Adding upstream version 15.4.upstream/15.4upstream

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

1 files changed, 291 insertions, 0 deletions

diff --git a/src/include/utils/tuplesort.h b/src/include/utils/tuplesort.h
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+/*-------------------------------------------------------------------------
+ *
+ * tuplesort.h
+ *	  Generalized tuple sorting routines.
+ *
+ * This module handles sorting of heap tuples, index tuples, or single
+ * Datums (and could easily support other kinds of sortable objects,
+ * if necessary).  It works efficiently for both small and large amounts
+ * of data.  Small amounts are sorted in-memory using qsort().  Large
+ * amounts are sorted using temporary files and a standard external sort
+ * algorithm.  Parallel sorts use a variant of this external sort
+ * algorithm, and are typically only used for large amounts of data.
+ *
+ * Portions Copyright (c) 1996-2022, PostgreSQL Global Development Group
+ * Portions Copyright (c) 1994, Regents of the University of California
+ *
+ * src/include/utils/tuplesort.h
+ *
+ *-------------------------------------------------------------------------
+ */
+#ifndef TUPLESORT_H
+#define TUPLESORT_H
+
+#include "access/itup.h"
+#include "executor/tuptable.h"
+#include "storage/dsm.h"
+#include "utils/relcache.h"
+
+
+/*
+ * Tuplesortstate and Sharedsort are opaque types whose details are not
+ * known outside tuplesort.c.
+ */
+typedef struct Tuplesortstate Tuplesortstate;
+typedef struct Sharedsort Sharedsort;
+
+/*
+ * Tuplesort parallel coordination state, allocated by each participant in
+ * local memory.  Participant caller initializes everything.  See usage notes
+ * below.
+ */
+typedef struct SortCoordinateData
+{
+	/* Worker process?  If not, must be leader. */
+	bool		isWorker;
+
+	/*
+	 * Leader-process-passed number of participants known launched (workers
+	 * set this to -1).  Includes state within leader needed for it to
+	 * participate as a worker, if any.
+	 */
+	int			nParticipants;
+
+	/* Private opaque state (points to shared memory) */
+	Sharedsort *sharedsort;
+}			SortCoordinateData;
+
+typedef struct SortCoordinateData *SortCoordinate;
+
+/*
+ * Data structures for reporting sort statistics.  Note that
+ * TuplesortInstrumentation can't contain any pointers because we
+ * sometimes put it in shared memory.
+ *
+ * The parallel-sort infrastructure relies on having a zero TuplesortMethod
+ * to indicate that a worker never did anything, so we assign zero to
+ * SORT_TYPE_STILL_IN_PROGRESS.  The other values of this enum can be
+ * OR'ed together to represent a situation where different workers used
+ * different methods, so we need a separate bit for each one.  Keep the
+ * NUM_TUPLESORTMETHODS constant in sync with the number of bits!
+ */
+typedef enum
+{
+	SORT_TYPE_STILL_IN_PROGRESS = 0,
+	SORT_TYPE_TOP_N_HEAPSORT = 1 << 0,
+	SORT_TYPE_QUICKSORT = 1 << 1,
+	SORT_TYPE_EXTERNAL_SORT = 1 << 2,
+	SORT_TYPE_EXTERNAL_MERGE = 1 << 3
+} TuplesortMethod;
+
+#define NUM_TUPLESORTMETHODS 4
+
+typedef enum
+{
+	SORT_SPACE_TYPE_DISK,
+	SORT_SPACE_TYPE_MEMORY
+} TuplesortSpaceType;
+
+/* Bitwise option flags for tuple sorts */
+#define TUPLESORT_NONE					0
+
+/* specifies whether non-sequential access to the sort result is required */
+#define	TUPLESORT_RANDOMACCESS			(1 << 0)
+
+/* specifies if the tuplesort is able to support bounded sorts */
+#define TUPLESORT_ALLOWBOUNDED			(1 << 1)
+
+typedef struct TuplesortInstrumentation
+{
+	TuplesortMethod sortMethod; /* sort algorithm used */
+	TuplesortSpaceType spaceType;	/* type of space spaceUsed represents */
+	int64		spaceUsed;		/* space consumption, in kB */
+} TuplesortInstrumentation;
+
+
+/*
+ * We provide multiple interfaces to what is essentially the same code,
+ * since different callers have different data to be sorted and want to
+ * specify the sort key information differently.  There are two APIs for
+ * sorting HeapTuples and two more for sorting IndexTuples.  Yet another
+ * API supports sorting bare Datums.
+ *
+ * Serial sort callers should pass NULL for their coordinate argument.
