PostgreSQL绍聚合函数实现中怎么使用的simplehash
这篇文章主要讲解了“PostgreSQL绍聚合函数实现中怎么使用的simplehash”，文中的讲解内容简单清晰，易于学习与理解，下面请大家跟着小编的思路慢慢深入，一起来研究和学习“PostgreSQL绍聚合函数实现中怎么使用的simplehash”吧！
我们注重客户提出的每个要求，我们充分考虑每一个细节，我们积极的做好成都网站设计、网站建设服务，我们努力开拓更好的视野，通过不懈的努力，成都创新互联赢得了业内的良好声誉，这一切，也不断的激励着我们更好的服务客户。 主要业务：网站建设,网站制作,网站设计,成都小程序开发,网站开发,技术开发实力，DIV+CSS，PHP及ASP，ASP.Net，SQL数据库的技术开发工程师。
//src/backend/executor/execGrouping.c #define SH_HASH_KEY(tb, key) TupleHashTableHash(tb, key) //SH_HASH_KEY --> TupleHashTableHash #define SH_EQUAL(tb, a, b) TupleHashTableMatch(tb, a, b) == 0 //SH_EQUAL --> TupleHashTableMatch
一、数据结构
TupleHashTable
哈希表定义
typedef struct TupleHashTableData *TupleHashTable;
typedef struct TupleHashTableData
{
//底层Hash表
tuplehash_hash *hashtab; /* underlying hash table */
//在检索键中的列数
int numCols; /* number of columns in lookup key */
//键列中的属性格式
AttrNumber *keyColIdx; /* attr numbers of key columns */
//数据类型的哈希函数
FmgrInfo *tab_hash_funcs; /* hash functions for table datatype(s) */
//数据类型比较器
ExprState *tab_eq_func; /* comparator for table datatype(s) */
//包含数据表的内存上下文
MemoryContext tablecxt; /* memory context containing table */
//函数解析上下文
MemoryContext tempcxt; /* context for function evaluations */
//构造每个哈希条目的实际大小
Size entrysize; /* actual size to make each hash entry */
//依赖数据表条目的slot
TupleTableSlot *tableslot; /* slot for referencing table entries */
/* The following fields are set transiently for each table search: */
//下面字段为每一个表检索时临时设置
//当前输入tuple slot
TupleTableSlot *inputslot; /* current input tuple's slot */
//输入数据类型的哈希函数
FmgrInfo *in_hash_funcs; /* hash functions for input datatype(s) */
//input vs table的比较器
ExprState *cur_eq_func; /* comparator for input vs. table */
//哈希函数IV
uint32 hash_iv; /* hash-function IV */
//表达式上下文
ExprContext *exprcontext; /* expression context */
} TupleHashTableData;
typedef tuplehash_iterator TupleHashIterator;
/* type definitions */
//哈希表类型定义
typedef struct SH_TYPE //tuplehash_hash
{
/*
* Size of data / bucket array, 64 bits to handle UINT32_MAX sized hash
* tables. Note that the maximum number of elements is lower
* (SH_MAX_FILLFACTOR)
* 数据/桶数组大小,64 bit用于处理UINT32_MAX哈希表.
