本篇内容介绍了“PostgreSQL中set_base_rel_sizes函数及其子函数案例分析”的有关知识，在实际案例的操作过程中，不少人都会遇到这样的困境，接下来就让小编带领大家学习一下如何处理这些情况吧！希望大家仔细阅读，能够学有所成！
make_one_rel源代码:
RelOptInfo *
make_one_rel(PlannerInfo *root, List *joinlist)
{
RelOptInfo *rel;
Index rti;
/*
* Construct the all_baserels Relids set.
*/
root->all_baserels = NULL;
for (rti = 1; rti < root->simple_rel_array_size; rti++)//遍历RelOptInfo
{
RelOptInfo *brel = root->simple_rel_array[rti];
/* there may be empty slots corresponding to non-baserel RTEs */
if (brel == NULL)
continue;
Assert(brel->relid == rti); /* sanity check on array */
/* ignore RTEs that are "other rels" */
if (brel->reloptkind != RELOPT_BASEREL)
continue;
root->all_baserels = bms_add_member(root->all_baserels, brel->relid);//添加到all_baserels遍历中
}
/* Mark base rels as to whether we care about fast-start plans */
//设置RelOptInfo的consider_param_startup变量,是否考量fast-start plans
set_base_rel_consider_startup(root);
/*
* Compute size estimates and consider_parallel flags for each base rel,
* then generate access paths.
*/
set_base_rel_sizes(root);//估算Relation的Size并且设置consider_parallel标记
set_base_rel_pathlists(root);//生成Relation的扫描(访问)路径
/*
* Generate access paths for the entire join tree.
* 通过动态规划或遗传算法生成连接路径
*/
rel = make_rel_from_joinlist(root, joinlist);
/*
* The result should join all and only the query's base rels.
*/
Assert(bms_equal(rel->relids, root->all_baserels));
//返回最上层的RelOptInfo
return rel;
}RelOptInfo
typedef struct RelOptInfo
{
NodeTag type;//节点标识
RelOptKind reloptkind;//RelOpt类型
/* all relations included in this RelOptInfo */
Relids relids; /*Relids(rtindex)集合 set of base relids (rangetable indexes) */
/* size estimates generated by planner */
double rows; /*结果元组的估算数量 estimated number of result tuples */
/* per-relation planner control flags */
bool consider_startup; /*是否考虑启动成本?是,需要保留启动成本低的路径 keep cheap-startup-cost paths? */
bool consider_param_startup; /*是否考虑参数化?的路径 ditto, for parameterized paths? */
bool consider_parallel; /*是否考虑并行处理路径 consider parallel paths? */
/* default result targetlist for Paths scanning this relation */
struct PathTarget *reltarget; /*扫描该Relation时默认的结果 list of Vars/Exprs, cost, width */
/* materialization information */
List *pathlist; /*访问路径链表 Path structures */
List *ppilist; /*路径链表中使用参数化路径进行 ParamPathInfos used in pathlist */
List *partial_pathlist; /* partial Paths */
struct Path *cheapest_startup_path;//代价最低的启动路径
struct Path *cheapest_total_path;//代价最低的整体路径
struct Path *cheapest_unique_path;//代价最低的获取唯一值的路径
List *cheapest_parameterized_paths;//代价最低的参数化?路径链表
/* parameterization information needed for both base rels and join rels */
/* (see also lateral_vars and lateral_referencers) */
Relids direct_lateral_relids; /*使用lateral语法,需依赖的Relids rels directly laterally referenced */
Relids lateral_relids; /* minimum parameterization of rel */
/* information about a base rel (not set for join rels!) */
//reloptkind=RELOPT_BASEREL时使用的数据结构
Index relid; /* Relation ID */
Oid reltablespace; /* 表空间 containing tablespace */
RTEKind rtekind; /* 基表?子查询?还是函数等等?RELATION, SUBQUERY, FUNCTION, etc */
AttrNumber min_attr; /* 最小的属性编号 smallest attrno of rel (often <0) */
AttrNumber max_attr; /* 最大的属性编号 largest attrno of rel */
Relids *attr_needed; /* 数组 array indexed [min_attr .. max_attr] */
int32 *attr_widths; /* 属性宽度 array indexed [min_attr .. max_attr] */
List *lateral_vars; /* 关系依赖的Vars/PHVs LATERAL Vars and PHVs referenced by rel */
Relids lateral_referencers; /*依赖该关系的Relids rels that reference me laterally */
List *indexlist; /* 该关系的IndexOptInfo链表 list of IndexOptInfo */
List *statlist; /* 统计信息链表 list of StatisticExtInfo */
BlockNumber pages; /* 块数 size estimates derived from pg_class */
double tuples; /* 元组数 */
double allvisfrac; /* ? */
PlannerInfo *subroot; /* 如为子查询,存储子查询的root if subquery */
List *subplan_params; /* 如为子查询,存储子查询的参数 if subquery */
int rel_parallel_workers; /* 并行执行,需要多少个workers? wanted number of parallel workers */
/* Information about foreign tables and foreign joins */
//FWD相关信息
Oid serverid; /* identifies server for the table or join */
Oid userid; /* identifies user to check access as */
bool useridiscurrent; /* join is only valid for current user */
/* use "struct FdwRoutine" to avoid including fdwapi.h here */
struct FdwRoutine *fdwroutine;
void *fdw_private;
/* cache space for remembering if we have proven this relation unique */
//已知的,可保证唯一的Relids链表
List *unique_for_rels; /* known unique for these other relid
* set(s) */
List *non_unique_for_rels; /* 已知的,不唯一的Relids链表 known not unique for these set(s) */
/* used by various scans and joins: */
List *baserestrictinfo; /* 如为基本关系,存储约束条件 RestrictInfo structures (if base rel) */
QualCost baserestrictcost; /* 解析约束表达式的成本? cost of evaluating the above */
Index baserestrict_min_security; /* 最低安全等级 min security_level found in
* baserestrictinfo */
List *joininfo; /* 连接语句的约束条件信息 RestrictInfo structures for join clauses
* involving this rel */
bool has_eclass_joins; /* 是否存在等价类连接? T means joininfo is incomplete */
/* used by partitionwise joins: */
bool consider_partitionwise_join; /* 分区? consider partitionwise
* join paths? (if
* partitioned rel) */
Relids top_parent_relids; /* Relids of topmost parents (if "other"
* rel) */
/* used for partitioned relations */
//分区表使用
PartitionScheme part_scheme; /* 分区的schema Partitioning scheme. */
int nparts; /* 分区数 number of partitions */
struct PartitionBoundInfoData *boundinfo; /* 分区边界信息 Partition bounds */
List *partition_qual; /* 分区约束 partition constraint */
struct RelOptInfo **part_rels; /* 分区的RelOptInfo数组 Array of RelOptInfos of partitions,
* stored in the same order of bounds */
List **partexprs; /* 非空分区键表达式 Non-nullable partition key expressions. */
List **nullable_partexprs; /* 可为空的分区键表达式 Nullable partition key expressions. */
List *partitioned_child_rels; /* RT Indexes链表 List of RT indexes. */
} RelOptInfo;make_one_rel函数调用了set_base_rel_sizes,该函数的主要实现逻辑通过调用set_rel_size实现.现重点考察函数set_rel_size中对基础关系进行估算的处理逻辑,即函数set_plain_rel_size的实现逻辑.