+ *
+ * The "heap" API actually stores/sorts MinimalTuples, which means it doesn't
+ * preserve the system columns (tuple identity and transaction visibility
+ * info).  The sort keys are specified by column numbers within the tuples
+ * and sort operator OIDs.  We save some cycles by passing and returning the
+ * tuples in TupleTableSlots, rather than forming actual HeapTuples (which'd
+ * have to be converted to MinimalTuples).  This API works well for sorts
+ * executed as parts of plan trees.
+ *
+ * The "cluster" API stores/sorts full HeapTuples including all visibility
+ * info. The sort keys are specified by reference to a btree index that is
+ * defined on the relation to be sorted.  Note that putheaptuple/getheaptuple
+ * go with this API, not the "begin_heap" one!
+ *
+ * The "index_btree" API stores/sorts IndexTuples (preserving all their
+ * header fields).  The sort keys are specified by a btree index definition.
+ *
+ * The "index_hash" API is similar to index_btree, but the tuples are
+ * actually sorted by their hash codes not the raw data.
+ *
+ * Parallel sort callers are required to coordinate multiple tuplesort states
+ * in a leader process and one or more worker processes.  The leader process
+ * must launch workers, and have each perform an independent "partial"
+ * tuplesort, typically fed by the parallel heap interface.  The leader later
+ * produces the final output (internally, it merges runs output by workers).
+ *
+ * Callers must do the following to perform a sort in parallel using multiple
+ * worker processes:
+ *
+ * 1. Request tuplesort-private shared memory for n workers.  Use
+ *    tuplesort_estimate_shared() to get the required size.
+ * 2. Have leader process initialize allocated shared memory using
+ *    tuplesort_initialize_shared().  Launch workers.
+ * 3. Initialize a coordinate argument within both the leader process, and
+ *    for each worker process.  This has a pointer to the shared
+ *    tuplesort-private structure, as well as some caller-initialized fields.
+ *    Leader's coordinate argument reliably indicates number of workers
+ *    launched (this is unused by workers).
+ * 4. Begin a tuplesort using some appropriate tuplesort_begin* routine,
+ *    (passing the coordinate argument) within each worker.  The workMem
+ *    arguments need not be identical.  All other arguments should match
+ *    exactly, though.
+ * 5. tuplesort_attach_shared() should be called by all workers.  Feed tuples
+ *    to each worker, and call tuplesort_performsort() within each when input
+ *    is exhausted.
+ * 6. Call tuplesort_end() in each worker process.  Worker processes can shut
+ *    down once tuplesort_end() returns.
+ * 7. Begin a tuplesort in the leader using the same tuplesort_begin*
+ *    routine, passing a leader-appropriate coordinate argument (this can
+ *    happen as early as during step 3, actually, since we only need to know
+ *    the number of workers successfully launched).  The leader must now wait
+ *    for workers to finish.  Caller must use own mechanism for ensuring that
+ *    next step isn't reached until all workers have called and returned from
+ *    tuplesort_performsort().  (Note that it's okay if workers have already
+ *    also called tuplesort_end() by then.)
+ * 8. Call tuplesort_performsort() in leader.  Consume output using the
+ *    appropriate tuplesort_get* routine.  Leader can skip this step if
+ *    tuplesort turns out to be unnecessary.
+ * 9. Call tuplesort_end() in leader.
+ *
+ * This division of labor assumes nothing about how input tuples are produced,
+ * but does require that caller combine the state of multiple tuplesorts for
+ * any purpose other than producing the final output.  For example, callers
+ * must consider that tuplesort_get_stats() reports on only one worker's role
+ * in a sort (or the leader's role), and not statistics for the sort as a
+ * whole.
+ *
+ * Note that callers may use the leader process to sort runs as if it was an
+ * independent worker process (prior to the process performing a leader sort
+ * to produce the final sorted output).  Doing so only requires a second
+ * "partial" tuplesort within the leader process, initialized like that of a
+ * worker process.  The steps above don't touch on this directly.  The only
+ * difference is that the tuplesort_attach_shared() call is never needed within
+ * leader process, because the backend as a whole holds the shared fileset
+ * reference.  A worker Tuplesortstate in leader is expected to do exactly the
+ * same amount of total initial processing work as a worker process
+ * Tuplesortstate, since the leader process has nothing else to do before
+ * workers finish.
+ *
+ * Note that only a very small amount of memory will be allocated prior to
+ * the leader state first consuming input, and that workers will free the
+ * vast majority of their memory upon returning from tuplesort_performsort().
+ * Callers can rely on this to arrange for memory to be used in a way that
+ * respects a workMem-style budget across an entire parallel sort operation.
