nodeHashjoin.c

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/*-------------------------------------------------------------------------
 *
 * nodeHashjoin.c
 *    Routines to handle hash join nodes
 *
 * Portions Copyright (c) 1996-2024, PostgreSQL Global Development Group
 * Portions Copyright (c) 1994, Regents of the University of California
 *
 *
 * IDENTIFICATION
 *    src/backend/executor/nodeHashjoin.c
 *
 * HASH JOIN
 *
 * This is based on the "hybrid hash join" algorithm described shortly in the
 * following page
 *
 *   https://en.wikipedia.org/wiki/Hash_join#Hybrid_hash_join
 *
 * and in detail in the referenced paper:
 *
 *   "An Adaptive Hash Join Algorithm for Multiuser Environments"
 *   Hansjörg Zeller; Jim Gray (1990). Proceedings of the 16th VLDB conference.
 *   Brisbane: 186–197.
 *
 * If the inner side tuples of a hash join do not fit in memory, the hash join
 * can be executed in multiple batches.
 *
 * If the statistics on the inner side relation are accurate, planner chooses a
 * multi-batch strategy and estimates the number of batches.
 *
 * The query executor measures the real size of the hashtable and increases the
 * number of batches if the hashtable grows too large.
 *
 * The number of batches is always a power of two, so an increase in the number
 * of batches doubles it.
 *
 * Serial hash join measures batch size lazily -- waiting until it is loading a
 * batch to determine if it will fit in memory. While inserting tuples into the
 * hashtable, serial hash join will, if that tuple were to exceed work_mem,
 * dump out the hashtable and reassign them either to other batch files or the
 * current batch resident in the hashtable.
 *
 * Parallel hash join, on the other hand, completes all changes to the number
 * of batches during the build phase. If it increases the number of batches, it
 * dumps out all the tuples from all batches and reassigns them to entirely new
 * batch files. Then it checks every batch to ensure it will fit in the space
 * budget for the query.
 *
 * In both parallel and serial hash join, the executor currently makes a best
 * effort. If a particular batch will not fit in memory, it tries doubling the
 * number of batches. If after a batch increase, there is a batch which
 * retained all or none of its tuples, the executor disables growth in the
 * number of batches globally. After growth is disabled, all batches that would
 * have previously triggered an increase in the number of batches instead
 * exceed the space allowed.
 *
 * PARALLELISM
 *
 * Hash joins can participate in parallel query execution in several ways.  A
 * parallel-oblivious hash join is one where the node is unaware that it is
 * part of a parallel plan.  In this case, a copy of the inner plan is used to
 * build a copy of the hash table in every backend, and the outer plan could
 * either be built from a partial or complete path, so that the results of the
 * hash join are correspondingly either partial or complete.  A parallel-aware
 * hash join is one that behaves differently, coordinating work between
 * backends, and appears as Parallel Hash Join in EXPLAIN output.  A Parallel
 * Hash Join always appears with a Parallel Hash node.
 *
 * Parallel-aware hash joins use the same per-backend state machine to track
 * progress through the hash join algorithm as parallel-oblivious hash joins.
 * In a parallel-aware hash join, there is also a shared state machine that
 * co-operating backends use to synchronize their local state machines and
 * program counters.  The shared state machine is managed with a Barrier IPC
 * primitive.  When all attached participants arrive at a barrier, the phase
 * advances and all waiting participants are released.
 *
 * When a participant begins working on a parallel hash join, it must first
 * figure out how much progress has already been made, because participants
 * don't wait for each other to begin.  For this reason there are switch
 * statements at key points in the code where we have to synchronize our local
 * state machine with the phase, and then jump to the correct part of the
 * algorithm so that we can get started.
 *
 * One barrier called build_barrier is used to coordinate the hashing phases.
 * The phase is represented by an integer which begins at zero and increments
 * one by one, but in the code it is referred to by symbolic names as follows.
 * An asterisk indicates a phase that is performed by a single arbitrarily
 * chosen process.
 *
 *   PHJ_BUILD_ELECT                 -- initial state
 *   PHJ_BUILD_ALLOCATE*             -- one sets up the batches and table 0
 *   PHJ_BUILD_HASH_INNER            -- all hash the inner rel
 *   PHJ_BUILD_HASH_OUTER            -- (multi-batch only) all hash the outer
 *   PHJ_BUILD_RUN                   -- building done, probing can begin
 *   PHJ_BUILD_FREE*                 -- all work complete, one frees batches
 *
 * While in the phase PHJ_BUILD_HASH_INNER a separate pair of barriers may
 * be used repeatedly as required to coordinate expansions in the number of
 * batches or buckets.  Their phases are as follows:
 *
 *   PHJ_GROW_BATCHES_ELECT          -- initial state
 *   PHJ_GROW_BATCHES_REALLOCATE*    -- one allocates new batches
 *   PHJ_GROW_BATCHES_REPARTITION    -- all repartition
 *   PHJ_GROW_BATCHES_DECIDE*        -- one detects skew and cleans up
 *   PHJ_GROW_BATCHES_FINISH         -- finished one growth cycle
 *
 *   PHJ_GROW_BUCKETS_ELECT          -- initial state
 *   PHJ_GROW_BUCKETS_REALLOCATE*    -- one allocates new buckets
 *   PHJ_GROW_BUCKETS_REINSERT       -- all insert tuples
 *
 * If the planner got the number of batches and buckets right, those won't be
 * necessary, but on the other hand we might finish up needing to expand the
 * buckets or batches multiple times while hashing the inner relation to stay
 * within our memory budget and load factor target.  For that reason it's a
 * separate pair of barriers using circular phases.
 *
 * The PHJ_BUILD_HASH_OUTER phase is required only for multi-batch joins,
 * because we need to divide the outer relation into batches up front in order
 * to be able to process batches entirely independently.  In contrast, the
 * parallel-oblivious algorithm simply throws tuples 'forward' to 'later'
 * batches whenever it encounters them while scanning and probing, which it
 * can do because it processes batches in serial order.
 *
 * Once PHJ_BUILD_RUN is reached, backends then split up and process
 * different batches, or gang up and work together on probing batches if there
 * aren't enough to go around.  For each batch there is a separate barrier
 * with the following phases:
 *
 *  PHJ_BATCH_ELECT          -- initial state
 *  PHJ_BATCH_ALLOCATE*      -- one allocates buckets
 *  PHJ_BATCH_LOAD           -- all load the hash table from disk
 *  PHJ_BATCH_PROBE          -- all probe
 *  PHJ_BATCH_SCAN*          -- one does right/right-anti/full unmatched scan
 *  PHJ_BATCH_FREE*          -- one frees memory
 *
 * Batch 0 is a special case, because it starts out in phase
 * PHJ_BATCH_PROBE; populating batch 0's hash table is done during
 * PHJ_BUILD_HASH_INNER so we can skip loading.
 *
 * Initially we try to plan for a single-batch hash join using the combined
 * hash_mem of all participants to create a large shared hash table.  If that
 * turns out either at planning or execution time to be impossible then we
 * fall back to regular hash_mem sized hash tables.
 *
 * To avoid deadlocks, we never wait for any barrier unless it is known that
 * all other backends attached to it are actively executing the node or have
 * finished.  Practically, that means that we never emit a tuple while attached
 * to a barrier, unless the barrier has reached a phase that means that no
 * process will wait on it again.  We emit tuples while attached to the build
 * barrier in phase PHJ_BUILD_RUN, and to a per-batch barrier in phase
 * PHJ_BATCH_PROBE.  These are advanced to PHJ_BUILD_FREE and PHJ_BATCH_SCAN
 * respectively without waiting, using BarrierArriveAndDetach() and
 * BarrierArriveAndDetachExceptLast() respectively.  The last to detach
 * receives a different return value so that it knows that it's safe to
 * clean up.  Any straggler process that attaches after that phase is reached
 * will see that it's too late to participate or access the relevant shared
 * memory objects.
 *
 *-------------------------------------------------------------------------
 */
 
