nodeHash.c

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/*-------------------------------------------------------------------------
 *
 * nodeHash.c
 *    Routines to hash relations for hashjoin
 *
 * Portions Copyright (c) 1996-2025, PostgreSQL Global Development Group
 * Portions Copyright (c) 1994, Regents of the University of California
 *
 *
 * IDENTIFICATION
 *    src/backend/executor/nodeHash.c
 *
 * See note on parallelism in nodeHashjoin.c.
 *
 *-------------------------------------------------------------------------
 */
/*
 * INTERFACE ROUTINES
 *      MultiExecHash   - generate an in-memory hash table of the relation
 *      ExecInitHash    - initialize node and subnodes
 *      ExecEndHash     - shutdown node and subnodes
 */
 
#include "postgres.h"
 
#include <math.h>
#include <limits.h>
 
#include "access/htup_details.h"
#include "access/parallel.h"
#include "catalog/pg_statistic.h"
#include "commands/tablespace.h"
#include "executor/executor.h"
#include "executor/hashjoin.h"
#include "executor/nodeHash.h"
#include "executor/nodeHashjoin.h"
#include "miscadmin.h"
#include "port/pg_bitutils.h"
#include "utils/dynahash.h"
#include "utils/lsyscache.h"
#include "utils/memutils.h"
#include "utils/syscache.h"
#include "utils/wait_event.h"
 
static void ExecHashIncreaseNumBatches(HashJoinTable hashtable);
static void ExecHashIncreaseNumBuckets(HashJoinTable hashtable);
static void ExecParallelHashIncreaseNumBatches(HashJoinTable hashtable);
static void ExecParallelHashIncreaseNumBuckets(HashJoinTable hashtable);
static void ExecHashBuildSkewHash(HashState *hashstate,
                                  HashJoinTable hashtable, Hash *node,
                                  int mcvsToUse);
static void ExecHashSkewTableInsert(HashJoinTable hashtable,
                                    TupleTableSlot *slot,
                                    uint32 hashvalue,
                                    int bucketNumber);
static void ExecHashRemoveNextSkewBucket(HashJoinTable hashtable);
 
static void *dense_alloc(HashJoinTable hashtable, Size size);
static HashJoinTuple ExecParallelHashTupleAlloc(HashJoinTable hashtable,
                                                size_t size,
                                                dsa_pointer *shared);
static void MultiExecPrivateHash(HashState *node);
static void MultiExecParallelHash(HashState *node);
static inline HashJoinTuple ExecParallelHashFirstTuple(HashJoinTable hashtable,
                                                       int bucketno);
static inline HashJoinTuple ExecParallelHashNextTuple(HashJoinTable hashtable,
                                                      HashJoinTuple tuple);
static inline void ExecParallelHashPushTuple(dsa_pointer_atomic *head,
                                             HashJoinTuple tuple,
                                             dsa_pointer tuple_shared);
static void ExecParallelHashJoinSetUpBatches(HashJoinTable hashtable, int nbatch);
static void ExecParallelHashEnsureBatchAccessors(HashJoinTable hashtable);
static void ExecParallelHashRepartitionFirst(HashJoinTable hashtable);
static void ExecParallelHashRepartitionRest(HashJoinTable hashtable);
static HashMemoryChunk ExecParallelHashPopChunkQueue(HashJoinTable hashtable,
                                                     dsa_pointer *shared);
static bool ExecParallelHashTuplePrealloc(HashJoinTable hashtable,
                                          int batchno,
                                          size_t size);
static void ExecParallelHashMergeCounters(HashJoinTable hashtable);
static void ExecParallelHashCloseBatchAccessors(HashJoinTable hashtable);
 
 
/* ----------------------------------------------------------------
 *      ExecHash
 *
 *      stub for pro forma compliance
 * ----------------------------------------------------------------
 */
static TupleTableSlot *
ExecHash(PlanState *pstate)
{
    elog(ERROR, "Hash node does not support ExecProcNode call convention");
    return NULL;
}
 
/* ----------------------------------------------------------------
 *      MultiExecHash
 *
 *      build hash table for hashjoin, doing partitioning if more
 *      than one batch is required.
 * ----------------------------------------------------------------
 */
Node *
MultiExecHash(HashState *node)
{
    /* must provide our own instrumentation support */
    if (node->ps.instrument)
        InstrStartNode(node->ps.instrument);
 
    if (node->parallel_state != NULL)
        MultiExecParallelHash(node);
    else
        MultiExecPrivateHash(node);
 
    /* must provide our own instrumentation support */
    if (node->ps.instrument)
        InstrStopNode(node->ps.instrument, node->hashtable->partialTuples);
 
    /*
     * We do not return the hash table directly because it's not a subtype of
     * Node, and so would violate the MultiExecProcNode API.  Instead, our
     * parent Hashjoin node is expected to know how to fish it out of our node
     * state.  Ugly but not really worth cleaning up, since Hashjoin knows
     * quite a bit more about Hash besides that.
     */
    return NULL;
}
 
/* ----------------------------------------------------------------
 *      MultiExecPrivateHash
 *
 *      parallel-oblivious version, building a backend-private
 *      hash table and (if necessary) batch files.
 * ----------------------------------------------------------------
 */
static void
MultiExecPrivateHash(HashState *node)
{
    PlanState  *outerNode;
    HashJoinTable hashtable;
    TupleTableSlot *slot;
    ExprContext *econtext;
 
    /*
     * get state info from node
     */
    outerNode = outerPlanState(node);
    hashtable = node->hashtable;
 
    /*
     * set expression context
     */
    econtext = node->ps.ps_ExprContext;
 
    /*
     * Get all tuples from the node below the Hash node and insert into the
     * hash table (or temp files).
     */
    for (;;)
    {
        bool        isnull;
        Datum       hashdatum;
 
        slot = ExecProcNode(outerNode);
        if (TupIsNull(slot))
            break;
        /* We have to compute the hash value */
        econtext->ecxt_outertuple = slot;
 
        ResetExprContext(econtext);
 
        hashdatum = ExecEvalExprSwitchContext(node->hash_expr, econtext,
                                              &isnull);
 
        if (!isnull)
        {
            uint32      hashvalue = DatumGetUInt32(hashdatum);
            int         bucketNumber;
 
            bucketNumber = ExecHashGetSkewBucket(hashtable, hashvalue);
            if (bucketNumber != INVALID_SKEW_BUCKET_NO)
            {
                /* It's a skew tuple, so put it into that hash table */
                ExecHashSkewTableInsert(hashtable, slot, hashvalue,
                                        bucketNumber);
                hashtable->skewTuples += 1;
            }
            else
            {
                /* Not subject to skew optimization, so insert normally */
                ExecHashTableInsert(hashtable, slot, hashvalue);
            }
            hashtable->totalTuples += 1;
        }
    }
 
    /* resize the hash table if needed (NTUP_PER_BUCKET exceeded) */
    if (hashtable->nbuckets != hashtable->nbuckets_optimal)
        ExecHashIncreaseNumBuckets(hashtable);
 
    /* Account for the buckets in spaceUsed (reported in EXPLAIN ANALYZE) */
    hashtable->spaceUsed += hashtable->nbuckets * sizeof(HashJoinTuple);
    if (hashtable->spaceUsed > hashtable->spacePeak)
        hashtable->spacePeak = hashtable->spaceUsed;
 
    hashtable->partialTuples = hashtable->totalTuples;
}
 
/* ----------------------------------------------------------------
 *      MultiExecParallelHash
 *
 *      parallel-aware version, building a shared hash table and
 *      (if necessary) batch files using the combined effort of
 *      a set of co-operating backends.
 * ----------------------------------------------------------------
 */
static void
MultiExecParallelHash(HashState *node)
{
    ParallelHashJoinState *pstate;
    PlanState  *outerNode;
    HashJoinTable hashtable;
    TupleTableSlot *slot;
    ExprContext *econtext;
    uint32      hashvalue;
    Barrier    *build_barrier;
    int         i;
 
    /*
     * get state info from node
     */
    outerNode = outerPlanState(node);
    hashtable = node->hashtable;
 
    /*
     * set expression context
     */
    econtext = node->ps.ps_ExprContext;
 
    /*
     * Synchronize the parallel hash table build.  At this stage we know that
     * the shared hash table has been or is being set up by
     * ExecHashTableCreate(), but we don't know if our peers have returned
     * from there or are here in MultiExecParallelHash(), and if so how far
     * through they are.  To find out, we check the build_barrier phase then
     * and jump to the right step in the build algorithm.
     */
    pstate = hashtable->parallel_state;
    build_barrier = &pstate->build_barrier;
    Assert(BarrierPhase(build_barrier) >= PHJ_BUILD_ALLOCATE);
    switch (BarrierPhase(build_barrier))
    {
        case PHJ_BUILD_ALLOCATE:
 
            /*
             * Either I just allocated the initial hash table in
             * ExecHashTableCreate(), or someone else is doing that.  Either
             * way, wait for everyone to arrive here so we can proceed.
             */
            BarrierArriveAndWait(build_barrier, WAIT_EVENT_HASH_BUILD_ALLOCATE);
            /* Fall through. */
 
        case PHJ_BUILD_HASH_INNER:
 
            /*
             * It's time to begin hashing, or if we just arrived here then
             * hashing is already underway, so join in that effort.  While
             * hashing we have to be prepared to help increase the number of
             * batches or buckets at any time, and if we arrived here when
             * that was already underway we'll have to help complete that work
             * immediately so that it's safe to access batches and buckets
             * below.
             */
            if (PHJ_GROW_BATCHES_PHASE(BarrierAttach(&pstate->grow_batches_barrier)) !=
                PHJ_GROW_BATCHES_ELECT)
                ExecParallelHashIncreaseNumBatches(hashtable);
            if (PHJ_GROW_BUCKETS_PHASE(BarrierAttach(&pstate->grow_buckets_barrier)) !=
                PHJ_GROW_BUCKETS_ELECT)
                ExecParallelHashIncreaseNumBuckets(hashtable);
            ExecParallelHashEnsureBatchAccessors(hashtable);
            ExecParallelHashTableSetCurrentBatch(hashtable, 0);
            for (;;)
            {
                bool        isnull;
 
                slot = ExecProcNode(outerNode);
                if (TupIsNull(slot))
                    break;
                econtext->ecxt_outertuple = slot;
 
                ResetExprContext(econtext);
 
                hashvalue = DatumGetUInt32(ExecEvalExprSwitchContext(node->hash_expr,
                                                                     econtext,
                                                                     &isnull));
 
                if (!isnull)
                    ExecParallelHashTableInsert(hashtable, slot, hashvalue);
                hashtable->partialTuples++;
            }
 
            /*
             * Make sure that any tuples we wrote to disk are visible to
             * others before anyone tries to load them.
             */
            for (i = 0; i < hashtable->nbatch; ++i)
                sts_end_write(hashtable->batches[i].inner_tuples);
 
            /*
             * Update shared counters.  We need an accurate total tuple count
             * to control the empty table optimization.
             */
            ExecParallelHashMergeCounters(hashtable);
 
            BarrierDetach(&pstate->grow_buckets_barrier);
            BarrierDetach(&pstate->grow_batches_barrier);
 
            /*
             * Wait for everyone to finish building and flushing files and
             * counters.
             */
            if (BarrierArriveAndWait(build_barrier,
                                     WAIT_EVENT_HASH_BUILD_HASH_INNER))
            {
                /*
                 * Elect one backend to disable any further growth.  Batches
                 * are now fixed.  While building them we made sure they'd fit
                 * in our memory budget when we load them back in later (or we
                 * tried to do that and gave up because we detected extreme
                 * skew).
                 */
                pstate->growth = PHJ_GROWTH_DISABLED;
            }
    }
 
    /*
     * We're not yet attached to a batch.  We all agree on the dimensions and
     * number of inner tuples (for the empty table optimization).
     */
    hashtable->curbatch = -1;
    hashtable->nbuckets = pstate->nbuckets;
    hashtable->log2_nbuckets = my_log2(hashtable->nbuckets);
    hashtable->totalTuples = pstate->total_tuples;
 
    /*
     * Unless we're completely done and the batch state has been freed, make
     * sure we have accessors.
     */
    if (BarrierPhase(build_barrier) < PHJ_BUILD_FREE)
        ExecParallelHashEnsureBatchAccessors(hashtable);
 
    /*
     * The next synchronization point is in ExecHashJoin's HJ_BUILD_HASHTABLE
     * case, which will bring the build phase to PHJ_BUILD_RUN (if it isn't
     * there already).
     */
    Assert(BarrierPhase(build_barrier) == PHJ_BUILD_HASH_OUTER ||
           BarrierPhase(build_barrier) == PHJ_BUILD_RUN ||
           BarrierPhase(build_barrier) == PHJ_BUILD_FREE);
}
 
/* ----------------------------------------------------------------
 *      ExecInitHash
 *
 *      Init routine for Hash node
 * ----------------------------------------------------------------
 */
HashState *
ExecInitHash(Hash *node, EState *estate, int eflags)
{
    HashState  *hashstate;
 
    /* check for unsupported flags */
    Assert(!(eflags & (EXEC_FLAG_BACKWARD | EXEC_FLAG_MARK)));
 
    /*
     * create state structure
     */
    hashstate = makeNode(HashState);
    hashstate->ps.plan = (Plan *) node;
    hashstate->ps.state = estate;
    hashstate->ps.ExecProcNode = ExecHash;
    /* delay building hashtable until ExecHashTableCreate() in executor run */
    hashstate->hashtable = NULL;
 
    /*
     * Miscellaneous initialization
     *
     * create expression context for node
     */
    ExecAssignExprContext(estate, &hashstate->ps);
 
    /*
     * initialize child nodes
     */
    outerPlanState(hashstate) = ExecInitNode(outerPlan(node), estate, eflags);
 
    /*
     * initialize our result slot and type. No need to build projection
     * because this node doesn't do projections.
     */
    ExecInitResultTupleSlotTL(&hashstate->ps, &TTSOpsMinimalTuple);
    hashstate->ps.ps_ProjInfo = NULL;
 
    Assert(node->plan.qual == NIL);
 
    /*
     * Delay initialization of hash_expr until ExecInitHashJoin().  We cannot
     * build the ExprState here as we don't yet know the join type we're going
     * to be hashing values for and we need to know that before calling
     * ExecBuildHash32Expr as the keep_nulls parameter depends on the join
     * type.
     */
    hashstate->hash_expr = NULL;
 
    return hashstate;
}
 
/* ---------------------------------------------------------------
 *      ExecEndHash
 *
 *      clean up routine for Hash node
 * ----------------------------------------------------------------
 */
void
ExecEndHash(HashState *node)
{
    PlanState  *outerPlan;
 
    /*
     * shut down the subplan
     */
    outerPlan = outerPlanState(node);
    ExecEndNode(outerPlan);
}
 
 
/* ----------------------------------------------------------------
 *      ExecHashTableCreate
 *
 *      create an empty hashtable data structure for hashjoin.
 * ----------------------------------------------------------------
 */
HashJoinTable
ExecHashTableCreate(HashState *state)
{
    Hash       *node;
    HashJoinTable hashtable;
    Plan       *outerNode;
    size_t      space_allowed;
    int         nbuckets;
    int         nbatch;
    double      rows;
    int         num_skew_mcvs;
    int         log2_nbuckets;
    MemoryContext oldcxt;
 
    /*
     * Get information about the size of the relation to be hashed (it's the
     * "outer" subtree of this node, but the inner relation of the hashjoin).
     * Compute the appropriate size of the hash table.
     */
    node = (Hash *) state->ps.plan;
    outerNode = outerPlan(node);
 
    /*
     * If this is shared hash table with a partial plan, then we can't use
     * outerNode->plan_rows to estimate its size.  We need an estimate of the
     * total number of rows across all copies of the partial plan.
     */
    rows = node->plan.parallel_aware ? node->rows_total : outerNode->plan_rows;
 
    ExecChooseHashTableSize(rows, outerNode->plan_width,
                            OidIsValid(node->skewTable),
                            state->parallel_state != NULL,
                            state->parallel_state != NULL ?
                            state->parallel_state->nparticipants - 1 : 0,
                            &space_allowed,
                            &nbuckets, &nbatch, &num_skew_mcvs);
 
    /* nbuckets must be a power of 2 */
    log2_nbuckets = my_log2(nbuckets);
    Assert(nbuckets == (1 << log2_nbuckets));
 
