0;
 
    if (aggstate->hash_spills != NULL)
    {
        for (setno = 0; setno < aggstate->num_hashes; setno++)
        {
            HashAggSpill *spill = &aggstate->hash_spills[setno];
 
            total_npartitions += spill->npartitions;
            hashagg_spill_finish(aggstate, spill, setno);
        }
 
        /*
         * We're not processing tuples from outer plan any more; only
         * processing batches of spilled tuples. The initial spill structures
         * are no longer needed.
         */
        pfree(aggstate->hash_spills);
        aggstate->hash_spills = NULL;
    }
 
    hash_agg_update_metrics(aggstate, false, total_npartitions);
    aggstate->hash_spill_mode = false;
}
 
/*
 * hashagg_spill_finish
 *
 * Transform spill partitions into new batches.
 */
static void
hashagg_spill_finish(AggState *aggstate, HashAggSpill *spill, int setno)
{
    int         i;
    int         used_bits = 32 - spill->shift;
 
    if (spill->npartitions == 0)
        return;                 /* didn't spill */
 
    for (i = 0; i < spill->npartitions; i++)
    {
        LogicalTape *tape = spill->partitions[i];
        HashAggBatch *new_batch;
        double      cardinality;
 
        /* if the partition is empty, don't create a new batch of work */
        if (spill->ntuples[i] == 0)
            continue;
 
        cardinality = estimateHyperLogLog(&spill->hll_card[i]);
        freeHyperLogLog(&spill->hll_card[i]);
 
        /* rewinding frees the buffer while not in use */
        LogicalTapeRewindForRead(tape, HASHAGG_READ_BUFFER_SIZE);
 
        new_batch = hashagg_batch_new(tape, setno,
                                      spill->ntuples[i], cardinality,
                                      used_bits);
        aggstate->hash_batches = lappend(aggstate->hash_batches, new_batch);
        aggstate->hash_batches_used++;
    }
 
    pfree(spill->ntuples);
    pfree(spill->hll_card);
    pfree(spill->partitions);
}
 
/*
 * Free resources related to a spilled HashAgg.
 */
static void
hashagg_reset_spill_state(AggState *aggstate)
{
    /* free spills from initial pass */
    if (aggstate->hash_spills != NULL)
    {
        int         setno;
 
        for (setno = 0; setno < aggstate->num_hashes; setno++)
        {
            HashAggSpill *spill = &aggstate->hash_spills[setno];
 
            pfree(spill->ntuples);
            pfree(spill->partitions);
        }
        pfree(aggstate->hash_spills);
        aggstate->hash_spills = NULL;
    }
 
    /* free batches */
    list_free_deep(aggstate->hash_batches);
    aggstate->hash_batches = NIL;
 
    /* close tape set */
    if (aggstate->hash_tapeset != NULL)
    {
        LogicalTapeSetClose(aggstate->hash_tapeset);
        aggstate->hash_tapeset = NULL;
    }
}
 
 
/* -----------------
 * ExecInitAgg
 *
 *  Creates the run-time information for the agg node produced by the
 *  planner and initializes its outer subtree.
 *
 * -----------------
 */
AggState *
ExecInitAgg(Agg *node, EState *estate, int eflags)
{
    AggState   *aggstate;
    AggStatePerAgg peraggs;
    AggStatePerTrans pertransstates;
    AggStatePerGroup *pergroups;
    Plan       *outerPlan;
    ExprContext *econtext;
    TupleDesc   scanDesc;
    int         max_aggno;
    int         max_transno;
    int         numaggrefs;
    int         numaggs;
    int         numtrans;
    int         phase;
    int         phaseidx;
    ListCell   *l;
    Bitmapset  *all_grouped_cols = NULL;
    int         numGroupingSets = 1;
    int         numPhases;
    int         numHashes;
    int         i = 0;
    int         j = 0;
    bool        use_hashing = (node->aggstrategy == AGG_HASHED ||
                               node->aggstrategy == AGG_MIXED);
 
    /* check for unsupported flags */
    Assert(!(eflags & (EXEC_FLAG_BACKWARD | EXEC_FLAG_MARK)));
 
    /*
     * create state structure
     */
    aggstate = makeNode(AggState);
    aggstate->ss.ps.plan = (Plan *) node;
    aggstate->ss.ps.state = estate;
    aggstate->ss.ps.ExecProcNode = ExecAgg;
 
    aggstate->aggs = NIL;
    aggstate->numaggs = 0;
    aggstate->numtrans = 0;
    aggstate->aggstrategy = node->aggstrategy;
    aggstate->aggsplit = node->aggsplit;
    aggstate->maxsets = 0;
    aggstate->projected_set = -1;
    aggstate->current_set = 0;
    aggstate->peragg = NULL;
    aggstate->pertrans = NULL;
    aggstate->curperagg = NULL;
    aggstate->curpertrans = NULL;
    aggstate->input_done = false;
    aggstate->agg_done = false;
    aggstate->pergroups = NULL;
    aggstate->grp_firstTuple = NULL;
    aggstate->sort_in = NULL;
    aggstate->sort_out = NULL;
 
    /*
     * phases[0] always exists, but is dummy in sorted/plain mode
     */
    numPhases = (use_hashing ? 1 : 2);
    numHashes = (use_hashing ? 1 : 0);
 
    /*
     * Calculate the maximum number of grouping sets in any phase; this
     * determines the size of some allocations.  Also calculate the number of
     * phases, since all hashed/mixed nodes contribute to only a single phase.
     */
    if (node->groupingSets)
    {
        numGroupingSets = list_length(node->groupingSets);
 
        foreach(l, node->chain)
        {
            Agg        *agg = lfirst(l);
 
            numGroupingSets = Max(numGroupingSets,
                                  list_length(agg->groupingSets));
 
            /*
             * additional AGG_HASHED aggs become part of phase 0, but all
             * others add an extra phase.
             */
            if (agg->aggstrategy != AGG_HASHED)
                ++numPhases;
            else
                ++numHashes;
        }
    }
 
    aggstate->maxsets = numGroupingSets;
    aggstate->numphases = numPhases;
 
    aggstate->aggcontexts = palloc0_array(ExprContext *, numGroupingSets);
 
    /*
     * Create expression contexts.  We need three or more, one for
     * per-input-tuple processing, one for per-output-tuple processing, one
     * for all the hashtables, and one for each grouping set.  The per-tuple
     * memory context of the per-grouping-set ExprContexts (aggcontexts)
     * replaces the standalone memory context formerly used to hold transition
     * values.  We cheat a little by using ExecAssignExprContext() to build
     * all of them.
     *
     * NOTE: the details of what is stored in aggcontexts and what is stored
     * in the regular per-query memory context are driven by a simple
     * decision: we want to reset the aggcontext at group boundaries (if not
     * hashing) and in ExecReScanAgg to recover no-longer-wanted space.
     */
    ExecAssignExprContext(estate, &aggstate->ss.ps);
    aggstate->tmpcontext = aggstate->ss.ps.ps_ExprContext;
 
    for (i = 0; i < numGroupingSets; ++i)
    {
        ExecAssignExprContext(estate, &aggstate->ss.ps);
        aggstate->aggcontexts[i] = aggstate->ss.ps.ps_ExprContext;
    }
 
    if (use_hashing)
        hash_create_memory(aggstate);
 
    ExecAssignExprContext(estate, &aggstate->ss.ps);
 