#include "postgres.h"
 
#include "access/htup_details.h"
#include "access/parallel.h"
#include "executor/executor.h"
#include "executor/hashjoin.h"
#include "executor/nodeHash.h"
#include "executor/nodeHashjoin.h"
#include "miscadmin.h"
#include "utils/sharedtuplestore.h"
#include "utils/wait_event.h"
 
 
/*
 * States of the ExecHashJoin state machine
 */
#define HJ_BUILD_HASHTABLE      1
#define HJ_NEED_NEW_OUTER       2
#define HJ_SCAN_BUCKET          3
#define HJ_FILL_OUTER_TUPLE     4
#define HJ_FILL_INNER_TUPLES    5
#define HJ_NEED_NEW_BATCH       6
 
/* Returns true if doing null-fill on outer relation */
#define HJ_FILL_OUTER(hjstate)  ((hjstate)->hj_NullInnerTupleSlot != NULL)
/* Returns true if doing null-fill on inner relation */
#define HJ_FILL_INNER(hjstate)  ((hjstate)->hj_NullOuterTupleSlot != NULL)
 
static TupleTableSlot *ExecHashJoinOuterGetTuple(PlanState *outerNode,
                                                 HashJoinState *hjstate,
                                                 uint32 *hashvalue);
static TupleTableSlot *ExecParallelHashJoinOuterGetTuple(PlanState *outerNode,
                                                         HashJoinState *hjstate,
                                                         uint32 *hashvalue);
static TupleTableSlot *ExecHashJoinGetSavedTuple(HashJoinState *hjstate,
                                                 BufFile *file,
                                                 uint32 *hashvalue,
                                                 TupleTableSlot *tupleSlot);
static bool ExecHashJoinNewBatch(HashJoinState *hjstate);
static bool ExecParallelHashJoinNewBatch(HashJoinState *hjstate);
static void ExecParallelHashJoinPartitionOuter(HashJoinState *hjstate);
 
 
/* ----------------------------------------------------------------
 *      ExecHashJoinImpl
 *
 *      This function implements the Hybrid Hashjoin algorithm.  It is marked
 *      with an always-inline attribute so that ExecHashJoin() and
 *      ExecParallelHashJoin() can inline it.  Compilers that respect the
 *      attribute should create versions specialized for parallel == true and
 *      parallel == false with unnecessary branches removed.
 *
 *      Note: the relation we build hash table on is the "inner"
 *            the other one is "outer".
 * ----------------------------------------------------------------
 */
static pg_attribute_always_inline TupleTableSlot *
ExecHashJoinImpl(PlanState *pstate, bool parallel)
{
    HashJoinState *node = castNode(HashJoinState, pstate);
    PlanState  *outerNode;
    HashState  *hashNode;
    ExprState  *joinqual;
    ExprState  *otherqual;
    ExprContext *econtext;
    HashJoinTable hashtable;
    TupleTableSlot *outerTupleSlot;
    uint32      hashvalue;
    int         batchno;
    ParallelHashJoinState *parallel_state;
 
    /*
     * get information from HashJoin node
     */
    joinqual = node->js.joinqual;
    otherqual = node->js.ps.qual;
    hashNode = (HashState *) innerPlanState(node);
    outerNode = outerPlanState(node);
    hashtable = node->hj_HashTable;
    econtext = node->js.ps.ps_ExprContext;
    parallel_state = hashNode->parallel_state;
 
    /*
     * Reset per-tuple memory context to free any expression evaluation
     * storage allocated in the previous tuple cycle.
     */
    ResetExprContext(econtext);
 
    /*
     * run the hash join state machine
     */
    for (;;)
    {
        /*
         * It's possible to iterate this loop many times before returning a
         * tuple, in some pathological cases such as needing to move much of
         * the current batch to a later batch.  So let's check for interrupts
         * each time through.
         */
        CHECK_FOR_INTERRUPTS();
 
        switch (node->hj_JoinState)
        {
            case HJ_BUILD_HASHTABLE:
 
                /*
                 * First time through: build hash table for inner relation.
                 */
                Assert(hashtable == NULL);
 
                /*
                 * If the outer relation is completely empty, and it's not
                 * right/right-anti/full join, we can quit without building
                 * the hash table.  However, for an inner join it is only a
                 * win to check this when the outer relation's startup cost is
                 * less than the projected cost of building the hash table.
                 * Otherwise it's best to build the hash table first and see
                 * if the inner relation is empty.  (When it's a left join, we
                 * should always make this check, since we aren't going to be
                 * able to skip the join on the strength of an empty inner
                 * relation anyway.)
                 *
                 * If we are rescanning the join, we make use of information
                 * gained on the previous scan: don't bother to try the
                 * prefetch if the previous scan found the outer relation
                 * nonempty. This is not 100% reliable since with new
                 * parameters the outer relation might yield different
                 * results, but it's a good heuristic.
                 *
                 * The only way to make the check is to try to fetch a tuple
                 * from the outer plan node.  If we succeed, we have to stash
                 * it away for later consumption by ExecHashJoinOuterGetTuple.
                 */
                if (HJ_FILL_INNER(node))
                {
                    /* no chance to not build the hash table */
                    node->hj_FirstOuterTupleSlot = NULL;
                }
                else if (parallel)
                {
                    /*
                     * The empty-outer optimization is not implemented for
                     * shared hash tables, because no one participant can
                     * determine that there are no outer tuples, and it's not
                     * yet clear that it's worth the synchronization overhead
                     * of reaching consensus to figure that out.  So we have
                     * to build the hash table.
                     */
                    node->hj_FirstOuterTupleSlot = NULL;
                }
                else if (HJ_FILL_OUTER(node) ||
                         (outerNode->plan->startup_cost < hashNode->ps.plan->total_cost &&
                          !node->hj_OuterNotEmpty))
                {
                    node->hj_FirstOuterTupleSlot = ExecProcNode(outerNode);
                    if (TupIsNull(node->hj_FirstOuterTupleSlot))
                    {
                        node->hj_OuterNotEmpty = false;
                        return NULL;
                    }
                    else
                        node->hj_OuterNotEmpty = true;
                }
                else
                    node->hj_FirstOuterTupleSlot = NULL;
 
                /*
                 * Create the hash table.  If using Parallel Hash, then
                 * whoever gets here first will create the hash table and any
                 * later arrivals will merely attach to it.
                 */
                hashtable = ExecHashTableCreate(hashNode,
                                                node->hj_HashOperators,
                                                node->hj_Collations,
                                                HJ_FILL_INNER(node));
                node->hj_HashTable = hashtable;
 
                /*
                 * Execute the Hash node, to build the hash table.  If using
                 * Parallel Hash, then we'll try to help hashing unless we
                 * arrived too late.
                 */
                hashNode->hashtable = hashtable;
                (void) MultiExecProcNode((PlanState *) hashNode);
 