* 注意元素最大格式小于(SH_MAX_FILLFACTOR)
*/
uint64 size;
/* how many elements have valid contents */
//有多少个元素具有有效内容
uint32 members;
/* mask for bucket and size calculations, based on size */
//基于大小,用于计算桶和大小的掩码
uint32 sizemask;
/* boundary after which to grow hashtable */
//哈希表增长的阈值
uint32 grow_threshold;
/* hash buckets */
//哈希桶
SH_ELEMENT_TYPE *data;
/* memory context to use for allocations */
//用于分配的内存上下文
MemoryContext ctx;
/* user defined data, useful for callbacks */
//用户自定义的数据,通常用于回调函数
void *private_data;
} SH_TYPE;//实际是tuplehash_hashTupleHashEntryData
哈希表条目
typedef struct TupleHashEntryData *TupleHashEntry;
typedef struct TupleHashTableData *TupleHashTable;
typedef struct TupleHashEntryData
{
//该组第一个元组的拷贝
MinimalTuple firstTuple; /* copy of first tuple in this group */
//用户数据
void *additional; /* user data */
//状态(见SH_STATUS)
uint32 status; /* hash status */
//哈希值(已缓存)
uint32 hash; /* hash value (cached) */
} TupleHashEntryData;
typedef enum SH_STATUS
{
SH_STATUS_EMPTY = 0x00,
SH_STATUS_IN_USE = 0x01
} SH_STATUS;MinimalTuple
最小化的元组定义
/*
* MinimalTuple is an alternative representation that is used for transient
* tuples inside the executor, in places where transaction status information
* is not required, the tuple rowtype is known, and shaving off a few bytes
* is worthwhile because we need to store many tuples. The representation
* is chosen so that tuple access routines can work with either full or
* minimal tuples via a HeapTupleData pointer structure. The access routines
* see no difference, except that they must not access the transaction status
* or t_ctid fields because those aren't there.
*
* For the most part, MinimalTuples should be accessed via TupleTableSlot
* routines. These routines will prevent access to the "system columns"
* and thereby prevent accidental use of the nonexistent fields.
*
* MinimalTupleData contains a length word, some padding, and fields matching
* HeapTupleHeaderData beginning with t_infomask2. The padding is chosen so
* that offsetof(t_infomask2) is the same modulo MAXIMUM_ALIGNOF in both
* structs. This makes data alignment rules equivalent in both cases.
*
* When a minimal tuple is accessed via a HeapTupleData pointer, t_data is
* set to point MINIMAL_TUPLE_OFFSET bytes before the actual start of the
* minimal tuple --- that is, where a full tuple matching the minimal tuple's
* data would start. This trick is what makes the structs seem equivalent.
*
* Note that t_hoff is computed the same as in a full tuple, hence it includes
* the MINIMAL_TUPLE_OFFSET distance. t_len does not include that, however.
*
* MINIMAL_TUPLE_DATA_OFFSET is the offset to the first useful (non-pad) data
* other than the length word. tuplesort.c and tuplestore.c use this to avoid
* writing the padding to disk.
*/
#define MINIMAL_TUPLE_OFFSET \
((offsetof(HeapTupleHeaderData, t_infomask2) - sizeof(uint32)) / MAXIMUM_ALIGNOF * MAXIMUM_ALIGNOF)
#define MINIMAL_TUPLE_PADDING \
((offsetof(HeapTupleHeaderData, t_infomask2) - sizeof(uint32)) % MAXIMUM_ALIGNOF)
#define MINIMAL_TUPLE_DATA_OFFSET \
offsetof(MinimalTupleData, t_infomask2)
struct MinimalTupleData
{
uint32 t_len; /* actual length of minimal tuple */
char mt_padding[MINIMAL_TUPLE_PADDING];
/* Fields below here must match HeapTupleHeaderData! */
uint16 t_infomask2; /* number of attributes + various flags */
uint16 t_infomask; /* various flag bits, see below */
uint8 t_hoff; /* sizeof header incl. bitmap, padding */
/* ^ - 23 bytes - ^ */
bits8 t_bits[FLEXIBLE_ARRAY_MEMBER]; /* bitmap of NULLs */
/* MORE DATA FOLLOWS AT END OF STRUCT */
};
/* typedef appears in htup.h */
#define SizeofMinimalTupleHeader offsetof(MinimalTupleData, t_bits)
typedef struct MinimalTupleData MinimalTupleData;
typedef MinimalTupleData *MinimalTuple;二、源码解读
TupleHashTableHash
TupleHashTableHash用于计算tuple的哈希值(分组列值)
/*
* Compute the hash value for a tuple
* 计算tuple的哈希值
*
* The passed-in key is a pointer to TupleHashEntryData. In an actual hash
* table entry, the firstTuple field points to a tuple (in MinimalTuple
* format). LookupTupleHashEntry sets up a dummy TupleHashEntryData with a
* NULL firstTuple field --- that cues us to look at the inputslot instead.
