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Diffstat (limited to 'src/backend/executor/nodeHashjoin.c')
| -rw-r--r-- | src/backend/executor/nodeHashjoin.c | 1551 |
1 files changed, 1551 insertions, 0 deletions
diff --git a/src/backend/executor/nodeHashjoin.c b/src/backend/executor/nodeHashjoin.c new file mode 100644 index 0000000..510bdd3 --- /dev/null +++ b/src/backend/executor/nodeHashjoin.c @@ -0,0 +1,1551 @@ +/*------------------------------------------------------------------------- + * + * nodeHashjoin.c + * Routines to handle hash join nodes + * + * Portions Copyright (c) 1996-2021, PostgreSQL Global Development Group + * Portions Copyright (c) 1994, Regents of the University of California + * + * + * IDENTIFICATION + * src/backend/executor/nodeHashjoin.c + * + * 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: + * + * PHJ_BUILD_ELECTING -- initial state + * PHJ_BUILD_ALLOCATING -- one sets up the batches and table 0 + * PHJ_BUILD_HASHING_INNER -- all hash the inner rel + * PHJ_BUILD_HASHING_OUTER -- (multi-batch only) all hash the outer + * PHJ_BUILD_DONE -- building done, probing can begin + * + * While in the phase PHJ_BUILD_HASHING_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_ELECTING -- initial state + * PHJ_GROW_BATCHES_ALLOCATING -- one allocates new batches + * PHJ_GROW_BATCHES_REPARTITIONING -- all repartition + * PHJ_GROW_BATCHES_FINISHING -- one cleans up, detects skew + * + * PHJ_GROW_BUCKETS_ELECTING -- initial state + * PHJ_GROW_BUCKETS_ALLOCATING -- one allocates new buckets + * PHJ_GROW_BUCKETS_REINSERTING -- 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_HASHING_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_DONE 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_ELECTING -- initial state + * PHJ_BATCH_ALLOCATING -- one allocates buckets + * PHJ_BATCH_LOADING -- all load the hash table from disk + * PHJ_BATCH_PROBING -- all probe + * PHJ_BATCH_DONE -- end + * + * Batch 0 is a special case, because it starts out in phase + * PHJ_BATCH_PROBING; populating batch 0's hash table is done during + * PHJ_BUILD_HASHING_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 + * already arrived. Practically, that means that we never return a tuple + * while attached to a barrier, unless the barrier has reached its final + * state. In the slightly special case of the per-batch barrier, we return + * tuples while in PHJ_BATCH_PROBING phase, but that's OK because we use + * BarrierArriveAndDetach() to advance it to PHJ_BATCH_DONE without waiting. + * + *------------------------------------------------------------------------- + */ + +#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 "pgstat.h" +#include "utils/memutils.h" +#include "utils/sharedtuplestore.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 *node); + + +/* ---------------------------------------------------------------- + * 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/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)) + 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 = ¶llel_state->build_barrier; + Assert(BarrierPhase(build_barrier) == PHJ_BUILD_HASHING_OUTER || + BarrierPhase(build_barrier) == PHJ_BUILD_DONE); + if (BarrierPhase(build_barrier) == PHJ_BUILD_HASHING_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); + } + Assert(BarrierPhase(build_barrier) == PHJ_BUILD_DONE); + + /* Each backend should now select a batch to work on. */ + 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 */ + 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]); + + 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; + } + } + + /* + * 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; + + if (parallel) + { + /* + * Full/right outer joins are currently not supported + * for parallel joins, so we don't need to set the + * match bit. Experiments show that it's worth + * avoiding the shared memory traffic on large + * systems. + */ + Assert(!HJ_FILL_INNER(node)); + } + else + { + /* + * This is really only needed if HJ_FILL_INNER(node), + * but we'll avoid the branch and just set it always. + */ + 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 join to the first matching inner + * tuple, then consider returning this one, but after that + * continue with next outer tuple. + */ + if (node->js.single_match) + node->hj_JoinState = HJ_NEED_NEW_OUTER; + + 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/full join, + * so any unmatched inner tuples in the hashtable have to be + * emitted before we continue to the next batch. + */ + if (!