    /*
     * Initialize child nodes.
     *
     * If we are doing a hashed aggregation then the child plan does not need
     * to handle REWIND efficiently; see ExecReScanAgg.
     */
    if (node->aggstrategy == AGG_HASHED)
        eflags &= ~EXEC_FLAG_REWIND;
    outerPlan = outerPlan(node);
    outerPlanState(aggstate) = ExecInitNode(outerPlan, estate, eflags);
 
    /*
     * initialize source tuple type.
     */
    aggstate->ss.ps.outerops =
        ExecGetResultSlotOps(outerPlanState(&aggstate->ss),
                             &aggstate->ss.ps.outeropsfixed);
    aggstate->ss.ps.outeropsset = true;
 
    ExecCreateScanSlotFromOuterPlan(estate, &aggstate->ss,
                                    aggstate->ss.ps.outerops);
    scanDesc = aggstate->ss.ss_ScanTupleSlot->tts_tupleDescriptor;
 
    /*
     * If there are more than two phases (including a potential dummy phase
     * 0), input will be resorted using tuplesort. Need a slot for that.
     */
    if (numPhases > 2)
    {
        aggstate->sort_slot = ExecInitExtraTupleSlot(estate, scanDesc,
                                                     &TTSOpsMinimalTuple);
 
        /*
         * The output of the tuplesort, and the output from the outer child
         * might not use the same type of slot. In most cases the child will
         * be a Sort, and thus return a TTSOpsMinimalTuple type slot - but the
         * input can also be presorted due an index, in which case it could be
         * a different type of slot.
         *
         * XXX: For efficiency it would be good to instead/additionally
         * generate expressions with corresponding settings of outerops* for
         * the individual phases - deforming is often a bottleneck for
         * aggregations with lots of rows per group. If there's multiple
         * sorts, we know that all but the first use TTSOpsMinimalTuple (via
         * the nodeAgg.c internal tuplesort).
         */
        if (aggstate->ss.ps.outeropsfixed &&
            aggstate->ss.ps.outerops != &TTSOpsMinimalTuple)
            aggstate->ss.ps.outeropsfixed = false;
    }
 
    /*
     * Initialize result type, slot and projection.
     */
    ExecInitResultTupleSlotTL(&aggstate->ss.ps, &TTSOpsVirtual);
    ExecAssignProjectionInfo(&aggstate->ss.ps, NULL);
 
    /*
     * initialize child expressions
     *
     * We expect the parser to have checked that no aggs contain other agg
     * calls in their arguments (and just to be sure, we verify it again while
     * initializing the plan node).  This would make no sense under SQL
     * semantics, and it's forbidden by the spec.  Because it is true, we
     * don't need to worry about evaluating the aggs in any particular order.
     *
     * Note: execExpr.c finds Aggrefs for us, and adds them to aggstate->aggs.
     * Aggrefs in the qual are found here; Aggrefs in the targetlist are found
     * during ExecAssignProjectionInfo, above.
     */
    aggstate->ss.ps.qual =
        ExecInitQual(node->plan.qual, (PlanState *) aggstate);
 
    /*
     * We should now have found all Aggrefs in the targetlist and quals.
     */
    numaggrefs = list_length(aggstate->aggs);
    max_aggno = -1;
    max_transno = -1;
    foreach(l, aggstate->aggs)
    {
        Aggref     *aggref = (Aggref *) lfirst(l);
 
        max_aggno = Max(max_aggno, aggref->aggno);
        max_transno = Max(max_transno, aggref->aggtransno);
    }
    aggstate->numaggs = numaggs = max_aggno + 1;
    aggstate->numtrans = numtrans = max_transno + 1;
 
    /*
     * For each phase, prepare grouping set data and fmgr lookup data for
     * compare functions.  Accumulate all_grouped_cols in passing.
     */
    aggstate->phases = palloc0_array(AggStatePerPhaseData, numPhases);
 
    aggstate->num_hashes = numHashes;
    if (numHashes)
    {
        aggstate->perhash = palloc0_array(AggStatePerHashData, numHashes);
        aggstate->phases[0].numsets = 0;
        aggstate->phases[0].gset_lengths = palloc_array(int, numHashes);
        aggstate->phases[0].grouped_cols = palloc_array(Bitmapset *, numHashes);
    }
 
    phase = 0;
    for (phaseidx = 0; phaseidx <= list_length(node->chain); ++phaseidx)
    {
        Agg        *aggnode;
        Sort       *sortnode;
 
        if (phaseidx > 0)
        {
            aggnode = list_nth_node(Agg, node->chain, phaseidx - 1);
            sortnode = castNode(Sort, outerPlan(aggnode));
        }
        else
        {
            aggnode = node;
            sortnode = NULL;
        }
 
        Assert(phase <= 1 || sortnode);
 
        if (aggnode->aggstrategy == AGG_HASHED
            || aggnode->aggstrategy == AGG_MIXED)
        {
            AggStatePerPhase phasedata = &aggstate->phases[0];
            AggStatePerHash perhash;
            Bitmapset  *cols = NULL;
 
            Assert(phase == 0);
            i = phasedata->numsets++;
            perhash = &aggstate->perhash[i];
 
            /* phase 0 always points to the "real" Agg in the hash case */
            phasedata->aggnode = node;
            phasedata->aggstrategy = node->aggstrategy;
 
            /* but the actual Agg node representing this hash is saved here */
            perhash->aggnode = aggnode;
 
            phasedata->gset_lengths[i] = perhash->numCols = aggnode->numCols;
 
            for (j = 0; j < aggnode->numCols; ++j)
                cols = bms_add_member(cols, aggnode->grpColIdx[j]);
 
            phasedata->grouped_cols[i] = cols;
 
            all_grouped_cols = bms_add_members(all_grouped_cols, cols);
            continue;
        }
        else
        {
            AggStatePerPhase phasedata = &aggstate->phases[++phase];
            int         num_sets;
 
            phasedata->numsets = num_sets = list_length(aggnode->groupingSets);
 
            if (num_sets)
            {
                phasedata->gset_lengths = palloc(num_sets * sizeof(int));
                phasedata->grouped_cols = palloc(num_sets * sizeof(Bitmapset *));
 
                i = 0;
                foreach(l, aggnode->groupingSets)
                {
                    int         current_length = list_length(lfirst(l));
                    Bitmapset  *cols = NULL;
 
                    /* planner forces this to be correct */
                    for (j = 0; j < current_length; ++j)
                        cols = bms_add_member(cols, aggnode->grpColIdx[j]);
 
                    phasedata->grouped_cols[i] = cols;
                    phasedata->gset_lengths[i] = current_length;
 
                    ++i;
                }
 
                all_grouped_cols = bms_add_members(all_grouped_cols,
                                                   phasedata->grouped_cols[0]);
            }
            else
            {
                Assert(phaseidx == 0);
 
                phasedata->gset_lengths = NULL;
                phasedata->grouped_cols = NULL;
            }
 
            /*
             * If we are grouping, precompute fmgr lookup data for inner loop.
             */
            if (aggnode->aggstrategy == AGG_SORTED)
            {
                /*
                 * Build a separate function for each subset of columns that
                 * need to be compared.
                 */
                phasedata->eqfunctions = palloc0_array(ExprState *, aggnode->numCols);
 
                /* for each grouping set */
                for (int k = 0; k < phasedata->numsets; k++)
                {
                    int         length = phasedata->gset_lengths[k];
 