    /*
     * Initialize the hash table control block.
     *
     * The hashtable control block is just palloc'd from the executor's
     * per-query memory context.  Everything else should be kept inside the
     * subsidiary hashCxt, batchCxt or spillCxt.
     */
    hashtable = palloc_object(HashJoinTableData);
    hashtable->nbuckets = nbuckets;
    hashtable->nbuckets_original = nbuckets;
    hashtable->nbuckets_optimal = nbuckets;
    hashtable->log2_nbuckets = log2_nbuckets;
    hashtable->log2_nbuckets_optimal = log2_nbuckets;
    hashtable->buckets.unshared = NULL;
    hashtable->skewEnabled = false;
    hashtable->skewBucket = NULL;
    hashtable->skewBucketLen = 0;
    hashtable->nSkewBuckets = 0;
    hashtable->skewBucketNums = NULL;
    hashtable->nbatch = nbatch;
    hashtable->curbatch = 0;
    hashtable->nbatch_original = nbatch;
    hashtable->nbatch_outstart = nbatch;
    hashtable->growEnabled = true;
    hashtable->totalTuples = 0;
    hashtable->partialTuples = 0;
    hashtable->skewTuples = 0;
    hashtable->innerBatchFile = NULL;
    hashtable->outerBatchFile = NULL;
    hashtable->spaceUsed = 0;
    hashtable->spacePeak = 0;
    hashtable->spaceAllowed = space_allowed;
    hashtable->spaceUsedSkew = 0;
    hashtable->spaceAllowedSkew =
        hashtable->spaceAllowed * SKEW_HASH_MEM_PERCENT / 100;
    hashtable->chunks = NULL;
    hashtable->current_chunk = NULL;
    hashtable->parallel_state = state->parallel_state;
    hashtable->area = state->ps.state->es_query_dsa;
    hashtable->batches = NULL;
 
#ifdef HJDEBUG
    printf("Hashjoin %p: initial nbatch = %d, nbuckets = %d\n",
           hashtable, nbatch, nbuckets);
#endif
 
    /*
     * Create temporary memory contexts in which to keep the hashtable working
     * storage.  See notes in executor/hashjoin.h.
     */
    hashtable->hashCxt = AllocSetContextCreate(CurrentMemoryContext,
                                               "HashTableContext",
                                               ALLOCSET_DEFAULT_SIZES);
 
    hashtable->batchCxt = AllocSetContextCreate(hashtable->hashCxt,
                                                "HashBatchContext",
                                                ALLOCSET_DEFAULT_SIZES);
 
    hashtable->spillCxt = AllocSetContextCreate(hashtable->hashCxt,
                                                "HashSpillContext",
                                                ALLOCSET_DEFAULT_SIZES);
 
    /* Allocate data that will live for the life of the hashjoin */
 
    oldcxt = MemoryContextSwitchTo(hashtable->hashCxt);
 
    if (nbatch > 1 && hashtable->parallel_state == NULL)
    {
        MemoryContext oldctx;
 
        /*
         * allocate and initialize the file arrays in hashCxt (not needed for
         * parallel case which uses shared tuplestores instead of raw files)
         */
        oldctx = MemoryContextSwitchTo(hashtable->spillCxt);
 
        hashtable->innerBatchFile = palloc0_array(BufFile *, nbatch);
        hashtable->outerBatchFile = palloc0_array(BufFile *, nbatch);
 
        MemoryContextSwitchTo(oldctx);
 
        /* The files will not be opened until needed... */
        /* ... but make sure we have temp tablespaces established for them */
        PrepareTempTablespaces();
    }
 
    MemoryContextSwitchTo(oldcxt);
 
    if (hashtable->parallel_state)
    {
        ParallelHashJoinState *pstate = hashtable->parallel_state;
        Barrier    *build_barrier;
 
        /*
         * Attach to the build barrier.  The corresponding detach operation is
         * in ExecHashTableDetach.  Note that we won't attach to the
         * batch_barrier for batch 0 yet.  We'll attach later and start it out
         * in PHJ_BATCH_PROBE phase, because batch 0 is allocated up front and
         * then loaded while hashing (the standard hybrid hash join
         * algorithm), and we'll coordinate that using build_barrier.
         */
        build_barrier = &pstate->build_barrier;
        BarrierAttach(build_barrier);
 
        /*
         * So far we have no idea whether there are any other participants,
         * and if so, what phase they are working on.  The only thing we care
         * about at this point is whether someone has already created the
         * SharedHashJoinBatch objects and the hash table for batch 0.  One
         * backend will be elected to do that now if necessary.
         */
        if (BarrierPhase(build_barrier) == PHJ_BUILD_ELECT &&
            BarrierArriveAndWait(build_barrier, WAIT_EVENT_HASH_BUILD_ELECT))
        {
            pstate->nbatch = nbatch;
            pstate->space_allowed = space_allowed;
            pstate->growth = PHJ_GROWTH_OK;
 
            /* Set up the shared state for coordinating batches. */
            ExecParallelHashJoinSetUpBatches(hashtable, nbatch);
 
            /*
             * Allocate batch 0's hash table up front so we can load it
             * directly while hashing.
             */
            pstate->nbuckets = nbuckets;
            ExecParallelHashTableAlloc(hashtable, 0);
        }
 
        /*
         * The next Parallel Hash synchronization point is in
         * MultiExecParallelHash(), which will progress it all the way to
         * PHJ_BUILD_RUN.  The caller must not return control from this
         * executor node between now and then.
         */
    }
    else
    {
        /*
         * Prepare context for the first-scan space allocations; allocate the
         * hashbucket array therein, and set each bucket "empty".
         */
        MemoryContextSwitchTo(hashtable->batchCxt);
 
        hashtable->buckets.unshared = palloc0_array(HashJoinTuple, nbuckets);
 
        /*
         * Set up for skew optimization, if possible and there's a need for
         * more than one batch.  (In a one-batch join, there's no point in
         * it.)
         */
        if (nbatch > 1)
            ExecHashBuildSkewHash(state, hashtable, node, num_skew_mcvs);
 
        MemoryContextSwitchTo(oldcxt);
    }
 
    return hashtable;
}
 
 
/*
 * Compute appropriate size for hashtable given the estimated size of the
 * relation to be hashed (number of rows and average row width).
 *
 * This is exported so that the planner's costsize.c can use it.
 */
 
/* Target bucket loading (tuples per bucket) */
#define NTUP_PER_BUCKET         1
 
void
ExecChooseHashTableSize(double ntuples, int tupwidth, bool useskew,
                        bool try_combined_hash_mem,
                        int parallel_workers,
                        size_t *space_allowed,
                        int *numbuckets,
                        int *numbatches,
                        int *num_skew_mcvs)
{
    int         tupsize;
    double      inner_rel_bytes;
    size_t      hash_table_bytes;
    size_t      bucket_bytes;
    size_t      max_pointers;
    int         nbatch = 1;
    int         nbuckets;
    double      dbuckets;
 
    /* Force a plausible relation size if no info */
    if (ntuples <= 0.0)
        ntuples = 1000.0;
 
    /*
     * Estimate tupsize based on footprint of tuple in hashtable... note this
     * does not allow for any palloc overhead.  The manipulations of spaceUsed
     * don't count palloc overhead either.
     */
    tupsize = HJTUPLE_OVERHEAD +
        MAXALIGN(SizeofMinimalTupleHeader) +
        MAXALIGN(tupwidth);
    inner_rel_bytes = ntuples * tupsize;
 
    /*
     * Compute in-memory hashtable size limit from GUCs.
     */
    hash_table_bytes = get_hash_memory_limit();
 
    /*
     * Parallel Hash tries to use the combined hash_mem of all workers to
     * avoid the need to batch.  If that won't work, it falls back to hash_mem
     * per worker and tries to process batches in parallel.
     */
    if (try_combined_hash_mem)
    {
        /* Careful, this could overflow size_t */
        double      newlimit;
 
        newlimit = (double) hash_table_bytes * (double) (parallel_workers + 1);
        newlimit = Min(newlimit, (double) SIZE_MAX);
        hash_table_bytes = (size_t) newlimit;
    }
 
    *space_allowed = hash_table_bytes;
 
    /*
     * If skew optimization is possible, estimate the number of skew buckets
     * that will fit in the memory allowed, and decrement the assumed space
     * available for the main hash table accordingly.
     *
     * We make the optimistic assumption that each skew bucket will contain
     * one inner-relation tuple.  If that turns out to be low, we will recover
     * at runtime by reducing the number of skew buckets.
     *
     * hashtable->skewBucket will have up to 8 times as many HashSkewBucket
     * pointers as the number of MCVs we allow, since ExecHashBuildSkewHash
     * will round up to the next power of 2 and then multiply by 4 to reduce
     * collisions.
     */
    if (useskew)
    {
        size_t      bytes_per_mcv;
        size_t      skew_mcvs;
 
        /*----------
         * Compute number of MCVs we could hold in hash_table_bytes
         *
         * Divisor is:
         * size of a hash tuple +
         * worst-case size of skewBucket[] per MCV +
         * size of skewBucketNums[] entry +
         * size of skew bucket struct itself
         *----------
         */
        bytes_per_mcv = tupsize +
            (8 * sizeof(HashSkewBucket *)) +
            sizeof(int) +
            SKEW_BUCKET_OVERHEAD;
        skew_mcvs = hash_table_bytes / bytes_per_mcv;
 
        /*
         * Now scale by SKEW_HASH_MEM_PERCENT (we do it in this order so as
         * not to worry about size_t overflow in the multiplication)
         */
        skew_mcvs = (skew_mcvs * SKEW_HASH_MEM_PERCENT) / 100;
 
        /* Now clamp to integer range */
        skew_mcvs = Min(skew_mcvs, INT_MAX);
 
        *num_skew_mcvs = (int) skew_mcvs;
 
        /* Reduce hash_table_bytes by the amount needed for the skew table */
        if (skew_mcvs > 0)
            hash_table_bytes -= skew_mcvs * bytes_per_mcv;
    }
    else
        *num_skew_mcvs = 0;
 
    /*
     * Set nbuckets to achieve an average bucket load of NTUP_PER_BUCKET when
     * memory is filled, assuming a single batch; but limit the value so that
     * the pointer arrays we'll try to allocate do not exceed hash_table_bytes
     * nor MaxAllocSize.
     *
     * Note that both nbuckets and nbatch must be powers of 2 to make
     * ExecHashGetBucketAndBatch fast.
     */
    max_pointers = hash_table_bytes / sizeof(HashJoinTuple);
    max_pointers = Min(max_pointers, MaxAllocSize / sizeof(HashJoinTuple));
    /* If max_pointers isn't a power of 2, must round it down to one */
    max_pointers = pg_prevpower2_size_t(max_pointers);
 
    /* Also ensure we avoid integer overflow in nbatch and nbuckets */
    /* (this step is redundant given the current value of MaxAllocSize) */
    max_pointers = Min(max_pointers, INT_MAX / 2 + 1);
 
    dbuckets = ceil(ntuples / NTUP_PER_BUCKET);
    dbuckets = Min(dbuckets, max_pointers);
    nbuckets = (int) dbuckets;
    /* don't let nbuckets be really small, though ... */
    nbuckets = Max(nbuckets, 1024);
    /* ... and force it to be a power of 2. */
    nbuckets = pg_nextpower2_32(nbuckets);
 
    /*
     * If there's not enough space to store the projected number of tuples and
     * the required bucket headers, we will need multiple batches.
     */
    bucket_bytes = sizeof(HashJoinTuple) * nbuckets;
    if (inner_rel_bytes + bucket_bytes > hash_table_bytes)
    {
        /* We'll need multiple batches */
        size_t      sbuckets;
        double      dbatch;
        int         minbatch;
        size_t      bucket_size;
 
        /*
         * If Parallel Hash with combined hash_mem would still need multiple
         * batches, we'll have to fall back to regular hash_mem budget.
         */
        if (try_combined_hash_mem)
        {
            ExecChooseHashTableSize(ntuples, tupwidth, useskew,
                                    false, parallel_workers,
                                    space_allowed,
                                    numbuckets,
                                    numbatches,
                                    num_skew_mcvs);
            return;
        }
 
        /*
         * Estimate the number of buckets we'll want to have when hash_mem is
         * entirely full.  Each bucket will contain a bucket pointer plus
         * NTUP_PER_BUCKET tuples, whose projected size already includes
         * overhead for the hash code, pointer to the next tuple, etc.
         */
        bucket_size = (tupsize * NTUP_PER_BUCKET + sizeof(HashJoinTuple));
        if (hash_table_bytes <= bucket_size)
            sbuckets = 1;       /* avoid pg_nextpower2_size_t(0) */
        else
            sbuckets = pg_nextpower2_size_t(hash_table_bytes / bucket_size);
        sbuckets = Min(sbuckets, max_pointers);
        nbuckets = (int) sbuckets;
        nbuckets = pg_nextpower2_32(nbuckets);
        bucket_bytes = nbuckets * sizeof(HashJoinTuple);
 
        /*
         * Buckets are simple pointers to hashjoin tuples, while tupsize
         * includes the pointer, hash code, and MinimalTupleData.  So buckets
         * should never really exceed 25% of hash_mem (even for
         * NTUP_PER_BUCKET=1); except maybe for hash_mem values that are not
         * 2^N bytes, where we might get more because of doubling. So let's
         * look for 50% here.
         */
        Assert(bucket_bytes <= hash_table_bytes / 2);
 
        /* Calculate required number of batches. */
        dbatch = ceil(inner_rel_bytes / (hash_table_bytes - bucket_bytes));
        dbatch = Min(dbatch, max_pointers);
        minbatch = (int) dbatch;
        nbatch = pg_nextpower2_32(Max(2, minbatch));
    }
 
    /*
     * Optimize the total amount of memory consumed by the hash node.
     *
     * The nbatch calculation above focuses on the size of the in-memory hash
     * table, assuming no per-batch overhead. Now adjust the number of batches
     * and the size of the hash table to minimize total memory consumed by the
     * hash node.
     *
     * Each batch file has a BLCKSZ buffer, and we may need two files per
     * batch (inner and outer side). So with enough batches this can be
     * significantly more memory than the hashtable itself.
     *
     * The total memory usage may be expressed by this formula:
     *
     * (inner_rel_bytes / nbatch) + (2 * nbatch * BLCKSZ) <= hash_table_bytes
     *
     * where (inner_rel_bytes / nbatch) is the size of the in-memory hash
     * table and (2 * nbatch * BLCKSZ) is the amount of memory used by file
     * buffers. But for sufficiently large values of inner_rel_bytes value
     * there may not be a nbatch value that would make both parts fit into
     * hash_table_bytes.
     *
     * In this case we can't enforce the memory limit - we're going to exceed
     * it. We can however minimize the impact and use as little memory as
     * possible. (We haven't really enforced it before either, as we simply
     * ignored the batch files.)
     *
     * The formula for total memory usage says that given an inner relation of
     * size inner_rel_bytes, we may divide it into an arbitrary number of
     * batches. This determines both the size of the in-memory hash table and
     * the amount of memory needed for batch files. These two terms work in
     * opposite ways - when one decreases, the other increases.
     *
     * For low nbatch values, the hash table takes most of the memory, but at
     * some point the batch files start to dominate. If you combine these two
     * terms, the memory consumption (for a fixed size of the inner relation)
     * has a u-shape, with a minimum at some nbatch value.
     *
     * Our goal is to find this nbatch value, minimizing the memory usage. We
     * calculate the memory usage with half the batches (i.e. nbatch/2), and
     * if it's lower than the current memory usage we know it's better to use
     * fewer batches. We repeat this until reducing the number of batches does
     * not reduce the memory usage - we found the optimum. We know the optimum
     * exists, thanks to the u-shape.
     *
     * We only want to do this when exceeding the memory limit, not every
     * time. The goal is not to minimize memory usage in every case, but to
     * minimize the memory usage when we can't stay within the memory limit.
     *
     * For this reason we only consider reducing the number of batches. We
     * could try the opposite direction too, but that would save memory only
     * when most of the memory is used by the hash table. And the hash table
     * was used for the initial sizing, so we shouldn't be exceeding the
     * memory limit too much. We might save memory by using more batches, but
     * it would result in spilling more batch files, which does not seem like
     * a great trade off.
     *
     * While growing the hashtable, we also adjust the number of buckets, to
     * not have more than one tuple per bucket (load factor 1). We can only do
     * this during the initial sizing - once we start building the hash,
     * nbucket is fixed.
     */
    while (nbatch > 0)
    {
        /* how much memory are we using with current nbatch value */
        size_t      current_space = hash_table_bytes + (2 * nbatch * BLCKSZ);
 