set_plain_rel_size
/*
* set_plain_rel_size
* Set size estimates for a plain relation (no subquery, no inheritance)
*/
static void
set_plain_rel_size(PlannerInfo *root, RelOptInfo *rel, RangeTblEntry *rte)
{
/*
* Test any partial indexes of rel for applicability. We must do this
* first since partial unique indexes can affect size estimates.
*/
check_index_predicates(root, rel);//验证部分(条件)索引的可用性
/* Mark rel with estimated output rows, width, etc */
set_baserel_size_estimates(root, rel);//标记rel的输出行数/行宽等信息
}set_plain_rel_size->check_index_predicates
如果部分(条件)索引的谓词与查询语句相匹配,则predOK设置为true
比如:
数据表t1(c1 int,c2 varchar(40),...),如存在索引idx_t1_partial_c1,条件为where c1 > 100
查询条件为where c1 > 100(是否支持>200?),那么该谓词与查询条件相匹配
//----------------------------------------- check_index_predicates
/*
* check_index_predicates
* Set the predicate-derived IndexOptInfo fields for each index
* of the specified relation.
*
* predOK is set true if the index is partial and its predicate is satisfied
* for this query, ie the query's WHERE clauses imply the predicate.
* 如果部分(条件)索引的谓词与查询语句相匹配,则predOK设置为true
* 比如:
* 数据表t1(c1 int,c2 varchar(40),...),如存在索引idx_t1_partial_c1,条件为where c1 > 100
* 查询条件为where c1 > 100(是否支持>200?),那么该谓词与查询条件相匹配
*
* indrestrictinfo is set to the relation's baserestrictinfo list less any
* conditions that are implied by the index's predicate. (Obviously, for a
* non-partial index, this is the same as baserestrictinfo.) Such conditions
* can be dropped from the plan when using the index, in certain cases.
*
* indrestrictinfo会加入到rel的baserestrictinfo链表中,减少了索引谓词所隐含的限制条件.
*
* At one time it was possible for this to get re-run after adding more
* restrictions to the rel, thus possibly letting us prove more indexes OK.
* That doesn't happen any more (at least not in the core code's usage),
* but this code still supports it in case extensions want to mess with the
* baserestrictinfo list. We assume that adding more restrictions can't make
* an index not predOK. We must recompute indrestrictinfo each time, though,
* to make sure any newly-added restrictions get into it if needed.
*/
void
check_index_predicates(PlannerInfo *root, RelOptInfo *rel)
{
List *clauselist;//条件链表
bool have_partial;//是否包含部分索引
bool is_target_rel;//目标rel?
Relids otherrels;//Relids
ListCell *lc;//临时变量
/* Indexes are available only on base or "other" member relations. */
Assert(IS_SIMPLE_REL(rel));//rel必须是基础关系
/*
* Initialize the indrestrictinfo lists to be identical to
* baserestrictinfo, and check whether there are any partial indexes. If
* not, this is all we need to do.
*/
have_partial = false;
foreach(lc, rel->indexlist)//遍历index
{
IndexOptInfo *index = (IndexOptInfo *) lfirst(lc);
index->indrestrictinfo = rel->baserestrictinfo;//设置索引约束条件
if (index->indpred)
have_partial = true;//存在部分索引
}
if (!have_partial)
return;
/*
* Construct a list of clauses that we can assume true for the purpose of
* proving the index(es) usable. Restriction clauses for the rel are
* always usable, and so are any join clauses that are "movable to" this
* rel. Also, we can consider any EC-derivable join clauses (which must
* be "movable to" this rel, by definition).
*/
clauselist = list_copy(rel->baserestrictinfo);//条件语句初始化
/* Scan the rel's join clauses */
foreach(lc, rel->joininfo)//遍历连接条件
{
RestrictInfo *rinfo = (RestrictInfo *) lfirst(lc);//条件
/* Check if clause can be moved to this rel */
if (!join_clause_is_movable_to(rinfo, rel))//条件是否可以下推到Rel中
continue;//不可用,下一个条件
clauselist = lappend(clauselist, rinfo);//可以,则添加到条件语句链表中
}
/*
* Add on any equivalence-derivable join clauses. Computing the correct
* relid sets for generate_join_implied_equalities is slightly tricky
* because the rel could be a child rel rather than a true baserel, and in
* that case we must remove its parents' relid(s) from all_baserels.
*/
if (rel->reloptkind == RELOPT_OTHER_MEMBER_REL)
otherrels = bms_difference(root->all_baserels,
find_childrel_parents(root, rel));//
else
otherrels = bms_difference(root->all_baserels, rel->relids);//获取与rel无关的其他rels
if (!bms_is_empty(otherrels))
clauselist =
list_concat(clauselist,
generate_join_implied_equalities(root,
bms_union(rel->relids,
otherrels),
otherrels,
rel));//添加到条件语句
/*
* Normally we remove quals that are implied by a partial index's
* predicate from indrestrictinfo, indicating that they need not be
* checked explicitly by an indexscan plan using this index. However, if
* the rel is a target relation of UPDATE/DELETE/SELECT FOR UPDATE, we
* cannot remove such quals from the plan, because they need to be in the
* plan so that they will be properly rechecked by EvalPlanQual testing.
* Some day we might want to remove such quals from the main plan anyway
* and pass them through to EvalPlanQual via a side channel; but for now,
* we just don't remove implied quals at all for target relations.
*/
is_target_rel = (rel->relid == root->parse->resultRelation ||
get_plan_rowmark(root->rowMarks, rel->relid) != NULL);
/*
* Now try to prove each index predicate true, and compute the
* indrestrictinfo lists for partial indexes. Note that we compute the
* indrestrictinfo list even for non-predOK indexes; this might seem
* wasteful, but we may be able to use such indexes in OR clauses, cf
* generate_bitmap_or_paths().