                    /* nothing to do for empty grouping set */
                    if (length == 0)
                        continue;
 
                    /* if we already had one of this length, it'll do */
                    if (phasedata->eqfunctions[length - 1] != NULL)
                        continue;
 
                    phasedata->eqfunctions[length - 1] =
                        execTuplesMatchPrepare(scanDesc,
                                               length,
                                               aggnode->grpColIdx,
                                               aggnode->grpOperators,
                                               aggnode->grpCollations,
                                               (PlanState *) aggstate);
                }
 
                /* and for all grouped columns, unless already computed */
                if (aggnode->numCols > 0 &&
                    phasedata->eqfunctions[aggnode->numCols - 1] == NULL)
                {
                    phasedata->eqfunctions[aggnode->numCols - 1] =
                        execTuplesMatchPrepare(scanDesc,
                                               aggnode->numCols,
                                               aggnode->grpColIdx,
                                               aggnode->grpOperators,
                                               aggnode->grpCollations,
                                               (PlanState *) aggstate);
                }
            }
 
            phasedata->aggnode = aggnode;
            phasedata->aggstrategy = aggnode->aggstrategy;
            phasedata->sortnode = sortnode;
        }
    }
 
    /*
     * Convert all_grouped_cols to a descending-order list.
     */
    i = -1;
    while ((i = bms_next_member(all_grouped_cols, i)) >= 0)
        aggstate->all_grouped_cols = lcons_int(i, aggstate->all_grouped_cols);
 
    /*
     * Set up aggregate-result storage in the output expr context, and also
     * allocate my private per-agg working storage
     */
    econtext = aggstate->ss.ps.ps_ExprContext;
    econtext->ecxt_aggvalues = palloc0_array(Datum, numaggs);
    econtext->ecxt_aggnulls = palloc0_array(bool, numaggs);
 
    peraggs = palloc0_array(AggStatePerAggData, numaggs);
    pertransstates = palloc0_array(AggStatePerTransData, numtrans);
 
    aggstate->peragg = peraggs;
    aggstate->pertrans = pertransstates;
 
 
    aggstate->all_pergroups = palloc0_array(AggStatePerGroup, numGroupingSets + numHashes);
    pergroups = aggstate->all_pergroups;
 
    if (node->aggstrategy != AGG_HASHED)
    {
        for (i = 0; i < numGroupingSets; i++)
        {
            pergroups[i] = palloc0_array(AggStatePerGroupData, numaggs);
        }
 
        aggstate->pergroups = pergroups;
        pergroups += numGroupingSets;
    }
 
    /*
     * Hashing can only appear in the initial phase.
     */
    if (use_hashing)
    {
        Plan       *outerplan = outerPlan(node);
        double      totalGroups = 0;
 
        aggstate->hash_spill_rslot = ExecInitExtraTupleSlot(estate, scanDesc,
                                                            &TTSOpsMinimalTuple);
        aggstate->hash_spill_wslot = ExecInitExtraTupleSlot(estate, scanDesc,
                                                            &TTSOpsVirtual);
 
        /* this is an array of pointers, not structures */
        aggstate->hash_pergroup = pergroups;
 
        aggstate->hashentrysize = hash_agg_entry_size(aggstate->numtrans,
                                                      outerplan->plan_width,
                                                      node->transitionSpace);
 
        /*
         * Consider all of the grouping sets together when setting the limits
         * and estimating the number of partitions. This can be inaccurate
         * when there is more than one grouping set, but should still be
         * reasonable.
         */
        for (int k = 0; k < aggstate->num_hashes; k++)
            totalGroups += aggstate->perhash[k].aggnode->numGroups;
 
        hash_agg_set_limits(aggstate->hashentrysize, totalGroups, 0,
                            &aggstate->hash_mem_limit,
                            &aggstate->hash_ngroups_limit,
                            &aggstate->hash_planned_partitions);
        find_hash_columns(aggstate);
 
        /* Skip massive memory allocation if we are just doing EXPLAIN */
        if (!(eflags & EXEC_FLAG_EXPLAIN_ONLY))
            build_hash_tables(aggstate);
 
        aggstate->table_filled = false;
 
        /* Initialize this to 1, meaning nothing spilled, yet */
        aggstate->hash_batches_used = 1;
    }
 
    /*
     * Initialize current phase-dependent values to initial phase. The initial
     * phase is 1 (first sort pass) for all strategies that use sorting (if
     * hashing is being done too, then phase 0 is processed last); but if only
     * hashing is being done, then phase 0 is all there is.
     */
    if (node->aggstrategy == AGG_HASHED)
    {
        aggstate->current_phase = 0;
        initialize_phase(aggstate, 0);
        select_current_set(aggstate, 0, true);
    }
    else
    {
        aggstate->current_phase = 1;
        initialize_phase(aggstate, 1);
        select_current_set(aggstate, 0, false);
    }
 
    /*
     * Perform lookups of aggregate function info, and initialize the
     * unchanging fields of the per-agg and per-trans data.
     */
    foreach(l, aggstate->aggs)
    {
        Aggref     *aggref = lfirst(l);
        AggStatePerAgg peragg;
        AggStatePerTrans pertrans;
        Oid         aggTransFnInputTypes[FUNC_MAX_ARGS];
        int         numAggTransFnArgs;
        int         numDirectArgs;
        HeapTuple   aggTuple;
        Form_pg_aggregate aggform;
        AclResult   aclresult;
        Oid         finalfn_oid;
        Oid         serialfn_oid,
                    deserialfn_oid;
        Oid         aggOwner;
        Expr       *finalfnexpr;
        Oid         aggtranstype;
 
        /* Planner should have assigned aggregate to correct level */
        Assert(aggref->agglevelsup == 0);
        /* ... and the split mode should match */
        Assert(aggref->aggsplit == aggstate->aggsplit);
 
        peragg = &peraggs[aggref->aggno];
 
        /* Check if we initialized the state for this aggregate already. */
        if (peragg->aggref != NULL)
            continue;
 
        peragg->aggref = aggref;
        peragg->transno = aggref->aggtransno;
 
        /* Fetch the pg_aggregate row */
        aggTuple = SearchSysCache1(AGGFNOID,
                                   ObjectIdGetDatum(aggref->aggfnoid));
        if (!HeapTupleIsValid(aggTuple))
            elog(ERROR, "cache lookup failed for aggregate %u",
                 aggref->aggfnoid);
        aggform = (Form_pg_aggregate) GETSTRUCT(aggTuple);
 
        /* Check permission to call aggregate function */
        aclresult = object_aclcheck(ProcedureRelationId, aggref->aggfnoid, GetUserId(),
                                    ACL_EXECUTE);
        if (aclresult != ACLCHECK_OK)
            aclcheck_error(aclresult, OBJECT_AGGREGATE,
                           get_func_name(aggref->aggfnoid));
        InvokeFunctionExecuteHook(aggref->aggfnoid);
 
        /* planner recorded transition state type in the Aggref itself */
        aggtranstype = aggref->aggtranstype;
        Assert(OidIsValid(aggtranstype));
 
        /* Final function only required if we're finalizing the aggregates */
        if (DO_AGGSPLIT_SKIPFINAL(aggstate->aggsplit))
            peragg->finalfn_oid = finalfn_oid = InvalidOid;
        else
            peragg->finalfn_oid = finalfn_oid = aggform->aggfinalfn;
 
        serialfn_oid = InvalidOid;
        deserialfn_oid = InvalidOid;
 