        /* how much memory would we use with half the batches */
        size_t      new_space = hash_table_bytes * 2 + (nbatch * BLCKSZ);
 
        /* If the memory usage would not decrease, we found the optimum. */
        if (current_space < new_space)
            break;
 
        /*
         * It's better to use half the batches, so do that and adjust the
         * nbucket in the opposite direction, and double the allowance.
         */
        nbatch /= 2;
        nbuckets *= 2;
 
        *space_allowed = (*space_allowed) * 2;
    }
 
    Assert(nbuckets > 0);
    Assert(nbatch > 0);
 
    *numbuckets = nbuckets;
    *numbatches = nbatch;
}
 
 
/* ----------------------------------------------------------------
 *      ExecHashTableDestroy
 *
 *      destroy a hash table
 * ----------------------------------------------------------------
 */
void
ExecHashTableDestroy(HashJoinTable hashtable)
{
    int         i;
 
    /*
     * Make sure all the temp files are closed.  We skip batch 0, since it
     * can't have any temp files (and the arrays might not even exist if
     * nbatch is only 1).  Parallel hash joins don't use these files.
     */
    if (hashtable->innerBatchFile != NULL)
    {
        for (i = 1; i < hashtable->nbatch; i++)
        {
            if (hashtable->innerBatchFile[i])
                BufFileClose(hashtable->innerBatchFile[i]);
            if (hashtable->outerBatchFile[i])
                BufFileClose(hashtable->outerBatchFile[i]);
        }
    }
 
    /* Release working memory (batchCxt is a child, so it goes away too) */
    MemoryContextDelete(hashtable->hashCxt);
 
    /* And drop the control block */
    pfree(hashtable);
}
 
/*
 * Consider adjusting the allowed hash table size, depending on the number
 * of batches, to minimize the overall memory usage (for both the hashtable
 * and batch files).
 *
 * We're adjusting the size of the hash table, not the (optimal) number of
 * buckets. We can't change that once we start building the hash, due to how
 * ExecHashGetBucketAndBatch calculates batchno/bucketno from the hash. This
 * means the load factor may not be optimal, but we're in damage control so
 * we accept slower lookups. It's still much better than batch explosion.
 *
 * Returns true if we chose to increase the batch size (and thus we don't
 * need to add batches), and false if we should increase nbatch.
 */
static bool
ExecHashIncreaseBatchSize(HashJoinTable hashtable)
{
    /*
     * How much additional memory would doubling nbatch use? Each batch may
     * require two buffered files (inner/outer), with a BLCKSZ buffer.
     */
    size_t      batchSpace = (hashtable->nbatch * 2 * BLCKSZ);
 
    /*
     * Compare the new space needed for doubling nbatch and for enlarging the
     * in-memory hash table. If doubling the hash table needs less memory,
     * just do that. Otherwise, continue with doubling the nbatch.
     *
     * We're either doubling spaceAllowed of batchSpace, so which of those
     * increases the memory usage the least is the same as comparing the
     * values directly.
     */
    if (hashtable->spaceAllowed <= batchSpace)
    {
        hashtable->spaceAllowed *= 2;
        return true;
    }
 
    return false;
}
 
/*
 * ExecHashIncreaseNumBatches
 *      increase the original number of batches in order to reduce
 *      current memory consumption
 */
static void
ExecHashIncreaseNumBatches(HashJoinTable hashtable)
{
    int         oldnbatch = hashtable->nbatch;
    int         curbatch = hashtable->curbatch;
    int         nbatch;
    long        ninmemory;
    long        nfreed;
    HashMemoryChunk oldchunks;
 
    /* do nothing if we've decided to shut off growth */
    if (!hashtable->growEnabled)
        return;
 
    /* safety check to avoid overflow */
    if (oldnbatch > Min(INT_MAX / 2, MaxAllocSize / (sizeof(void *) * 2)))
        return;
 
    /* consider increasing size of the in-memory hash table instead */
    if (ExecHashIncreaseBatchSize(hashtable))
        return;
 
    nbatch = oldnbatch * 2;
    Assert(nbatch > 1);
 
#ifdef HJDEBUG
    printf("Hashjoin %p: increasing nbatch to %d because space = %zu\n",
           hashtable, nbatch, hashtable->spaceUsed);
#endif
 
    if (hashtable->innerBatchFile == NULL)
    {
        MemoryContext oldcxt = MemoryContextSwitchTo(hashtable->spillCxt);
 
        /* we had no file arrays before */
        hashtable->innerBatchFile = palloc0_array(BufFile *, nbatch);
        hashtable->outerBatchFile = palloc0_array(BufFile *, nbatch);
 
        MemoryContextSwitchTo(oldcxt);
 
        /* time to establish the temp tablespaces, too */
        PrepareTempTablespaces();
    }
    else
    {
        /* enlarge arrays and zero out added entries */
        hashtable->innerBatchFile = repalloc0_array(hashtable->innerBatchFile, BufFile *, oldnbatch, nbatch);
        hashtable->outerBatchFile = repalloc0_array(hashtable->outerBatchFile, BufFile *, oldnbatch, nbatch);
    }
 
    hashtable->nbatch = nbatch;
 
    /*
     * Scan through the existing hash table entries and dump out any that are
     * no longer of the current batch.
     */
    ninmemory = nfreed = 0;
 
    /* If know we need to resize nbuckets, we can do it while rebatching. */
    if (hashtable->nbuckets_optimal != hashtable->nbuckets)
    {
        /* we never decrease the number of buckets */
        Assert(hashtable->nbuckets_optimal > hashtable->nbuckets);
 
        hashtable->nbuckets = hashtable->nbuckets_optimal;
        hashtable->log2_nbuckets = hashtable->log2_nbuckets_optimal;
 
        hashtable->buckets.unshared =
            repalloc_array(hashtable->buckets.unshared,
                           HashJoinTuple, hashtable->nbuckets);
    }
 
    /*
     * We will scan through the chunks directly, so that we can reset the
     * buckets now and not have to keep track which tuples in the buckets have
     * already been processed. We will free the old chunks as we go.
     */
    memset(hashtable->buckets.unshared, 0,
           sizeof(HashJoinTuple) * hashtable->nbuckets);
    oldchunks = hashtable->chunks;
    hashtable->chunks = NULL;
 
    /* so, let's scan through the old chunks, and all tuples in each chunk */
    while (oldchunks != NULL)
    {
        HashMemoryChunk nextchunk = oldchunks->next.unshared;
 
        /* position within the buffer (up to oldchunks->used) */
        size_t      idx = 0;
 
        /* process all tuples stored in this chunk (and then free it) */
        while (idx < oldchunks->used)
        {
            HashJoinTuple hashTuple = (HashJoinTuple) (HASH_CHUNK_DATA(oldchunks) + idx);
            MinimalTuple tuple = HJTUPLE_MINTUPLE(hashTuple);
            int         hashTupleSize = (HJTUPLE_OVERHEAD + tuple->t_len);
            int         bucketno;
            int         batchno;
 
            ninmemory++;
            ExecHashGetBucketAndBatch(hashtable, hashTuple->hashvalue,
                                      &bucketno, &batchno);
 
            if (batchno == curbatch)
            {
                /* keep tuple in memory - copy it into the new chunk */
                HashJoinTuple copyTuple;
 
                copyTuple = (HashJoinTuple) dense_alloc(hashtable, hashTupleSize);
                memcpy(copyTuple, hashTuple, hashTupleSize);
 
                /* and add it back to the appropriate bucket */
                copyTuple->next.unshared = hashtable->buckets.unshared[bucketno];
                hashtable->buckets.unshared[bucketno] = copyTuple;
            }
            else
            {
                /* dump it out */
                Assert(batchno > curbatch);
                ExecHashJoinSaveTuple(HJTUPLE_MINTUPLE(hashTuple),
                                      hashTuple->hashvalue,
                                      &hashtable->innerBatchFile[batchno],
                                      hashtable);
 
                hashtable->spaceUsed -= hashTupleSize;
                nfreed++;
            }
 
            /* next tuple in this chunk */
            idx += MAXALIGN(hashTupleSize);
 
            /* allow this loop to be cancellable */
            CHECK_FOR_INTERRUPTS();
        }
 
        /* we're done with this chunk - free it and proceed to the next one */
        pfree(oldchunks);
        oldchunks = nextchunk;
    }
 
#ifdef HJDEBUG
    printf("Hashjoin %p: freed %ld of %ld tuples, space now %zu\n",
           hashtable, nfreed, ninmemory, hashtable->spaceUsed);
#endif
 
    /*
     * If we dumped out either all or none of the tuples in the table, disable
     * further expansion of nbatch.  This situation implies that we have
     * enough tuples of identical hashvalues to overflow spaceAllowed.
     * Increasing nbatch will not fix it since there's no way to subdivide the
     * group any more finely. We have to just gut it out and hope the server
     * has enough RAM.
     */
    if (nfreed == 0 || nfreed == ninmemory)
    {
        hashtable->growEnabled = false;
#ifdef HJDEBUG
        printf("Hashjoin %p: disabling further increase of nbatch\n",
               hashtable);
#endif
    }
}
 
/*
 * ExecParallelHashIncreaseNumBatches
 *      Every participant attached to grow_batches_barrier must run this
 *      function when it observes growth == PHJ_GROWTH_NEED_MORE_BATCHES.
 */
static void
ExecParallelHashIncreaseNumBatches(HashJoinTable hashtable)
{
    ParallelHashJoinState *pstate = hashtable->parallel_state;
 
    Assert(BarrierPhase(&pstate->build_barrier) == PHJ_BUILD_HASH_INNER);
 
    /*
     * It's unlikely, but we need to be prepared for new participants to show
     * up while we're in the middle of this operation so we need to switch on
     * barrier phase here.
     */
    switch (PHJ_GROW_BATCHES_PHASE(BarrierPhase(&pstate->grow_batches_barrier)))
    {
        case PHJ_GROW_BATCHES_ELECT:
 
            /*
             * Elect one participant to prepare to grow the number of batches.
             * This involves reallocating or resetting the buckets of batch 0
             * in preparation for all participants to begin repartitioning the
             * tuples.
             */
            if (BarrierArriveAndWait(&pstate->grow_batches_barrier,
                                     WAIT_EVENT_HASH_GROW_BATCHES_ELECT))
            {
                dsa_pointer_atomic *buckets;
                ParallelHashJoinBatch *old_batch0;
                int         new_nbatch;
                int         i;
 
                /* Move the old batch out of the way. */
                old_batch0 = hashtable->batches[0].shared;
                pstate->old_batches = pstate->batches;
                pstate->old_nbatch = hashtable->nbatch;
                pstate->batches = InvalidDsaPointer;
 
                /* Free this backend's old accessors. */
                ExecParallelHashCloseBatchAccessors(hashtable);
 
                /* Figure out how many batches to use. */
                if (hashtable->nbatch == 1)
                {
                    /*
                     * We are going from single-batch to multi-batch.  We need
                     * to switch from one large combined memory budget to the
                     * regular hash_mem budget.
                     */
                    pstate->space_allowed = get_hash_memory_limit();
 
                    /*
                     * The combined hash_mem of all participants wasn't
                     * enough. Therefore one batch per participant would be
                     * approximately equivalent and would probably also be
                     * insufficient.  So try two batches per participant,
                     * rounded up to a power of two.
                     */
                    new_nbatch = pg_nextpower2_32(pstate->nparticipants * 2);
                }
                else
                {
                    /*
                     * We were already multi-batched.  Try doubling the number
                     * of batches.
                     */
                    new_nbatch = hashtable->nbatch * 2;
                }
 
                /* Allocate new larger generation of batches. */
                Assert(hashtable->nbatch == pstate->nbatch);
                ExecParallelHashJoinSetUpBatches(hashtable, new_nbatch);
                Assert(hashtable->nbatch == pstate->nbatch);
 
                /* Replace or recycle batch 0's bucket array. */
                if (pstate->old_nbatch == 1)
                {
                    double      dtuples;
                    double      dbuckets;
                    int         new_nbuckets;
                    uint32      max_buckets;
 
                    /*
                     * We probably also need a smaller bucket array.  How many
                     * tuples do we expect per batch, assuming we have only
                     * half of them so far?  Normally we don't need to change
                     * the bucket array's size, because the size of each batch
                     * stays the same as we add more batches, but in this
                     * special case we move from a large batch to many smaller
                     * batches and it would be wasteful to keep the large
                     * array.
                     */
                    dtuples = (old_batch0->ntuples * 2.0) / new_nbatch;
 
                    /*
                     * We need to calculate the maximum number of buckets to
                     * stay within the MaxAllocSize boundary.  Round the
                     * maximum number to the previous power of 2 given that
                     * later we round the number to the next power of 2.
                     */
                    max_buckets = pg_prevpower2_32((uint32)
                                                   (MaxAllocSize / sizeof(dsa_pointer_atomic)));
                    dbuckets = ceil(dtuples / NTUP_PER_BUCKET);
                    dbuckets = Min(dbuckets, max_buckets);
                    new_nbuckets = (int) dbuckets;
                    new_nbuckets = Max(new_nbuckets, 1024);
                    new_nbuckets = pg_nextpower2_32(new_nbuckets);
                    dsa_free(hashtable->area, old_batch0->buckets);
                    hashtable->batches[0].shared->buckets =
                        dsa_allocate(hashtable->area,
                                     sizeof(dsa_pointer_atomic) * new_nbuckets);
                    buckets = (dsa_pointer_atomic *)
                        dsa_get_address(hashtable->area,
                                        hashtable->batches[0].shared->buckets);
                    for (i = 0; i < new_nbuckets; ++i)
                        dsa_pointer_atomic_init(&buckets[i], InvalidDsaPointer);
                    pstate->nbuckets = new_nbuckets;
                }
                else
                {
                    /* Recycle the existing bucket array. */
                    hashtable->batches[0].shared->buckets = old_batch0->buckets;
                    buckets = (dsa_pointer_atomic *)
                        dsa_get_address(hashtable->area, old_batch0->buckets);
                    for (i = 0; i < hashtable->nbuckets; ++i)
                        dsa_pointer_atomic_write(&buckets[i], InvalidDsaPointer);
                }
 
                /* Move all chunks to the work queue for parallel processing. */
                pstate->chunk_work_queue = old_batch0->chunks;
 
                /* Disable further growth temporarily while we're growing. */
                pstate->growth = PHJ_GROWTH_DISABLED;
            }
            else
            {
                /* All other participants just flush their tuples to disk. */
                ExecParallelHashCloseBatchAccessors(hashtable);
            }
            /* Fall through. */
 
        case PHJ_GROW_BATCHES_REALLOCATE:
            /* Wait for the above to be finished. */
            BarrierArriveAndWait(&pstate->grow_batches_barrier,
                                 WAIT_EVENT_HASH_GROW_BATCHES_REALLOCATE);
            /* Fall through. */
 
        case PHJ_GROW_BATCHES_REPARTITION:
            /* Make sure that we have the current dimensions and buckets. */
            ExecParallelHashEnsureBatchAccessors(hashtable);
            ExecParallelHashTableSetCurrentBatch(hashtable, 0);
            /* Then partition, flush counters. */
            ExecParallelHashRepartitionFirst(hashtable);
            ExecParallelHashRepartitionRest(hashtable);
            ExecParallelHashMergeCounters(hashtable);
            /* Wait for the above to be finished. */
            BarrierArriveAndWait(&pstate->grow_batches_barrier,
                                 WAIT_EVENT_HASH_GROW_BATCHES_REPARTITION);
            /* Fall through. */
 
        case PHJ_GROW_BATCHES_DECIDE:
 
            /*
             * Elect one participant to clean up and decide whether further
             * repartitioning is needed, or should be disabled because it's
             * not helping.
             */
            if (BarrierArriveAndWait(&pstate->grow_batches_barrier,
                                     WAIT_EVENT_HASH_GROW_BATCHES_DECIDE))
            {
                ParallelHashJoinBatch *old_batches;
                bool        space_exhausted = false;
                bool        extreme_skew_detected = false;
 
                /* Make sure that we have the current dimensions and buckets. */
                ExecParallelHashEnsureBatchAccessors(hashtable);
                ExecParallelHashTableSetCurrentBatch(hashtable, 0);
 
                old_batches = dsa_get_address(hashtable->area, pstate->old_batches);
 