* This convention avoids the need to materialize virtual input tuples unless
* they actually need to get copied into the table.
* 传入的key是指向TupleHashEntryData结构体的指针.
* 在实际的哈希表条目中,firstTuple字段指向一个元组(以MinimalTuple格式保存).
* LookupTupleHashEntry会使用NULL firstTuple字段设置一个虚拟的TupleHashEntryData.
* --- 这可以提示我们转而查看inputslot.
* 这个转换避免了物化虚拟输入元组,除非它们需要实际拷贝到数据表中.
*
* Also, the caller must select an appropriate memory context for running
* the hash functions. (dynahash.c doesn't change CurrentMemoryContext.)
* 同时,调用者必须选择合适的内存上下文用于运行哈希函数.
* (dynahash.c不会改变CurrentMemoryContext)
*/
static uint32
TupleHashTableHash(struct tuplehash_hash *tb, const MinimalTuple tuple)
{
//Tuple 哈希表
TupleHashTable hashtable = (TupleHashTable) tb->private_data;
//列数
int numCols = hashtable->numCols;
//属性编号
AttrNumber *keyColIdx = hashtable->keyColIdx;
//哈希key
uint32 hashkey = hashtable->hash_iv;
//元组slot
TupleTableSlot *slot;
//哈希函数指针
FmgrInfo *hashfunctions;
int i;
if (tuple == NULL)//元组为NULL
{
/* Process the current input tuple for the table */
//处理当前输入元组
slot = hashtable->inputslot;
hashfunctions = hashtable->in_hash_funcs;
}
else
{
/*
* Process a tuple already stored in the table.
* 处理已存储在数据表中的元组.
*
* (this case never actually occurs due to the way simplehash.h is
* used, as the hash-value is stored in the entries)
* (这种情况因为simplehash.h的使用,实际上不会发生,因为哈希值存储在条目中)
*/
slot = hashtable->tableslot;
//存储MinimalTuple
ExecStoreMinimalTuple(tuple, slot, false);
hashfunctions = hashtable->tab_hash_funcs;
}
for (i = 0; i < numCols; i++)
{
//------- 循环遍历列数
//获取属性编号
AttrNumber att = keyColIdx[i];
Datum attr;//属性
bool isNull;//是否为NULL?
/* rotate hashkey left 1 bit at each step */
//每一步向左移动一位
hashkey = (hashkey << 1) | ((hashkey & 0x80000000) ? 1 : 0);
//获取属性值
attr = slot_getattr(slot, att, &isNull);
//如为null,则哈希key设置为0
if (!isNull) /* treat nulls as having hash key 0 */
{
//不为NULL
uint32 hkey;
//调用哈希函数
hkey = DatumGetUInt32(FunctionCall1(&hashfunctions[i],
attr));
hashkey ^= hkey;
}
}
/*
* The way hashes are combined above, among each other and with the IV,
* doesn't lead to good bit perturbation. As the IV's goal is to lead to
* achieve that, perform a round of hashing of the combined hash -
* resulting in near perfect perturbation.
* 上面哈希的的组合方式,彼此之间以及与IV的组合方式,都不会导致位扰动.
* 因为IV存在的目的是实现该目标,执行组合哈希的hashing取整 -- 结果是完美的扰动.
*/
return murmurhash42(hashkey);
}TupleHashTableMatch
TupleHashTableMatch用于判断两个tuples是否匹配(有相同的hash值)
/*
* See whether two tuples (presumably of the same hash value) match
* 检查两个tuples是否匹配(有相同的hash值)
*
* As above, the passed pointers are pointers to TupleHashEntryData.
* 如上所述,传入的指针指向TupleHashEntryData
*/
static int
TupleHashTableMatch(struct tuplehash_hash *tb, const MinimalTuple tuple1, const MinimalTuple tuple2)
{
TupleTableSlot *slot1;
TupleTableSlot *slot2;
TupleHashTable hashtable = (TupleHashTable) tb->private_data;
ExprContext *econtext = hashtable->exprcontext;
/*
* We assume that simplehash.h will only ever call us with the first
* argument being an actual table entry, and the second argument being
* LookupTupleHashEntry's dummy TupleHashEntryData. The other direction
* could be supported too, but is not currently required.