+ *
+ * Callers are responsible for parallel safety in general.  However, they
+ * can at least rely on there being no parallel safety hazards within
+ * tuplesort, because tuplesort thinks of the sort as several independent
+ * sorts whose results are combined.  Since, in general, the behavior of
+ * sort operators is immutable, caller need only worry about the parallel
+ * safety of whatever the process is through which input tuples are
+ * generated (typically, caller uses a parallel heap scan).
+ */
+
+extern Tuplesortstate *tuplesort_begin_heap(TupleDesc tupDesc,
+											int nkeys, AttrNumber *attNums,
+											Oid *sortOperators, Oid *sortCollations,
+											bool *nullsFirstFlags,
+											int workMem, SortCoordinate coordinate,
+											int sortopt);
+extern Tuplesortstate *tuplesort_begin_cluster(TupleDesc tupDesc,
+											   Relation indexRel, int workMem,
+											   SortCoordinate coordinate,
+											   int sortopt);
+extern Tuplesortstate *tuplesort_begin_index_btree(Relation heapRel,
+												   Relation indexRel,
+												   bool enforceUnique,
+												   bool uniqueNullsNotDistinct,
+												   int workMem, SortCoordinate coordinate,
+												   int sortopt);
+extern Tuplesortstate *tuplesort_begin_index_hash(Relation heapRel,
+												  Relation indexRel,
+												  uint32 high_mask,
+												  uint32 low_mask,
+												  uint32 max_buckets,
+												  int workMem, SortCoordinate coordinate,
+												  int sortopt);
+extern Tuplesortstate *tuplesort_begin_index_gist(Relation heapRel,
+												  Relation indexRel,
+												  int workMem, SortCoordinate coordinate,
+												  int sortopt);
+extern Tuplesortstate *tuplesort_begin_datum(Oid datumType,
+											 Oid sortOperator, Oid sortCollation,
+											 bool nullsFirstFlag,
+											 int workMem, SortCoordinate coordinate,
+											 int sortopt);
+
+extern void tuplesort_set_bound(Tuplesortstate *state, int64 bound);
+extern bool tuplesort_used_bound(Tuplesortstate *state);
+
+extern void tuplesort_puttupleslot(Tuplesortstate *state,
+								   TupleTableSlot *slot);
+extern void tuplesort_putheaptuple(Tuplesortstate *state, HeapTuple tup);
+extern void tuplesort_putindextuplevalues(Tuplesortstate *state,
+										  Relation rel, ItemPointer self,
+										  Datum *values, bool *isnull);
+extern void tuplesort_putdatum(Tuplesortstate *state, Datum val,
+							   bool isNull);
+
+extern void tuplesort_performsort(Tuplesortstate *state);
+
+extern bool tuplesort_gettupleslot(Tuplesortstate *state, bool forward,
+								   bool copy, TupleTableSlot *slot, Datum *abbrev);
+extern HeapTuple tuplesort_getheaptuple(Tuplesortstate *state, bool forward);
+extern IndexTuple tuplesort_getindextuple(Tuplesortstate *state, bool forward);
+extern bool tuplesort_getdatum(Tuplesortstate *state, bool forward,
+							   Datum *val, bool *isNull, Datum *abbrev);
+
+extern bool tuplesort_skiptuples(Tuplesortstate *state, int64 ntuples,
+								 bool forward);
+
+extern void tuplesort_end(Tuplesortstate *state);
+
+extern void tuplesort_reset(Tuplesortstate *state);
+
+extern void tuplesort_get_stats(Tuplesortstate *state,
+								TuplesortInstrumentation *stats);
+extern const char *tuplesort_method_name(TuplesortMethod m);
+extern const char *tuplesort_space_type_name(TuplesortSpaceType t);
+
+extern int	tuplesort_merge_order(int64 allowedMem);
+
+extern Size tuplesort_estimate_shared(int nworkers);
+extern void tuplesort_initialize_shared(Sharedsort *shared, int nWorkers,
+										dsm_segment *seg);
+extern void tuplesort_attach_shared(Sharedsort *shared, dsm_segment *seg);
+
+/*
+ * These routines may only be called if TUPLESORT_RANDOMACCESS was specified
+ * during tuplesort_begin_*.  Additionally backwards scan in gettuple/getdatum
+ * also require TUPLESORT_RANDOMACCESS.  Note that parallel sorts do not
+ * support random access.
+ */
+extern void tuplesort_rescan(Tuplesortstate *state);
+extern void tuplesort_markpos(Tuplesortstate *state);
+extern void tuplesort_restorepos(Tuplesortstate *state);
+
+#endif							/* TUPLESORT_H */