*/
foreach(lc, rel->indexlist)//遍历index
{
IndexOptInfo *index = (IndexOptInfo *) lfirst(lc);
ListCell *lcr;
if (index->indpred == NIL)
continue; /* ignore non-partial indexes here */
if (!index->predOK) /* don't repeat work if already proven OK */
index->predOK = predicate_implied_by(index->indpred, clauselist,
false);//设置predOK参数
/* If rel is an update target, leave indrestrictinfo as set above */
if (is_target_rel)
continue;
/* Else compute indrestrictinfo as the non-implied quals */
index->indrestrictinfo = NIL;
foreach(lcr, rel->baserestrictinfo)
{
RestrictInfo *rinfo = (RestrictInfo *) lfirst(lcr);
/* predicate_implied_by() assumes first arg is immutable */
if (contain_mutable_functions((Node *) rinfo->clause) ||
!predicate_implied_by(list_make1(rinfo->clause),
index->indpred, false))
index->indrestrictinfo = lappend(index->indrestrictinfo, rinfo);//
}
}
}set_plain_rel_size->set_baserel_size_estimates
函数注释:
//----------------------------------------- set_baserel_size_estimates /* * set_baserel_size_estimates * Set the size estimates for the given base relation. * 估算base rel的估算大小 * * The rel's targetlist and restrictinfo list must have been constructed * already, and rel->tuples must be set. * rel的targetlist和限制条件链表已构建,并且tuples已获取. * * We set the following fields of the rel node: * 通过该方法,设置以下3个变量 * rows: the estimated number of output tuples (after applying * restriction clauses). * 应用限制条件后,估算得出的输出元组数目 * width: the estimated average output tuple width in bytes. * 以字节为单位输出估算的平均元组大小 * baserestrictcost: estimated cost of evaluating baserestrictinfo clauses. * 解析限制条件的估算成本 */
源代码:
void
set_baserel_size_estimates(PlannerInfo *root, RelOptInfo *rel)
{
double nrows;
/* Should only be applied to base relations */
Assert(rel->relid > 0);
nrows = rel->tuples *
clauselist_selectivity(root,
rel->baserestrictinfo,
0,
JOIN_INNER,
NULL);//元组总数*选择率
rel->rows = clamp_row_est(nrows);
cost_qual_eval(&rel->baserestrictcost, rel->baserestrictinfo, root);
set_rel_width(root, rel);
}
//----------------------------------------- clauselist_selectivity
/*
* clauselist_selectivity -
* Compute the selectivity of an implicitly-ANDed list of boolean
* expression clauses. The list can be empty, in which case 1.0
* must be returned. List elements may be either RestrictInfos
* or bare expression clauses --- the former is preferred since
* it allows caching of results.
*
* 计算布尔表达式条件(隐式AND条件语句链表保存)的选择性.如果链表为空,
* 则返回1.0.链表中的元素可以是RestrictInfo结构体,也可以是裸条件表达式
* (前者因为允许缓存,因此是首选)
*
* See clause_selectivity() for the meaning of the additional parameters.
*
* Our basic approach is to take the product of the selectivities of the
* subclauses. However, that's only right if the subclauses have independent
* probabilities, and in reality they are often NOT independent. So,
* we want to be smarter where we can.
*
* 采取的基本方法是subclauses的选择性乘积。采取这种做法的前台是子项具有独立的概率.
* 但实际上它们往往不是独立的,因此,需要在能做到的地方变得更好。
*
* If the clauses taken together refer to just one relation, we'll try to
* apply selectivity estimates using any extended statistics for that rel.
* Currently we only have (soft) functional dependencies, so apply these in as
* many cases as possible, and fall back on normal estimates for remaining
* clauses.
*
* 如果在一起的子句只涉及一个关系，将尝试应用关系上的扩展统计进行选择性的估算。
*
* We also recognize "range queries", such as "x > 34 AND x < 42". Clauses
* are recognized as possible range query components if they are restriction
* opclauses whose operators have scalarltsel or a related function as their
* restriction selectivity estimator. We pair up clauses of this form that
* refer to the same variable. An unpairable clause of this kind is simply
* multiplied into the selectivity product in the normal way. But when we
* find a pair, we know that the selectivities represent the relative
* positions of the low and high bounds within the column's range, so instead
* of figuring the selectivity as hisel * losel, we can figure it as hisel +
* losel - 1. (To visualize this, see that hisel is the fraction of the range
* below the high bound, while losel is the fraction above the low bound; so
* hisel can be interpreted directly as a 0..1 value but we need to convert
* losel to 1-losel before interpreting it as a value. Then the available
* range is 1-losel to hisel. However, this calculation double-excludes
* nulls, so really we need hisel + losel + null_frac - 1.)
*
* 优化器还可以识别范围查询,比如x > 34 AND x < 42,这类范围查询不能简单的把x > 34
* 的选择率乘以x < 42的选择率,为方便起见,假定x < 42的选择率为hisel,x < 34的选择率为losel,
* 那么计算公式应该为hisel - (1 - losel),即hisel + losel -1,考虑NULL值,则范围查询的选择率
* 为hisel + losel + null_frac - 1
*
* If either selectivity is exactly DEFAULT_INEQ_SEL, we forget this equation
* and instead use DEFAULT_RANGE_INEQ_SEL. The same applies if the equation
* yields an impossible (negative) result.
*
* 如果任意一个选择性都恰好是DEFAULT_INEQ_SEL，那么我们将忘记这个等式，
* 而使用DEFAULT_RANGE_INEQ_SEL。这种情况同样适用于如果等式产生了一个不可能的(负的)结果。
*
* A free side-effect is that we can recognize redundant inequalities such
* as "x < 4 AND x < 5"; only the tighter constraint will be counted.
*
* 我们可以识别冗余的不等式,比如x < 4 AND x <5,只有严格的约束条件才会计算在内
*
* Of course this is all very dependent on the behavior of the inequality
* selectivity functions; perhaps some day we can generalize the approach.
*
* 这完全取决于不等选择性函数的行为,也许有一天我们可以推广这种方法.
*
*/
Selectivity
clauselist_selectivity(PlannerInfo *root,
List *clauses,
int varRelid,
JoinType jointype,
SpecialJoinInfo *sjinfo)
{
Selectivity s1 = 1.0;//默认返回值
RelOptInfo *rel;//
Bitmapset *estimatedclauses = NULL;//位图集合
RangeQueryClause *rqlist = NULL;//范围查询语句
ListCell *l;//临时变量
int listidx;
/*
* If there's exactly one clause, just go directly to
* clause_selectivity(). None of what we might do below is relevant.