                /*
                 * If the inner relation is completely empty, and we're not
                 * doing a left outer join, we can quit without scanning the
                 * outer relation.
                 */
                if (hashtable->totalTuples == 0 && !HJ_FILL_OUTER(node))
                {
                    if (parallel)
                    {
                        /*
                         * Advance the build barrier to PHJ_BUILD_RUN before
                         * proceeding so we can negotiate resource cleanup.
                         */
                        Barrier    *build_barrier = &parallel_state->build_barrier;
 
                        while (BarrierPhase(build_barrier) < PHJ_BUILD_RUN)
                            BarrierArriveAndWait(build_barrier, 0);
                    }
                    return NULL;
                }
 
                /*
                 * need to remember whether nbatch has increased since we
                 * began scanning the outer relation
                 */
                hashtable->nbatch_outstart = hashtable->nbatch;
 
                /*
                 * Reset OuterNotEmpty for scan.  (It's OK if we fetched a
                 * tuple above, because ExecHashJoinOuterGetTuple will
                 * immediately set it again.)
                 */
                node->hj_OuterNotEmpty = false;
 
                if (parallel)
                {
                    Barrier    *build_barrier;
 
                    build_barrier = &parallel_state->build_barrier;
                    Assert(BarrierPhase(build_barrier) == PHJ_BUILD_HASH_OUTER ||
                           BarrierPhase(build_barrier) == PHJ_BUILD_RUN ||
                           BarrierPhase(build_barrier) == PHJ_BUILD_FREE);
                    if (BarrierPhase(build_barrier) == PHJ_BUILD_HASH_OUTER)
                    {
                        /*
                         * If multi-batch, we need to hash the outer relation
                         * up front.
                         */
                        if (hashtable->nbatch > 1)
                            ExecParallelHashJoinPartitionOuter(node);
                        BarrierArriveAndWait(build_barrier,
                                             WAIT_EVENT_HASH_BUILD_HASH_OUTER);
                    }
                    else if (BarrierPhase(build_barrier) == PHJ_BUILD_FREE)
                    {
                        /*
                         * If we attached so late that the job is finished and
                         * the batch state has been freed, we can return
                         * immediately.
                         */
                        return NULL;
                    }
 
                    /* Each backend should now select a batch to work on. */
                    Assert(BarrierPhase(build_barrier) == PHJ_BUILD_RUN);
                    hashtable->curbatch = -1;
                    node->hj_JoinState = HJ_NEED_NEW_BATCH;
 
                    continue;
                }
                else
                    node->hj_JoinState = HJ_NEED_NEW_OUTER;
 
                /* FALL THRU */
 
            case HJ_NEED_NEW_OUTER:
 
                /*
                 * We don't have an outer tuple, try to get the next one
                 */
                if (parallel)
                    outerTupleSlot =
                        ExecParallelHashJoinOuterGetTuple(outerNode, node,
                                                          &hashvalue);
                else
                    outerTupleSlot =
                        ExecHashJoinOuterGetTuple(outerNode, node, &hashvalue);
 
                if (TupIsNull(outerTupleSlot))
                {
                    /* end of batch, or maybe whole join */
                    if (HJ_FILL_INNER(node))
                    {
                        /* set up to scan for unmatched inner tuples */
                        if (parallel)
                        {
                            /*
                             * Only one process is currently allow to handle
                             * each batch's unmatched tuples, in a parallel
                             * join.
                             */
                            if (ExecParallelPrepHashTableForUnmatched(node))
                                node->hj_JoinState = HJ_FILL_INNER_TUPLES;
                            else
                                node->hj_JoinState = HJ_NEED_NEW_BATCH;
                        }
                        else
                        {
                            ExecPrepHashTableForUnmatched(node);
                            node->hj_JoinState = HJ_FILL_INNER_TUPLES;
                        }
                    }
                    else
                        node->hj_JoinState = HJ_NEED_NEW_BATCH;
                    continue;
                }
 
                econtext->ecxt_outertuple = outerTupleSlot;
                node->hj_MatchedOuter = false;
 
                /*
                 * Find the corresponding bucket for this tuple in the main
                 * hash table or skew hash table.
                 */
                node->hj_CurHashValue = hashvalue;
                ExecHashGetBucketAndBatch(hashtable, hashvalue,
                                          &node->hj_CurBucketNo, &batchno);
                node->hj_CurSkewBucketNo = ExecHashGetSkewBucket(hashtable,
                                                                 hashvalue);
                node->hj_CurTuple = NULL;
 
                /*
                 * The tuple might not belong to the current batch (where
                 * "current batch" includes the skew buckets if any).
                 */
                if (batchno != hashtable->curbatch &&
                    node->hj_CurSkewBucketNo == INVALID_SKEW_BUCKET_NO)
                {
                    bool        shouldFree;
                    MinimalTuple mintuple = ExecFetchSlotMinimalTuple(outerTupleSlot,
                                                                      &shouldFree);
 
                    /*
                     * Need to postpone this outer tuple to a later batch.
                     * Save it in the corresponding outer-batch file.
                     */
                    Assert(parallel_state == NULL);
                    Assert(batchno > hashtable->curbatch);
                    ExecHashJoinSaveTuple(mintuple, hashvalue,
                                          &hashtable->outerBatchFile[batchno],
                                          hashtable);
 
                    if (shouldFree)
                        heap_free_minimal_tuple(mintuple);
 
                    /* Loop around, staying in HJ_NEED_NEW_OUTER state */
                    continue;
                }
 
                /* OK, let's scan the bucket for matches */
                node->hj_JoinState = HJ_SCAN_BUCKET;
 
                /* FALL THRU */
 
            case HJ_SCAN_BUCKET:
 
                /*
                 * Scan the selected hash bucket for matches to current outer
                 */
                if (parallel)
                {
                    if (!ExecParallelScanHashBucket(node, econtext))
                    {
                        /* out of matches; check for possible outer-join fill */
                        node->hj_JoinState = HJ_FILL_OUTER_TUPLE;
                        continue;
                    }
                }
                else
                {
                    if (!ExecScanHashBucket(node, econtext))
                    {
                        /* out of matches; check for possible outer-join fill */
                        node->hj_JoinState = HJ_FILL_OUTER_TUPLE;
                        continue;
                    }
                }
 
                /*
                 * In a right-semijoin, we only need the first match for each
                 * inner tuple.
                 */
                if (node->js.jointype == JOIN_RIGHT_SEMI &&
                    HeapTupleHeaderHasMatch(HJTUPLE_MINTUPLE(node->hj_CurTuple)))
                    continue;
 
                /*
                 * We've got a match, but still need to test non-hashed quals.
                 * ExecScanHashBucket already set up all the state needed to
                 * call ExecQual.
                 *
                 * If we pass the qual, then save state for next call and have
                 * ExecProject form the projection, store it in the tuple
                 * table, and return the slot.
                 *
                 * Only the joinquals determine tuple match status, but all
                 * quals must pass to actually return the tuple.
                 */
                if (joinqual == NULL || ExecQual(joinqual, econtext))
                {
                    node->hj_MatchedOuter = true;
 
                    /*
                     * This is really only needed if HJ_FILL_INNER(node) or if
                     * we are in a right-semijoin, but we'll avoid the branch
                     * and just set it always.
                     */
                    if (!HeapTupleHeaderHasMatch(HJTUPLE_MINTUPLE(node->hj_CurTuple)))
                        HeapTupleHeaderSetMatch(HJTUPLE_MINTUPLE(node->hj_CurTuple));
 
                    /* In an antijoin, we never return a matched tuple */
                    if (node->js.jointype == JOIN_ANTI)
                    {
                        node->hj_JoinState = HJ_NEED_NEW_OUTER;
                        continue;
                    }
 
