postgresql/src/backend/executor/nodeHashjoin.c

/*-------------------------------------------------------------------------
 *
 * nodeHashjoin.c
 *	  Routines to handle hash join nodes
 *
 * Portions Copyright (c) 1996-2023, 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 "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 *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;
					}
				}

				/*
				 * 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), 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;
					}

					/*
					 * In a right-antijoin, we never return a matched tuple.
					 * And 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 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/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:
			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;
	}

	/*
	 * 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 */
	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 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);
}