        /*
         * Check if serialization/deserialization is required.  We only do it
         * for aggregates that have transtype INTERNAL.
         */
        if (aggtranstype == INTERNALOID)
        {
            /*
             * The planner should only have generated a serialize agg node if
             * every aggregate with an INTERNAL state has a serialization
             * function.  Verify that.
             */
            if (DO_AGGSPLIT_SERIALIZE(aggstate->aggsplit))
            {
                /* serialization only valid when not running finalfn */
                Assert(DO_AGGSPLIT_SKIPFINAL(aggstate->aggsplit));
 
                if (!OidIsValid(aggform->aggserialfn))
                    elog(ERROR, "serialfunc not provided for serialization aggregation");
                serialfn_oid = aggform->aggserialfn;
            }
 
            /* Likewise for deserialization functions */
            if (DO_AGGSPLIT_DESERIALIZE(aggstate->aggsplit))
            {
                /* deserialization only valid when combining states */
                Assert(DO_AGGSPLIT_COMBINE(aggstate->aggsplit));
 
                if (!OidIsValid(aggform->aggdeserialfn))
                    elog(ERROR, "deserialfunc not provided for deserialization aggregation");
                deserialfn_oid = aggform->aggdeserialfn;
            }
        }
 
        /* Check that aggregate owner has permission to call component fns */
        {
            HeapTuple   procTuple;
 
            procTuple = SearchSysCache1(PROCOID,
                                        ObjectIdGetDatum(aggref->aggfnoid));
            if (!HeapTupleIsValid(procTuple))
                elog(ERROR, "cache lookup failed for function %u",
                     aggref->aggfnoid);
            aggOwner = ((Form_pg_proc) GETSTRUCT(procTuple))->proowner;
            ReleaseSysCache(procTuple);
 
            if (OidIsValid(finalfn_oid))
            {
                aclresult = object_aclcheck(ProcedureRelationId, finalfn_oid, aggOwner,
                                            ACL_EXECUTE);
                if (aclresult != ACLCHECK_OK)
                    aclcheck_error(aclresult, OBJECT_FUNCTION,
                                   get_func_name(finalfn_oid));
                InvokeFunctionExecuteHook(finalfn_oid);
            }
            if (OidIsValid(serialfn_oid))
            {
                aclresult = object_aclcheck(ProcedureRelationId, serialfn_oid, aggOwner,
                                            ACL_EXECUTE);
                if (aclresult != ACLCHECK_OK)
                    aclcheck_error(aclresult, OBJECT_FUNCTION,
                                   get_func_name(serialfn_oid));
                InvokeFunctionExecuteHook(serialfn_oid);
            }
            if (OidIsValid(deserialfn_oid))
            {
                aclresult = object_aclcheck(ProcedureRelationId, deserialfn_oid, aggOwner,
                                            ACL_EXECUTE);
                if (aclresult != ACLCHECK_OK)
                    aclcheck_error(aclresult, OBJECT_FUNCTION,
                                   get_func_name(deserialfn_oid));
                InvokeFunctionExecuteHook(deserialfn_oid);
            }
        }
 
        /*
         * Get actual datatypes of the (nominal) aggregate inputs.  These
         * could be different from the agg's declared input types, when the
         * agg accepts ANY or a polymorphic type.
         */
        numAggTransFnArgs = get_aggregate_argtypes(aggref,
                                                   aggTransFnInputTypes);
 
        /* Count the "direct" arguments, if any */
        numDirectArgs = list_length(aggref->aggdirectargs);
 
        /* Detect how many arguments to pass to the finalfn */
        if (aggform->aggfinalextra)
            peragg->numFinalArgs = numAggTransFnArgs + 1;
        else
            peragg->numFinalArgs = numDirectArgs + 1;
 
        /* Initialize any direct-argument expressions */
        peragg->aggdirectargs = ExecInitExprList(aggref->aggdirectargs,
                                                 (PlanState *) aggstate);
 
        /*
         * build expression trees using actual argument & result types for the
         * finalfn, if it exists and is required.
         */
        if (OidIsValid(finalfn_oid))
        {
            build_aggregate_finalfn_expr(aggTransFnInputTypes,
                                         peragg->numFinalArgs,
                                         aggtranstype,
                                         aggref->aggtype,
                                         aggref->inputcollid,
                                         finalfn_oid,
                                         &finalfnexpr);
            fmgr_info(finalfn_oid, &peragg->finalfn);
            fmgr_info_set_expr((Node *) finalfnexpr, &peragg->finalfn);
        }
 
        /* get info about the output value's datatype */
        get_typlenbyval(aggref->aggtype,
                        &peragg->resulttypeLen,
                        &peragg->resulttypeByVal);
 
        /*
         * Build working state for invoking the transition function, if we
         * haven't done it already.
         */
        pertrans = &pertransstates[aggref->aggtransno];
        if (pertrans->aggref == NULL)
        {
            Datum       textInitVal;
            Datum       initValue;
            bool        initValueIsNull;
            Oid         transfn_oid;
 
            /*
             * If this aggregation is performing state combines, then instead
             * of using the transition function, we'll use the combine
             * function.
             */
            if (DO_AGGSPLIT_COMBINE(aggstate->aggsplit))
            {
                transfn_oid = aggform->aggcombinefn;
 
                /* If not set then the planner messed up */
                if (!OidIsValid(transfn_oid))
                    elog(ERROR, "combinefn not set for aggregate function");
            }
            else
                transfn_oid = aggform->aggtransfn;
 
            aclresult = object_aclcheck(ProcedureRelationId, transfn_oid, aggOwner, ACL_EXECUTE);
            if (aclresult != ACLCHECK_OK)
                aclcheck_error(aclresult, OBJECT_FUNCTION,
                               get_func_name(transfn_oid));
            InvokeFunctionExecuteHook(transfn_oid);
 
            /*
             * initval is potentially null, so don't try to access it as a
             * struct field. Must do it the hard way with SysCacheGetAttr.
             */
            textInitVal = SysCacheGetAttr(AGGFNOID, aggTuple,
                                          Anum_pg_aggregate_agginitval,
                                          &initValueIsNull);
            if (initValueIsNull)
                initValue = (Datum) 0;
            else
                initValue = GetAggInitVal(textInitVal, aggtranstype);
 
            if (DO_AGGSPLIT_COMBINE(aggstate->aggsplit))
            {
                Oid         combineFnInputTypes[] = {aggtranstype,
                aggtranstype};
 
                /*
                 * When combining there's only one input, the to-be-combined
                 * transition value.  The transition value is not counted
                 * here.
                 */
                pertrans->numTransInputs = 1;
 
                /* aggcombinefn always has two arguments of aggtranstype */
                build_pertrans_for_aggref(pertrans, aggstate, estate,
                                          aggref, transfn_oid, aggtranstype,
                                          serialfn_oid, deserialfn_oid,
                                          initValue, initValueIsNull,
                                          combineFnInputTypes, 2);
 