*/
Assert(tuple1 != NULL);
slot1 = hashtable->tableslot;
ExecStoreMinimalTuple(tuple1, slot1, false);
Assert(tuple2 == NULL);
slot2 = hashtable->inputslot;
/* For crosstype comparisons, the inputslot must be first */
econtext->ecxt_innertuple = slot2;
econtext->ecxt_outertuple = slot1;
return !ExecQualAndReset(hashtable->cur_eq_func, econtext);
}三、跟踪分析
测试脚本
-- 禁用并行 set max_parallel_workers_per_gather=0; select bh,avg(c1),min(c1),max(c2) from t_agg_simple group by bh;
跟踪分析
(gdb) b TupleHashTableHash Breakpoint 1 at 0x6d3b2b: file execGrouping.c, line 379. (gdb) b TupleHashTableMatch Breakpoint 2 at 0x6d3c79: file execGrouping.c, line 446. (gdb) (gdb) c Continuing. Breakpoint 1, TupleHashTableHash (tb=0x2dd2720, tuple=0x0) at execGrouping.c:379 379 TupleHashTable hashtable = (TupleHashTable) tb->private_data; (gdb)
输入参数
(gdb) p *tb
$1 = {size = 256, members = 0, sizemask = 255, grow_threshold = 230, data = 0x2ddca00, ctx = 0x2db5310,
private_data = 0x2dd2890}
(gdb) p *tb->data
$2 = {firstTuple = 0x0, additional = 0x0, status = 0, hash = 0}获取分组列数
(gdb) n
380 int numCols = hashtable->numCols;
(gdb) p *hashtable
$3 = {hashtab = 0x2dd2720, numCols = 1, keyColIdx = 0x2dd2680, tab_hash_funcs = 0x2db72d0, tab_eq_func = 0x2ddea18,
tablecxt = 0x2dcc370, tempcxt = 0x2db7320, entrysize = 24, tableslot = 0x2dd2928, inputslot = 0x2db7238,
in_hash_funcs = 0x2db72d0, cur_eq_func = 0x2ddea18, hash_iv = 0, exprcontext = 0x2ddf338}
(gdb) p tb->private_data
$4 = (void *) 0x2dd2890获取分组列属性编号
(gdb) n 381 AttrNumber *keyColIdx = hashtable->keyColIdx; (gdb) 382 uint32 hashkey = hashtable->hash_iv; (gdb) p *keyColIdx $5 = 1
如输入tuple为NULL,设置slot和哈希函数
(gdb) n 387 if (tuple == NULL) (gdb) p hashkey $6 = 0 (gdb) n 390 slot = hashtable->inputslot; (gdb) 391 hashfunctions = hashtable->in_hash_funcs;
开始遍历分组列
获取hashkey
(gdb) n 406 for (i = 0; i < numCols; i++) (gdb) p numCols $8 = 1 (gdb) n 408 AttrNumber att = keyColIdx[i]; (gdb) 413 hashkey = (hashkey << 1) | ((hashkey & 0x80000000) ? 1 : 0); (gdb) p att $9 = 1 (gdb) p hashkey $10 = 0
获取属性值
(gdb) n 415 attr = slot_getattr(slot, att, &isNull); (gdb) p hashkey $11 = 0 (gdb) n 417 if (!isNull) /* treat nulls as having hash key 0 */ (gdb) p attr $12 = 140535426168416 (gdb) x\16c attr Invalid character '\' in expression. (gdb) x/16c attr 0x7fd0f427b660: 11 '\v' 71 'G' 90 'Z' 48 '0' 49 '1' 0 '\000' 0 '\000' 0 '\000' 0x7fd0f427b668: 1 '\001' 0 '\000' 0 '\000' 0 '\000' 1 '\001' 0 '\000' 0 '\000' 0 '\000'
计算哈希值
(gdb) n
