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/*-------------------------------------------------------------------------
*
* hashjoin.h
* internal structures for hash joins
*
*
* Portions Copyright (c) 1996-2016, PostgreSQL Global Development Group
* Portions Copyright (c) 1994, Regents of the University of California
*
* src/include/executor/hashjoin.h
*
*-------------------------------------------------------------------------
*/
#ifndef HASHJOIN_H
#define HASHJOIN_H
#include "nodes/execnodes.h"
#include "storage/buffile.h"
/* ----------------------------------------------------------------
* hash-join hash table structures
*
* Each active hashjoin has a HashJoinTable control block, which is
* palloc'd in the executor's per-query context. All other storage needed
* for the hashjoin is kept in private memory contexts, two for each hashjoin.
* This makes it easy and fast to release the storage when we don't need it
* anymore. (Exception: data associated with the temp files lives in the
* per-query context too, since we always call buffile.c in that context.)
*
* The hashtable contexts are made children of the per-query context, ensuring
* that they will be discarded at end of statement even if the join is
* aborted early by an error. (Likewise, any temporary files we make will
* be cleaned up by the virtual file manager in event of an error.)
*
* Storage that should live through the entire join is allocated from the
* "hashCxt", while storage that is only wanted for the current batch is
* allocated in the "batchCxt". By resetting the batchCxt at the end of
* each batch, we free all the per-batch storage reliably and without tedium.
*
* During first scan of inner relation, we get its tuples from executor.
* If nbatch > 1 then tuples that don't belong in first batch get saved
* into inner-batch temp files. The same statements apply for the
* first scan of the outer relation, except we write tuples to outer-batch
* temp files. After finishing the first scan, we do the following for
* each remaining batch:
* 1. Read tuples from inner batch file, load into hash buckets.
* 2. Read tuples from outer batch file, match to hash buckets and output.
*
* It is possible to increase nbatch on the fly if the in-memory hash table
* gets too big. The hash-value-to-batch computation is arranged so that this
* can only cause a tuple to go into a later batch than previously thought,
* never into an earlier batch. When we increase nbatch, we rescan the hash
* table and dump out any tuples that are now of a later batch to the correct
* inner batch file. Subsequently, while reading either inner or outer batch
* files, we might find tuples that no longer belong to the current batch;
* if so, we just dump them out to the correct batch file.
* ----------------------------------------------------------------
*/
/* these are in nodes/execnodes.h: */
/* typedef struct HashJoinTupleData *HashJoinTuple; */
/* typedef struct HashJoinTableData *HashJoinTable; */
typedef struct HashJoinTupleData
{
struct HashJoinTupleData *next; /* link to next tuple in same bucket */
uint32 hashvalue; /* tuple's hash code */
/* Tuple data, in MinimalTuple format, follows on a MAXALIGN boundary */
} HashJoinTupleData;
#define HJTUPLE_OVERHEAD MAXALIGN(sizeof(HashJoinTupleData))
#define HJTUPLE_MINTUPLE(hjtup) \
((MinimalTuple) ((char *) (hjtup) + HJTUPLE_OVERHEAD))
/*
* If the outer relation's distribution is sufficiently nonuniform, we attempt
* to optimize the join by treating the hash values corresponding to the outer
* relation's MCVs specially. Inner relation tuples matching these hash
* values go into the "skew" hashtable instead of the main hashtable, and
* outer relation tuples with these hash values are matched against that
* table instead of the main one. Thus, tuples with these hash values are
* effectively handled as part of the first batch and will never go to disk.
* The skew hashtable is limited to SKEW_WORK_MEM_PERCENT of the total memory
* allowed for the join; while building the hashtables, we decrease the number
* of MCVs being specially treated if needed to stay under this limit.
*
* Note: you might wonder why we look at the outer relation stats for this,
* rather than the inner. One reason is that the outer relation is typically
* bigger, so we get more I/O savings by optimizing for its most common values.
* Also, for similarly-sized relations, the planner prefers to put the more
* uniformly distributed relation on the inside, so we're more likely to find
* interesting skew in the outer relation.