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: + break; + case JOIN_LEFT: + case JOIN_ANTI: + hjstate->hj_NullInnerTupleSlot = + ExecInitNullTupleSlot(estate, innerDesc, &TTSOpsVirtual); + break; + case JOIN_RIGHT: + 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; + } + + /* + * Free the exprcontext + */ + ExecFreeExprContext(&node->js.ps); + + /* + * clean out the tuple table + */ + ExecClearTuple(node->js.ps.ps_ResultTupleSlot); + ExecClearTuple(node->hj_OuterTupleSlot); + ExecClearTuple(node->hj_HashTupleSlot); + + /* + * 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 */ + 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/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, 0L, 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, 0L, 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 started up so late that the batch tracking array has been freed + * already by ExecHashTableDetach(), then we are finished. See also + * ExecParallelHashEnsureBatchAccessors(). + */ + if (hashtable->batches == NULL) + return false; + + /* + * 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_ELECTING: + + /* One backend allocates the hash table. */ + if (BarrierArriveAndWait(batch_barrier, + WAIT_EVENT_HASH_BATCH_ELECT)) + ExecParallelHashTableAlloc(hashtable, batchno); + /* Fall through. */ + + case PHJ_BATCH_ALLOCATING: + /* Wait for allocation to complete. */ + BarrierArriveAndWait(batch_barrier, + WAIT_EVENT_HASH_BATCH_ALLOCATE); + /* Fall through. */ + + case PHJ_BATCH_LOADING: + /* 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_PROBING: + + /* + * 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 call + * BarrierArriveAndDetach() so that the final phase + * PHJ_BATCH_DONE can be reached. + */ + ExecParallelHashTableSetCurrentBatch(hashtable, batchno); + sts_begin_parallel_scan(hashtable->batches[batchno].outer_tuples); + return true; + + case PHJ_BATCH_DONE: + + /* + * 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. + * + * Note: it is important always to call this in the regular executor + * context, not in a shorter-lived context; else the temp file buffers + * will get messed up. + */ +void +ExecHashJoinSaveTuple(MinimalTuple tuple, uint32 hashvalue, + BufFile **fileptr) +{ + BufFile *file = *fileptr; + + if (file == NULL) + { + /* First write to this batch file, so open it. */ + file = BufFileCreateTemp(false); + *fileptr = file; + } + + BufFileWrite(file, (void *) &hashvalue, sizeof(uint32)); + BufFileWrite(file, (void *) 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 = BufFileRead(file, (void *) header, sizeof(header)); + if (nread == 0) /* end of file */ + { + ExecClearTuple(tupleSlot); + return NULL; + } + if (nread != sizeof(header)) + ereport(ERROR, + (errcode_for_file_access(), + errmsg("could not read from hash-join temporary file: read only %zu of %zu bytes", + nread, sizeof(header)))); + *hashvalue = header[0]; + tuple = (MinimalTuple) palloc(header[1]); + tuple->t_len = header[1]; + nread = BufFileRead(file, + (void *) ((char *) tuple + sizeof(uint32)), + header[1] - sizeof(uint32)); + if (nread != header[1] - sizeof(uint32)) + ereport(ERROR, + (errcode_for_file_access(), + errmsg("could not read from hash-join temporary file: read only %zu of %zu bytes", + nread, header[1] - sizeof(uint32)))); + ExecForceStoreMinimalTuple(tuple, tupleSlot, true); + return tupleSlot; +} + + +void +ExecReScanHashJoin(HashJoinState *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 && + node->js.ps.righttree->chgParam == NULL) + { + /* + * Okay to reuse the hash table; needn't rescan inner, either. + * + * However, if it's a right/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, innerPlanState(node)); + + 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 (node->js.ps.righttree->chgParam == NULL) + ExecReScan(node->js.ps.righttree); + } + } + + /* 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 (node->js.ps.lefttree->chgParam == NULL) + ExecReScan(node->js.ps.lefttree); +} + +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 *cxt) +{ + int plan_node_id = state->js.ps.plan->plan_node_id; + ParallelHashJoinState *pstate = + shm_toc_lookup(cxt->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_DONE and batch 0's batch_barrier to PHJ_BATCH_PROBING, 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_ELECTING 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); +} |