                    /*
                     * If we only need to consider the first matching inner
                     * tuple, then advance to next outer tuple after we've
                     * processed this one.
                     */
                    if (node->js.single_match)
                        node->hj_JoinState = HJ_NEED_NEW_OUTER;
 
                    /*
                     * In a right-antijoin, we never return a matched tuple.
                     * If it's not an inner_unique join, we need to stay on
                     * the current outer tuple to continue scanning the inner
                     * side for matches.
                     */
                    if (node->js.jointype == JOIN_RIGHT_ANTI)
                        continue;
 
                    if (otherqual == NULL || ExecQual(otherqual, econtext))
                        return ExecProject(node->js.ps.ps_ProjInfo);
                    else
                        InstrCountFiltered2(node, 1);
                }
                else
                    InstrCountFiltered1(node, 1);
                break;
 
            case HJ_FILL_OUTER_TUPLE:
 
                /*
                 * The current outer tuple has run out of matches, so check
                 * whether to emit a dummy outer-join tuple.  Whether we emit
                 * one or not, the next state is NEED_NEW_OUTER.
                 */
                node->hj_JoinState = HJ_NEED_NEW_OUTER;
 
                if (!node->hj_MatchedOuter &&
                    HJ_FILL_OUTER(node))
                {
                    /*
                     * Generate a fake join tuple with nulls for the inner
                     * tuple, and return it if it passes the non-join quals.
                     */
                    econtext->ecxt_innertuple = node->hj_NullInnerTupleSlot;
 
                    if (otherqual == NULL || ExecQual(otherqual, econtext))
                        return ExecProject(node->js.ps.ps_ProjInfo);
                    else
                        InstrCountFiltered2(node, 1);
                }
                break;
 
            case HJ_FILL_INNER_TUPLES:
 
                /*
                 * We have finished a batch, but we are doing
                 * right/right-anti/full join, so any unmatched inner tuples
                 * in the hashtable have to be emitted before we continue to
                 * the next batch.
                 */
                if (!(parallel ? ExecParallelScanHashTableForUnmatched(node, econtext)
                      : ExecScanHashTableForUnmatched(node, econtext)))
                {
                    /* no more unmatched tuples */
                    node->hj_JoinState = HJ_NEED_NEW_BATCH;
                    continue;
                }
 
                /*
                 * Generate a fake join tuple with nulls for the outer tuple,
                 * and return it if it passes the non-join quals.
                 */
                econtext->ecxt_outertuple = node->hj_NullOuterTupleSlot;
 
                if (otherqual == NULL || ExecQual(otherqual, econtext))
                    return ExecProject(node->js.ps.ps_ProjInfo);
                else
                    InstrCountFiltered2(node, 1);
                break;
 
            case HJ_NEED_NEW_BATCH:
 
                /*
                 * Try to advance to next batch.  Done if there are no more.
                 */
                if (parallel)
                {
                    if (!ExecParallelHashJoinNewBatch(node))
                        return NULL;    /* end of parallel-aware join */
                }
                else
                {
                    if (!ExecHashJoinNewBatch(node))
                        return NULL;    /* end of parallel-oblivious join */
                }
                node->hj_JoinState = HJ_NEED_NEW_OUTER;
                break;
 
            default:
                elog(ERROR, "unrecognized hashjoin state: %d",
                     (int) node->hj_JoinState);
        }
    }
}
 
/* ----------------------------------------------------------------
 *      ExecHashJoin
 *
 *      Parallel-oblivious version.
 * ----------------------------------------------------------------
 */
static TupleTableSlot *         /* return: a tuple or NULL */
ExecHashJoin(PlanState *pstate)
{
    /*
     * On sufficiently smart compilers this should be inlined with the
     * parallel-aware branches removed.
     */
    return ExecHashJoinImpl(pstate, false);
}
 
/* ----------------------------------------------------------------
 *      ExecParallelHashJoin
 *
 *      Parallel-aware version.
 * ----------------------------------------------------------------
 */
static TupleTableSlot *         /* return: a tuple or NULL */
ExecParallelHashJoin(PlanState *pstate)
{
    /*
     * On sufficiently smart compilers this should be inlined with the
     * parallel-oblivious branches removed.
     */
    return ExecHashJoinImpl(pstate, true);
}
 
/* ----------------------------------------------------------------
 *      ExecInitHashJoin
 *
 *      Init routine for HashJoin node.
 * ----------------------------------------------------------------
 */
HashJoinState *
ExecInitHashJoin(HashJoin *node, EState *estate, int eflags)
{
    HashJoinState *hjstate;
    Plan       *outerNode;
    Hash       *hashNode;
    TupleDesc   outerDesc,
                innerDesc;
    const TupleTableSlotOps *ops;
 
    /* check for unsupported flags */
    Assert(!(eflags & (EXEC_FLAG_BACKWARD | EXEC_FLAG_MARK)));
 
    /*
     * create state structure
     */
    hjstate = makeNode(HashJoinState);
    hjstate->js.ps.plan = (Plan *) node;
    hjstate->js.ps.state = estate;
 
    /*
     * See ExecHashJoinInitializeDSM() and ExecHashJoinInitializeWorker()
     * where this function may be replaced with a parallel version, if we
     * managed to launch a parallel query.
     */
    hjstate->js.ps.ExecProcNode = ExecHashJoin;
    hjstate->js.jointype = node->join.jointype;
 
    /*
     * Miscellaneous initialization
     *
     * create expression context for node
     */
    ExecAssignExprContext(estate, &hjstate->js.ps);
 
    /*
     * initialize child nodes
     *
     * Note: we could suppress the REWIND flag for the inner input, which
     * would amount to betting that the hash will be a single batch.  Not
     * clear if this would be a win or not.
     */
    outerNode = outerPlan(node);
    hashNode = (Hash *) innerPlan(node);
 
    outerPlanState(hjstate) = ExecInitNode(outerNode, estate, eflags);
    outerDesc = ExecGetResultType(outerPlanState(hjstate));
    innerPlanState(hjstate) = ExecInitNode((Plan *) hashNode, estate, eflags);
    innerDesc = ExecGetResultType(innerPlanState(hjstate));
 
    /*
     * Initialize result slot, type and projection.
     */
    ExecInitResultTupleSlotTL(&hjstate->js.ps, &TTSOpsVirtual);
    ExecAssignProjectionInfo(&hjstate->js.ps, NULL);
 
    /*
     * tuple table initialization
     */
    ops = ExecGetResultSlotOps(outerPlanState(hjstate), NULL);
    hjstate->hj_OuterTupleSlot = ExecInitExtraTupleSlot(estate, outerDesc,
                                                        ops);
 
    /*
     * detect whether we need only consider the first matching inner tuple
     */
    hjstate->js.single_match = (node->join.inner_unique ||
                                node->join.jointype == JOIN_SEMI);
 
    /* set up null tuples for outer joins, if needed */
    switch (node->join.jointype)
    {
        case JOIN_INNER:
        case JOIN_SEMI:
        case JOIN_RIGHT_SEMI:
            break;
        case JOIN_LEFT:
        case JOIN_ANTI:
            hjstate->hj_NullInnerTupleSlot =
                ExecInitNullTupleSlot(estate, innerDesc, &TTSOpsVirtual);
            break;
        case JOIN_RIGHT:
        case JOIN_RIGHT_ANTI:
            hjstate->hj_NullOuterTupleSlot =
                ExecInitNullTupleSlot(estate, outerDesc, &TTSOpsVirtual);
            break;
        case JOIN_FULL:
            hjstate->hj_NullOuterTupleSlot =
                ExecInitNullTupleSlot(estate, outerDesc, &TTSOpsVirtual);
            hjstate->hj_NullInnerTupleSlot =
                ExecInitNullTupleSlot(estate, innerDesc, &TTSOpsVirtual);
            break;
        default:
            elog(ERROR, "unrecognized join type: %d",
                 (int) node->join.jointype);
    }
 