                /* Are any of the new generation of batches exhausted? */
                for (int i = 0; i < hashtable->nbatch; ++i)
                {
                    ParallelHashJoinBatch *batch;
                    ParallelHashJoinBatch *old_batch;
                    int         parent;
 
                    batch = hashtable->batches[i].shared;
                    if (batch->space_exhausted ||
                        batch->estimated_size > pstate->space_allowed)
                        space_exhausted = true;
 
                    parent = i % pstate->old_nbatch;
                    old_batch = NthParallelHashJoinBatch(old_batches, parent);
                    if (old_batch->space_exhausted ||
                        batch->estimated_size > pstate->space_allowed)
                    {
                        /*
                         * Did this batch receive ALL of the tuples from its
                         * parent batch?  That would indicate that further
                         * repartitioning isn't going to help (the hash values
                         * are probably all the same).
                         */
                        if (batch->ntuples == hashtable->batches[parent].shared->old_ntuples)
                            extreme_skew_detected = true;
                    }
                }
 
                /* Don't keep growing if it's not helping or we'd overflow. */
                if (extreme_skew_detected || hashtable->nbatch >= INT_MAX / 2)
                    pstate->growth = PHJ_GROWTH_DISABLED;
                else if (space_exhausted)
                    pstate->growth = PHJ_GROWTH_NEED_MORE_BATCHES;
                else
                    pstate->growth = PHJ_GROWTH_OK;
 
                /* Free the old batches in shared memory. */
                dsa_free(hashtable->area, pstate->old_batches);
                pstate->old_batches = InvalidDsaPointer;
            }
            /* Fall through. */
 
        case PHJ_GROW_BATCHES_FINISH:
            /* Wait for the above to complete. */
            BarrierArriveAndWait(&pstate->grow_batches_barrier,
                                 WAIT_EVENT_HASH_GROW_BATCHES_FINISH);
    }
}
 
/*
 * Repartition the tuples currently loaded into memory for inner batch 0
 * because the number of batches has been increased.  Some tuples are retained
 * in memory and some are written out to a later batch.
 */
static void
ExecParallelHashRepartitionFirst(HashJoinTable hashtable)
{
    dsa_pointer chunk_shared;
    HashMemoryChunk chunk;
 
    Assert(hashtable->nbatch == hashtable->parallel_state->nbatch);
 
    while ((chunk = ExecParallelHashPopChunkQueue(hashtable, &chunk_shared)))
    {
        size_t      idx = 0;
 
        /* Repartition all tuples in this chunk. */
        while (idx < chunk->used)
        {
            HashJoinTuple hashTuple = (HashJoinTuple) (HASH_CHUNK_DATA(chunk) + idx);
            MinimalTuple tuple = HJTUPLE_MINTUPLE(hashTuple);
            HashJoinTuple copyTuple;
            dsa_pointer shared;
            int         bucketno;
            int         batchno;
 
            ExecHashGetBucketAndBatch(hashtable, hashTuple->hashvalue,
                                      &bucketno, &batchno);
 
            Assert(batchno < hashtable->nbatch);
            if (batchno == 0)
            {
                /* It still belongs in batch 0.  Copy to a new chunk. */
                copyTuple =
                    ExecParallelHashTupleAlloc(hashtable,
                                               HJTUPLE_OVERHEAD + tuple->t_len,
                                               &shared);
                copyTuple->hashvalue = hashTuple->hashvalue;
                memcpy(HJTUPLE_MINTUPLE(copyTuple), tuple, tuple->t_len);
                ExecParallelHashPushTuple(&hashtable->buckets.shared[bucketno],
                                          copyTuple, shared);
            }
            else
            {
                size_t      tuple_size =
                    MAXALIGN(HJTUPLE_OVERHEAD + tuple->t_len);
 
                /* It belongs in a later batch. */
                hashtable->batches[batchno].estimated_size += tuple_size;
                sts_puttuple(hashtable->batches[batchno].inner_tuples,
                             &hashTuple->hashvalue, tuple);
            }
 
            /* Count this tuple. */
            ++hashtable->batches[0].old_ntuples;
            ++hashtable->batches[batchno].ntuples;
 
            idx += MAXALIGN(HJTUPLE_OVERHEAD +
                            HJTUPLE_MINTUPLE(hashTuple)->t_len);
        }
 
        /* Free this chunk. */
        dsa_free(hashtable->area, chunk_shared);
 
        CHECK_FOR_INTERRUPTS();
    }
}
 
/*
 * Help repartition inner batches 1..n.
 */
static void
ExecParallelHashRepartitionRest(HashJoinTable hashtable)
{
    ParallelHashJoinState *pstate = hashtable->parallel_state;
    int         old_nbatch = pstate->old_nbatch;
    SharedTuplestoreAccessor **old_inner_tuples;
    ParallelHashJoinBatch *old_batches;
    int         i;
 
    /* Get our hands on the previous generation of batches. */
    old_batches = (ParallelHashJoinBatch *)
        dsa_get_address(hashtable->area, pstate->old_batches);
    old_inner_tuples = palloc0_array(SharedTuplestoreAccessor *, old_nbatch);
    for (i = 1; i < old_nbatch; ++i)
    {
        ParallelHashJoinBatch *shared =
            NthParallelHashJoinBatch(old_batches, i);
 
        old_inner_tuples[i] = sts_attach(ParallelHashJoinBatchInner(shared),
                                         ParallelWorkerNumber + 1,
                                         &pstate->fileset);
    }
 
    /* Join in the effort to repartition them. */
    for (i = 1; i < old_nbatch; ++i)
    {
        MinimalTuple tuple;
        uint32      hashvalue;
 
        /* Scan one partition from the previous generation. */
        sts_begin_parallel_scan(old_inner_tuples[i]);
        while ((tuple = sts_parallel_scan_next(old_inner_tuples[i], &hashvalue)))
        {
            size_t      tuple_size = MAXALIGN(HJTUPLE_OVERHEAD + tuple->t_len);
            int         bucketno;
            int         batchno;
 
            /* Decide which partition it goes to in the new generation. */
            ExecHashGetBucketAndBatch(hashtable, hashvalue, &bucketno,
                                      &batchno);
 
            hashtable->batches[batchno].estimated_size += tuple_size;
            ++hashtable->batches[batchno].ntuples;
            ++hashtable->batches[i].old_ntuples;
 
            /* Store the tuple its new batch. */
            sts_puttuple(hashtable->batches[batchno].inner_tuples,
                         &hashvalue, tuple);
 
            CHECK_FOR_INTERRUPTS();
        }
        sts_end_parallel_scan(old_inner_tuples[i]);
    }
 
    pfree(old_inner_tuples);
}
 
/*
 * Transfer the backend-local per-batch counters to the shared totals.
 */
static void
ExecParallelHashMergeCounters(HashJoinTable hashtable)
{
    ParallelHashJoinState *pstate = hashtable->parallel_state;
    int         i;
 
    LWLockAcquire(&pstate->lock, LW_EXCLUSIVE);
    pstate->total_tuples = 0;
    for (i = 0; i < hashtable->nbatch; ++i)
    {
        ParallelHashJoinBatchAccessor *batch = &hashtable->batches[i];
 
        batch->shared->size += batch->size;
        batch->shared->estimated_size += batch->estimated_size;
        batch->shared->ntuples += batch->ntuples;
        batch->shared->old_ntuples += batch->old_ntuples;
        batch->size = 0;
        batch->estimated_size = 0;
        batch->ntuples = 0;
        batch->old_ntuples = 0;
        pstate->total_tuples += batch->shared->ntuples;
    }
    LWLockRelease(&pstate->lock);
}
 
/*
 * ExecHashIncreaseNumBuckets
 *      increase the original number of buckets in order to reduce
 *      number of tuples per bucket
 */
static void
ExecHashIncreaseNumBuckets(HashJoinTable hashtable)
{
    HashMemoryChunk chunk;
 
    /* do nothing if not an increase (it's called increase for a reason) */
    if (hashtable->nbuckets >= hashtable->nbuckets_optimal)
        return;
 
#ifdef HJDEBUG
    printf("Hashjoin %p: increasing nbuckets %d => %d\n",
           hashtable, hashtable->nbuckets, hashtable->nbuckets_optimal);
#endif
 
    hashtable->nbuckets = hashtable->nbuckets_optimal;
    hashtable->log2_nbuckets = hashtable->log2_nbuckets_optimal;
 
    Assert(hashtable->nbuckets > 1);
    Assert(hashtable->nbuckets <= (INT_MAX / 2));
    Assert(hashtable->nbuckets == (1 << hashtable->log2_nbuckets));
 
    /*
     * Just reallocate the proper number of buckets - we don't need to walk
     * through them - we can walk the dense-allocated chunks (just like in
     * ExecHashIncreaseNumBatches, but without all the copying into new
     * chunks)
     */
    hashtable->buckets.unshared =
        repalloc_array(hashtable->buckets.unshared,
                       HashJoinTuple, hashtable->nbuckets);
 
    memset(hashtable->buckets.unshared, 0,
           hashtable->nbuckets * sizeof(HashJoinTuple));
 
    /* scan through all tuples in all chunks to rebuild the hash table */
    for (chunk = hashtable->chunks; chunk != NULL; chunk = chunk->next.unshared)
    {
        /* process all tuples stored in this chunk */
        size_t      idx = 0;
 
        while (idx < chunk->used)
        {
            HashJoinTuple hashTuple = (HashJoinTuple) (HASH_CHUNK_DATA(chunk) + idx);
            int         bucketno;
            int         batchno;
 
            ExecHashGetBucketAndBatch(hashtable, hashTuple->hashvalue,
                                      &bucketno, &batchno);
 
            /* add the tuple to the proper bucket */
            hashTuple->next.unshared = hashtable->buckets.unshared[bucketno];
            hashtable->buckets.unshared[bucketno] = hashTuple;
 
            /* advance index past the tuple */
            idx += MAXALIGN(HJTUPLE_OVERHEAD +
                            HJTUPLE_MINTUPLE(hashTuple)->t_len);
        }
 
        /* allow this loop to be cancellable */
        CHECK_FOR_INTERRUPTS();
    }
}
 
static void
ExecParallelHashIncreaseNumBuckets(HashJoinTable hashtable)
{
    ParallelHashJoinState *pstate = hashtable->parallel_state;
    int         i;
    HashMemoryChunk chunk;
    dsa_pointer chunk_s;
 
    Assert(BarrierPhase(&pstate->build_barrier) == PHJ_BUILD_HASH_INNER);
 
    /*
     * It's unlikely, but we need to be prepared for new participants to show
     * up while we're in the middle of this operation so we need to switch on
     * barrier phase here.
     */
    switch (PHJ_GROW_BUCKETS_PHASE(BarrierPhase(&pstate->grow_buckets_barrier)))
    {
        case PHJ_GROW_BUCKETS_ELECT:
            /* Elect one participant to prepare to increase nbuckets. */
            if (BarrierArriveAndWait(&pstate->grow_buckets_barrier,
                                     WAIT_EVENT_HASH_GROW_BUCKETS_ELECT))
            {
                size_t      size;
                dsa_pointer_atomic *buckets;
 
                /* Double the size of the bucket array. */
                pstate->nbuckets *= 2;
                size = pstate->nbuckets * sizeof(dsa_pointer_atomic);
                hashtable->batches[0].shared->size += size / 2;
                dsa_free(hashtable->area, hashtable->batches[0].shared->buckets);
                hashtable->batches[0].shared->buckets =
                    dsa_allocate(hashtable->area, size);
                buckets = (dsa_pointer_atomic *)
                    dsa_get_address(hashtable->area,
                                    hashtable->batches[0].shared->buckets);
                for (i = 0; i < pstate->nbuckets; ++i)
                    dsa_pointer_atomic_init(&buckets[i], InvalidDsaPointer);
 
                /* Put the chunk list onto the work queue. */
                pstate->chunk_work_queue = hashtable->batches[0].shared->chunks;
 
                /* Clear the flag. */
                pstate->growth = PHJ_GROWTH_OK;
            }
            /* Fall through. */
 
        case PHJ_GROW_BUCKETS_REALLOCATE:
            /* Wait for the above to complete. */
            BarrierArriveAndWait(&pstate->grow_buckets_barrier,
                                 WAIT_EVENT_HASH_GROW_BUCKETS_REALLOCATE);
            /* Fall through. */
 
        case PHJ_GROW_BUCKETS_REINSERT:
            /* Reinsert all tuples into the hash table. */
            ExecParallelHashEnsureBatchAccessors(hashtable);
            ExecParallelHashTableSetCurrentBatch(hashtable, 0);
            while ((chunk = ExecParallelHashPopChunkQueue(hashtable, &chunk_s)))
            {
                size_t      idx = 0;
 
                while (idx < chunk->used)
                {
                    HashJoinTuple hashTuple = (HashJoinTuple) (HASH_CHUNK_DATA(chunk) + idx);
                    dsa_pointer shared = chunk_s + HASH_CHUNK_HEADER_SIZE + idx;
                    int         bucketno;
                    int         batchno;
 
                    ExecHashGetBucketAndBatch(hashtable, hashTuple->hashvalue,
                                              &bucketno, &batchno);
                    Assert(batchno == 0);
 
                    /* add the tuple to the proper bucket */
                    ExecParallelHashPushTuple(&hashtable->buckets.shared[bucketno],
                                              hashTuple, shared);
 
                    /* advance index past the tuple */
                    idx += MAXALIGN(HJTUPLE_OVERHEAD +
                                    HJTUPLE_MINTUPLE(hashTuple)->t_len);
                }
 
                /* allow this loop to be cancellable */
                CHECK_FOR_INTERRUPTS();
            }
            BarrierArriveAndWait(&pstate->grow_buckets_barrier,
                                 WAIT_EVENT_HASH_GROW_BUCKETS_REINSERT);
    }
}
 
/*
 * ExecHashTableInsert
 *      insert a tuple into the hash table depending on the hash value
 *      it may just go to a temp file for later batches
 *
 * Note: the passed TupleTableSlot may contain a regular, minimal, or virtual
 * tuple; the minimal case in particular is certain to happen while reloading
 * tuples from batch files.  We could save some cycles in the regular-tuple
 * case by not forcing the slot contents into minimal form; not clear if it's
 * worth the messiness required.
 */
void
ExecHashTableInsert(HashJoinTable hashtable,
                    TupleTableSlot *slot,
                    uint32 hashvalue)
{
    bool        shouldFree;
    MinimalTuple tuple = ExecFetchSlotMinimalTuple(slot, &shouldFree);
    int         bucketno;
    int         batchno;
 
    ExecHashGetBucketAndBatch(hashtable, hashvalue,
                              &bucketno, &batchno);
 
    /*
     * decide whether to put the tuple in the hash table or a temp file
     */
    if (batchno == hashtable->curbatch)
    {
        /*
         * put the tuple in hash table
         */
        HashJoinTuple hashTuple;
        int         hashTupleSize;
        double      ntuples = (hashtable->totalTuples - hashtable->skewTuples);
 
        /* Create the HashJoinTuple */
        hashTupleSize = HJTUPLE_OVERHEAD + tuple->t_len;
        hashTuple = (HashJoinTuple) dense_alloc(hashtable, hashTupleSize);
 
        hashTuple->hashvalue = hashvalue;
        memcpy(HJTUPLE_MINTUPLE(hashTuple), tuple, tuple->t_len);
 
        /*
         * We always reset the tuple-matched flag on insertion.  This is okay
         * even when reloading a tuple from a batch file, since the tuple
         * could not possibly have been matched to an outer tuple before it
         * went into the batch file.
         */
        HeapTupleHeaderClearMatch(HJTUPLE_MINTUPLE(hashTuple));
 
        /* Push it onto the front of the bucket's list */
        hashTuple->next.unshared = hashtable->buckets.unshared[bucketno];
        hashtable->buckets.unshared[bucketno] = hashTuple;
 
        /*
         * Increase the (optimal) number of buckets if we just exceeded the
         * NTUP_PER_BUCKET threshold, but only when there's still a single
         * batch.
         */
        if (hashtable->nbatch == 1 &&
            ntuples > (hashtable->nbuckets_optimal * NTUP_PER_BUCKET))
        {
            /* Guard against integer overflow and alloc size overflow */
            if (hashtable->nbuckets_optimal <= INT_MAX / 2 &&
                hashtable->nbuckets_optimal * 2 <= MaxAllocSize / sizeof(HashJoinTuple))
            {
                hashtable->nbuckets_optimal *= 2;
                hashtable->log2_nbuckets_optimal += 1;
            }
        }
 