*/
if (list_length(clauses) == 1)
return clause_selectivity(root, (Node *) linitial(clauses),
varRelid, jointype, sjinfo);//单个条件
/*
* Determine if these clauses reference a single relation. If so, and if
* it has extended statistics, try to apply those.
*/
//如果条件链表中的元素依赖的rel有且只有一个,则返回此rel
rel = find_single_rel_for_clauses(root, clauses);
//应用dependencies_clauselist_selectivity中的可用的条件进行选择率估算
if (rel && rel->rtekind == RTE_RELATION && rel->statlist != NIL)
{
/*
* Perform selectivity estimations on any clauses found applicable by
* dependencies_clauselist_selectivity. 'estimatedclauses' will be
* filled with the 0-based list positions of clauses used that way, so
* that we can ignore them below.
*/
s1 *= dependencies_clauselist_selectivity(root, clauses, varRelid,
jointype, sjinfo, rel,
&estimatedclauses);
/*
* This would be the place to apply any other types of extended
* statistics selectivity estimations for remaining clauses.
*/
}
/*
* Apply normal selectivity estimates for remaining clauses. We'll be
* careful to skip any clauses which were already estimated above.
* 剩下的条件语句,应用常规的选择率估算.
*
* Anything that doesn't look like a potential rangequery clause gets
* multiplied into s1 and forgotten. Anything that does gets inserted into
* an rqlist entry.
* 非范围条件语句乘上s1后被丢弃,范围条件语句则加入到rqlist链表中.
*/
listidx = -1;
foreach(l, clauses)//遍历
{
Node *clause = (Node *) lfirst(l);//链表中的元素
RestrictInfo *rinfo;
Selectivity s2;
listidx++;
/*
* Skip this clause if it's already been estimated by some other
* statistics above.
*/
if (bms_is_member(listidx, estimatedclauses))//跳过已处理的条件
continue;
/* Always compute the selectivity using clause_selectivity */
s2 = clause_selectivity(root, clause, varRelid, jointype, sjinfo);//获取条件选择率
/*
* Check for being passed a RestrictInfo.
*
* If it's a pseudoconstant RestrictInfo, then s2 is either 1.0 or
* 0.0; just use that rather than looking for range pairs.
*/
if (IsA(clause, RestrictInfo))//条件语句是RestrictInfo类型
{
rinfo = (RestrictInfo *) clause;
if (rinfo->pseudoconstant)//常量
{
s1 = s1 * s2;//直接相乘
continue;
}
clause = (Node *) rinfo->clause;//条件表达式
}
else
rinfo = NULL;//不是RestrictInfo类型,rinfo设置为NULL
/*
* See if it looks like a restriction clause with a pseudoconstant on
* one side. (Anything more complicated than that might not behave in
* the simple way we are expecting.) Most of the tests here can be
* done more efficiently with rinfo than without.
*/
if (is_opclause(clause) && list_length(((OpExpr *) clause)->args) == 2)//OpExpr
{
OpExpr *expr = (OpExpr *) clause;//条件语句
bool varonleft = true;
bool ok;
if (rinfo)//rinfo中的条件语句
{
ok = (bms_membership(rinfo->clause_relids) == BMS_SINGLETON) &&
(is_pseudo_constant_clause_relids(lsecond(expr->args),
rinfo->right_relids) ||
(varonleft = false,
is_pseudo_constant_clause_relids(linitial(expr->args),
rinfo->left_relids)));
}
else//裸条件语句
{
ok = (NumRelids(clause) == 1) &&
(is_pseudo_constant_clause(lsecond(expr->args)) ||
(varonleft = false,
is_pseudo_constant_clause(linitial(expr->args))));
}
if (ok)//校验通过
{
/*
* If it's not a "<"/"<="/">"/">=" operator, just merge the
* selectivity in generically. But if it's the right oprrest,
* add the clause to rqlist for later processing.
*/
switch (get_oprrest(expr->opno))
{
case F_SCALARLTSEL:
case F_SCALARLESEL:
addRangeClause(&rqlist, clause,
varonleft, true, s2);//范围条件
break;
case F_SCALARGTSEL:
case F_SCALARGESEL:
addRangeClause(&rqlist, clause,
varonleft, false, s2);//范围条件
break;
default:
/* Just merge the selectivity in generically */
s1 = s1 * s2;//直接相乘
break;
}
continue; /* drop to loop bottom */
}
}
/* Not the right form, so treat it generically. */
s1 = s1 * s2;//直接相乘
}
/*
* Now scan the rangequery pair list.
*/
while (rqlist != NULL)//处理范围条件
{
RangeQueryClause *rqnext;
if (rqlist->have_lobound && rqlist->have_hibound)//存在上下限
{
/* Successfully matched a pair of range clauses */
Selectivity s2;//选择率
/*
* Exact equality to the default value probably means the
* selectivity function punted. This is not airtight but should
* be good enough.
*/
if (rqlist->hibound == DEFAULT_INEQ_SEL ||
rqlist->lobound == DEFAULT_INEQ_SEL)//默认值
{
s2 = DEFAULT_RANGE_INEQ_SEL;//默认为DEFAULT_RANGE_INEQ_SEL
}
else
{
s2 = rqlist->hibound + rqlist->lobound - 1.0;//计算公式在注释已解释
/* Adjust for double-exclusion of NULLs */
s2 += nulltestsel(root, IS_NULL, rqlist->var,
varRelid, jointype, sjinfo);//NULL值
/*
* A zero or slightly negative s2 should be converted into a
* small positive value; we probably are dealing with a very
* tight range and got a bogus result due to roundoff errors.
* However, if s2 is very negative, then we probably have
* default selectivity estimates on one or both sides of the
* range that we failed to recognize above for some reason.
*/
if (s2 <= 0.0)//小于0?
{
if (s2 < -0.01)
{
/*
* No data available --- use a default estimate that
* is small, but not real small.
*/
s2 = DEFAULT_RANGE_INEQ_SEL;//小于﹣1%,默认值
}
else
{
/*
* It's just roundoff error; use a small positive
* value
*/
s2 = 1.0e-10;,//否则设置为1的﹣10次方
}
}
}
/* Merge in the selectivity of the pair of clauses */
s1 *= s2;//直接相乘
}
else//只有其中一个限制
{
/* Only found one of a pair, merge it in generically */
if (rqlist->have_lobound)
s1 *= rqlist->lobound;//下限
else
s1 *= rqlist->hibound;//上限
}
/* release storage and advance */
rqnext = rqlist->next;//释放资源
pfree(rqlist);
rqlist = rqnext;
}
return s1;//返回选择率
}
/*
* clause_selectivity -
* Compute the selectivity of a general boolean expression clause.