    /*
     * now for some voodoo.  our temporary tuple slot is actually the result
     * tuple slot of the Hash node (which is our inner plan).  we can do this
     * because Hash nodes don't return tuples via ExecProcNode() -- instead
     * the hash join node uses ExecScanHashBucket() to get at the contents of
     * the hash table.  -cim 6/9/91
     */
    {
        HashState  *hashstate = (HashState *) innerPlanState(hjstate);
        TupleTableSlot *slot = hashstate->ps.ps_ResultTupleSlot;
 
        hjstate->hj_HashTupleSlot = slot;
    }
 
    /*
     * initialize child expressions
     */
    hjstate->js.ps.qual =
        ExecInitQual(node->join.plan.qual, (PlanState *) hjstate);
    hjstate->js.joinqual =
        ExecInitQual(node->join.joinqual, (PlanState *) hjstate);
    hjstate->hashclauses =
        ExecInitQual(node->hashclauses, (PlanState *) hjstate);
 
    /*
     * initialize hash-specific info
     */
    hjstate->hj_HashTable = NULL;
    hjstate->hj_FirstOuterTupleSlot = NULL;
 
    hjstate->hj_CurHashValue = 0;
    hjstate->hj_CurBucketNo = 0;
    hjstate->hj_CurSkewBucketNo = INVALID_SKEW_BUCKET_NO;
    hjstate->hj_CurTuple = NULL;
 
    hjstate->hj_OuterHashKeys = ExecInitExprList(node->hashkeys,
                                                 (PlanState *) hjstate);
    hjstate->hj_HashOperators = node->hashoperators;
    hjstate->hj_Collations = node->hashcollations;
 
    hjstate->hj_JoinState = HJ_BUILD_HASHTABLE;
    hjstate->hj_MatchedOuter = false;
    hjstate->hj_OuterNotEmpty = false;
 
    return hjstate;
}
 
/* ----------------------------------------------------------------
 *      ExecEndHashJoin
 *
 *      clean up routine for HashJoin node
 * ----------------------------------------------------------------
 */
void
ExecEndHashJoin(HashJoinState *node)
{
    /*
     * Free hash table
     */
    if (node->hj_HashTable)
    {
        ExecHashTableDestroy(node->hj_HashTable);
        node->hj_HashTable = NULL;
    }
 
    /*
     * clean up subtrees
     */
    ExecEndNode(outerPlanState(node));
    ExecEndNode(innerPlanState(node));
}
 
/*
 * ExecHashJoinOuterGetTuple
 *
 *      get the next outer tuple for a parallel oblivious hashjoin: either by
 *      executing the outer plan node in the first pass, or from the temp
 *      files for the hashjoin batches.
 *
 * Returns a null slot if no more outer tuples (within the current batch).
 *
 * On success, the tuple's hash value is stored at *hashvalue --- this is
 * either originally computed, or re-read from the temp file.
 */
static TupleTableSlot *
ExecHashJoinOuterGetTuple(PlanState *outerNode,
                          HashJoinState *hjstate,
                          uint32 *hashvalue)
{
    HashJoinTable hashtable = hjstate->hj_HashTable;
    int         curbatch = hashtable->curbatch;
    TupleTableSlot *slot;
 
    if (curbatch == 0)          /* if it is the first pass */
    {
        /*
         * Check to see if first outer tuple was already fetched by
         * ExecHashJoin() and not used yet.
         */
        slot = hjstate->hj_FirstOuterTupleSlot;
        if (!TupIsNull(slot))
            hjstate->hj_FirstOuterTupleSlot = NULL;
        else
            slot = ExecProcNode(outerNode);
 
        while (!TupIsNull(slot))
        {
            /*
             * We have to compute the tuple's hash value.
             */
            ExprContext *econtext = hjstate->js.ps.ps_ExprContext;
 
            econtext->ecxt_outertuple = slot;
            if (ExecHashGetHashValue(hashtable, econtext,
                                     hjstate->hj_OuterHashKeys,
                                     true,  /* outer tuple */
                                     HJ_FILL_OUTER(hjstate),
                                     hashvalue))
            {
                /* remember outer relation is not empty for possible rescan */
                hjstate->hj_OuterNotEmpty = true;
 
                return slot;
            }
 
            /*
             * That tuple couldn't match because of a NULL, so discard it and
             * continue with the next one.
             */
            slot = ExecProcNode(outerNode);
        }
    }
    else if (curbatch < hashtable->nbatch)
    {
        BufFile    *file = hashtable->outerBatchFile[curbatch];
 
        /*
         * In outer-join cases, we could get here even though the batch file
         * is empty.
         */
        if (file == NULL)
            return NULL;
 
        slot = ExecHashJoinGetSavedTuple(hjstate,
                                         file,
                                         hashvalue,
                                         hjstate->hj_OuterTupleSlot);
        if (!TupIsNull(slot))
            return slot;
    }
 
    /* End of this batch */
    return NULL;
}
 
/*
 * ExecHashJoinOuterGetTuple variant for the parallel case.
 */
static TupleTableSlot *
ExecParallelHashJoinOuterGetTuple(PlanState *outerNode,
                                  HashJoinState *hjstate,
                                  uint32 *hashvalue)
{
    HashJoinTable hashtable = hjstate->hj_HashTable;
    int         curbatch = hashtable->curbatch;
    TupleTableSlot *slot;
 
    /*
     * In the Parallel Hash case we only run the outer plan directly for
     * single-batch hash joins.  Otherwise we have to go to batch files, even
     * for batch 0.
     */
    if (curbatch == 0 && hashtable->nbatch == 1)
    {
        slot = ExecProcNode(outerNode);
 
        while (!TupIsNull(slot))
        {
            ExprContext *econtext = hjstate->js.ps.ps_ExprContext;
 
            econtext->ecxt_outertuple = slot;
            if (ExecHashGetHashValue(hashtable, econtext,
                                     hjstate->hj_OuterHashKeys,
                                     true,  /* outer tuple */
                                     HJ_FILL_OUTER(hjstate),
                                     hashvalue))
                return slot;
 
            /*
             * That tuple couldn't match because of a NULL, so discard it and
             * continue with the next one.
             */
            slot = ExecProcNode(outerNode);
        }
    }
    else if (curbatch < hashtable->nbatch)
    {
        MinimalTuple tuple;
 
        tuple = sts_parallel_scan_next(hashtable->batches[curbatch].outer_tuples,
                                       hashvalue);
        if (tuple != NULL)
        {
            ExecForceStoreMinimalTuple(tuple,
                                       hjstate->hj_OuterTupleSlot,
                                       false);
            slot = hjstate->hj_OuterTupleSlot;
            return slot;
        }
        else
            ExecClearTuple(hjstate->hj_OuterTupleSlot);
    }
 