        /* Account for space used, and back off if we've used too much */
        hashtable->spaceUsed += hashTupleSize;
        if (hashtable->spaceUsed > hashtable->spacePeak)
            hashtable->spacePeak = hashtable->spaceUsed;
        if (hashtable->spaceUsed +
            hashtable->nbuckets_optimal * sizeof(HashJoinTuple)
            > hashtable->spaceAllowed)
            ExecHashIncreaseNumBatches(hashtable);
    }
    else
    {
        /*
         * put the tuple into a temp file for later batches
         */
        Assert(batchno > hashtable->curbatch);
        ExecHashJoinSaveTuple(tuple,
                              hashvalue,
                              &hashtable->innerBatchFile[batchno],
                              hashtable);
    }
 
    if (shouldFree)
        heap_free_minimal_tuple(tuple);
}
 
/*
 * ExecParallelHashTableInsert
 *      insert a tuple into a shared hash table or shared batch tuplestore
 */
void
ExecParallelHashTableInsert(HashJoinTable hashtable,
                            TupleTableSlot *slot,
                            uint32 hashvalue)
{
    bool        shouldFree;
    MinimalTuple tuple = ExecFetchSlotMinimalTuple(slot, &shouldFree);
    dsa_pointer shared;
    int         bucketno;
    int         batchno;
 
retry:
    ExecHashGetBucketAndBatch(hashtable, hashvalue, &bucketno, &batchno);
 
    if (batchno == 0)
    {
        HashJoinTuple hashTuple;
 
        /* Try to load it into memory. */
        Assert(BarrierPhase(&hashtable->parallel_state->build_barrier) ==
               PHJ_BUILD_HASH_INNER);
        hashTuple = ExecParallelHashTupleAlloc(hashtable,
                                               HJTUPLE_OVERHEAD + tuple->t_len,
                                               &shared);
        if (hashTuple == NULL)
            goto retry;
 
        /* Store the hash value in the HashJoinTuple header. */
        hashTuple->hashvalue = hashvalue;
        memcpy(HJTUPLE_MINTUPLE(hashTuple), tuple, tuple->t_len);
        HeapTupleHeaderClearMatch(HJTUPLE_MINTUPLE(hashTuple));
 
        /* Push it onto the front of the bucket's list */
        ExecParallelHashPushTuple(&hashtable->buckets.shared[bucketno],
                                  hashTuple, shared);
    }
    else
    {
        size_t      tuple_size = MAXALIGN(HJTUPLE_OVERHEAD + tuple->t_len);
 
        Assert(batchno > 0);
 
        /* Try to preallocate space in the batch if necessary. */
        if (hashtable->batches[batchno].preallocated < tuple_size)
        {
            if (!ExecParallelHashTuplePrealloc(hashtable, batchno, tuple_size))
                goto retry;
        }
 
        Assert(hashtable->batches[batchno].preallocated >= tuple_size);
        hashtable->batches[batchno].preallocated -= tuple_size;
        sts_puttuple(hashtable->batches[batchno].inner_tuples, &hashvalue,
                     tuple);
    }
    ++hashtable->batches[batchno].ntuples;
 
    if (shouldFree)
        heap_free_minimal_tuple(tuple);
}
 
/*
 * Insert a tuple into the current hash table.  Unlike
 * ExecParallelHashTableInsert, this version is not prepared to send the tuple
 * to other batches or to run out of memory, and should only be called with
 * tuples that belong in the current batch once growth has been disabled.
 */
void
ExecParallelHashTableInsertCurrentBatch(HashJoinTable hashtable,
                                        TupleTableSlot *slot,
                                        uint32 hashvalue)
{
    bool        shouldFree;
    MinimalTuple tuple = ExecFetchSlotMinimalTuple(slot, &shouldFree);
    HashJoinTuple hashTuple;
    dsa_pointer shared;
    int         batchno;
    int         bucketno;
 
    ExecHashGetBucketAndBatch(hashtable, hashvalue, &bucketno, &batchno);
    Assert(batchno == hashtable->curbatch);
    hashTuple = ExecParallelHashTupleAlloc(hashtable,
                                           HJTUPLE_OVERHEAD + tuple->t_len,
                                           &shared);
    hashTuple->hashvalue = hashvalue;
    memcpy(HJTUPLE_MINTUPLE(hashTuple), tuple, tuple->t_len);
    HeapTupleHeaderClearMatch(HJTUPLE_MINTUPLE(hashTuple));
    ExecParallelHashPushTuple(&hashtable->buckets.shared[bucketno],
                              hashTuple, shared);
 
    if (shouldFree)
        heap_free_minimal_tuple(tuple);
}
 
 
/*
 * ExecHashGetBucketAndBatch
 *      Determine the bucket number and batch number for a hash value
 *
 * Note: on-the-fly increases of nbatch must not change the bucket number
 * for a given hash code (since we don't move tuples to different hash
 * chains), and must only cause the batch number to remain the same or
 * increase.  Our algorithm is
 *      bucketno = hashvalue MOD nbuckets
 *      batchno = ROR(hashvalue, log2_nbuckets) MOD nbatch
 * where nbuckets and nbatch are both expected to be powers of 2, so we can
 * do the computations by shifting and masking.  (This assumes that all hash
 * functions are good about randomizing all their output bits, else we are
 * likely to have very skewed bucket or batch occupancy.)
 *
 * nbuckets and log2_nbuckets may change while nbatch == 1 because of dynamic
 * bucket count growth.  Once we start batching, the value is fixed and does
 * not change over the course of the join (making it possible to compute batch
 * number the way we do here).
 *
 * nbatch is always a power of 2; we increase it only by doubling it.  This
 * effectively adds one more bit to the top of the batchno.  In very large
 * joins, we might run out of bits to add, so we do this by rotating the hash
 * value.  This causes batchno to steal bits from bucketno when the number of
 * virtual buckets exceeds 2^32.  It's better to have longer bucket chains
 * than to lose the ability to divide batches.
 */
void
ExecHashGetBucketAndBatch(HashJoinTable hashtable,
                          uint32 hashvalue,
                          int *bucketno,
                          int *batchno)
{
    uint32      nbuckets = (uint32) hashtable->nbuckets;
    uint32      nbatch = (uint32) hashtable->nbatch;
 
    if (nbatch > 1)
    {
        *bucketno = hashvalue & (nbuckets - 1);
        *batchno = pg_rotate_right32(hashvalue,
                                     hashtable->log2_nbuckets) & (nbatch - 1);
    }
    else
    {
        *bucketno = hashvalue & (nbuckets - 1);
        *batchno = 0;
    }
}
 
/*
 * ExecScanHashBucket
 *      scan a hash bucket for matches to the current outer tuple
 *
 * The current outer tuple must be stored in econtext->ecxt_outertuple.
 *
 * On success, the inner tuple is stored into hjstate->hj_CurTuple and
 * econtext->ecxt_innertuple, using hjstate->hj_HashTupleSlot as the slot
 * for the latter.
 */
bool
ExecScanHashBucket(HashJoinState *hjstate,
                   ExprContext *econtext)
{
    ExprState  *hjclauses = hjstate->hashclauses;
    HashJoinTable hashtable = hjstate->hj_HashTable;
    HashJoinTuple hashTuple = hjstate->hj_CurTuple;
    uint32      hashvalue = hjstate->hj_CurHashValue;
 
    /*
     * hj_CurTuple is the address of the tuple last returned from the current
     * bucket, or NULL if it's time to start scanning a new bucket.
     *
     * If the tuple hashed to a skew bucket then scan the skew bucket
     * otherwise scan the standard hashtable bucket.
     */
    if (hashTuple != NULL)
        hashTuple = hashTuple->next.unshared;
    else if (hjstate->hj_CurSkewBucketNo != INVALID_SKEW_BUCKET_NO)
        hashTuple = hashtable->skewBucket[hjstate->hj_CurSkewBucketNo]->tuples;
    else
        hashTuple = hashtable->buckets.unshared[hjstate->hj_CurBucketNo];
 
    while (hashTuple != NULL)
    {
        if (hashTuple->hashvalue == hashvalue)
        {
            TupleTableSlot *inntuple;
 
            /* insert hashtable's tuple into exec slot so ExecQual sees it */
            inntuple = ExecStoreMinimalTuple(HJTUPLE_MINTUPLE(hashTuple),
                                             hjstate->hj_HashTupleSlot,
                                             false);    /* do not pfree */
            econtext->ecxt_innertuple = inntuple;
 
            if (ExecQualAndReset(hjclauses, econtext))
            {
                hjstate->hj_CurTuple = hashTuple;
                return true;
            }
        }
 
        hashTuple = hashTuple->next.unshared;
    }
 
    /*
     * no match
     */
    return false;
}
 
/*
 * ExecParallelScanHashBucket
 *      scan a hash bucket for matches to the current outer tuple
 *
 * The current outer tuple must be stored in econtext->ecxt_outertuple.
 *
 * On success, the inner tuple is stored into hjstate->hj_CurTuple and
 * econtext->ecxt_innertuple, using hjstate->hj_HashTupleSlot as the slot
 * for the latter.
 */
bool
ExecParallelScanHashBucket(HashJoinState *hjstate,
                           ExprContext *econtext)
{
    ExprState  *hjclauses = hjstate->hashclauses;
    HashJoinTable hashtable = hjstate->hj_HashTable;
    HashJoinTuple hashTuple = hjstate->hj_CurTuple;
    uint32      hashvalue = hjstate->hj_CurHashValue;
 
    /*
     * hj_CurTuple is the address of the tuple last returned from the current
     * bucket, or NULL if it's time to start scanning a new bucket.
     */
    if (hashTuple != NULL)
        hashTuple = ExecParallelHashNextTuple(hashtable, hashTuple);
    else
        hashTuple = ExecParallelHashFirstTuple(hashtable,
                                               hjstate->hj_CurBucketNo);
 
    while (hashTuple != NULL)
    {
        if (hashTuple->hashvalue == hashvalue)
        {
            TupleTableSlot *inntuple;
 
            /* insert hashtable's tuple into exec slot so ExecQual sees it */
            inntuple = ExecStoreMinimalTuple(HJTUPLE_MINTUPLE(hashTuple),
                                             hjstate->hj_HashTupleSlot,
                                             false);    /* do not pfree */
            econtext->ecxt_innertuple = inntuple;
 
            if (ExecQualAndReset(hjclauses, econtext))
            {
                hjstate->hj_CurTuple = hashTuple;
                return true;
            }
        }
 
        hashTuple = ExecParallelHashNextTuple(hashtable, hashTuple);
    }
 
    /*
     * no match
     */
    return false;
}
 
/*
 * ExecPrepHashTableForUnmatched
 *      set up for a series of ExecScanHashTableForUnmatched calls
 */
void
ExecPrepHashTableForUnmatched(HashJoinState *hjstate)
{
    /*----------
     * During this scan we use the HashJoinState fields as follows:
     *
     * hj_CurBucketNo: next regular bucket to scan
     * hj_CurSkewBucketNo: next skew bucket (an index into skewBucketNums)
     * hj_CurTuple: last tuple returned, or NULL to start next bucket
     *----------
     */
    hjstate->hj_CurBucketNo = 0;
    hjstate->hj_CurSkewBucketNo = 0;
    hjstate->hj_CurTuple = NULL;
}
 
/*
 * Decide if this process is allowed to run the unmatched scan.  If so, the
 * batch barrier is advanced to PHJ_BATCH_SCAN and true is returned.
 * Otherwise the batch is detached and false is returned.
 */
bool
ExecParallelPrepHashTableForUnmatched(HashJoinState *hjstate)
{
    HashJoinTable hashtable = hjstate->hj_HashTable;
    int         curbatch = hashtable->curbatch;
    ParallelHashJoinBatch *batch = hashtable->batches[curbatch].shared;
 
    Assert(BarrierPhase(&batch->batch_barrier) == PHJ_BATCH_PROBE);
 
    /*
     * It would not be deadlock-free to wait on the batch barrier, because it
     * is in PHJ_BATCH_PROBE phase, and thus processes attached to it have
     * already emitted tuples.  Therefore, we'll hold a wait-free election:
     * only one process can continue to the next phase, and all others detach
     * from this batch.  They can still go any work on other batches, if there
     * are any.
     */
    if (!BarrierArriveAndDetachExceptLast(&batch->batch_barrier))
    {
        /* This process considers the batch to be done. */
        hashtable->batches[hashtable->curbatch].done = true;
 
        /* Make sure any temporary files are closed. */
        sts_end_parallel_scan(hashtable->batches[curbatch].inner_tuples);
        sts_end_parallel_scan(hashtable->batches[curbatch].outer_tuples);
 
        /*
         * Track largest batch we've seen, which would normally happen in
         * ExecHashTableDetachBatch().
         */
        hashtable->spacePeak =
            Max(hashtable->spacePeak,
                batch->size + sizeof(dsa_pointer_atomic) * hashtable->nbuckets);
        hashtable->curbatch = -1;
        return false;
    }
 
    /* Now we are alone with this batch. */
    Assert(BarrierPhase(&batch->batch_barrier) == PHJ_BATCH_SCAN);
 
    /*
     * Has another process decided to give up early and command all processes
     * to skip the unmatched scan?
     */
    if (batch->skip_unmatched)
    {
        hashtable->batches[hashtable->curbatch].done = true;
        ExecHashTableDetachBatch(hashtable);
        return false;
    }
 
    /* Now prepare the process local state, just as for non-parallel join. */
    ExecPrepHashTableForUnmatched(hjstate);
 
    return true;
}
 
/*
 * ExecScanHashTableForUnmatched
 *      scan the hash table for unmatched inner tuples
 *
 * On success, the inner tuple is stored into hjstate->hj_CurTuple and
 * econtext->ecxt_innertuple, using hjstate->hj_HashTupleSlot as the slot
 * for the latter.
 */
bool
ExecScanHashTableForUnmatched(HashJoinState *hjstate, ExprContext *econtext)
{
    HashJoinTable hashtable = hjstate->hj_HashTable;
    HashJoinTuple hashTuple = hjstate->hj_CurTuple;
 
    for (;;)
    {
        /*
         * hj_CurTuple is the address of the tuple last returned from the
         * current bucket, or NULL if it's time to start scanning a new
         * bucket.
         */
        if (hashTuple != NULL)
            hashTuple = hashTuple->next.unshared;
        else if (hjstate->hj_CurBucketNo < hashtable->nbuckets)
        {
            hashTuple = hashtable->buckets.unshared[hjstate->hj_CurBucketNo];
            hjstate->hj_CurBucketNo++;
        }
        else if (hjstate->hj_CurSkewBucketNo < hashtable->nSkewBuckets)
        {
            int         j = hashtable->skewBucketNums[hjstate->hj_CurSkewBucketNo];
 
            hashTuple = hashtable->skewBucket[j]->tuples;
            hjstate->hj_CurSkewBucketNo++;
        }
        else
            break;              /* finished all buckets */
 
        while (hashTuple != NULL)
        {
            if (!HeapTupleHeaderHasMatch(HJTUPLE_MINTUPLE(hashTuple)))
            {
                TupleTableSlot *inntuple;
 
                /* insert hashtable's tuple into exec slot */
                inntuple = ExecStoreMinimalTuple(HJTUPLE_MINTUPLE(hashTuple),
                                                 hjstate->hj_HashTupleSlot,
                                                 false);    /* do not pfree */
                econtext->ecxt_innertuple = inntuple;
 
                /*
                 * Reset temp memory each time; although this function doesn't
                 * do any qual eval, the caller will, so let's keep it
                 * parallel to ExecScanHashBucket.
                 */
                ResetExprContext(econtext);
 
                hjstate->hj_CurTuple = hashTuple;
                return true;
            }
 
            hashTuple = hashTuple->next.unshared;
        }
 
        /* allow this loop to be cancellable */
        CHECK_FOR_INTERRUPTS();
    }
 
    /*
     * no more unmatched tuples
     */
    return false;
}
 
/*
 * ExecParallelScanHashTableForUnmatched
 *      scan the hash table for unmatched inner tuples, in parallel join
 *
 * On success, the inner tuple is stored into hjstate->hj_CurTuple and
 * econtext->ecxt_innertuple, using hjstate->hj_HashTupleSlot as the slot
 * for the latter.
 */
bool
ExecParallelScanHashTableForUnmatched(HashJoinState *hjstate,
                                      ExprContext *econtext)
{
    HashJoinTable hashtable = hjstate->hj_HashTable;
    HashJoinTuple hashTuple = hjstate->hj_CurTuple;
 
    for (;;)
    {
        /*
         * hj_CurTuple is the address of the tuple last returned from the
         * current bucket, or NULL if it's time to start scanning a new
         * bucket.
         */
        if (hashTuple != NULL)
            hashTuple = ExecParallelHashNextTuple(hashtable, hashTuple);
        else if (hjstate->hj_CurBucketNo < hashtable->nbuckets)
            hashTuple = ExecParallelHashFirstTuple(hashtable,
                                                   hjstate->hj_CurBucketNo++);
        else
            break;              /* finished all buckets */
 
        while (hashTuple != NULL)
        {
            if (!HeapTupleHeaderHasMatch(HJTUPLE_MINTUPLE(hashTuple)))
            {
                TupleTableSlot *inntuple;
 