* 计算布尔表达式条件语句的选择率
*
* The clause can be either a RestrictInfo or a plain expression. If it's
* a RestrictInfo, we try to cache the selectivity for possible re-use,
* so passing RestrictInfos is preferred.
* clause可以是RestrictInfo结构体或者是常规的表达式.如果是RestrictInfo,
* 那么我们会尝试缓存结果已便于重用.
*
* varRelid is either 0 or a rangetable index.
* varRelid是0或者是RTE编号
*
* When varRelid is not 0, only variables belonging to that relation are
* considered in computing selectivity; other vars are treated as constants
* of unknown values. This is appropriate for estimating the selectivity of
* a join clause that is being used as a restriction clause in a scan of a
* nestloop join's inner relation --- varRelid should then be the ID of the
* inner relation.
* 如果varRelid不为0,只有属于该Rel的变量才会考虑计算选择率,其他变量作为未知常量处理
* 这种情况常见于嵌套循环内表的选择率估算(varRelid是内部的RTE)
*
* When varRelid is 0, all variables are treated as variables. This
* is appropriate for ordinary join clauses and restriction clauses.
* 如果varRelid为0,所有的变量都需要考虑,用于常规的连接条件和限制条件估算
*
*
* jointype is the join type, if the clause is a join clause. Pass JOIN_INNER
* if the clause isn't a join clause.
* 如果条件是连接条件,那么jointype是连接类型,如果不是连接调整,则该参数为JOIN_INNER
*
* sjinfo is NULL for a non-join clause, otherwise it provides additional
* context information about the join being performed. There are some
* special cases:
* 1. For a special (not INNER) join, sjinfo is always a member of
* root->join_info_list.非INNER_JOIN,sjinfo通常是oot->join_info_list的一个元素
* 2. For an INNER join, sjinfo is just a transient struct, and only the
* relids and jointype fields in it can be trusted.INNER_JOIN,sjinfo通常是临时的结构
* It is possible for jointype to be different from sjinfo->jointype.//jointype可能跟sjinfo中的jointype不同
* This indicates we are considering a variant join: either with
* the LHS and RHS switched, or with one input unique-ified.这意味着连接有可能会变换
*
* Note: when passing nonzero varRelid, it's normally appropriate to set
* jointype == JOIN_INNER, sjinfo == NULL, even if the clause is really a
* join clause; because we aren't treating it as a join clause.
*/
Selectivity
clause_selectivity(PlannerInfo *root,
Node *clause,
int varRelid,
JoinType jointype,
SpecialJoinInfo *sjinfo)
{
Selectivity s1 = 0.5; /* 默认值,default for any unhandled clause type */
RestrictInfo *rinfo = NULL;
bool cacheable = false;
if (clause == NULL) /* can this still happen? */
return s1;
if (IsA(clause, RestrictInfo))//RestrictInfo
{
rinfo = (RestrictInfo *) clause;
/*
* If the clause is marked pseudoconstant, then it will be used as a
* gating qual and should not affect selectivity estimates; hence
* return 1.0. The only exception is that a constant FALSE may be
* taken as having selectivity 0.0, since it will surely mean no rows
* out of the plan. This case is simple enough that we need not
* bother caching the result.
*/
if (rinfo->pseudoconstant)//pseudoconstant,不影响选择率
{
if (!IsA(rinfo->clause, Const))
return (Selectivity) 1.0;//返回1.0
}
/*
* If the clause is marked redundant, always return 1.0.
*/
if (rinfo->norm_selec > 1)
return (Selectivity) 1.0;//返回1.0
/*
* If possible, cache the result of the selectivity calculation for
* the clause. We can cache if varRelid is zero or the clause
* contains only vars of that relid --- otherwise varRelid will affect
* the result, so mustn't cache. Outer join quals might be examined
* with either their join's actual jointype or JOIN_INNER, so we need
* two cache variables to remember both cases. Note: we assume the
* result won't change if we are switching the input relations or
* considering a unique-ified case, so we only need one cache variable
* for all non-JOIN_INNER cases.
*/
if (varRelid == 0 ||
bms_is_subset_singleton(rinfo->clause_relids, varRelid))//varRelid为0
{
/* Cacheable --- do we already have the result? */
if (jointype == JOIN_INNER)
{
if (rinfo->norm_selec >= 0)
return rinfo->norm_selec;
}
else
{
if (rinfo->outer_selec >= 0)
return rinfo->outer_selec;
}
cacheable = true;
}
/*
* Proceed with examination of contained clause. If the clause is an
* OR-clause, we want to look at the variant with sub-RestrictInfos,
* so that per-subclause selectivities can be cached.
*/
if (rinfo->orclause)
clause = (Node *) rinfo->orclause;
else
clause = (Node *) rinfo->clause;
}
if (IsA(clause, Var))//Var
{
Var *var = (Var *) clause;
/*
* We probably shouldn't ever see an uplevel Var here, but if we do,
* return the default selectivity...
*/
if (var->varlevelsup == 0 &&
(varRelid == 0 || varRelid == (int) var->varno))
{
/* Use the restriction selectivity function for a bool Var */
s1 = boolvarsel(root, (Node *) var, varRelid);//bool Var选择率
}
}
else if (IsA(clause, Const))//常量
{
/* bool constant is pretty easy... */
Const *con = (Const *) clause;
s1 = con->constisnull ? 0.0 :
DatumGetBool(con->constvalue) ? 1.0 : 0.0;//常量有效则为1.0,否则为0.0
}
else if (IsA(clause, Param))//参数
{
/* see if we can replace the Param */
Node *subst = estimate_expression_value(root, clause);
if (IsA(subst, Const))
{
/* bool constant is pretty easy... */
Const *con = (Const *) subst;
s1 = con->constisnull ? 0.0 :
DatumGetBool(con->constvalue) ? 1.0 : 0.0;
}
else
{
/* XXX any way to do better than default? */
}
}
else if (not_clause(clause))//反选
{
/* inverse of the selectivity of the underlying clause */
s1 = 1.0 - clause_selectivity(root,
(Node *) get_notclausearg((Expr *) clause),
varRelid,
jointype,
sjinfo);
}
else if (and_clause(clause))//AND语句
{
/* share code with clauselist_selectivity() */
s1 = clauselist_selectivity(root,
((BoolExpr *) clause)->args,
varRelid,
jointype,
sjinfo);//递归调用
}
else if (or_clause(clause))//OR语句
{
/*
* Selectivities for an OR clause are computed as s1+s2 - s1*s2 to
* account for the probable overlap of selected tuple sets.