421 hkey = DatumGetUInt32(FunctionCall1(&hashfunctions[i],
(gdb) p hashfunctions[i]
$13 = {fn_addr = 0x4c8a31 , fn_oid = 400, fn_nargs = 1, fn_strict = true, fn_retset = false, fn_stats = 2 '\002',
fn_extra = 0x0, fn_mcxt = 0x2db5310, fn_expr = 0x0}
(gdb) p i
$14 = 0
(gdb) n
423 hashkey ^= hkey;
(gdb) p hkey
$15 = 3431319292
(gdb) n
406 for (i = 0; i < numCols; i++)
(gdb) p hashkey
$16 = 3431319292 返回结果
(gdb) n 433 return murmurhash42(hashkey); (gdb) p murmurhash42(hashkey) $17 = 443809650 (gdb) n 434 } (gdb) tuplehash_insert (tb=0x2dd2720, key=0x0, found=0x7fff585be487) at ../../../src/include/lib/simplehash.h:497 497 insertdist = 0; (gdb)
TupleHashTableMatch
进入TupleHashTableMatch
(gdb) c Continuing. Breakpoint 2, TupleHashTableMatch (tb=0x2dd2720, tuple1=0x2dcc488, tuple2=0x0) at execGrouping.c:446 446 TupleHashTable hashtable = (TupleHashTable) tb->private_data; (gdb)
输入参数
(gdb) p *tb
$18 = {size = 256, members = 1, sizemask = 255, grow_threshold = 230, data = 0x2ddca00, ctx = 0x2db5310,
private_data = 0x2dd2890}
(gdb) p *tuple1
$19 = {t_len = 21, mt_padding = "\000\000\000\000\000", t_infomask2 = 1, t_infomask = 2, t_hoff = 24 '\030',
t_bits = 0x2dcc497 ""}对比是否匹配
(gdb) n
447 ExprContext *econtext = hashtable->exprcontext;
(gdb)
455 Assert(tuple1 != NULL);
(gdb)
456 slot1 = hashtable->tableslot;
(gdb)
457 ExecStoreMinimalTuple(tuple1, slot1, false);
(gdb)
458 Assert(tuple2 == NULL);
(gdb)
459 slot2 = hashtable->inputslot;
(gdb)
462 econtext->ecxt_innertuple = slot2;
(gdb)
463 econtext->ecxt_outertuple = slot1;
(gdb)
464 return !ExecQualAndReset(hashtable->cur_eq_func, econtext);
(gdb) p hashtable->cur_eq_func
$20 = (ExprState *) 0x2ddea18
(gdb) p *hashtable->cur_eq_func
$21 = {tag = {type = T_ExprState}, flags = 7 '\a', resnull = false, resvalue = 0, resultslot = 0x0, steps = 0x2ddeab0,
evalfunc = 0x6cd882 , expr = 0x0, evalfunc_private = 0x6cb43e , steps_len = 7,
steps_alloc = 16, parent = 0x0, ext_params = 0x0, innermost_caseval = 0x0, innermost_casenull = 0x0,
innermost_domainval = 0x0, innermost_domainnull = 0x0} 返回值
$22 = true (gdb) n 465 } (gdb) tuplehash_insert (tb=0x2dd2720, key=0x0, found=0x7fff585be487) at ../../../src/include/lib/simplehash.h:556 556 Assert(entry->status == SH_STATUS_IN_USE); (gdb)
感谢各位的阅读，以上就是“PostgreSQL绍聚合函数实现中怎么使用的simplehash”的内容了，经过本文的学习后，相信大家对PostgreSQL绍聚合函数实现中怎么使用的simplehash这一问题有了更深刻的体会，具体使用情况还需要大家实践验证。这里是创新互联，小编将为大家推送更多相关知识点的文章，欢迎关注！
分享题目：PostgreSQL绍聚合函数实现中怎么使用的simplehash
链接分享：http://cdiso.cn/article/pisisj.html