    /* End of this batch */
    hashtable->batches[curbatch].outer_eof = true;
 
    return NULL;
}
 
/*
 * ExecHashJoinNewBatch
 *      switch to a new hashjoin batch
 *
 * Returns true if successful, false if there are no more batches.
 */
static bool
ExecHashJoinNewBatch(HashJoinState *hjstate)
{
    HashJoinTable hashtable = hjstate->hj_HashTable;
    int         nbatch;
    int         curbatch;
    BufFile    *innerFile;
    TupleTableSlot *slot;
    uint32      hashvalue;
 
    nbatch = hashtable->nbatch;
    curbatch = hashtable->curbatch;
 
    if (curbatch > 0)
    {
        /*
         * We no longer need the previous outer batch file; close it right
         * away to free disk space.
         */
        if (hashtable->outerBatchFile[curbatch])
            BufFileClose(hashtable->outerBatchFile[curbatch]);
        hashtable->outerBatchFile[curbatch] = NULL;
    }
    else                        /* we just finished the first batch */
    {
        /*
         * Reset some of the skew optimization state variables, since we no
         * longer need to consider skew tuples after the first batch. The
         * memory context reset we are about to do will release the skew
         * hashtable itself.
         */
        hashtable->skewEnabled = false;
        hashtable->skewBucket = NULL;
        hashtable->skewBucketNums = NULL;
        hashtable->nSkewBuckets = 0;
        hashtable->spaceUsedSkew = 0;
    }
 
    /*
     * We can always skip over any batches that are completely empty on both
     * sides.  We can sometimes skip over batches that are empty on only one
     * side, but there are exceptions:
     *
     * 1. In a left/full outer join, we have to process outer batches even if
     * the inner batch is empty.  Similarly, in a right/right-anti/full outer
     * join, we have to process inner batches even if the outer batch is
     * empty.
     *
     * 2. If we have increased nbatch since the initial estimate, we have to
     * scan inner batches since they might contain tuples that need to be
     * reassigned to later inner batches.
     *
     * 3. Similarly, if we have increased nbatch since starting the outer
     * scan, we have to rescan outer batches in case they contain tuples that
     * need to be reassigned.
     */
    curbatch++;
    while (curbatch < nbatch &&
           (hashtable->outerBatchFile[curbatch] == NULL ||
            hashtable->innerBatchFile[curbatch] == NULL))
    {
        if (hashtable->outerBatchFile[curbatch] &&
            HJ_FILL_OUTER(hjstate))
            break;              /* must process due to rule 1 */
        if (hashtable->innerBatchFile[curbatch] &&
            HJ_FILL_INNER(hjstate))
            break;              /* must process due to rule 1 */
        if (hashtable->innerBatchFile[curbatch] &&
            nbatch != hashtable->nbatch_original)
            break;              /* must process due to rule 2 */
        if (hashtable->outerBatchFile[curbatch] &&
            nbatch != hashtable->nbatch_outstart)
            break;              /* must process due to rule 3 */
        /* We can ignore this batch. */
        /* Release associated temp files right away. */
        if (hashtable->innerBatchFile[curbatch])
            BufFileClose(hashtable->innerBatchFile[curbatch]);
        hashtable->innerBatchFile[curbatch] = NULL;
        if (hashtable->outerBatchFile[curbatch])
            BufFileClose(hashtable->outerBatchFile[curbatch]);
        hashtable->outerBatchFile[curbatch] = NULL;
        curbatch++;
    }
 
    if (curbatch >= nbatch)
        return false;           /* no more batches */
 
    hashtable->curbatch = curbatch;
 
    /*
     * Reload the hash table with the new inner batch (which could be empty)
     */
    ExecHashTableReset(hashtable);
 
    innerFile = hashtable->innerBatchFile[curbatch];
 
    if (innerFile != NULL)
    {
        if (BufFileSeek(innerFile, 0, 0, SEEK_SET))
            ereport(ERROR,
                    (errcode_for_file_access(),
                     errmsg("could not rewind hash-join temporary file")));
 
        while ((slot = ExecHashJoinGetSavedTuple(hjstate,
                                                 innerFile,
                                                 &hashvalue,
                                                 hjstate->hj_HashTupleSlot)))
        {
            /*
             * NOTE: some tuples may be sent to future batches.  Also, it is
             * possible for hashtable->nbatch to be increased here!
             */
            ExecHashTableInsert(hashtable, slot, hashvalue);
        }
 
        /*
         * after we build the hash table, the inner batch file is no longer
         * needed
         */
        BufFileClose(innerFile);
        hashtable->innerBatchFile[curbatch] = NULL;
    }
 
    /*
     * Rewind outer batch file (if present), so that we can start reading it.
     */
    if (hashtable->outerBatchFile[curbatch] != NULL)
    {
        if (BufFileSeek(hashtable->outerBatchFile[curbatch], 0, 0, SEEK_SET))
            ereport(ERROR,
                    (errcode_for_file_access(),
                     errmsg("could not rewind hash-join temporary file")));
    }
 
    return true;
}
 
/*
 * Choose a batch to work on, and attach to it.  Returns true if successful,
 * false if there are no more batches.
 */
static bool
ExecParallelHashJoinNewBatch(HashJoinState *hjstate)
{
    HashJoinTable hashtable = hjstate->hj_HashTable;
    int         start_batchno;
    int         batchno;
 
    /*
     * If we were already attached to a batch, remember not to bother checking
     * it again, and detach from it (possibly freeing the hash table if we are
     * last to detach).
     */
    if (hashtable->curbatch >= 0)
    {
        hashtable->batches[hashtable->curbatch].done = true;
        ExecHashTableDetachBatch(hashtable);
    }
 
    /*
     * Search for a batch that isn't done.  We use an atomic counter to start
     * our search at a different batch in every participant when there are
     * more batches than participants.
     */
    batchno = start_batchno =
        pg_atomic_fetch_add_u32(&hashtable->parallel_state->distributor, 1) %
        hashtable->nbatch;
    do
    {
        uint32      hashvalue;
        MinimalTuple tuple;
        TupleTableSlot *slot;
 
        if (!hashtable->batches[batchno].done)
        {
            SharedTuplestoreAccessor *inner_tuples;
            Barrier    *batch_barrier =
                &hashtable->batches[batchno].shared->batch_barrier;
 
            switch (BarrierAttach(batch_barrier))
            {
                case PHJ_BATCH_ELECT:
 
                    /* One backend allocates the hash table. */
                    if (BarrierArriveAndWait(batch_barrier,
                                             WAIT_EVENT_HASH_BATCH_ELECT))
                        ExecParallelHashTableAlloc(hashtable, batchno);
                    /* Fall through. */
 
                case PHJ_BATCH_ALLOCATE:
                    /* Wait for allocation to complete. */
                    BarrierArriveAndWait(batch_barrier,
                                         WAIT_EVENT_HASH_BATCH_ALLOCATE);
                    /* Fall through. */
 
                case PHJ_BATCH_LOAD:
                    /* Start (or join in) loading tuples. */
                    ExecParallelHashTableSetCurrentBatch(hashtable, batchno);
                    inner_tuples = hashtable->batches[batchno].inner_tuples;
                    sts_begin_parallel_scan(inner_tuples);
                    while ((tuple = sts_parallel_scan_next(inner_tuples,
                                                           &hashvalue)))
                    {
                        ExecForceStoreMinimalTuple(tuple,
                                                   hjstate->hj_HashTupleSlot,
                                                   false);
                        slot = hjstate->hj_HashTupleSlot;
                        ExecParallelHashTableInsertCurrentBatch(hashtable, slot,
                                                                hashvalue);
                    }
                    sts_end_parallel_scan(inner_tuples);
                    BarrierArriveAndWait(batch_barrier,
                                         WAIT_EVENT_HASH_BATCH_LOAD);
                    /* Fall through. */
 
                case PHJ_BATCH_PROBE:
 