*
* XXX is this too conservative?
*/
ListCell *arg;
s1 = 0.0;
foreach(arg, ((BoolExpr *) clause)->args)
{
Selectivity s2 = clause_selectivity(root,
(Node *) lfirst(arg),
varRelid,
jointype,
sjinfo);//递归调用
s1 = s1 + s2 - s1 * s2;
}
}
else if (is_opclause(clause) || IsA(clause, DistinctExpr))
{
OpExpr *opclause = (OpExpr *) clause;
Oid opno = opclause->opno;
if (treat_as_join_clause(clause, rinfo, varRelid, sjinfo))
{
/* Estimate selectivity for a join clause. */
s1 = join_selectivity(root, opno,
opclause->args,
opclause->inputcollid,
jointype,
sjinfo);//连接条件
}
else
{
/* Estimate selectivity for a restriction clause. */
s1 = restriction_selectivity(root, opno,
opclause->args,
opclause->inputcollid,
varRelid);//限制条件
}
/*
* DistinctExpr has the same representation as OpExpr, but the
* contained operator is "=" not "<>", so we must negate the result.
* This estimation method doesn't give the right behavior for nulls,
* but it's better than doing nothing.
*/
if (IsA(clause, DistinctExpr))
s1 = 1.0 - s1;//Distinct?
}
else if (IsA(clause, ScalarArrayOpExpr))//数组
{
/* Use node specific selectivity calculation function */
s1 = scalararraysel(root,
(ScalarArrayOpExpr *) clause,
treat_as_join_clause(clause, rinfo,
varRelid, sjinfo),
varRelid,
jointype,
sjinfo);
}
else if (IsA(clause, RowCompareExpr))//行对比
{
/* Use node specific selectivity calculation function */
s1 = rowcomparesel(root,
(RowCompareExpr *) clause,
varRelid,
jointype,
sjinfo);
}
else if (IsA(clause, NullTest))//NullTest
{
/* Use node specific selectivity calculation function */
s1 = nulltestsel(root,
((NullTest *) clause)->nulltesttype,
(Node *) ((NullTest *) clause)->arg,
varRelid,
jointype,
sjinfo);
}
else if (IsA(clause, BooleanTest))//BooleanTest
{
/* Use node specific selectivity calculation function */
s1 = booltestsel(root,
((BooleanTest *) clause)->booltesttype,
(Node *) ((BooleanTest *) clause)->arg,
varRelid,
jointype,
sjinfo);
}
else if (IsA(clause, CurrentOfExpr))//CurrentOfExpr
{
/* CURRENT OF selects at most one row of its table */
CurrentOfExpr *cexpr = (CurrentOfExpr *) clause;
RelOptInfo *crel = find_base_rel(root, cexpr->cvarno);
if (crel->tuples > 0)
s1 = 1.0 / crel->tuples;
}
else if (IsA(clause, RelabelType))//RelabelType
{
/* Not sure this case is needed, but it can't hurt */
s1 = clause_selectivity(root,
(Node *) ((RelabelType *) clause)->arg,
varRelid,
jointype,
sjinfo);
}
else if (IsA(clause, CoerceToDomain))//CoerceToDomain
{
/* Not sure this case is needed, but it can't hurt */
s1 = clause_selectivity(root,
(Node *) ((CoerceToDomain *) clause)->arg,
varRelid,
jointype,
sjinfo);
}
else
{
/*
* For anything else, see if we can consider it as a boolean variable.
* This only works if it's an immutable expression in Vars of a single
* relation; but there's no point in us checking that here because
* boolvarsel() will do it internally, and return a suitable default
* selectivity if not.
*/
s1 = boolvarsel(root, clause, varRelid);//默认为bool Var
}
/* Cache the result if possible */
if (cacheable)//缓存?
{
if (jointype == JOIN_INNER)
rinfo->norm_selec = s1;
else
rinfo->outer_selec = s1;
}
#ifdef SELECTIVITY_DEBUG
elog(DEBUG4, "clause_selectivity: s1 %f", s1);
#endif /* SELECTIVITY_DEBUG */
return s1;
}
/*
* find_single_rel_for_clauses
* Examine each clause in 'clauses' and determine if all clauses
* reference only a single relation. If so return that relation,
* otherwise return NULL.
*
* 如果条件链表中的元素依赖的rel有且只有一个,则返回此rel
*/
static RelOptInfo *
find_single_rel_for_clauses(PlannerInfo *root, List *clauses)
{
int lastrelid = 0;
ListCell *l;
foreach(l, clauses)
{
RestrictInfo *rinfo = (RestrictInfo *) lfirst(l);
int relid;
/*
* If we have a list of bare clauses rather than RestrictInfos, we
* could pull out their relids the hard way with pull_varnos().
* However, currently the extended-stats machinery won't do anything
* with non-RestrictInfo clauses anyway, so there's no point in
* spending extra cycles; just fail if that's what we have.
*/
if (!IsA(rinfo, RestrictInfo))
return NULL;
if (bms_is_empty(rinfo->clause_relids))
continue; /* we can ignore variable-free clauses */
if (!bms_get_singleton_member(rinfo->clause_relids, &relid))
return NULL; /* multiple relations in this clause */
if (lastrelid == 0)
lastrelid = relid; /* first clause referencing a relation */
else if (relid != lastrelid)
return NULL; /* relation not same as last one */
}
if (lastrelid != 0)
return find_base_rel(root, lastrelid);
return NULL; /* no clauses */
}
//---------------------------------------------- clamp_row_est
/*
* clamp_row_est
* Force a row-count estimate to a sane value.
* 返回合法值
*/
double
clamp_row_est(double nrows)
{
/*
* Force estimate to be at least one row, to make explain output look
* better and to avoid possible divide-by-zero when interpolating costs.
* Make it an integer, too.
*/
if (nrows <= 1.0)
nrows = 1.0;//小于1,返回1
else
nrows = rint(nrows);//整型
return nrows;
}
//---------------------------------------------- cost_qual_eval
/*
* cost_qual_eval
* Estimate the CPU costs of evaluating a WHERE clause.
* The input can be either an implicitly-ANDed list of boolean
* expressions, or a list of RestrictInfo nodes. (The latter is
* preferred since it allows caching of the results.)
* The result includes both a one-time (startup) component,
* and a per-evaluation component.
*/
void
cost_qual_eval(QualCost *cost, List *quals, PlannerInfo *root)
{
cost_qual_eval_context context;
ListCell *l;
context.root = root;
context.total.startup = 0;
context.total.per_tuple = 0;
/* We don't charge any cost for the implicit ANDing at top level ... */
foreach(l, quals)
{
Node *qual = (Node *) lfirst(l);
cost_qual_eval_walker(qual, &context);
}
*cost = context.total;
}
//---------------------------------------------- set_rel_width
/*
* set_rel_width
* Set the estimated output width of a base relation.
