本篇内容介绍了“PostgreSQL中Review subquery_planner函数的实现逻辑是什么”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！
subquery_planner函数由函数standard_planner调用,生成最终的结果Relation(成本最低),其输出作为生成实际执行计划的输入,在此函数中会调用grouping_planner执行主要的计划过程
/*--------------------
* subquery_planner
* Invokes the planner on a subquery. We recurse to here for each
* sub-SELECT found in the query tree.
* 对子查询进行执行规划。对于查询树中的每个子查询(sub-SELECT)，都会递归此处理过程。
*
* glob is the global state for the current planner run.
* parse is the querytree produced by the parser & rewriter.
* parent_root is the immediate parent Query's info (NULL at the top level).
* hasRecursion is true if this is a recursive WITH query.
* tuple_fraction is the fraction of tuples we expect will be retrieved.
* tuple_fraction is interpreted as explained for grouping_planner, below.
* glob-当前计划器运行的全局状态。
* parse-由解析器和重写器生成的查询树querytree。
* parent_root是父查询的信息(如为顶层则为空)。
* hasRecursion-如果这是一个带查询的递归，值为T。
* tuple_fraction-扫描元组的比例。tuple_fraction在grouping_planner中详细解释。
*
* Basically, this routine does the stuff that should only be done once
* per Query object. It then calls grouping_planner. At one time,
* grouping_planner could be invoked recursively on the same Query object;
* that's not currently true, but we keep the separation between the two
* routines anyway, in case we need it again someday.
* 基本上，这个函数包含完成了每个Query只需要执行一次的任务。
* 该函数调用grouping_planner一次。在同一个Query上，每次递归grouping_planner都调用一次;
* 当然，这不是通常的情况，但我们仍然保持这两个例程（subquery_planner和grouping_planner)之间的分离，
* 以防有一天我们再次需要它。
*
* subquery_planner will be called recursively to handle sub-Query nodes
* found within the query's expressions and rangetable.
* 函数subquery_planner将被递归调用，以处理表达式和RTE中的子查询节点。
*
* Returns the PlannerInfo struct ("root") that contains all data generated
* while planning the subquery. In particular, the Path(s) attached to
* the (UPPERREL_FINAL, NULL) upperrel represent our conclusions about the
* cheapest way(s) to implement the query. The top level will select the
* best Path and pass it through createplan.c to produce a finished Plan.
* 返回PlannerInfo struct(“root”)，它包含在计划子查询时生成的所有数据。
* 特别地，访问路径附加到(UPPERREL_FINAL, NULL) 上层关系中,以代表优化器已找到查询成本最低的方法.
* 顶层将选择最佳路径并将其通过createplan.c传递以制定一个已完成的计划。
*--------------------
*/
/*
输入:
glob-PlannerGlobal
parse-Query结构体指针
parent_root-父PlannerInfo Root节点
hasRecursion-是否递归?
tuple_fraction-扫描Tuple比例
输出:
PlannerInfo指针
*/
PlannerInfo *
subquery_planner(PlannerGlobal *glob, Query *parse,
PlannerInfo *parent_root,
bool hasRecursion, double tuple_fraction)
{
PlannerInfo *root;//返回值
List *newWithCheckOptions;//
List *newHaving;//Having子句
bool hasOuterJoins;//是否存在Outer Join?
RelOptInfo *final_rel;//
ListCell *l;//临时变量
/* Create a PlannerInfo data structure for this subquery */
//创建一个规划器数据结构:PlannerInfo
root = makeNode(PlannerInfo);//构造返回值
root->parse = parse;
root->glob = glob;
root->query_level = parent_root ? parent_root->query_level + 1 : 1;
root->parent_root = parent_root;
root->plan_params = NIL;
root->outer_params = NULL;
root->planner_cxt = CurrentMemoryContext;
root->init_plans = NIL;
root->cte_plan_ids = NIL;
root->multiexpr_params = NIL;
root->eq_classes = NIL;
root->append_rel_list = NIL;
root->rowMarks = NIL;
memset(root->upper_rels, 0, sizeof(root->upper_rels));
memset(root->upper_targets, 0, sizeof(root->upper_targets));
root->processed_tlist = NIL;
root->grouping_map = NULL;
root->minmax_aggs = NIL;
root->qual_security_level = 0;
root->inhTargetKind = INHKIND_NONE;
root->hasRecursion = hasRecursion;
if (hasRecursion)
root->wt_param_id = SS_assign_special_param(root);
else
root->wt_param_id = -1;
root->non_recursive_path = NULL;
root->partColsUpdated = false;
/*
* If there is a WITH list, process each WITH query and build an initplan
* SubPlan structure for it.