                /* insert hashtable's tuple into exec slot */
                inntuple = ExecStoreMinimalTuple(HJTUPLE_MINTUPLE(hashTuple),
                                                 hjstate->hj_HashTupleSlot,
                                                 false);    /* do not pfree */
                econtext->ecxt_innertuple = inntuple;
 
                /*
                 * Reset temp memory each time; although this function doesn't
                 * do any qual eval, the caller will, so let's keep it
                 * parallel to ExecScanHashBucket.
                 */
                ResetExprContext(econtext);
 
                hjstate->hj_CurTuple = hashTuple;
                return true;
            }
 
            hashTuple = ExecParallelHashNextTuple(hashtable, hashTuple);
        }
 
        /* allow this loop to be cancellable */
        CHECK_FOR_INTERRUPTS();
    }
 
    /*
     * no more unmatched tuples
     */
    return false;
}
 
/*
 * ExecHashTableReset
 *
 *      reset hash table header for new batch
 */
void
ExecHashTableReset(HashJoinTable hashtable)
{
    MemoryContext oldcxt;
    int         nbuckets = hashtable->nbuckets;
 
    /*
     * Release all the hash buckets and tuples acquired in the prior pass, and
     * reinitialize the context for a new pass.
     */
    MemoryContextReset(hashtable->batchCxt);
    oldcxt = MemoryContextSwitchTo(hashtable->batchCxt);
 
    /* Reallocate and reinitialize the hash bucket headers. */
    hashtable->buckets.unshared = palloc0_array(HashJoinTuple, nbuckets);
 
    hashtable->spaceUsed = 0;
 
    MemoryContextSwitchTo(oldcxt);
 
    /* Forget the chunks (the memory was freed by the context reset above). */
    hashtable->chunks = NULL;
}
 
/*
 * ExecHashTableResetMatchFlags
 *      Clear all the HeapTupleHeaderHasMatch flags in the table
 */
void
ExecHashTableResetMatchFlags(HashJoinTable hashtable)
{
    HashJoinTuple tuple;
    int         i;
 
    /* Reset all flags in the main table ... */
    for (i = 0; i < hashtable->nbuckets; i++)
    {
        for (tuple = hashtable->buckets.unshared[i]; tuple != NULL;
             tuple = tuple->next.unshared)
            HeapTupleHeaderClearMatch(HJTUPLE_MINTUPLE(tuple));
    }
 
    /* ... and the same for the skew buckets, if any */
    for (i = 0; i < hashtable->nSkewBuckets; i++)
    {
        int         j = hashtable->skewBucketNums[i];
        HashSkewBucket *skewBucket = hashtable->skewBucket[j];
 
        for (tuple = skewBucket->tuples; tuple != NULL; tuple = tuple->next.unshared)
            HeapTupleHeaderClearMatch(HJTUPLE_MINTUPLE(tuple));
    }
}
 
 
void
ExecReScanHash(HashState *node)
{
    PlanState  *outerPlan = outerPlanState(node);
 
    /*
     * if chgParam of subnode is not null then plan will be re-scanned by
     * first ExecProcNode.
     */
    if (outerPlan->chgParam == NULL)
        ExecReScan(outerPlan);
}
 
 
/*
 * ExecHashBuildSkewHash
 *
 *      Set up for skew optimization if we can identify the most common values
 *      (MCVs) of the outer relation's join key.  We make a skew hash bucket
 *      for the hash value of each MCV, up to the number of slots allowed
 *      based on available memory.
 */
static void
ExecHashBuildSkewHash(HashState *hashstate, HashJoinTable hashtable,
                      Hash *node, int mcvsToUse)
{
    HeapTupleData *statsTuple;
    AttStatsSlot sslot;
 
    /* Do nothing if planner didn't identify the outer relation's join key */
    if (!OidIsValid(node->skewTable))
        return;
    /* Also, do nothing if we don't have room for at least one skew bucket */
    if (mcvsToUse <= 0)
        return;
 
    /*
     * Try to find the MCV statistics for the outer relation's join key.
     */
    statsTuple = SearchSysCache3(STATRELATTINH,
                                 ObjectIdGetDatum(node->skewTable),
                                 Int16GetDatum(node->skewColumn),
                                 BoolGetDatum(node->skewInherit));
    if (!HeapTupleIsValid(statsTuple))
        return;
 
    if (get_attstatsslot(&sslot, statsTuple,
                         STATISTIC_KIND_MCV, InvalidOid,
                         ATTSTATSSLOT_VALUES | ATTSTATSSLOT_NUMBERS))
    {
        double      frac;
        int         nbuckets;
        int         i;
 
        if (mcvsToUse > sslot.nvalues)
            mcvsToUse = sslot.nvalues;
 
        /*
         * Calculate the expected fraction of outer relation that will
         * participate in the skew optimization.  If this isn't at least
         * SKEW_MIN_OUTER_FRACTION, don't use skew optimization.
         */
        frac = 0;
        for (i = 0; i < mcvsToUse; i++)
            frac += sslot.numbers[i];
        if (frac < SKEW_MIN_OUTER_FRACTION)
        {
            free_attstatsslot(&sslot);
            ReleaseSysCache(statsTuple);
            return;
        }
 
        /*
         * Okay, set up the skew hashtable.
         *
         * skewBucket[] is an open addressing hashtable with a power of 2 size
         * that is greater than the number of MCV values.  (This ensures there
         * will be at least one null entry, so searches will always
         * terminate.)
         *
         * Note: this code could fail if mcvsToUse exceeds INT_MAX/8 or
         * MaxAllocSize/sizeof(void *)/8, but that is not currently possible
         * since we limit pg_statistic entries to much less than that.
         */
        nbuckets = pg_nextpower2_32(mcvsToUse + 1);
        /* use two more bits just to help avoid collisions */
        nbuckets <<= 2;
 
        hashtable->skewEnabled = true;
        hashtable->skewBucketLen = nbuckets;
 
        /*
         * We allocate the bucket memory in the hashtable's batch context. It
         * is only needed during the first batch, and this ensures it will be
         * automatically removed once the first batch is done.
         */
        hashtable->skewBucket = (HashSkewBucket **)
            MemoryContextAllocZero(hashtable->batchCxt,
                                   nbuckets * sizeof(HashSkewBucket *));
        hashtable->skewBucketNums = (int *)
            MemoryContextAllocZero(hashtable->batchCxt,
                                   mcvsToUse * sizeof(int));
 
        hashtable->spaceUsed += nbuckets * sizeof(HashSkewBucket *)
            + mcvsToUse * sizeof(int);
        hashtable->spaceUsedSkew += nbuckets * sizeof(HashSkewBucket *)
            + mcvsToUse * sizeof(int);
        if (hashtable->spaceUsed > hashtable->spacePeak)
            hashtable->spacePeak = hashtable->spaceUsed;
 
        /*
         * Create a skew bucket for each MCV hash value.
         *
         * Note: it is very important that we create the buckets in order of
         * decreasing MCV frequency.  If we have to remove some buckets, they
         * must be removed in reverse order of creation (see notes in
         * ExecHashRemoveNextSkewBucket) and we want the least common MCVs to
         * be removed first.
         */
 
        for (i = 0; i < mcvsToUse; i++)
        {
            uint32      hashvalue;
            int         bucket;
 
            hashvalue = DatumGetUInt32(FunctionCall1Coll(hashstate->skew_hashfunction,
                                                         hashstate->skew_collation,
                                                         sslot.values[i]));
 
            /*
             * While we have not hit a hole in the hashtable and have not hit
             * the desired bucket, we have collided with some previous hash
             * value, so try the next bucket location.  NB: this code must
             * match ExecHashGetSkewBucket.
             */
            bucket = hashvalue & (nbuckets - 1);
            while (hashtable->skewBucket[bucket] != NULL &&
                   hashtable->skewBucket[bucket]->hashvalue != hashvalue)
                bucket = (bucket + 1) & (nbuckets - 1);
 
            /*
             * If we found an existing bucket with the same hashvalue, leave
             * it alone.  It's okay for two MCVs to share a hashvalue.
             */
            if (hashtable->skewBucket[bucket] != NULL)
                continue;
 
            /* Okay, create a new skew bucket for this hashvalue. */
            hashtable->skewBucket[bucket] = (HashSkewBucket *)
                MemoryContextAlloc(hashtable->batchCxt,
                                   sizeof(HashSkewBucket));
            hashtable->skewBucket[bucket]->hashvalue = hashvalue;
            hashtable->skewBucket[bucket]->tuples = NULL;
            hashtable->skewBucketNums[hashtable->nSkewBuckets] = bucket;
            hashtable->nSkewBuckets++;
            hashtable->spaceUsed += SKEW_BUCKET_OVERHEAD;
            hashtable->spaceUsedSkew += SKEW_BUCKET_OVERHEAD;
            if (hashtable->spaceUsed > hashtable->spacePeak)
                hashtable->spacePeak = hashtable->spaceUsed;
        }
 
        free_attstatsslot(&sslot);
    }
 
    ReleaseSysCache(statsTuple);
}
 
/*
 * ExecHashGetSkewBucket
 *
 *      Returns the index of the skew bucket for this hashvalue,
 *      or INVALID_SKEW_BUCKET_NO if the hashvalue is not
 *      associated with any active skew bucket.
 */
int
ExecHashGetSkewBucket(HashJoinTable hashtable, uint32 hashvalue)
{
    int         bucket;
 
    /*
     * Always return INVALID_SKEW_BUCKET_NO if not doing skew optimization (in
     * particular, this happens after the initial batch is done).
     */
    if (!hashtable->skewEnabled)
        return INVALID_SKEW_BUCKET_NO;
 
    /*
     * Since skewBucketLen is a power of 2, we can do a modulo by ANDing.
     */
    bucket = hashvalue & (hashtable->skewBucketLen - 1);
 
    /*
     * While we have not hit a hole in the hashtable and have not hit the
     * desired bucket, we have collided with some other hash value, so try the
     * next bucket location.
     */
    while (hashtable->skewBucket[bucket] != NULL &&
           hashtable->skewBucket[bucket]->hashvalue != hashvalue)
        bucket = (bucket + 1) & (hashtable->skewBucketLen - 1);
 
    /*
     * Found the desired bucket?
     */
    if (hashtable->skewBucket[bucket] != NULL)
        return bucket;
 
    /*
     * There must not be any hashtable entry for this hash value.
     */
    return INVALID_SKEW_BUCKET_NO;
}
 
/*
 * ExecHashSkewTableInsert
 *
 *      Insert a tuple into the skew hashtable.
 *
 * This should generally match up with the current-batch case in
 * ExecHashTableInsert.
 */
static void
ExecHashSkewTableInsert(HashJoinTable hashtable,
                        TupleTableSlot *slot,
                        uint32 hashvalue,
                        int bucketNumber)
{
    bool        shouldFree;
    MinimalTuple tuple = ExecFetchSlotMinimalTuple(slot, &shouldFree);
    HashJoinTuple hashTuple;
    int         hashTupleSize;
 
    /* Create the HashJoinTuple */
    hashTupleSize = HJTUPLE_OVERHEAD + tuple->t_len;
    hashTuple = (HashJoinTuple) MemoryContextAlloc(hashtable->batchCxt,
                                                   hashTupleSize);
    hashTuple->hashvalue = hashvalue;
    memcpy(HJTUPLE_MINTUPLE(hashTuple), tuple, tuple->t_len);
    HeapTupleHeaderClearMatch(HJTUPLE_MINTUPLE(hashTuple));
 
    /* Push it onto the front of the skew bucket's list */
    hashTuple->next.unshared = hashtable->skewBucket[bucketNumber]->tuples;
    hashtable->skewBucket[bucketNumber]->tuples = hashTuple;
    Assert(hashTuple != hashTuple->next.unshared);
 
    /* Account for space used, and back off if we've used too much */
    hashtable->spaceUsed += hashTupleSize;
    hashtable->spaceUsedSkew += hashTupleSize;
    if (hashtable->spaceUsed > hashtable->spacePeak)
        hashtable->spacePeak = hashtable->spaceUsed;
    while (hashtable->spaceUsedSkew > hashtable->spaceAllowedSkew)
        ExecHashRemoveNextSkewBucket(hashtable);
 
    /* Check we are not over the total spaceAllowed, either */
    if (hashtable->spaceUsed > hashtable->spaceAllowed)
        ExecHashIncreaseNumBatches(hashtable);
 
    if (shouldFree)
        heap_free_minimal_tuple(tuple);
}
 
/*
 *      ExecHashRemoveNextSkewBucket
 *
 *      Remove the least valuable skew bucket by pushing its tuples into
 *      the main hash table.
 */
static void
ExecHashRemoveNextSkewBucket(HashJoinTable hashtable)
{
    int         bucketToRemove;
    HashSkewBucket *bucket;
    uint32      hashvalue;
    int         bucketno;
    int         batchno;
    HashJoinTuple hashTuple;
 
    /* Locate the bucket to remove */
    bucketToRemove = hashtable->skewBucketNums[hashtable->nSkewBuckets - 1];
    bucket = hashtable->skewBucket[bucketToRemove];
 
    /*
     * Calculate which bucket and batch the tuples belong to in the main
     * hashtable.  They all have the same hash value, so it's the same for all
     * of them.  Also note that it's not possible for nbatch to increase while
     * we are processing the tuples.
     */
    hashvalue = bucket->hashvalue;
    ExecHashGetBucketAndBatch(hashtable, hashvalue, &bucketno, &batchno);
 
    /* Process all tuples in the bucket */
    hashTuple = bucket->tuples;
    while (hashTuple != NULL)
    {
        HashJoinTuple nextHashTuple = hashTuple->next.unshared;
        MinimalTuple tuple;
        Size        tupleSize;
 
        /*
         * This code must agree with ExecHashTableInsert.  We do not use
         * ExecHashTableInsert directly as ExecHashTableInsert expects a
         * TupleTableSlot while we already have HashJoinTuples.
         */
        tuple = HJTUPLE_MINTUPLE(hashTuple);
        tupleSize = HJTUPLE_OVERHEAD + tuple->t_len;
 
        /* Decide whether to put the tuple in the hash table or a temp file */
        if (batchno == hashtable->curbatch)
        {
            /* Move the tuple to the main hash table */
            HashJoinTuple copyTuple;
 
            /*
             * We must copy the tuple into the dense storage, else it will not
             * be found by, eg, ExecHashIncreaseNumBatches.
             */
            copyTuple = (HashJoinTuple) dense_alloc(hashtable, tupleSize);
            memcpy(copyTuple, hashTuple, tupleSize);
            pfree(hashTuple);
 
            copyTuple->next.unshared = hashtable->buckets.unshared[bucketno];
            hashtable->buckets.unshared[bucketno] = copyTuple;
 
            /* We have reduced skew space, but overall space doesn't change */
            hashtable->spaceUsedSkew -= tupleSize;
        }
        else
        {
            /* Put the tuple into a temp file for later batches */
            Assert(batchno > hashtable->curbatch);
            ExecHashJoinSaveTuple(tuple, hashvalue,
                                  &hashtable->innerBatchFile[batchno],
                                  hashtable);
            pfree(hashTuple);
            hashtable->spaceUsed -= tupleSize;
            hashtable->spaceUsedSkew -= tupleSize;
        }
 
        hashTuple = nextHashTuple;
 
        /* allow this loop to be cancellable */
        CHECK_FOR_INTERRUPTS();
    }
 
    /*
     * Free the bucket struct itself and reset the hashtable entry to NULL.
     *
     * NOTE: this is not nearly as simple as it looks on the surface, because
     * of the possibility of collisions in the hashtable.  Suppose that hash
     * values A and B collide at a particular hashtable entry, and that A was
     * entered first so B gets shifted to a different table entry.  If we were
     * to remove A first then ExecHashGetSkewBucket would mistakenly start
     * reporting that B is not in the hashtable, because it would hit the NULL
     * before finding B.  However, we always remove entries in the reverse
     * order of creation, so this failure cannot happen.
     */
    hashtable->skewBucket[bucketToRemove] = NULL;
    hashtable->nSkewBuckets--;
    pfree(bucket);
    hashtable->spaceUsed -= SKEW_BUCKET_OVERHEAD;
    hashtable->spaceUsedSkew -= SKEW_BUCKET_OVERHEAD;
 