*
* The estimated output width is the sum of the per-attribute width estimates
* for the actually-referenced columns, plus any PHVs or other expressions
* that have to be calculated at this relation. This is the amount of data
* we'd need to pass upwards in case of a sort, hash, etc.
*
* This function also sets reltarget->cost, so it's a bit misnamed now.
*
* NB: this works best on plain relations because it prefers to look at
* real Vars. For subqueries, set_subquery_size_estimates will already have
* copied up whatever per-column estimates were made within the subquery,
* and for other types of rels there isn't much we can do anyway. We fall
* back on (fairly stupid) datatype-based width estimates if we can't get
* any better number.
*
* The per-attribute width estimates are cached for possible re-use while
* building join relations or post-scan/join pathtargets.
*/
static void
set_rel_width(PlannerInfo *root, RelOptInfo *rel)
{
Oid reloid = planner_rt_fetch(rel->relid, root)->relid;
int32 tuple_width = 0;
bool have_wholerow_var = false;
ListCell *lc;
/* Vars are assumed to have cost zero, but other exprs do not */
rel->reltarget->cost.startup = 0;
rel->reltarget->cost.per_tuple = 0;
foreach(lc, rel->reltarget->exprs)
{
Node *node = (Node *) lfirst(lc);
/*
* Ordinarily, a Var in a rel's targetlist must belong to that rel;
* but there are corner cases involving LATERAL references where that
* isn't so. If the Var has the wrong varno, fall through to the
* generic case (it doesn't seem worth the trouble to be any smarter).
*/
if (IsA(node, Var) &&
((Var *) node)->varno == rel->relid)
{
Var *var = (Var *) node;
int ndx;
int32 item_width;
Assert(var->varattno >= rel->min_attr);
Assert(var->varattno <= rel->max_attr);
ndx = var->varattno - rel->min_attr;
/*
* If it's a whole-row Var, we'll deal with it below after we have
* already cached as many attr widths as possible.
*/
if (var->varattno == 0)
{
have_wholerow_var = true;
continue;
}
/*
* The width may have been cached already (especially if it's a
* subquery), so don't duplicate effort.
*/
if (rel->attr_widths[ndx] > 0)
{
tuple_width += rel->attr_widths[ndx];
continue;
}
/* Try to get column width from statistics */
if (reloid != InvalidOid && var->varattno > 0)
{
item_width = get_attavgwidth(reloid, var->varattno);
if (item_width > 0)
{
rel->attr_widths[ndx] = item_width;
tuple_width += item_width;
continue;
}
}
/*
* Not a plain relation, or can't find statistics for it. Estimate
* using just the type info.
*/
item_width = get_typavgwidth(var->vartype, var->vartypmod);
Assert(item_width > 0);
rel->attr_widths[ndx] = item_width;
tuple_width += item_width;
}
else if (IsA(node, PlaceHolderVar))
{
/*
* We will need to evaluate the PHV's contained expression while
* scanning this rel, so be sure to include it in reltarget->cost.
*/
PlaceHolderVar *phv = (PlaceHolderVar *) node;
PlaceHolderInfo *phinfo = find_placeholder_info(root, phv, false);
QualCost cost;
tuple_width += phinfo->ph_width;
cost_qual_eval_node(&cost, (Node *) phv->phexpr, root);
rel->reltarget->cost.startup += cost.startup;
rel->reltarget->cost.per_tuple += cost.per_tuple;
}
else
{
/*
* We could be looking at an expression pulled up from a subquery,
* or a ROW() representing a whole-row child Var, etc. Do what we
* can using the expression type information.
*/
int32 item_width;
QualCost cost;
item_width = get_typavgwidth(exprType(node), exprTypmod(node));
Assert(item_width > 0);
tuple_width += item_width;
/* Not entirely clear if we need to account for cost, but do so */
cost_qual_eval_node(&cost, node, root);
rel->reltarget->cost.startup += cost.startup;
rel->reltarget->cost.per_tuple += cost.per_tuple;
}
}
/*
* If we have a whole-row reference, estimate its width as the sum of
* per-column widths plus heap tuple header overhead.
*/
if (have_wholerow_var)
{
int32 wholerow_width = MAXALIGN(SizeofHeapTupleHeader);
if (reloid != InvalidOid)
{
/* Real relation, so estimate true tuple width */
wholerow_width += get_relation_data_width(reloid,
rel->attr_widths - rel->min_attr);
}
else
{
/* Do what we can with info for a phony rel */
AttrNumber i;
for (i = 1; i <= rel->max_attr; i++)
wholerow_width += rel->attr_widths[i - rel->min_attr];
}
rel->attr_widths[0 - rel->min_attr] = wholerow_width;
/*
* Include the whole-row Var as part of the output tuple. Yes, that
* really is what happens at runtime.