                /*
                 * Ensure that a combine function to combine INTERNAL states
                 * is not strict. This should have been checked during CREATE
                 * AGGREGATE, but the strict property could have been changed
                 * since then.
                 */
                if (pertrans->transfn.fn_strict && aggtranstype == INTERNALOID)
                    ereport(ERROR,
                            (errcode(ERRCODE_INVALID_FUNCTION_DEFINITION),
                             errmsg("combine function with transition type %s must not be declared STRICT",
                                    format_type_be(aggtranstype))));
            }
            else
            {
                /* Detect how many arguments to pass to the transfn */
                if (AGGKIND_IS_ORDERED_SET(aggref->aggkind))
                    pertrans->numTransInputs = list_length(aggref->args);
                else
                    pertrans->numTransInputs = numAggTransFnArgs;
 
                build_pertrans_for_aggref(pertrans, aggstate, estate,
                                          aggref, transfn_oid, aggtranstype,
                                          serialfn_oid, deserialfn_oid,
                                          initValue, initValueIsNull,
                                          aggTransFnInputTypes,
                                          numAggTransFnArgs);
 
                /*
                 * If the transfn is strict and the initval is NULL, make sure
                 * input type and transtype are the same (or at least
                 * binary-compatible), so that it's OK to use the first
                 * aggregated input value as the initial transValue.  This
                 * should have been checked at agg definition time, but we
                 * must check again in case the transfn's strictness property
                 * has been changed.
                 */
                if (pertrans->transfn.fn_strict && pertrans->initValueIsNull)
                {
                    if (numAggTransFnArgs <= numDirectArgs ||
                        !IsBinaryCoercible(aggTransFnInputTypes[numDirectArgs],
                                           aggtranstype))
                        ereport(ERROR,
                                (errcode(ERRCODE_INVALID_FUNCTION_DEFINITION),
                                 errmsg("aggregate %u needs to have compatible input type and transition type",
                                        aggref->aggfnoid)));
                }
            }
        }
        else
            pertrans->aggshared = true;
        ReleaseSysCache(aggTuple);
    }
 
    /*
     * Last, check whether any more aggregates got added onto the node while
     * we processed the expressions for the aggregate arguments (including not
     * only the regular arguments and FILTER expressions handled immediately
     * above, but any direct arguments we might've handled earlier).  If so,
     * we have nested aggregate functions, which is semantically nonsensical,
     * so complain.  (This should have been caught by the parser, so we don't
     * need to work hard on a helpful error message; but we defend against it
     * here anyway, just to be sure.)
     */
    if (numaggrefs != list_length(aggstate->aggs))
        ereport(ERROR,
                (errcode(ERRCODE_GROUPING_ERROR),
                 errmsg("aggregate function calls cannot be nested")));
 
    /*
     * Build expressions doing all the transition work at once. We build a
     * different one for each phase, as the number of transition function
     * invocation can differ between phases. Note this'll work both for
     * transition and combination functions (although there'll only be one
     * phase in the latter case).
     */
    for (phaseidx = 0; phaseidx < aggstate->numphases; phaseidx++)
    {
        AggStatePerPhase phase = &aggstate->phases[phaseidx];
        bool        dohash = false;
        bool        dosort = false;
 
        /* phase 0 doesn't necessarily exist */
        if (!phase->aggnode)
            continue;
 
        if (aggstate->aggstrategy == AGG_MIXED && phaseidx == 1)
        {
            /*
             * Phase one, and only phase one, in a mixed agg performs both
             * sorting and aggregation.
             */
            dohash = true;
            dosort = true;
        }
        else if (aggstate->aggstrategy == AGG_MIXED && phaseidx == 0)
        {
            /*
             * No need to compute a transition function for an AGG_MIXED phase
             * 0 - the contents of the hashtables will have been computed
             * during phase 1.
             */
            continue;
        }
        else if (phase->aggstrategy == AGG_PLAIN ||
                 phase->aggstrategy == AGG_SORTED)
        {
            dohash = false;
            dosort = true;
        }
        else if (phase->aggstrategy == AGG_HASHED)
        {
            dohash = true;
            dosort = false;
        }
        else
            Assert(false);
 
        phase->evaltrans = ExecBuildAggTrans(aggstate, phase, dosort, dohash,
                                             false);
 
        /* cache compiled expression for outer slot without NULL check */
        phase->evaltrans_cache[0][0] = phase->evaltrans;
    }
 
    return aggstate;
}
 
/*
 * Build the state needed to calculate a state value for an aggregate.
 *
 * This initializes all the fields in 'pertrans'. 'aggref' is the aggregate
 * to initialize the state for. 'transfn_oid', 'aggtranstype', and the rest
 * of the arguments could be calculated from 'aggref', but the caller has
 * calculated them already, so might as well pass them.
 *
 * 'transfn_oid' may be either the Oid of the aggtransfn or the aggcombinefn.
 */
static void
build_pertrans_for_aggref(AggStatePerTrans pertrans,
                          AggState *aggstate, EState *estate,
                          Aggref *aggref,
                          Oid transfn_oid, Oid aggtranstype,
                          Oid aggserialfn, Oid aggdeserialfn,
                          Datum initValue, bool initValueIsNull,
                          Oid *inputTypes, int numArguments)
{
    int         numGroupingSets = Max(aggstate->maxsets, 1);
    Expr       *transfnexpr;
    int         numTransArgs;
    Expr       *serialfnexpr = NULL;
    Expr       *deserialfnexpr = NULL;
    ListCell   *lc;
    int         numInputs;
    int         numDirectArgs;
    List       *sortlist;
    int         numSortCols;
    int         numDistinctCols;
    int         i;
 
    /* Begin filling in the pertrans data */
    pertrans->aggref = aggref;
    pertrans->aggshared = false;
    pertrans->aggCollation = aggref->inputcollid;
    pertrans->transfn_oid = transfn_oid;
    pertrans->serialfn_oid = aggserialfn;
    pertrans->deserialfn_oid = aggdeserialfn;
    pertrans->initValue = initValue;
    pertrans->initValueIsNull = initValueIsNull;
 
    /* Count the "direct" arguments, if any */
    numDirectArgs = list_length(aggref->aggdirectargs);
 
    /* Count the number of aggregated input columns */
    pertrans->numInputs = numInputs = list_length(aggref->args);
 
    pertrans->aggtranstype = aggtranstype;
 
    /* account for the current transition state */
    numTransArgs = pertrans->numTransInputs + 1;
 
    /*
     * Set up infrastructure for calling the transfn.  Note that invtransfn is
     * not needed here.
     */
    build_aggregate_transfn_expr(inputTypes,
                                 numArguments,
                                 numDirectArgs,
                                 aggref->aggvariadic,
                                 aggtranstype,
                                 aggref->inputcollid,
                                 transfn_oid,
                                 InvalidOid,
                                 &transfnexpr,
                                 NULL);
 
    fmgr_info(transfn_oid, &pertrans->transfn);
    fmgr_info_set_expr((Node *) transfnexpr, &pertrans->transfn);
 
    pertrans->transfn_fcinfo =
        (FunctionCallInfo) palloc(SizeForFunctionCallInfo(numTransArgs));
    InitFunctionCallInfoData(*pertrans->transfn_fcinfo,
                             &pertrans->transfn,
                             numTransArgs,
                             pertrans->aggCollation,
                             (Node *) aggstate, NULL);
 