*/
typedef struct HashSkewBucket
{
uint32 hashvalue; /* common hash value */
HashJoinTuple tuples; /* linked list of inner-relation tuples */
} HashSkewBucket;
#define SKEW_BUCKET_OVERHEAD MAXALIGN(sizeof(HashSkewBucket))
#define INVALID_SKEW_BUCKET_NO (-1)
#define SKEW_WORK_MEM_PERCENT 2
#define SKEW_MIN_OUTER_FRACTION 0.01
/*
* To reduce palloc overhead, the HashJoinTuples for the current batch are
* packed in 32kB buffers instead of pallocing each tuple individually.
*/
typedef struct HashMemoryChunkData
{
int ntuples; /* number of tuples stored in this chunk */
size_t maxlen; /* size of the buffer holding the tuples */
size_t used; /* number of buffer bytes already used */
struct HashMemoryChunkData *next; /* pointer to the next chunk (linked
* list) */
char data[FLEXIBLE_ARRAY_MEMBER]; /* buffer allocated at the end */
} HashMemoryChunkData;
typedef struct HashMemoryChunkData *HashMemoryChunk;
#define HASH_CHUNK_SIZE (32 * 1024L)
#define HASH_CHUNK_THRESHOLD (HASH_CHUNK_SIZE / 4)
typedef struct HashJoinTableData
{
int nbuckets; /* # buckets in the in-memory hash table */
int log2_nbuckets; /* its log2 (nbuckets must be a power of 2) */
int nbuckets_original; /* # buckets when starting the first
* hash */
int nbuckets_optimal; /* optimal # buckets (per batch) */
int log2_nbuckets_optimal; /* log2(nbuckets_optimal) */
/* buckets[i] is head of list of tuples in i'th in-memory bucket */
struct HashJoinTupleData **buckets;
/* buckets array is per-batch storage, as are all the tuples */
bool keepNulls; /* true to store unmatchable NULL tuples */
bool skewEnabled; /* are we using skew optimization? */
HashSkewBucket **skewBucket; /* hashtable of skew buckets */
int skewBucketLen; /* size of skewBucket array (a power of 2!) */
int nSkewBuckets; /* number of active skew buckets */
int *skewBucketNums; /* array indexes of active skew buckets */
int nbatch; /* number of batches */
int curbatch; /* current batch #; 0 during 1st pass */
int nbatch_original; /* nbatch when we started inner scan */
int nbatch_outstart; /* nbatch when we started outer scan */
bool growEnabled; /* flag to shut off nbatch increases */
double totalTuples; /* # tuples obtained from inner plan */
double skewTuples; /* # tuples inserted into skew tuples */
/*
* These arrays are allocated for the life of the hash join, but only if
* nbatch > 1. A file is opened only when we first write a tuple into it
* (otherwise its pointer remains NULL). Note that the zero'th array
* elements never get used, since we will process rather than dump out any
* tuples of batch zero.
*/
BufFile **innerBatchFile; /* buffered virtual temp file per batch */
BufFile **outerBatchFile; /* buffered virtual temp file per batch */
/*
* Info about the datatype-specific hash functions for the datatypes being
* hashed. These are arrays of the same length as the number of hash join
* clauses (hash keys).
*/
FmgrInfo *outer_hashfunctions; /* lookup data for hash functions */
FmgrInfo *inner_hashfunctions; /* lookup data for hash functions */
bool *hashStrict; /* is each hash join operator strict? */
Size spaceUsed; /* memory space currently used by tuples */
Size spaceAllowed; /* upper limit for space used */
Size spacePeak; /* peak space used */
Size spaceUsedSkew; /* skew hash table's current space usage */
Size spaceAllowedSkew; /* upper limit for skew hashtable */
MemoryContext hashCxt; /* context for whole-hash-join storage */
MemoryContext batchCxt; /* context for this-batch-only storage */
/* used for dense allocation of tuples (into linked chunks) */
HashMemoryChunk chunks; /* one list for the whole batch */
} HashJoinTableData;
#endif /* HASHJOIN_H */
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