    /*
     * If we have removed all skew buckets then give up on skew optimization.
     * Release the arrays since they aren't useful any more.
     */
    if (hashtable->nSkewBuckets == 0)
    {
        hashtable->skewEnabled = false;
        pfree(hashtable->skewBucket);
        pfree(hashtable->skewBucketNums);
        hashtable->skewBucket = NULL;
        hashtable->skewBucketNums = NULL;
        hashtable->spaceUsed -= hashtable->spaceUsedSkew;
        hashtable->spaceUsedSkew = 0;
    }
}
 
/*
 * Reserve space in the DSM segment for instrumentation data.
 */
void
ExecHashEstimate(HashState *node, ParallelContext *pcxt)
{
    size_t      size;
 
    /* don't need this if not instrumenting or no workers */
    if (!node->ps.instrument || pcxt->nworkers == 0)
        return;
 
    size = mul_size(pcxt->nworkers, sizeof(HashInstrumentation));
    size = add_size(size, offsetof(SharedHashInfo, hinstrument));
    shm_toc_estimate_chunk(&pcxt->estimator, size);
    shm_toc_estimate_keys(&pcxt->estimator, 1);
}
 
/*
 * Set up a space in the DSM for all workers to record instrumentation data
 * about their hash table.
 */
void
ExecHashInitializeDSM(HashState *node, ParallelContext *pcxt)
{
    size_t      size;
 
    /* don't need this if not instrumenting or no workers */
    if (!node->ps.instrument || pcxt->nworkers == 0)
        return;
 
    size = offsetof(SharedHashInfo, hinstrument) +
        pcxt->nworkers * sizeof(HashInstrumentation);
    node->shared_info = (SharedHashInfo *) shm_toc_allocate(pcxt->toc, size);
 
    /* Each per-worker area must start out as zeroes. */
    memset(node->shared_info, 0, size);
 
    node->shared_info->num_workers = pcxt->nworkers;
    shm_toc_insert(pcxt->toc, node->ps.plan->plan_node_id,
                   node->shared_info);
}
 
/*
 * Locate the DSM space for hash table instrumentation data that we'll write
 * to at shutdown time.
 */
void
ExecHashInitializeWorker(HashState *node, ParallelWorkerContext *pwcxt)
{
    SharedHashInfo *shared_info;
 
    /* don't need this if not instrumenting */
    if (!node->ps.instrument)
        return;
 
    /*
     * Find our entry in the shared area, and set up a pointer to it so that
     * we'll accumulate stats there when shutting down or rebuilding the hash
     * table.
     */
    shared_info = (SharedHashInfo *)
        shm_toc_lookup(pwcxt->toc, node->ps.plan->plan_node_id, false);
    node->hinstrument = &shared_info->hinstrument[ParallelWorkerNumber];
}
 
/*
 * Collect EXPLAIN stats if needed, saving them into DSM memory if
 * ExecHashInitializeWorker was called, or local storage if not.  In the
 * parallel case, this must be done in ExecShutdownHash() rather than
 * ExecEndHash() because the latter runs after we've detached from the DSM
 * segment.
 */
void
ExecShutdownHash(HashState *node)
{
    /* Allocate save space if EXPLAIN'ing and we didn't do so already */
    if (node->ps.instrument && !node->hinstrument)
        node->hinstrument = palloc0_object(HashInstrumentation);
    /* Now accumulate data for the current (final) hash table */
    if (node->hinstrument && node->hashtable)
        ExecHashAccumInstrumentation(node->hinstrument, node->hashtable);
}
 
/*
 * Retrieve instrumentation data from workers before the DSM segment is
 * detached, so that EXPLAIN can access it.
 */
void
ExecHashRetrieveInstrumentation(HashState *node)
{
    SharedHashInfo *shared_info = node->shared_info;
    size_t      size;
 
    if (shared_info == NULL)
        return;
 
    /* Replace node->shared_info with a copy in backend-local memory. */
    size = offsetof(SharedHashInfo, hinstrument) +
        shared_info->num_workers * sizeof(HashInstrumentation);
    node->shared_info = palloc(size);
    memcpy(node->shared_info, shared_info, size);
}
 
/*
 * Accumulate instrumentation data from 'hashtable' into an
 * initially-zeroed HashInstrumentation struct.
 *
 * This is used to merge information across successive hash table instances
 * within a single plan node.  We take the maximum values of each interesting
 * number.  The largest nbuckets and largest nbatch values might have occurred
 * in different instances, so there's some risk of confusion from reporting
 * unrelated numbers; but there's a bigger risk of misdiagnosing a performance
 * issue if we don't report the largest values.  Similarly, we want to report
 * the largest spacePeak regardless of whether it happened in the same
 * instance as the largest nbuckets or nbatch.  All the instances should have
 * the same nbuckets_original and nbatch_original; but there's little value
 * in depending on that here, so handle them the same way.
 */
void
ExecHashAccumInstrumentation(HashInstrumentation *instrument,
                             HashJoinTable hashtable)
{
    instrument->nbuckets = Max(instrument->nbuckets,
                               hashtable->nbuckets);
    instrument->nbuckets_original = Max(instrument->nbuckets_original,
                                        hashtable->nbuckets_original);
    instrument->nbatch = Max(instrument->nbatch,
                             hashtable->nbatch);
    instrument->nbatch_original = Max(instrument->nbatch_original,
                                      hashtable->nbatch_original);
    instrument->space_peak = Max(instrument->space_peak,
                                 hashtable->spacePeak);
}
 
/*
 * Allocate 'size' bytes from the currently active HashMemoryChunk
 */
static void *
dense_alloc(HashJoinTable hashtable, Size size)
{
    HashMemoryChunk newChunk;
    char       *ptr;
 
    /* just in case the size is not already aligned properly */
    size = MAXALIGN(size);
 
    /*
     * If tuple size is larger than threshold, allocate a separate chunk.
     */
    if (size > HASH_CHUNK_THRESHOLD)
    {
        /* allocate new chunk and put it at the beginning of the list */
        newChunk = (HashMemoryChunk) MemoryContextAlloc(hashtable->batchCxt,
                                                        HASH_CHUNK_HEADER_SIZE + size);
        newChunk->maxlen = size;
        newChunk->used = size;
        newChunk->ntuples = 1;
 
        /*
         * Add this chunk to the list after the first existing chunk, so that
         * we don't lose the remaining space in the "current" chunk.
         */
        if (hashtable->chunks != NULL)
        {
            newChunk->next = hashtable->chunks->next;
            hashtable->chunks->next.unshared = newChunk;
        }
        else
        {
            newChunk->next.unshared = hashtable->chunks;
            hashtable->chunks = newChunk;
        }
 
        return HASH_CHUNK_DATA(newChunk);
    }
 
    /*
     * See if we have enough space for it in the current chunk (if any). If
     * not, allocate a fresh chunk.
     */
    if ((hashtable->chunks == NULL) ||
        (hashtable->chunks->maxlen - hashtable->chunks->used) < size)
    {
        /* allocate new chunk and put it at the beginning of the list */
        newChunk = (HashMemoryChunk) MemoryContextAlloc(hashtable->batchCxt,
                                                        HASH_CHUNK_HEADER_SIZE + HASH_CHUNK_SIZE);
 
        newChunk->maxlen = HASH_CHUNK_SIZE;
        newChunk->used = size;
        newChunk->ntuples = 1;
 
        newChunk->next.unshared = hashtable->chunks;
        hashtable->chunks = newChunk;
 
        return HASH_CHUNK_DATA(newChunk);
    }
 
    /* There is enough space in the current chunk, let's add the tuple */
    ptr = HASH_CHUNK_DATA(hashtable->chunks) + hashtable->chunks->used;
    hashtable->chunks->used += size;
    hashtable->chunks->ntuples += 1;
 
    /* return pointer to the start of the tuple memory */
    return ptr;
}
 
/*
 * Allocate space for a tuple in shared dense storage.  This is equivalent to
 * dense_alloc but for Parallel Hash using shared memory.
 *
 * While loading a tuple into shared memory, we might run out of memory and
 * decide to repartition, or determine that the load factor is too high and
 * decide to expand the bucket array, or discover that another participant has
 * commanded us to help do that.  Return NULL if number of buckets or batches
 * has changed, indicating that the caller must retry (considering the
 * possibility that the tuple no longer belongs in the same batch).
 */
static HashJoinTuple
ExecParallelHashTupleAlloc(HashJoinTable hashtable, size_t size,
                           dsa_pointer *shared)
{
    ParallelHashJoinState *pstate = hashtable->parallel_state;
    dsa_pointer chunk_shared;
    HashMemoryChunk chunk;
    Size        chunk_size;
    HashJoinTuple result;
    int         curbatch = hashtable->curbatch;
 
    size = MAXALIGN(size);
 
    /*
     * Fast path: if there is enough space in this backend's current chunk,
     * then we can allocate without any locking.
     */
    chunk = hashtable->current_chunk;
    if (chunk != NULL &&
        size <= HASH_CHUNK_THRESHOLD &&
        chunk->maxlen - chunk->used >= size)
    {
 
        chunk_shared = hashtable->current_chunk_shared;
        Assert(chunk == dsa_get_address(hashtable->area, chunk_shared));
        *shared = chunk_shared + HASH_CHUNK_HEADER_SIZE + chunk->used;
        result = (HashJoinTuple) (HASH_CHUNK_DATA(chunk) + chunk->used);
        chunk->used += size;
 
        Assert(chunk->used <= chunk->maxlen);
        Assert(result == dsa_get_address(hashtable->area, *shared));
 
        return result;
    }
 
    /* Slow path: try to allocate a new chunk. */
    LWLockAcquire(&pstate->lock, LW_EXCLUSIVE);
 
    /*
     * Check if we need to help increase the number of buckets or batches.
     */
    if (pstate->growth == PHJ_GROWTH_NEED_MORE_BATCHES ||
        pstate->growth == PHJ_GROWTH_NEED_MORE_BUCKETS)
    {
        ParallelHashGrowth growth = pstate->growth;
 
        hashtable->current_chunk = NULL;
        LWLockRelease(&pstate->lock);
 
        /* Another participant has commanded us to help grow. */
        if (growth == PHJ_GROWTH_NEED_MORE_BATCHES)
            ExecParallelHashIncreaseNumBatches(hashtable);
        else if (growth == PHJ_GROWTH_NEED_MORE_BUCKETS)
            ExecParallelHashIncreaseNumBuckets(hashtable);
 
        /* The caller must retry. */
        return NULL;
    }
 
    /* Oversized tuples get their own chunk. */
    if (size > HASH_CHUNK_THRESHOLD)
        chunk_size = size + HASH_CHUNK_HEADER_SIZE;
    else
        chunk_size = HASH_CHUNK_SIZE;
 
    /* Check if it's time to grow batches or buckets. */
    if (pstate->growth != PHJ_GROWTH_DISABLED)
    {
        Assert(curbatch == 0);
        Assert(BarrierPhase(&pstate->build_barrier) == PHJ_BUILD_HASH_INNER);
 
        /*
         * Check if our space limit would be exceeded.  To avoid choking on
         * very large tuples or very low hash_mem setting, we'll always allow
         * each backend to allocate at least one chunk.
         */
        if (hashtable->batches[0].at_least_one_chunk &&
            hashtable->batches[0].shared->size +
            chunk_size > pstate->space_allowed)
        {
            pstate->growth = PHJ_GROWTH_NEED_MORE_BATCHES;
            hashtable->batches[0].shared->space_exhausted = true;
            LWLockRelease(&pstate->lock);
 
            return NULL;
        }
 
        /* Check if our load factor limit would be exceeded. */
        if (hashtable->nbatch == 1)
        {
            hashtable->batches[0].shared->ntuples += hashtable->batches[0].ntuples;
            hashtable->batches[0].ntuples = 0;
            /* Guard against integer overflow and alloc size overflow */
            if (hashtable->batches[0].shared->ntuples + 1 >
                hashtable->nbuckets * NTUP_PER_BUCKET &&
                hashtable->nbuckets < (INT_MAX / 2) &&
                hashtable->nbuckets * 2 <=
                MaxAllocSize / sizeof(dsa_pointer_atomic))
            {
                pstate->growth = PHJ_GROWTH_NEED_MORE_BUCKETS;
                LWLockRelease(&pstate->lock);
 
                return NULL;
            }
        }
    }
 
    /* We are cleared to allocate a new chunk. */
    chunk_shared = dsa_allocate(hashtable->area, chunk_size);
    hashtable->batches[curbatch].shared->size += chunk_size;
    hashtable->batches[curbatch].at_least_one_chunk = true;
 
    /* Set up the chunk. */
    chunk = (HashMemoryChunk) dsa_get_address(hashtable->area, chunk_shared);
    *shared = chunk_shared + HASH_CHUNK_HEADER_SIZE;
    chunk->maxlen = chunk_size - HASH_CHUNK_HEADER_SIZE;
    chunk->used = size;
 
    /*
     * Push it onto the list of chunks, so that it can be found if we need to
     * increase the number of buckets or batches (batch 0 only) and later for
     * freeing the memory (all batches).
     */
    chunk->next.shared = hashtable->batches[curbatch].shared->chunks;
    hashtable->batches[curbatch].shared->chunks = chunk_shared;
 
    if (size <= HASH_CHUNK_THRESHOLD)
    {
        /*
         * Make this the current chunk so that we can use the fast path to
         * fill the rest of it up in future calls.
         */
        hashtable->current_chunk = chunk;
        hashtable->current_chunk_shared = chunk_shared;
    }
    LWLockRelease(&pstate->lock);
 
    Assert(HASH_CHUNK_DATA(chunk) == dsa_get_address(hashtable->area, *shared));
    result = (HashJoinTuple) HASH_CHUNK_DATA(chunk);
 
    return result;
}
 
/*
 * One backend needs to set up the shared batch state including tuplestores.
 * Other backends will ensure they have correctly configured accessors by
 * called ExecParallelHashEnsureBatchAccessors().
 */
static void
ExecParallelHashJoinSetUpBatches(HashJoinTable hashtable, int nbatch)
{
    ParallelHashJoinState *pstate = hashtable->parallel_state;
    ParallelHashJoinBatch *batches;
    MemoryContext oldcxt;
    int         i;
 
    Assert(hashtable->batches == NULL);
 
    /* Allocate space. */
    pstate->batches =
        dsa_allocate0(hashtable->area,
                      EstimateParallelHashJoinBatch(hashtable) * nbatch);
    pstate->nbatch = nbatch;
    batches = dsa_get_address(hashtable->area, pstate->batches);
 
    /*
     * Use hash join spill memory context to allocate accessors, including
     * buffers for the temporary files.
     */
    oldcxt = MemoryContextSwitchTo(hashtable->spillCxt);
 
    /* Allocate this backend's accessor array. */
    hashtable->nbatch = nbatch;
    hashtable->batches =
        palloc0_array(ParallelHashJoinBatchAccessor, hashtable->nbatch);
 
    /* Set up the shared state, tuplestores and backend-local accessors. */
    for (i = 0; i < hashtable->nbatch; ++i)
    {
        ParallelHashJoinBatchAccessor *accessor = &hashtable->batches[i];
        ParallelHashJoinBatch *shared = NthParallelHashJoinBatch(batches, i);
        char        name[MAXPGPATH];
 
        /*
         * All members of shared were zero-initialized.  We just need to set
         * up the Barrier.
         */
        BarrierInit(&shared->batch_barrier, 0);
        if (i == 0)
        {
            /* Batch 0 doesn't need to be loaded. */
            BarrierAttach(&shared->batch_barrier);
            while (BarrierPhase(&shared->batch_barrier) < PHJ_BATCH_PROBE)
                BarrierArriveAndWait(&shared->batch_barrier, 0);
            BarrierDetach(&shared->batch_barrier);
        }
 
        /* Initialize accessor state.  All members were zero-initialized. */
        accessor->shared = shared;
 