    /* get info about the state value's datatype */
    get_typlenbyval(aggtranstype,
                    &pertrans->transtypeLen,
                    &pertrans->transtypeByVal);
 
    if (OidIsValid(aggserialfn))
    {
        build_aggregate_serialfn_expr(aggserialfn,
                                      &serialfnexpr);
        fmgr_info(aggserialfn, &pertrans->serialfn);
        fmgr_info_set_expr((Node *) serialfnexpr, &pertrans->serialfn);
 
        pertrans->serialfn_fcinfo =
            (FunctionCallInfo) palloc(SizeForFunctionCallInfo(1));
        InitFunctionCallInfoData(*pertrans->serialfn_fcinfo,
                                 &pertrans->serialfn,
                                 1,
                                 InvalidOid,
                                 (Node *) aggstate, NULL);
    }
 
    if (OidIsValid(aggdeserialfn))
    {
        build_aggregate_deserialfn_expr(aggdeserialfn,
                                        &deserialfnexpr);
        fmgr_info(aggdeserialfn, &pertrans->deserialfn);
        fmgr_info_set_expr((Node *) deserialfnexpr, &pertrans->deserialfn);
 
        pertrans->deserialfn_fcinfo =
            (FunctionCallInfo) palloc(SizeForFunctionCallInfo(2));
        InitFunctionCallInfoData(*pertrans->deserialfn_fcinfo,
                                 &pertrans->deserialfn,
                                 2,
                                 InvalidOid,
                                 (Node *) aggstate, NULL);
    }
 
    /*
     * If we're doing either DISTINCT or ORDER BY for a plain agg, then we
     * have a list of SortGroupClause nodes; fish out the data in them and
     * stick them into arrays.  We ignore ORDER BY for an ordered-set agg,
     * however; the agg's transfn and finalfn are responsible for that.
     *
     * When the planner has set the aggpresorted flag, the input to the
     * aggregate is already correctly sorted.  For ORDER BY aggregates we can
     * simply treat these as normal aggregates.  For presorted DISTINCT
     * aggregates an extra step must be added to remove duplicate consecutive
     * inputs.
     *
     * Note that by construction, if there is a DISTINCT clause then the ORDER
     * BY clause is a prefix of it (see transformDistinctClause).
     */
    if (AGGKIND_IS_ORDERED_SET(aggref->aggkind))
    {
        sortlist = NIL;
        numSortCols = numDistinctCols = 0;
        pertrans->aggsortrequired = false;
    }
    else if (aggref->aggpresorted && aggref->aggdistinct == NIL)
    {
        sortlist = NIL;
        numSortCols = numDistinctCols = 0;
        pertrans->aggsortrequired = false;
    }
    else if (aggref->aggdistinct)
    {
        sortlist = aggref->aggdistinct;
        numSortCols = numDistinctCols = list_length(sortlist);
        Assert(numSortCols >= list_length(aggref->aggorder));
        pertrans->aggsortrequired = !aggref->aggpresorted;
    }
    else
    {
        sortlist = aggref->aggorder;
        numSortCols = list_length(sortlist);
        numDistinctCols = 0;
        pertrans->aggsortrequired = (numSortCols > 0);
    }
 
    pertrans->numSortCols = numSortCols;
    pertrans->numDistinctCols = numDistinctCols;
 
    /*
     * If we have either sorting or filtering to do, create a tupledesc and
     * slot corresponding to the aggregated inputs (including sort
     * expressions) of the agg.
     */
    if (numSortCols > 0 || aggref->aggfilter)
    {
        pertrans->sortdesc = ExecTypeFromTL(aggref->args);
        pertrans->sortslot =
            ExecInitExtraTupleSlot(estate, pertrans->sortdesc,
                                   &TTSOpsMinimalTuple);
    }
 
    if (numSortCols > 0)
    {
        /*
         * We don't implement DISTINCT or ORDER BY aggs in the HASHED case
         * (yet)
         */
        Assert(aggstate->aggstrategy != AGG_HASHED && aggstate->aggstrategy != AGG_MIXED);
 
        /* ORDER BY aggregates are not supported with partial aggregation */
        Assert(!DO_AGGSPLIT_COMBINE(aggstate->aggsplit));
 
        /* If we have only one input, we need its len/byval info. */
        if (numInputs == 1)
        {
            get_typlenbyval(inputTypes[numDirectArgs],
                            &pertrans->inputtypeLen,
                            &pertrans->inputtypeByVal);
        }
        else if (numDistinctCols > 0)
        {
            /* we will need an extra slot to store prior values */
            pertrans->uniqslot =
                ExecInitExtraTupleSlot(estate, pertrans->sortdesc,
                                       &TTSOpsMinimalTuple);
        }
 
        /* Extract the sort information for use later */
        pertrans->sortColIdx =
            (AttrNumber *) palloc(numSortCols * sizeof(AttrNumber));
        pertrans->sortOperators =
            (Oid *) palloc(numSortCols * sizeof(Oid));
        pertrans->sortCollations =
            (Oid *) palloc(numSortCols * sizeof(Oid));
        pertrans->sortNullsFirst =
            (bool *) palloc(numSortCols * sizeof(bool));
 
        i = 0;
        foreach(lc, sortlist)
        {
            SortGroupClause *sortcl = (SortGroupClause *) lfirst(lc);
            TargetEntry *tle = get_sortgroupclause_tle(sortcl, aggref->args);
 
            /* the parser should have made sure of this */
            Assert(OidIsValid(sortcl->sortop));
 
            pertrans->sortColIdx[i] = tle->resno;
            pertrans->sortOperators[i] = sortcl->sortop;
            pertrans->sortCollations[i] = exprCollation((Node *) tle->expr);
            pertrans->sortNullsFirst[i] = sortcl->nulls_first;
            i++;
        }
        Assert(i == numSortCols);
    }
 
    if (aggref->aggdistinct)
    {
        Oid        *ops;
 
        Assert(numArguments > 0);
        Assert(list_length(aggref->aggdistinct) == numDistinctCols);
 
        ops = palloc(numDistinctCols * sizeof(Oid));
 
        i = 0;
        foreach(lc, aggref->aggdistinct)
            ops[i++] = ((SortGroupClause *) lfirst(lc))->eqop;
 
        /* lookup / build the necessary comparators */
        if (numDistinctCols == 1)
            fmgr_info(get_opcode(ops[0]), &pertrans->equalfnOne);
        else
            pertrans->equalfnMulti =
                execTuplesMatchPrepare(pertrans->sortdesc,
                                       numDistinctCols,
                                       pertrans->sortColIdx,
                                       ops,
                                       pertrans->sortCollations,
                                       &aggstate->ss.ps);
        pfree(ops);
    }
 
    pertrans->sortstates = palloc0_array(Tuplesortstate *, numGroupingSets);
}
 
 
static Datum
GetAggInitVal(Datum textInitVal, Oid transtype)
{
    Oid         typinput,
                typioparam;
    char       *strInitVal;
    Datum       initVal;
 
    getTypeInputInfo(transtype, &typinput, &typioparam);
    strInitVal = TextDatumGetCString(textInitVal);
    initVal = OidInputFunctionCall(typinput, strInitVal,
                                   typioparam, -1);
    pfree(strInitVal);
    return initVal;
}
 
void
ExecEndAgg(AggState *node)
{
    PlanState  *outerPlan;
    int         transno;
    int         numGroupingSets = Max(node->maxsets, 1);
    int         setno;
 
    /*
     * When ending a parallel worker, copy the statistics gathered by the
     * worker back into shared memory so that it can be picked up by the main
     * process to report in EXPLAIN ANALYZE.
     */
    if (node->shared_info && IsParallelWorker())
    {
        AggregateInstrumentation *si;
 