* 如果有一个WITH链表，使用查询处理每个链表，并为其构建一个initplan子计划结构。
*/
if (parse->cteList)
SS_process_ctes(root);//处理With 语句
/*
* Look for ANY and EXISTS SubLinks in WHERE and JOIN/ON clauses, and try
* to transform them into joins. Note that this step does not descend
* into subqueries; if we pull up any subqueries below, their SubLinks are
* processed just before pulling them up.
* 查找WHERE和JOIN/ON子句中的ANY/EXISTS子句，并尝试将它们转换为JOIN。
* 注意，此步骤不会下降为子查询;如果我们上拉子查询，它们的SubLinks将在调出它们上拉前被处理。
*/
if (parse->hasSubLinks)
pull_up_sublinks(root); //上拉子链接
/*
* Scan the rangetable for set-returning functions, and inline them if
* possible (producing subqueries that might get pulled up next).
* Recursion issues here are handled in the same way as for SubLinks.
* 扫描RTE中的set-returning函数，
* 如果可能，内联它们(生成下一个可能被上拉的子查询)。
* 这里递归问题的处理方式与SubLinks相同。
*/
inline_set_returning_functions(root);//
/*
* Check to see if any subqueries in the jointree can be merged into this
* query.
* 检查连接树中的子查询是否可以合并到该查询中(上拉子查询)
*/
pull_up_subqueries(root);//上拉子查询
/*
* If this is a simple UNION ALL query, flatten it into an appendrel. We
* do this now because it requires applying pull_up_subqueries to the leaf
* queries of the UNION ALL, which weren't touched above because they
* weren't referenced by the jointree (they will be after we do this).
* 如果这是一个简单的UNION ALL查询，则将其ftatten为appendrel结构。
* 我们现在这样做是因为它需要对UNION ALL的叶子查询应用pull_up_subqueries，
* 上面没有涉及到这些查询，因为它们没有被jointree引用(在我们这样做之后它们将被引用)。
*/
if (parse->setOperations)
flatten_simple_union_all(root);//扁平化处理UNION ALL
/*
* Detect whether any rangetable entries are RTE_JOIN kind; if not, we can
* avoid the expense of doing flatten_join_alias_vars(). Also check for
* outer joins --- if none, we can skip reduce_outer_joins(). And check
* for LATERAL RTEs, too. This must be done after we have done
* pull_up_subqueries(), of course.
* 检测是否有任何RTE中的元素是RTE_JOIN类型;如果没有，可以避免执行refin_join_alias_vars()的开销。
* 检查外部连接——如果没有，可以跳过reduce_outer_join()函数。同样的,我们会检查LATERAL RTEs。
* 当然，这必须在我们完成pull_up_subqueries()调用之后完成。
*/
//判断RTE中是否存在RTE_JOIN?
root->hasJoinRTEs = false;
root->hasLateralRTEs = false;
hasOuterJoins = false;
foreach(l, parse->rtable)
{
RangeTblEntry *rte = lfirst_node(RangeTblEntry, l);
if (rte->rtekind == RTE_JOIN)
{
root->hasJoinRTEs = true;
if (IS_OUTER_JOIN(rte->jointype))
hasOuterJoins = true;
}
if (rte->lateral)
root->hasLateralRTEs = true;
}
/*
* Preprocess RowMark information. We need to do this after subquery
* pullup (so that all non-inherited RTEs are present) and before
* inheritance expansion (so that the info is available for
* expand_inherited_tables to examine and modify).
* 预处理RowMark信息。
* 我们需要在子查询上拉(以便所有非继承的RTEs都存在)和继承展开之后完成
* (以便expand_inherited_tables可以使用这个信息来检查和修改)。
*/
//预处理RowMark信息
preprocess_rowmarks(root);
/*
* Expand any rangetable entries that are inheritance sets into "append
* relations". This can add entries to the rangetable, but they must be
* plain base relations not joins, so it's OK (and marginally more
* efficient) to do it after checking for join RTEs. We must do it after
* pulling up subqueries, else we'd fail to handle inherited tables in
* subqueries.
