/*-------------------------------------------------------------------------
*
* hashjoin.h
* internal structures for hash joins
*
*
* Portions Copyright (c) 1996-2018, 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 "port/atomics.h"
#include "storage/barrier.h"
#include "storage/buffile.h"
#include "storage/lwlock.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
{
/* link to next tuple in same bucket */
union
{
struct HashJoinTupleData *unshared;
dsa_pointer shared;
} next;
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 chunk's tuple buffer */
size_t used; /* number of buffer bytes already used */
/* pointer to the next chunk (linked list) */
union
{
struct HashMemoryChunkData *unshared;
dsa_pointer shared;
} next;
/*
* The chunk's tuple buffer starts after the HashMemoryChunkData struct,
* at offset HASH_CHUNK_HEADER_SIZE (which must be maxaligned). Note that
* that offset is not included in "maxlen" or "used".
*/
} HashMemoryChunkData;
typedef struct HashMemoryChunkData *HashMemoryChunk;
#define HASH_CHUNK_SIZE (32 * 1024L)
#define HASH_CHUNK_HEADER_SIZE MAXALIGN(sizeof(HashMemoryChunkData))
#define HASH_CHUNK_DATA(hc) (((char *) (hc)) + HASH_CHUNK_HEADER_SIZE)
/* tuples exceeding HASH_CHUNK_THRESHOLD bytes are put in their own chunk */
#define HASH_CHUNK_THRESHOLD (HASH_CHUNK_SIZE / 4)
/*
* For each batch of a Parallel Hash Join, we have a ParallelHashJoinBatch
* object in shared memory to coordinate access to it. Since they are
* followed by variable-sized objects, they are arranged in contiguous memory
* but not accessed directly as an array.
*/
typedef struct ParallelHashJoinBatch
{
dsa_pointer buckets; /* array of hash table buckets */
Barrier batch_barrier; /* synchronization for joining this batch */
dsa_pointer chunks; /* chunks of tuples loaded */
size_t size; /* size of buckets + chunks in memory */
size_t estimated_size; /* size of buckets + chunks while writing */
size_t ntuples; /* number of tuples loaded */
size_t old_ntuples; /* number of tuples before repartitioning */
bool space_exhausted;
/*
* Variable-sized SharedTuplestore objects follow this struct in memory.
* See the accessor macros below.
*/
} ParallelHashJoinBatch;
/* Accessor for inner batch tuplestore following a ParallelHashJoinBatch. */
#define ParallelHashJoinBatchInner(batch) \
((SharedTuplestore *) \
((char *) (batch) + MAXALIGN(sizeof(ParallelHashJoinBatch))))
/* Accessor for outer batch tuplestore following a ParallelHashJoinBatch. */
#define ParallelHashJoinBatchOuter(batch, nparticipants) \
((SharedTuplestore *) \
((char *) ParallelHashJoinBatchInner(batch) + \
MAXALIGN(sts_estimate(nparticipants))))
/* Total size of a ParallelHashJoinBatch and tuplestores. */
#define EstimateParallelHashJoinBatch(hashtable) \
(MAXALIGN(sizeof(ParallelHashJoinBatch)) + \
MAXALIGN(sts_estimate((hashtable)->parallel_state->nparticipants)) * 2)
/* Accessor for the nth ParallelHashJoinBatch given the base. */
#define NthParallelHashJoinBatch(base, n) \
((ParallelHashJoinBatch *) \
((char *) (base) + \
EstimateParallelHashJoinBatch(hashtable) * (n)))
/*
* Each backend requires a small amount of per-batch state to interact with
* each ParallelHashJoinBatch.
*/
typedef struct ParallelHashJoinBatchAccessor
{
ParallelHashJoinBatch *shared; /* pointer to shared state */
/* Per-backend partial counters to reduce contention. */
size_t preallocated; /* pre-allocated space for this backend */
size_t ntuples; /* number of tuples */
size_t size; /* size of partition in memory */
size_t estimated_size; /* size of partition on disk */
size_t old_ntuples; /* how many tuples before repartitioning? */
bool at_least_one_chunk; /* has this backend allocated a chunk? */
bool done; /* flag to remember that a batch is done */
SharedTuplestoreAccessor *inner_tuples;
SharedTuplestoreAccessor *outer_tuples;
} ParallelHashJoinBatchAccessor;
/*
* While hashing the inner relation, any participant might determine that it's
* time to increase the number of buckets to reduce the load factor or batches
* to reduce the memory size. This is indicated by setting the growth flag to
* these values.