        /* Initialize the shared tuplestores. */
        snprintf(name, sizeof(name), "i%dof%d", i, hashtable->nbatch);
        accessor->inner_tuples =
            sts_initialize(ParallelHashJoinBatchInner(shared),
                           pstate->nparticipants,
                           ParallelWorkerNumber + 1,
                           sizeof(uint32),
                           SHARED_TUPLESTORE_SINGLE_PASS,
                           &pstate->fileset,
                           name);
        snprintf(name, sizeof(name), "o%dof%d", i, hashtable->nbatch);
        accessor->outer_tuples =
            sts_initialize(ParallelHashJoinBatchOuter(shared,
                                                      pstate->nparticipants),
                           pstate->nparticipants,
                           ParallelWorkerNumber + 1,
                           sizeof(uint32),
                           SHARED_TUPLESTORE_SINGLE_PASS,
                           &pstate->fileset,
                           name);
    }
 
    MemoryContextSwitchTo(oldcxt);
}
 
/*
 * Free the current set of ParallelHashJoinBatchAccessor objects.
 */
static void
ExecParallelHashCloseBatchAccessors(HashJoinTable hashtable)
{
    int         i;
 
    for (i = 0; i < hashtable->nbatch; ++i)
    {
        /* Make sure no files are left open. */
        sts_end_write(hashtable->batches[i].inner_tuples);
        sts_end_write(hashtable->batches[i].outer_tuples);
        sts_end_parallel_scan(hashtable->batches[i].inner_tuples);
        sts_end_parallel_scan(hashtable->batches[i].outer_tuples);
    }
    pfree(hashtable->batches);
    hashtable->batches = NULL;
}
 
/*
 * Make sure this backend has up-to-date accessors for the current set of
 * batches.
 */
static void
ExecParallelHashEnsureBatchAccessors(HashJoinTable hashtable)
{
    ParallelHashJoinState *pstate = hashtable->parallel_state;
    ParallelHashJoinBatch *batches;
    MemoryContext oldcxt;
    int         i;
 
    if (hashtable->batches != NULL)
    {
        if (hashtable->nbatch == pstate->nbatch)
            return;
        ExecParallelHashCloseBatchAccessors(hashtable);
    }
 
    /*
     * We should never see a state where the batch-tracking array is freed,
     * because we should have given up sooner if we join when the build
     * barrier has reached the PHJ_BUILD_FREE phase.
     */
    Assert(DsaPointerIsValid(pstate->batches));
 
    /*
     * Use hash join spill memory context to allocate accessors, including
     * buffers for the temporary files.
     */
    oldcxt = MemoryContextSwitchTo(hashtable->spillCxt);
 
    /* Allocate this backend's accessor array. */
    hashtable->nbatch = pstate->nbatch;
    hashtable->batches =
        palloc0_array(ParallelHashJoinBatchAccessor, hashtable->nbatch);
 
    /* Find the base of the pseudo-array of ParallelHashJoinBatch objects. */
    batches = (ParallelHashJoinBatch *)
        dsa_get_address(hashtable->area, pstate->batches);
 
    /* Set up the accessor array and attach to the tuplestores. */
    for (i = 0; i < hashtable->nbatch; ++i)
    {
        ParallelHashJoinBatchAccessor *accessor = &hashtable->batches[i];
        ParallelHashJoinBatch *shared = NthParallelHashJoinBatch(batches, i);
 
        accessor->shared = shared;
        accessor->preallocated = 0;
        accessor->done = false;
        accessor->outer_eof = false;
        accessor->inner_tuples =
            sts_attach(ParallelHashJoinBatchInner(shared),
                       ParallelWorkerNumber + 1,
                       &pstate->fileset);
        accessor->outer_tuples =
            sts_attach(ParallelHashJoinBatchOuter(shared,
                                                  pstate->nparticipants),
                       ParallelWorkerNumber + 1,
                       &pstate->fileset);
    }
 
    MemoryContextSwitchTo(oldcxt);
}
 
/*
 * Allocate an empty shared memory hash table for a given batch.
 */
void
ExecParallelHashTableAlloc(HashJoinTable hashtable, int batchno)
{
    ParallelHashJoinBatch *batch = hashtable->batches[batchno].shared;
    dsa_pointer_atomic *buckets;
    int         nbuckets = hashtable->parallel_state->nbuckets;
    int         i;
 
    batch->buckets =
        dsa_allocate(hashtable->area, sizeof(dsa_pointer_atomic) * nbuckets);
    buckets = (dsa_pointer_atomic *)
        dsa_get_address(hashtable->area, batch->buckets);
    for (i = 0; i < nbuckets; ++i)
        dsa_pointer_atomic_init(&buckets[i], InvalidDsaPointer);
}
 
/*
 * If we are currently attached to a shared hash join batch, detach.  If we
 * are last to detach, clean up.
 */
void
ExecHashTableDetachBatch(HashJoinTable hashtable)
{
    if (hashtable->parallel_state != NULL &&
        hashtable->curbatch >= 0)
    {
        int         curbatch = hashtable->curbatch;
        ParallelHashJoinBatch *batch = hashtable->batches[curbatch].shared;
        bool        attached = true;
 
        /* Make sure any temporary files are closed. */
        sts_end_parallel_scan(hashtable->batches[curbatch].inner_tuples);
        sts_end_parallel_scan(hashtable->batches[curbatch].outer_tuples);
 
        /* After attaching we always get at least to PHJ_BATCH_PROBE. */
        Assert(BarrierPhase(&batch->batch_barrier) == PHJ_BATCH_PROBE ||
               BarrierPhase(&batch->batch_barrier) == PHJ_BATCH_SCAN);
 
        /*
         * If we're abandoning the PHJ_BATCH_PROBE phase early without having
         * reached the end of it, it means the plan doesn't want any more
         * tuples, and it is happy to abandon any tuples buffered in this
         * process's subplans.  For correctness, we can't allow any process to
         * execute the PHJ_BATCH_SCAN phase, because we will never have the
         * complete set of match bits.  Therefore we skip emitting unmatched
         * tuples in all backends (if this is a full/right join), as if those
         * tuples were all due to be emitted by this process and it has
         * abandoned them too.
         */
        if (BarrierPhase(&batch->batch_barrier) == PHJ_BATCH_PROBE &&
            !hashtable->batches[curbatch].outer_eof)
        {
            /*
             * This flag may be written to by multiple backends during
             * PHJ_BATCH_PROBE phase, but will only be read in PHJ_BATCH_SCAN
             * phase so requires no extra locking.
             */
            batch->skip_unmatched = true;
        }
 
        /*
         * Even if we aren't doing a full/right outer join, we'll step through
         * the PHJ_BATCH_SCAN phase just to maintain the invariant that
         * freeing happens in PHJ_BATCH_FREE, but that'll be wait-free.
         */
        if (BarrierPhase(&batch->batch_barrier) == PHJ_BATCH_PROBE)
            attached = BarrierArriveAndDetachExceptLast(&batch->batch_barrier);
        if (attached && BarrierArriveAndDetach(&batch->batch_barrier))
        {
            /*
             * We are not longer attached to the batch barrier, but we're the
             * process that was chosen to free resources and it's safe to
             * assert the current phase.  The ParallelHashJoinBatch can't go
             * away underneath us while we are attached to the build barrier,
             * making this access safe.
             */
            Assert(BarrierPhase(&batch->batch_barrier) == PHJ_BATCH_FREE);
 
            /* Free shared chunks and buckets. */
            while (DsaPointerIsValid(batch->chunks))
            {
                HashMemoryChunk chunk =
                    dsa_get_address(hashtable->area, batch->chunks);
                dsa_pointer next = chunk->next.shared;
 
                dsa_free(hashtable->area, batch->chunks);
                batch->chunks = next;
            }
            if (DsaPointerIsValid(batch->buckets))
            {
                dsa_free(hashtable->area, batch->buckets);
                batch->buckets = InvalidDsaPointer;
            }
        }
 
        /*
         * Track the largest batch we've been attached to.  Though each
         * backend might see a different subset of batches, explain.c will
         * scan the results from all backends to find the largest value.
         */
        hashtable->spacePeak =
            Max(hashtable->spacePeak,
                batch->size + sizeof(dsa_pointer_atomic) * hashtable->nbuckets);
 
        /* Remember that we are not attached to a batch. */
        hashtable->curbatch = -1;
    }
}
 
/*
 * Detach from all shared resources.  If we are last to detach, clean up.
 */
void
ExecHashTableDetach(HashJoinTable hashtable)
{
    ParallelHashJoinState *pstate = hashtable->parallel_state;
 
    /*
     * If we're involved in a parallel query, we must either have gotten all
     * the way to PHJ_BUILD_RUN, or joined too late and be in PHJ_BUILD_FREE.
     */
    Assert(!pstate ||
           BarrierPhase(&pstate->build_barrier) >= PHJ_BUILD_RUN);
 
    if (pstate && BarrierPhase(&pstate->build_barrier) == PHJ_BUILD_RUN)
    {
        int         i;
 
        /* Make sure any temporary files are closed. */
        if (hashtable->batches)
        {
            for (i = 0; i < hashtable->nbatch; ++i)
            {
                sts_end_write(hashtable->batches[i].inner_tuples);
                sts_end_write(hashtable->batches[i].outer_tuples);
                sts_end_parallel_scan(hashtable->batches[i].inner_tuples);
                sts_end_parallel_scan(hashtable->batches[i].outer_tuples);
            }
        }
 
        /* If we're last to detach, clean up shared memory. */
        if (BarrierArriveAndDetach(&pstate->build_barrier))
        {
            /*
             * Late joining processes will see this state and give up
             * immediately.
             */
            Assert(BarrierPhase(&pstate->build_barrier) == PHJ_BUILD_FREE);
 
            if (DsaPointerIsValid(pstate->batches))
            {
                dsa_free(hashtable->area, pstate->batches);
                pstate->batches = InvalidDsaPointer;
            }
        }
    }
    hashtable->parallel_state = NULL;
}
 
/*
 * Get the first tuple in a given bucket identified by number.
 */
static inline HashJoinTuple
ExecParallelHashFirstTuple(HashJoinTable hashtable, int bucketno)
{
    HashJoinTuple tuple;
    dsa_pointer p;
 
    Assert(hashtable->parallel_state);
    p = dsa_pointer_atomic_read(&hashtable->buckets.shared[bucketno]);
    tuple = (HashJoinTuple) dsa_get_address(hashtable->area, p);
 
    return tuple;
}
 
/*
 * Get the next tuple in the same bucket as 'tuple'.
 */
static inline HashJoinTuple
ExecParallelHashNextTuple(HashJoinTable hashtable, HashJoinTuple tuple)
{
    HashJoinTuple next;
 
    Assert(hashtable->parallel_state);
    next = (HashJoinTuple) dsa_get_address(hashtable->area, tuple->next.shared);
 
    return next;
}
 
/*
 * Insert a tuple at the front of a chain of tuples in DSA memory atomically.
 */
static inline void
ExecParallelHashPushTuple(dsa_pointer_atomic *head,
                          HashJoinTuple tuple,
                          dsa_pointer tuple_shared)
{
    for (;;)
    {
        tuple->next.shared = dsa_pointer_atomic_read(head);
        if (dsa_pointer_atomic_compare_exchange(head,
                                                &tuple->next.shared,
                                                tuple_shared))
            break;
    }
}
 
/*
 * Prepare to work on a given batch.
 */
void
ExecParallelHashTableSetCurrentBatch(HashJoinTable hashtable, int batchno)
{
    Assert(hashtable->batches[batchno].shared->buckets != InvalidDsaPointer);
 
    hashtable->curbatch = batchno;
    hashtable->buckets.shared = (dsa_pointer_atomic *)
        dsa_get_address(hashtable->area,
                        hashtable->batches[batchno].shared->buckets);
    hashtable->nbuckets = hashtable->parallel_state->nbuckets;
    hashtable->log2_nbuckets = my_log2(hashtable->nbuckets);
    hashtable->current_chunk = NULL;
    hashtable->current_chunk_shared = InvalidDsaPointer;
    hashtable->batches[batchno].at_least_one_chunk = false;
}
 
/*
 * Take the next available chunk from the queue of chunks being worked on in
 * parallel.  Return NULL if there are none left.  Otherwise return a pointer
 * to the chunk, and set *shared to the DSA pointer to the chunk.
 */
static HashMemoryChunk
ExecParallelHashPopChunkQueue(HashJoinTable hashtable, dsa_pointer *shared)
{
    ParallelHashJoinState *pstate = hashtable->parallel_state;
    HashMemoryChunk chunk;
 
    LWLockAcquire(&pstate->lock, LW_EXCLUSIVE);
    if (DsaPointerIsValid(pstate->chunk_work_queue))
    {
        *shared = pstate->chunk_work_queue;
        chunk = (HashMemoryChunk)
            dsa_get_address(hashtable->area, *shared);
        pstate->chunk_work_queue = chunk->next.shared;
    }
    else
        chunk = NULL;
    LWLockRelease(&pstate->lock);
 
    return chunk;
}
 
/*
 * Increase the space preallocated in this backend for a given inner batch by
 * at least a given amount.  This allows us to track whether a given batch
 * would fit in memory when loaded back in.  Also increase the number of
 * batches or buckets if required.
 *
 * This maintains a running estimation of how much space will be taken when we
 * load the batch back into memory by simulating the way chunks will be handed
 * out to workers.  It's not perfectly accurate because the tuples will be
 * packed into memory chunks differently by ExecParallelHashTupleAlloc(), but
 * it should be pretty close.  It tends to overestimate by a fraction of a
 * chunk per worker since all workers gang up to preallocate during hashing,
 * but workers tend to reload batches alone if there are enough to go around,
 * leaving fewer partially filled chunks.  This effect is bounded by
 * nparticipants.
 *
 * Return false if the number of batches or buckets has changed, and the
 * caller should reconsider which batch a given tuple now belongs in and call
 * again.
 */
static bool
ExecParallelHashTuplePrealloc(HashJoinTable hashtable, int batchno, size_t size)
{
    ParallelHashJoinState *pstate = hashtable->parallel_state;
    ParallelHashJoinBatchAccessor *batch = &hashtable->batches[batchno];
    size_t      want = Max(size, HASH_CHUNK_SIZE - HASH_CHUNK_HEADER_SIZE);
 
    Assert(batchno > 0);
    Assert(batchno < hashtable->nbatch);
    Assert(size == MAXALIGN(size));
 
    LWLockAcquire(&pstate->lock, LW_EXCLUSIVE);
 
    /* Has another participant commanded us to help grow? */
    if (pstate->growth == PHJ_GROWTH_NEED_MORE_BATCHES ||
        pstate->growth == PHJ_GROWTH_NEED_MORE_BUCKETS)
    {
        ParallelHashGrowth growth = pstate->growth;
 
        LWLockRelease(&pstate->lock);
        if (growth == PHJ_GROWTH_NEED_MORE_BATCHES)
            ExecParallelHashIncreaseNumBatches(hashtable);
        else if (growth == PHJ_GROWTH_NEED_MORE_BUCKETS)
            ExecParallelHashIncreaseNumBuckets(hashtable);
 
        return false;
    }
 
    if (pstate->growth != PHJ_GROWTH_DISABLED &&
        batch->at_least_one_chunk &&
        (batch->shared->estimated_size + want + HASH_CHUNK_HEADER_SIZE
         > pstate->space_allowed))
    {
        /*
         * We have determined that this batch would exceed the space budget if
         * loaded into memory.  Command all participants to help repartition.
         */
        batch->shared->space_exhausted = true;
        pstate->growth = PHJ_GROWTH_NEED_MORE_BATCHES;
        LWLockRelease(&pstate->lock);
 
        return false;
    }
 
    batch->at_least_one_chunk = true;
    batch->shared->estimated_size += want + HASH_CHUNK_HEADER_SIZE;
    batch->preallocated = want;
    LWLockRelease(&pstate->lock);
 
    return true;
}
 
/*
 * Calculate the limit on how much memory can be used by Hash and similar
 * plan types.  This is work_mem times hash_mem_multiplier, and is
 * expressed in bytes.
 *
 * Exported for use by the planner, as well as other hash-like executor
 * nodes.  This is a rather random place for this, but there is no better
 * place.
 */
size_t
get_hash_memory_limit(void)
{
    double      mem_limit;
 
    /* Do initial calculation in double arithmetic */
    mem_limit = (double) work_mem * hash_mem_multiplier * 1024.0;
 
    /* Clamp in case it doesn't fit in size_t */
    mem_limit = Min(mem_limit, (double) SIZE_MAX);
 
    return (size_t) mem_limit;
}