*/
tuple_width += wholerow_width;
}
Assert(tuple_width >= 0);
rel->reltarget->width = tuple_width;
}测试脚本:
单位信息表,插入100,000行数据,dwbh为主键,同时创建函数索引和部分索引
drop table if exists t_dwxx; create table t_dwxx(dwmc varchar(100),dwbh varchar(20),dwdz varchar(100)); alter table t_dwxx add primary key(dwbh); create index idx_dwxx_expr on t_dwxx(trim(dwmc)); create index idx_dwxx_predicate_dwbh on t_dwxx(dwbh) where dwbh > '50000'; truncate table t_dwxx; insert into t_dwxx(dwmc,dwbh,dwdz) select 'DWMC'||generate_series(1,100000),generate_series(1,100000)||'','DWDZ'||generate_series(1,100000);
个人信息表,插入5,000,000行数据,在grbh和dwbh上创建索引
drop table if exists t_grxx; create table t_grxx(dwbh varchar(10),grbh varchar(10),xm varchar(20),xb varchar(10),nl int); insert into t_grxx(dwbh,grbh,xm,xb,nl) select generate_series(1,5000000)/50||'',generate_series(1,5000000),'XM'||generate_series(1,5000000), (case when (floor(random()*2)=0) then '男' else '女' end),floor(random() * 100 + 1)::int; create index idx_t_grxx_grbh on t_grxx(grbh); create index idx_t_dwxx_grbh on t_grxx(dwbh);
个人缴费信息表,在grbh上创建索引,多次插入5,000,000行数据
drop table if exists t_jfxx; create table t_jfxx(grbh varchar(10),ny varchar(10),je float); -- 根据实际情况,多次执行以下SQL insert into t_jfxx(grbh,ny,je) select generate_series(1,5000000), to_char(now()::timestamp - (floor(random()*240+1)||' month')::interval,'yyyymm'), floor(random()*10000+1); create index idx_t_jfxx_grbh on t_jfxx(grbh);
执行简单的查询SQL:
select t1.* from t_dwxx t1 where dwbh > '60000' and dwbh < '70000' and dwbh < '65000';
执行计划如下:
testdb=# explain (analyze true,verbose) select t1.* from t_dwxx t1 where dwbh > '60000' and dwbh < '70000' and dwbh < '65000'; QUERY PLAN ----------------------------------------------------------------------------------------------------------------------------- ----------- Bitmap Heap Scan on public.t_dwxx t1 (cost=134.19..956.12 rows=5482 width=23) (actual time=1.484..2.744 rows=5554 loops=1) Output: dwmc, dwbh, dwdz Recheck Cond: (((t1.dwbh)::text > '60000'::text) AND ((t1.dwbh)::text < '70000'::text) AND ((t1.dwbh)::text < '65000'::tex t)) Heap Blocks: exact=45 -> Bitmap Index Scan on idx_dwxx_predicate_dwbh (cost=0.00..132.81 rows=5482 width=0) (actual time=1.467..1.467 rows=555 4 loops=1) Index Cond: (((t1.dwbh)::text > '60000'::text) AND ((t1.dwbh)::text < '70000'::text) AND ((t1.dwbh)::text < '65000': :text)) Planning Time: 0.204 ms Execution Time: 3.288 ms
启动gdb跟踪分析:
(gdb) b set_baserel_size_estimates Breakpoint 1 at 0x747bf5: file costsize.c, line 4302. (gdb) c Continuing. Breakpoint 1, set_baserel_size_estimates (root=0x2686fa8, rel=0x26873b8) at costsize.c:4302 4302 nrows = rel->tuples *
进入函数clauselist_selectivity:
(gdb) step
clauselist_selectivity (root=0x2686fa8, clauses=0x271f600, varRelid=0, jointype=JOIN_INNER, sjinfo=0x0) at clausesel.c:105
105 Selectivity s1 = 1.0;
...
124 rel = find_single_rel_for_clauses(root, clauses);
(gdb)
125 if (rel && rel->rtekind == RTE_RELATION && rel->statlist != NIL)
#与限制条件相关的rel(t_dwxx)
(gdb) p *rel
$1 = {type = T_RelOptInfo, reloptkind = RELOPT_BASEREL, relids = 0x2687728, rows = 0, consider_startup = false,
consider_param_startup = false, consider_parallel = true, reltarget = 0x271e228, pathlist = 0x0, ppilist = 0x0,
partial_pathlist = 0x0, cheapest_startup_path = 0x0, cheapest_total_path = 0x0, cheapest_unique_path = 0x0,
cheapest_parameterized_paths = 0x0, direct_lateral_relids = 0x0, lateral_relids = 0x0, relid = 1, reltablespace = 0,
rtekind = RTE_RELATION, min_attr = -7, max_attr = 3, attr_needed = 0x271e278, attr_widths = 0x271e308,
lateral_vars = 0x0, lateral_referencers = 0x0, indexlist = 0x271e700, statlist = 0x0, pages = 726, tuples = 100000,
allvisfrac = 0, subroot = 0x0, subplan_params = 0x0, rel_parallel_workers = -1, serverid = 0, userid = 0,
useridiscurrent = false, fdwroutine = 0x0, fdw_private = 0x0, unique_for_rels = 0x0, non_unique_for_rels = 0x0,
baserestrictinfo = 0x271f600, baserestrictcost = {startup = 0, per_tuple = 0}, baserestrict_min_security = 0,
joininfo = 0x0, has_eclass_joins = false, top_parent_relids = 0x0, part_scheme = 0x0, nparts = 0, boundinfo = 0x0,
partition_qual = 0x0, part_rels = 0x0, partexprs = 0x0, nullable_partexprs = 0x0, partitioned_child_rels = 0x0}开始循环处理:
152 foreach(l, clauses) ...
第一个条件语句,调用clause_selectivity后,选择率为0.44...
168 s2 = clause_selectivity(root, clause, varRelid, jointype, sjinfo); (gdb) 176 if (IsA(clause, RestrictInfo)) (gdb) p s2 $2 = 0.44045086705202319
添加到范围条件语句中:
... 225 switch (get_oprrest(expr->opno)) (gdb) 234 addRangeClause(&rqlist, clause, (gdb) 236 break;
第二个条件语句,调用clause_selectivity后,选择率为0.66...,,同样会添加到范围条件语句中:
168 s2 = clause_selectivity(root, clause, varRelid, jointype, sjinfo); (gdb) 176 if (IsA(clause, RestrictInfo)) (gdb) p s2 $3 = 0.66904390539053915 ... 225 switch (get_oprrest(expr->opno)) (gdb) 229 addRangeClause(&rqlist, clause,
第三个条件语句,调用clause_selectivity后,选择率为0.61...,,同样会添加到范围条件语句中:
168 s2 = clause_selectivity(root, clause, varRelid, jointype, sjinfo); (gdb) 176 if (IsA(clause, RestrictInfo)) (gdb) p s2 $4 = 0.61437297872340435 ... 225 switch (get_oprrest(expr->opno)) (gdb) 229 addRangeClause(&rqlist, clause,
结束循环,开始处理范围条件语句:
253 while (rqlist != NULL)
(gdb) n
#既有上限,也有下限
(gdb) p *rqlist
$7 = {next = 0x0, var = 0x271dba8, have_lobound = true, have_hibound = true, lobound = 0.44045086705202319,
hibound = 0.61437297872340435}
...
#计算公式注释已作介绍
(gdb) n
274 s2 = rqlist->hibound + rqlist->lobound - 1.0;
(gdb)
277 s2 += nulltestsel(root, IS_NULL, rqlist->var,
#最终结果
(gdb)
325 return s1;
(gdb) p s1
$11 = 0.054823845775427538
...回到主函数:
(gdb) set_baserel_size_estimates (root=0x2686fa8, rel=0x26873b8) at costsize.c:4302 4302 nrows = rel->tuples * (gdb) 4309 rel->rows = clamp_row_est(nrows); (gdb) 4311 cost_qual_eval(&rel->baserestrictcost, rel->baserestrictinfo, root); (gdb) 4313 set_rel_width(root, rel); (gdb) p rel->rows $12 = 5482
结果为5482,执行计划中的rows=5482就是这么来的.
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