*/
typedef enum ParallelHashGrowth
{
/* The current dimensions are sufficient. */
PHJ_GROWTH_OK,
/* The load factor is too high, so we need to add buckets. */
PHJ_GROWTH_NEED_MORE_BUCKETS,
/* The memory budget would be exhausted, so we need to repartition. */
PHJ_GROWTH_NEED_MORE_BATCHES,
/* Repartitioning didn't help last time, so don't try to do that again. */
PHJ_GROWTH_DISABLED
} ParallelHashGrowth;
/*
* The shared state used to coordinate a Parallel Hash Join. This is stored
* in the DSM segment.
*/
typedef struct ParallelHashJoinState
{
dsa_pointer batches; /* array of ParallelHashJoinBatch */
dsa_pointer old_batches; /* previous generation during repartition */
int nbatch; /* number of batches now */
int old_nbatch; /* previous number of batches */
int nbuckets; /* number of buckets */
ParallelHashGrowth growth; /* control batch/bucket growth */
dsa_pointer chunk_work_queue; /* chunk work queue */
int nparticipants;
size_t space_allowed;
size_t total_tuples; /* total number of inner tuples */
LWLock lock; /* lock protecting the above */
Barrier build_barrier; /* synchronization for the build phases */
Barrier grow_batches_barrier;
Barrier grow_buckets_barrier;
pg_atomic_uint32 distributor; /* counter for load balancing */
SharedFileSet fileset; /* space for shared temporary files */
} ParallelHashJoinState;
/* The phases for building batches, used by build_barrier. */
#define PHJ_BUILD_ELECTING 0
#define PHJ_BUILD_ALLOCATING 1
#define PHJ_BUILD_HASHING_INNER 2
#define PHJ_BUILD_HASHING_OUTER 3
#define PHJ_BUILD_RUNNING 4
#define PHJ_BUILD_DONE 5
/* The phases for probing each batch, used by for batch_barrier. */
#define PHJ_BATCH_ELECTING 0
#define PHJ_BATCH_ALLOCATING 1
#define PHJ_BATCH_LOADING 2
#define PHJ_BATCH_PROBING 3
#define PHJ_BATCH_DONE 4
/* The phases of batch growth while hashing, for grow_batches_barrier. */
#define PHJ_GROW_BATCHES_ELECTING 0
#define PHJ_GROW_BATCHES_ALLOCATING 1
#define PHJ_GROW_BATCHES_REPARTITIONING 2
#define PHJ_GROW_BATCHES_DECIDING 3
#define PHJ_GROW_BATCHES_FINISHING 4
#define PHJ_GROW_BATCHES_PHASE(n) ((n) % 5) /* circular phases */
/* The phases of bucket growth while hashing, for grow_buckets_barrier. */
#define PHJ_GROW_BUCKETS_ELECTING 0
#define PHJ_GROW_BUCKETS_ALLOCATING 1
#define PHJ_GROW_BUCKETS_REINSERTING 2
#define PHJ_GROW_BUCKETS_PHASE(n) ((n) % 3) /* circular phases */
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 */
union
{
/* unshared array is per-batch storage, as are all the tuples */
struct HashJoinTupleData **unshared;
/* shared array is per-query DSA area, as are all the tuples */
dsa_pointer_atomic *shared;
} buckets;
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 partialTuples; /* # tuples obtained from inner plan by me */
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 */
/* Shared and private state for Parallel Hash. */
HashMemoryChunk current_chunk; /* this backend's current chunk */
dsa_area *area; /* DSA area to allocate memory from */
ParallelHashJoinState *parallel_state;
ParallelHashJoinBatchAccessor *batches;
dsa_pointer current_chunk_shared;
} HashJoinTableData;
#endif /* HASHJOIN_H */