PostgreSQL绍聚合函数实现中怎么使用的simplehash
发表于:2025-01-31 作者:千家信息网编辑
千家信息网最后更新 2025年01月31日,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"PostgreSQ
千家信息网最后更新 2025年01月31日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!
//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_hash
TupleHashEntryData
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 uint32TupleHashTableHash(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 intTupleHashTableMatch(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 TupleHashTableHashBreakpoint 1 at 0x6d3b2b: file execGrouping.c, line 379.(gdb) b TupleHashTableMatchBreakpoint 2 at 0x6d3c79: file execGrouping.c, line 446.(gdb) (gdb) cContinuing.Breakpoint 1, TupleHashTableHash (tb=0x2dd2720, tuple=0x0) at execGrouping.c:379379 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) n380 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) n381 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) n387 if (tuple == NULL)(gdb) p hashkey$6 = 0(gdb) n390 slot = hashtable->inputslot;(gdb) 391 hashfunctions = hashtable->in_hash_funcs;
开始遍历分组列
获取hashkey
(gdb) n406 for (i = 0; i < numCols; i++)(gdb) p numCols$8 = 1(gdb) n408 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) n415 attr = slot_getattr(slot, att, &isNull);(gdb) p hashkey$11 = 0(gdb) n417 if (!isNull) /* treat nulls as having hash key 0 */(gdb) p attr$12 = 140535426168416(gdb) x\16c attrInvalid character '\' in expression.(gdb) x/16c attr0x7fd0f427b660: 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) n421 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) n423 hashkey ^= hkey;(gdb) p hkey$15 = 3431319292(gdb) n406 for (i = 0; i < numCols; i++)(gdb) p hashkey$16 = 3431319292
返回结果
(gdb) n433 return murmurhash42(hashkey);(gdb) p murmurhash42(hashkey)$17 = 443809650(gdb) n434 }(gdb) tuplehash_insert (tb=0x2dd2720, key=0x0, found=0x7fff585be487) at ../../../src/include/lib/simplehash.h:497497 insertdist = 0;(gdb)
TupleHashTableMatch
进入TupleHashTableMatch
(gdb) cContinuing.Breakpoint 2, TupleHashTableMatch (tb=0x2dd2720, tuple1=0x2dcc488, tuple2=0x0) at execGrouping.c:446446 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) n447 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) n465 }(gdb) tuplehash_insert (tb=0x2dd2720, key=0x0, found=0x7fff585be487) at ../../../src/include/lib/simplehash.h:556556 Assert(entry->status == SH_STATUS_IN_USE);(gdb)
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