        Assert(ParallelWorkerNumber <= node->shared_info->num_workers);
        si = &node->shared_info->sinstrument[ParallelWorkerNumber];
        si->hash_batches_used = node->hash_batches_used;
        si->hash_disk_used = node->hash_disk_used;
        si->hash_mem_peak = node->hash_mem_peak;
    }
 
    /* Make sure we have closed any open tuplesorts */
 
    if (node->sort_in)
        tuplesort_end(node->sort_in);
    if (node->sort_out)
        tuplesort_end(node->sort_out);
 
    hashagg_reset_spill_state(node);
 
    /* Release hash tables too */
    if (node->hash_metacxt != NULL)
    {
        MemoryContextDelete(node->hash_metacxt);
        node->hash_metacxt = NULL;
    }
    if (node->hash_tuplescxt != NULL)
    {
        MemoryContextDelete(node->hash_tuplescxt);
        node->hash_tuplescxt = NULL;
    }
 
    for (transno = 0; transno < node->numtrans; transno++)
    {
        AggStatePerTrans pertrans = &node->pertrans[transno];
 
        for (setno = 0; setno < numGroupingSets; setno++)
        {
            if (pertrans->sortstates[setno])
                tuplesort_end(pertrans->sortstates[setno]);
        }
    }
 
    /* And ensure any agg shutdown callbacks have been called */
    for (setno = 0; setno < numGroupingSets; setno++)
        ReScanExprContext(node->aggcontexts[setno]);
    if (node->hashcontext)
        ReScanExprContext(node->hashcontext);
 
    outerPlan = outerPlanState(node);
    ExecEndNode(outerPlan);
}
 
void
ExecReScanAgg(AggState *node)
{
    ExprContext *econtext = node->ss.ps.ps_ExprContext;
    PlanState  *outerPlan = outerPlanState(node);
    Agg        *aggnode = (Agg *) node->ss.ps.plan;
    int         transno;
    int         numGroupingSets = Max(node->maxsets, 1);
    int         setno;
 
    node->agg_done = false;
 
    if (node->aggstrategy == AGG_HASHED)
    {
        /*
         * In the hashed case, if we haven't yet built the hash table then we
         * can just return; nothing done yet, so nothing to undo. If subnode's
         * chgParam is not NULL then it will be re-scanned by ExecProcNode,
         * else no reason to re-scan it at all.
         */
        if (!node->table_filled)
            return;
 
        /*
         * If we do have the hash table, and it never spilled, and the subplan
         * does not have any parameter changes, and none of our own parameter
         * changes affect input expressions of the aggregated functions, then
         * we can just rescan the existing hash table; no need to build it
         * again.
         */
        if (outerPlan->chgParam == NULL && !node->hash_ever_spilled &&
            !bms_overlap(node->ss.ps.chgParam, aggnode->aggParams))
        {
            ResetTupleHashIterator(node->perhash[0].hashtable,
                                   &node->perhash[0].hashiter);
            select_current_set(node, 0, true);
            return;
        }
    }
 
    /* Make sure we have closed any open tuplesorts */
    for (transno = 0; transno < node->numtrans; transno++)
    {
        for (setno = 0; setno < numGroupingSets; setno++)
        {
            AggStatePerTrans pertrans = &node->pertrans[transno];
 
            if (pertrans->sortstates[setno])
            {
                tuplesort_end(pertrans->sortstates[setno]);
                pertrans->sortstates[setno] = NULL;
            }
        }
    }
 
    /*
     * We don't need to ReScanExprContext the output tuple context here;
     * ExecReScan already did it. But we do need to reset our per-grouping-set
     * contexts, which may have transvalues stored in them. (We use rescan
     * rather than just reset because transfns may have registered callbacks
     * that need to be run now.) For the AGG_HASHED case, see below.
     */
 
    for (setno = 0; setno < numGroupingSets; setno++)
    {
        ReScanExprContext(node->aggcontexts[setno]);
    }
 
    /* Release first tuple of group, if we have made a copy */
    if (node->grp_firstTuple != NULL)
    {
        heap_freetuple(node->grp_firstTuple);
        node->grp_firstTuple = NULL;
    }
    ExecClearTuple(node->ss.ss_ScanTupleSlot);
 
    /* Forget current agg values */
    MemSet(econtext->ecxt_aggvalues, 0, sizeof(Datum) * node->numaggs);
    MemSet(econtext->ecxt_aggnulls, 0, sizeof(bool) * node->numaggs);
 
    /*
     * With AGG_HASHED/MIXED, the hash table is allocated in a sub-context of
     * the hashcontext. This used to be an issue, but now, resetting a context
     * automatically deletes sub-contexts too.
     */
    if (node->aggstrategy == AGG_HASHED || node->aggstrategy == AGG_MIXED)
    {
        hashagg_reset_spill_state(node);
 
        node->hash_ever_spilled = false;
        node->hash_spill_mode = false;
        node->hash_ngroups_current = 0;
 
        ReScanExprContext(node->hashcontext);
        /* Rebuild empty hash table(s) */
        build_hash_tables(node);
        node->table_filled = false;
        /* iterator will be reset when the table is filled */
 
        hashagg_recompile_expressions(node, false, false);
    }
 
    if (node->aggstrategy != AGG_HASHED)
    {
        /*
         * Reset the per-group state (in particular, mark transvalues null)
         */
        for (setno = 0; setno < numGroupingSets; setno++)
        {
            MemSet(node->pergroups[setno], 0,
                   sizeof(AggStatePerGroupData) * node->numaggs);
        }
 
        /* reset to phase 1 */
        initialize_phase(node, 1);
 
        node->input_done = false;
        node->projected_set = -1;
    }
 
    if (outerPlan->chgParam == NULL)
        ExecReScan(outerPlan);
}
 
 
/***********************************************************************
 * API exposed to aggregate functions
 ***********************************************************************/
 
 
/*
 * AggCheckCallContext - test if a SQL function is being called as an aggregate
 *
 * The transition and/or final functions of an aggregate may want to verify
 * that they are being called as aggregates, rather than as plain SQL
 * functions.  They should use this function to do so.  The return value
 * is nonzero if being called as an aggregate, or zero if not.  (Specific
 * nonzero values are AGG_CONTEXT_AGGREGATE or AGG_CONTEXT_WINDOW, but more
 * values could conceivably appear in future.)
 *
 * If aggcontext isn't NULL, the function also stores at *aggcontext the
 * identity of the memory context that aggregate transition values are being
 * stored in.  Note that the same aggregate call site (flinfo) may be called
 * interleaved on different transition values in different contexts, so it's
 * not kosher to cache aggcontext under fn_extra.  It is, however, kosher to
 * cache it in the transvalue itself (for internal-type transvalues).
 */
int
AggCheckCallContext(FunctionCallInfo fcinfo, MemoryContext *aggcontext)
{
    if (fcinfo->context && IsA(fcinfo->context, AggState))
    {
        if (aggcontext)
        {
            AggState   *aggstate = ((AggState *) fcinfo->context);
            ExprContext *cxt = aggstate->curaggcontext;
 
            *aggcontext = cxt->ecxt_per_tuple_memory;
        }
        return AGG_CONTEXT_AGGREGATE;
    }
    if (fcinfo->context && IsA(fcinfo->context, WindowAggState))
    {
        if (aggcontext)
            *aggcontext = ((WindowAggState *) fcinfo->context)->curaggcontext;
        return AGG_CONTEXT_WINDOW;
    }
 
    /* this is just to prevent "uninitialized variable" warnings */
    if (aggcontext)
        *aggcontext = NULL;
    return 0;
}
 