                    /*
                     * This batch is ready to probe.  Return control to
                     * caller. We stay attached to batch_barrier so that the
                     * hash table stays alive until everyone's finished
                     * probing it, but no participant is allowed to wait at
                     * this barrier again (or else a deadlock could occur).
                     * All attached participants must eventually detach from
                     * the barrier and one worker must advance the phase so
                     * that the final phase is reached.
                     */
                    ExecParallelHashTableSetCurrentBatch(hashtable, batchno);
                    sts_begin_parallel_scan(hashtable->batches[batchno].outer_tuples);
 
                    return true;
                case PHJ_BATCH_SCAN:
 
                    /*
                     * In principle, we could help scan for unmatched tuples,
                     * since that phase is already underway (the thing we
                     * can't do under current deadlock-avoidance rules is wait
                     * for others to arrive at PHJ_BATCH_SCAN, because
                     * PHJ_BATCH_PROBE emits tuples, but in this case we just
                     * got here without waiting).  That is not yet done.  For
                     * now, we just detach and go around again.  We have to
                     * use ExecHashTableDetachBatch() because there's a small
                     * chance we'll be the last to detach, and then we're
                     * responsible for freeing memory.
                     */
                    ExecParallelHashTableSetCurrentBatch(hashtable, batchno);
                    hashtable->batches[batchno].done = true;
                    ExecHashTableDetachBatch(hashtable);
                    break;
 
                case PHJ_BATCH_FREE:
 
                    /*
                     * Already done.  Detach and go around again (if any
                     * remain).
                     */
                    BarrierDetach(batch_barrier);
                    hashtable->batches[batchno].done = true;
                    hashtable->curbatch = -1;
                    break;
 
                default:
                    elog(ERROR, "unexpected batch phase %d",
                         BarrierPhase(batch_barrier));
            }
        }
        batchno = (batchno + 1) % hashtable->nbatch;
    } while (batchno != start_batchno);
 
    return false;
}
 
/*
 * ExecHashJoinSaveTuple
 *      save a tuple to a batch file.
 *
 * The data recorded in the file for each tuple is its hash value,
 * then the tuple in MinimalTuple format.
 *
 * fileptr points to a batch file in one of the hashtable arrays.
 *
 * The batch files (and their buffers) are allocated in the spill context
 * created for the hashtable.
 */
void
ExecHashJoinSaveTuple(MinimalTuple tuple, uint32 hashvalue,
                      BufFile **fileptr, HashJoinTable hashtable)
{
    BufFile    *file = *fileptr;
 
    /*
     * The batch file is lazily created. If this is the first tuple written to
     * this batch, the batch file is created and its buffer is allocated in
     * the spillCxt context, NOT in the batchCxt.
     *
     * During the build phase, buffered files are created for inner batches.
     * Each batch's buffered file is closed (and its buffer freed) after the
     * batch is loaded into memory during the outer side scan. Therefore, it
     * is necessary to allocate the batch file buffer in a memory context
     * which outlives the batch itself.
     *
     * Also, we use spillCxt instead of hashCxt for a better accounting of the
     * spilling memory consumption.
     */
    if (file == NULL)
    {
        MemoryContext oldctx = MemoryContextSwitchTo(hashtable->spillCxt);
 
        file = BufFileCreateTemp(false);
        *fileptr = file;
 
        MemoryContextSwitchTo(oldctx);
    }
 
    BufFileWrite(file, &hashvalue, sizeof(uint32));
    BufFileWrite(file, tuple, tuple->t_len);
}
 
/*
 * ExecHashJoinGetSavedTuple
 *      read the next tuple from a batch file.  Return NULL if no more.
 *
 * On success, *hashvalue is set to the tuple's hash value, and the tuple
 * itself is stored in the given slot.
 */
static TupleTableSlot *
ExecHashJoinGetSavedTuple(HashJoinState *hjstate,
                          BufFile *file,
                          uint32 *hashvalue,
                          TupleTableSlot *tupleSlot)
{
    uint32      header[2];
    size_t      nread;
    MinimalTuple tuple;
 
    /*
     * We check for interrupts here because this is typically taken as an
     * alternative code path to an ExecProcNode() call, which would include
     * such a check.
     */
    CHECK_FOR_INTERRUPTS();
 
    /*
     * Since both the hash value and the MinimalTuple length word are uint32,
     * we can read them both in one BufFileRead() call without any type
     * cheating.
     */
    nread = BufFileReadMaybeEOF(file, header, sizeof(header), true);
    if (nread == 0)             /* end of file */
    {
        ExecClearTuple(tupleSlot);
        return NULL;
    }
    *hashvalue = header[0];
    tuple = (MinimalTuple) palloc(header[1]);
    tuple->t_len = header[1];
    BufFileReadExact(file,
                     (char *) tuple + sizeof(uint32),
                     header[1] - sizeof(uint32));
    ExecForceStoreMinimalTuple(tuple, tupleSlot, true);
    return tupleSlot;
}
 
 
void
ExecReScanHashJoin(HashJoinState *node)
{
    PlanState  *outerPlan = outerPlanState(node);
    PlanState  *innerPlan = innerPlanState(node);
 
    /*
     * In a multi-batch join, we currently have to do rescans the hard way,
     * primarily because batch temp files may have already been released. But
     * if it's a single-batch join, and there is no parameter change for the
     * inner subnode, then we can just re-use the existing hash table without
     * rebuilding it.
     */
    if (node->hj_HashTable != NULL)
    {
        if (node->hj_HashTable->nbatch == 1 &&
            innerPlan->chgParam == NULL)
        {
            /*
             * Okay to reuse the hash table; needn't rescan inner, either.
             *
             * However, if it's a right/right-anti/full join, we'd better
             * reset the inner-tuple match flags contained in the table.
             */
            if (HJ_FILL_INNER(node))
                ExecHashTableResetMatchFlags(node->hj_HashTable);
 
            /*
             * Also, we need to reset our state about the emptiness of the
             * outer relation, so that the new scan of the outer will update
             * it correctly if it turns out to be empty this time. (There's no
             * harm in clearing it now because ExecHashJoin won't need the
             * info.  In the other cases, where the hash table doesn't exist
             * or we are destroying it, we leave this state alone because
             * ExecHashJoin will need it the first time through.)
             */
            node->hj_OuterNotEmpty = false;
 
            /* ExecHashJoin can skip the BUILD_HASHTABLE step */
            node->hj_JoinState = HJ_NEED_NEW_OUTER;
        }
        else
        {
            /* must destroy and rebuild hash table */
            HashState  *hashNode = castNode(HashState, innerPlan);
 
            Assert(hashNode->hashtable == node->hj_HashTable);
            /* accumulate stats from old hash table, if wanted */
            /* (this should match ExecShutdownHash) */
            if (hashNode->ps.instrument && !hashNode->hinstrument)
                hashNode->hinstrument = (HashInstrumentation *)
                    palloc0(sizeof(HashInstrumentation));
            if (hashNode->hinstrument)
                ExecHashAccumInstrumentation(hashNode->hinstrument,
                                             hashNode->hashtable);
            /* for safety, be sure to clear child plan node's pointer too */
            hashNode->hashtable = NULL;
 
            ExecHashTableDestroy(node->hj_HashTable);
            node->hj_HashTable = NULL;
            node->hj_JoinState = HJ_BUILD_HASHTABLE;
 