/*
 * AggGetAggref - allow an aggregate support function to get its Aggref
 *
 * If the function is being called as an aggregate support function,
 * return the Aggref node for the aggregate call.  Otherwise, return NULL.
 *
 * Aggregates sharing the same inputs and transition functions can get
 * merged into a single transition calculation.  If the transition function
 * calls AggGetAggref, it will get some one of the Aggrefs for which it is
 * executing.  It must therefore not pay attention to the Aggref fields that
 * relate to the final function, as those are indeterminate.  But if a final
 * function calls AggGetAggref, it will get a precise result.
 *
 * Note that if an aggregate is being used as a window function, this will
 * return NULL.  We could provide a similar function to return the relevant
 * WindowFunc node in such cases, but it's not needed yet.
 */
Aggref *
AggGetAggref(FunctionCallInfo fcinfo)
{
    if (fcinfo->context && IsA(fcinfo->context, AggState))
    {
        AggState   *aggstate = (AggState *) fcinfo->context;
        AggStatePerAgg curperagg;
        AggStatePerTrans curpertrans;
 
        /* check curperagg (valid when in a final function) */
        curperagg = aggstate->curperagg;
 
        if (curperagg)
            return curperagg->aggref;
 
        /* check curpertrans (valid when in a transition function) */
        curpertrans = aggstate->curpertrans;
 
        if (curpertrans)
            return curpertrans->aggref;
    }
    return NULL;
}
 
/*
 * AggGetTempMemoryContext - fetch short-term memory context for aggregates
 *
 * This is useful in agg final functions; the context returned is one that
 * the final function can safely reset as desired.  This isn't useful for
 * transition functions, since the context returned MAY (we don't promise)
 * be the same as the context those are called in.
 *
 * As above, this is currently not useful for aggs called as window functions.
 */
MemoryContext
AggGetTempMemoryContext(FunctionCallInfo fcinfo)
{
    if (fcinfo->context && IsA(fcinfo->context, AggState))
    {
        AggState   *aggstate = (AggState *) fcinfo->context;
 
        return aggstate->tmpcontext->ecxt_per_tuple_memory;
    }
    return NULL;
}
 
/*
 * AggStateIsShared - find out whether transition state is shared
 *
 * If the function is being called as an aggregate support function,
 * return true if the aggregate's transition state is shared across
 * multiple aggregates, false if it is not.
 *
 * Returns true if not called as an aggregate support function.
 * This is intended as a conservative answer, ie "no you'd better not
 * scribble on your input".  In particular, will return true if the
 * aggregate is being used as a window function, which is a scenario
 * in which changing the transition state is a bad idea.  We might
 * want to refine the behavior for the window case in future.
 */
bool
AggStateIsShared(FunctionCallInfo fcinfo)
{
    if (fcinfo->context && IsA(fcinfo->context, AggState))
    {
        AggState   *aggstate = (AggState *) fcinfo->context;
        AggStatePerAgg curperagg;
        AggStatePerTrans curpertrans;
 
        /* check curperagg (valid when in a final function) */
        curperagg = aggstate->curperagg;
 
        if (curperagg)
            return aggstate->pertrans[curperagg->transno].aggshared;
 
        /* check curpertrans (valid when in a transition function) */
        curpertrans = aggstate->curpertrans;
 
        if (curpertrans)
            return curpertrans->aggshared;
    }
    return true;
}
 
/*
 * AggRegisterCallback - register a cleanup callback for an aggregate
 *
 * This is useful for aggs to register shutdown callbacks, which will ensure
 * that non-memory resources are freed.  The callback will occur just before
 * the associated aggcontext (as returned by AggCheckCallContext) is reset,
 * either between groups or as a result of rescanning the query.  The callback
 * will NOT be called on error paths.  The typical use-case is for freeing of
 * tuplestores or tuplesorts maintained in aggcontext, or pins held by slots
 * created by the agg functions.  (The callback will not be called until after
 * the result of the finalfn is no longer needed, so it's safe for the finalfn
 * to return data that will be freed by the callback.)
 *
 * As above, this is currently not useful for aggs called as window functions.
 */
void
AggRegisterCallback(FunctionCallInfo fcinfo,
                    ExprContextCallbackFunction func,
                    Datum arg)
{
    if (fcinfo->context && IsA(fcinfo->context, AggState))
    {
        AggState   *aggstate = (AggState *) fcinfo->context;
        ExprContext *cxt = aggstate->curaggcontext;
 
        RegisterExprContextCallback(cxt, func, arg);
 
        return;
    }
    elog(ERROR, "aggregate function cannot register a callback in this context");
}
 
 
/* ----------------------------------------------------------------
 *                      Parallel Query Support
 * ----------------------------------------------------------------
 */
 
 /* ----------------------------------------------------------------
  *     ExecAggEstimate
  *
  *     Estimate space required to propagate aggregate statistics.
  * ----------------------------------------------------------------
  */
void
ExecAggEstimate(AggState *node, ParallelContext *pcxt)
{
    Size        size;
 
    /* don't need this if not instrumenting or no workers */
    if (!node->ss.ps.instrument || pcxt->nworkers == 0)
        return;
 
    size = mul_size(pcxt->nworkers, sizeof(AggregateInstrumentation));
    size = add_size(size, offsetof(SharedAggInfo, sinstrument));
    shm_toc_estimate_chunk(&pcxt->estimator, size);
    shm_toc_estimate_keys(&pcxt->estimator, 1);
}
 
/* ----------------------------------------------------------------
 *      ExecAggInitializeDSM
 *
 *      Initialize DSM space for aggregate statistics.
 * ----------------------------------------------------------------
 */
void
ExecAggInitializeDSM(AggState *node, ParallelContext *pcxt)
{
    Size        size;
 
    /* don't need this if not instrumenting or no workers */
    if (!node->ss.ps.instrument || pcxt->nworkers == 0)
        return;
 
    size = offsetof(SharedAggInfo, sinstrument)
        + pcxt->nworkers * sizeof(AggregateInstrumentation);
    node->shared_info = shm_toc_allocate(pcxt->toc, size);
    /* ensure any unfilled slots will contain zeroes */
    memset(node->shared_info, 0, size);
    node->shared_info->num_workers = pcxt->nworkers;
    shm_toc_insert(pcxt->toc, node->ss.ps.plan->plan_node_id,
                   node->shared_info);
}
 
/* ----------------------------------------------------------------
 *      ExecAggInitializeWorker
 *
 *      Attach worker to DSM space for aggregate statistics.
 * ----------------------------------------------------------------
 */
void
ExecAggInitializeWorker(AggState *node, ParallelWorkerContext *pwcxt)
{
    node->shared_info =
        shm_toc_lookup(pwcxt->toc, node->ss.ps.plan->plan_node_id, true);
}
 
/* ----------------------------------------------------------------
 *      ExecAggRetrieveInstrumentation
 *
 *      Transfer aggregate statistics from DSM to private memory.
 * ----------------------------------------------------------------
 */
void
ExecAggRetrieveInstrumentation(AggState *node)
{
    Size        size;
    SharedAggInfo *si;
 
    if (node->shared_info == NULL)
        return;
 
    size = offsetof(SharedAggInfo, sinstrument)
        + node->shared_info->num_workers * sizeof(AggregateInstrumentation);
    si = palloc(size);
    memcpy(si, node->shared_info, size);
    node->shared_info = si;
}