            /*
             * if chgParam of subnode is not null then plan will be re-scanned
             * by first ExecProcNode.
             */
            if (innerPlan->chgParam == NULL)
                ExecReScan(innerPlan);
        }
    }
 
    /* Always reset intra-tuple state */
    node->hj_CurHashValue = 0;
    node->hj_CurBucketNo = 0;
    node->hj_CurSkewBucketNo = INVALID_SKEW_BUCKET_NO;
    node->hj_CurTuple = NULL;
 
    node->hj_MatchedOuter = false;
    node->hj_FirstOuterTupleSlot = NULL;
 
    /*
     * if chgParam of subnode is not null then plan will be re-scanned by
     * first ExecProcNode.
     */
    if (outerPlan->chgParam == NULL)
        ExecReScan(outerPlan);
}
 
void
ExecShutdownHashJoin(HashJoinState *node)
{
    if (node->hj_HashTable)
    {
        /*
         * Detach from shared state before DSM memory goes away.  This makes
         * sure that we don't have any pointers into DSM memory by the time
         * ExecEndHashJoin runs.
         */
        ExecHashTableDetachBatch(node->hj_HashTable);
        ExecHashTableDetach(node->hj_HashTable);
    }
}
 
static void
ExecParallelHashJoinPartitionOuter(HashJoinState *hjstate)
{
    PlanState  *outerState = outerPlanState(hjstate);
    ExprContext *econtext = hjstate->js.ps.ps_ExprContext;
    HashJoinTable hashtable = hjstate->hj_HashTable;
    TupleTableSlot *slot;
    uint32      hashvalue;
    int         i;
 
    Assert(hjstate->hj_FirstOuterTupleSlot == NULL);
 
    /* Execute outer plan, writing all tuples to shared tuplestores. */
    for (;;)
    {
        slot = ExecProcNode(outerState);
        if (TupIsNull(slot))
            break;
        econtext->ecxt_outertuple = slot;
        if (ExecHashGetHashValue(hashtable, econtext,
                                 hjstate->hj_OuterHashKeys,
                                 true,  /* outer tuple */
                                 HJ_FILL_OUTER(hjstate),
                                 &hashvalue))
        {
            int         batchno;
            int         bucketno;
            bool        shouldFree;
            MinimalTuple mintup = ExecFetchSlotMinimalTuple(slot, &shouldFree);
 
            ExecHashGetBucketAndBatch(hashtable, hashvalue, &bucketno,
                                      &batchno);
            sts_puttuple(hashtable->batches[batchno].outer_tuples,
                         &hashvalue, mintup);
 
            if (shouldFree)
                heap_free_minimal_tuple(mintup);
        }
        CHECK_FOR_INTERRUPTS();
    }
 
    /* Make sure all outer partitions are readable by any backend. */
    for (i = 0; i < hashtable->nbatch; ++i)
        sts_end_write(hashtable->batches[i].outer_tuples);
}
 
void
ExecHashJoinEstimate(HashJoinState *state, ParallelContext *pcxt)
{
    shm_toc_estimate_chunk(&pcxt->estimator, sizeof(ParallelHashJoinState));
    shm_toc_estimate_keys(&pcxt->estimator, 1);
}
 
void
ExecHashJoinInitializeDSM(HashJoinState *state, ParallelContext *pcxt)
{
    int         plan_node_id = state->js.ps.plan->plan_node_id;
    HashState  *hashNode;
    ParallelHashJoinState *pstate;
 
    /*
     * Disable shared hash table mode if we failed to create a real DSM
     * segment, because that means that we don't have a DSA area to work with.
     */
    if (pcxt->seg == NULL)
        return;
 
    ExecSetExecProcNode(&state->js.ps, ExecParallelHashJoin);
 
    /*
     * Set up the state needed to coordinate access to the shared hash
     * table(s), using the plan node ID as the toc key.
     */
    pstate = shm_toc_allocate(pcxt->toc, sizeof(ParallelHashJoinState));
    shm_toc_insert(pcxt->toc, plan_node_id, pstate);
 
    /*
     * Set up the shared hash join state with no batches initially.
     * ExecHashTableCreate() will prepare at least one later and set nbatch
     * and space_allowed.
     */
    pstate->nbatch = 0;
    pstate->space_allowed = 0;
    pstate->batches = InvalidDsaPointer;
    pstate->old_batches = InvalidDsaPointer;
    pstate->nbuckets = 0;
    pstate->growth = PHJ_GROWTH_OK;
    pstate->chunk_work_queue = InvalidDsaPointer;
    pg_atomic_init_u32(&pstate->distributor, 0);
    pstate->nparticipants = pcxt->nworkers + 1;
    pstate->total_tuples = 0;
    LWLockInitialize(&pstate->lock,
                     LWTRANCHE_PARALLEL_HASH_JOIN);
    BarrierInit(&pstate->build_barrier, 0);
    BarrierInit(&pstate->grow_batches_barrier, 0);
    BarrierInit(&pstate->grow_buckets_barrier, 0);
 
    /* Set up the space we'll use for shared temporary files. */
    SharedFileSetInit(&pstate->fileset, pcxt->seg);
 
    /* Initialize the shared state in the hash node. */
    hashNode = (HashState *) innerPlanState(state);
    hashNode->parallel_state = pstate;
}
 
/* ----------------------------------------------------------------
 *      ExecHashJoinReInitializeDSM
 *
 *      Reset shared state before beginning a fresh scan.
 * ----------------------------------------------------------------
 */
void
ExecHashJoinReInitializeDSM(HashJoinState *state, ParallelContext *pcxt)
{
    int         plan_node_id = state->js.ps.plan->plan_node_id;
    ParallelHashJoinState *pstate =
        shm_toc_lookup(pcxt->toc, plan_node_id, false);
 
    /*
     * It would be possible to reuse the shared hash table in single-batch
     * cases by resetting and then fast-forwarding build_barrier to
     * PHJ_BUILD_FREE and batch 0's batch_barrier to PHJ_BATCH_PROBE, but
     * currently shared hash tables are already freed by now (by the last
     * participant to detach from the batch).  We could consider keeping it
     * around for single-batch joins.  We'd also need to adjust
     * finalize_plan() so that it doesn't record a dummy dependency for
     * Parallel Hash nodes, preventing the rescan optimization.  For now we
     * don't try.
     */
 
    /* Detach, freeing any remaining shared memory. */
    if (state->hj_HashTable != NULL)
    {
        ExecHashTableDetachBatch(state->hj_HashTable);
        ExecHashTableDetach(state->hj_HashTable);
    }
 
    /* Clear any shared batch files. */
    SharedFileSetDeleteAll(&pstate->fileset);
 
    /* Reset build_barrier to PHJ_BUILD_ELECT so we can go around again. */
    BarrierInit(&pstate->build_barrier, 0);
}
 
void
ExecHashJoinInitializeWorker(HashJoinState *state,
                             ParallelWorkerContext *pwcxt)
{
    HashState  *hashNode;
    int         plan_node_id = state->js.ps.plan->plan_node_id;
    ParallelHashJoinState *pstate =
        shm_toc_lookup(pwcxt->toc, plan_node_id, false);
 
    /* Attach to the space for shared temporary files. */
    SharedFileSetAttach(&pstate->fileset, pwcxt->seg);
 
    /* Attach to the shared state in the hash node. */
    hashNode = (HashState *) innerPlanState(state);
    hashNode->parallel_state = pstate;
 
    ExecSetExecProcNode(&state->js.ps, ExecParallelHashJoin);
}