* 将继承集的任何可范围条目展开为“append relations”。
* 将相关的relation添加到RTE中，但它们必须是纯基础关系而不是连接，
* 因此在检查连接RTEs之后执行它是可以的(而且更有效)。
* 我们必须在启动子查询后执行，否则我们将无法在子查询中处理继承表。
*/
//展开继承表
expand_inherited_tables(root);
/*
* Set hasHavingQual to remember if HAVING clause is present. Needed
* because preprocess_expression will reduce a constant-true condition to
* an empty qual list ... but "HAVING TRUE" is not a semantic no-op.
* 如果存在HAVING子句，则务必设置hasHavingQual属性。
* 因为preprocess_expression将把constant-true条件减少为空的条件qual列表…
* 但是，“HAVING TRUE”并没有语义错误。
*/
//是否存在Having表达式
root->hasHavingQual = (parse->havingQual != NULL);
/* Clear this flag; might get set in distribute_qual_to_rels */
//清除hasPseudoConstantQuals标记,该标记可能在distribute_qual_to_rels函数中设置
root->hasPseudoConstantQuals = false;
/*
* Do expression preprocessing on targetlist and quals, as well as other
* random expressions in the querytree. Note that we do not need to
* handle sort/group expressions explicitly, because they are actually
* part of the targetlist.
* 对targetlist和quals以及querytree中的其他随机表达式进行表达式预处理。
* 注意，我们不需要显式地处理sort/group表达式，因为它们实际上是targetlist的一部分。
*/
//预处理表达式:targetList(投影列)
parse->targetList = (List *)
preprocess_expression(root, (Node *) parse->targetList,
EXPRKIND_TARGET);
/* Constant-folding might have removed all set-returning functions */
//Constant-folding 可能已经把set-returning函数去掉
if (parse->hasTargetSRFs)
parse->hasTargetSRFs = expression_returns_set((Node *) parse->targetList);
newWithCheckOptions = NIL;
foreach(l, parse->withCheckOptions)//witch Check Options
{
WithCheckOption *wco = lfirst_node(WithCheckOption, l);
wco->qual = preprocess_expression(root, wco->qual,
EXPRKIND_QUAL);
if (wco->qual != NULL)
newWithCheckOptions = lappend(newWithCheckOptions, wco);
}
parse->withCheckOptions = newWithCheckOptions;
//返回列信息returningList
parse->returningList = (List *)
preprocess_expression(root, (Node *) parse->returningList,
EXPRKIND_TARGET);
//预处理条件表达式
preprocess_qual_conditions(root, (Node *) parse->jointree);
//预处理Having表达式
parse->havingQual = preprocess_expression(root, parse->havingQual,
EXPRKIND_QUAL);
//窗口函数
foreach(l, parse->windowClause)
{
WindowClause *wc = lfirst_node(WindowClause, l);
/* partitionClause/orderClause are sort/group expressions */
wc->startOffset = preprocess_expression(root, wc->startOffset,
EXPRKIND_LIMIT);
wc->endOffset = preprocess_expression(root, wc->endOffset,
EXPRKIND_LIMIT);
}
//Limit子句
parse->limitOffset = preprocess_expression(root, parse->limitOffset,
EXPRKIND_LIMIT);
parse->limitCount = preprocess_expression(root, parse->limitCount,
EXPRKIND_LIMIT);
//On Conflict子句
if (parse->onConflict)
{
parse->onConflict->arbiterElems = (List *)
preprocess_expression(root,
(Node *) parse->onConflict->arbiterElems,
EXPRKIND_ARBITER_ELEM);
parse->onConflict->arbiterWhere =
preprocess_expression(root,
parse->onConflict->arbiterWhere,
EXPRKIND_QUAL);
parse->onConflict->onConflictSet = (List *)
preprocess_expression(root,
(Node *) parse->onConflict->onConflictSet,
EXPRKIND_TARGET);
parse->onConflict->onConflictWhere =
preprocess_expression(root,
parse->onConflict->onConflictWhere,
EXPRKIND_QUAL);
/* exclRelTlist contains only Vars, so no preprocessing needed */
}
//集合操作(AppendRelInfo)
root->append_rel_list = (List *)
preprocess_expression(root, (Node *) root->append_rel_list,
EXPRKIND_APPINFO);
//RTE
/* Also need to preprocess expressions within RTEs */
foreach(l, parse->rtable)
{
RangeTblEntry *rte = lfirst_node(RangeTblEntry, l);
int kind;
ListCell *lcsq;
if (rte->rtekind == RTE_RELATION)
{
if (rte->tablesample)
rte->tablesample = (TableSampleClause *)
preprocess_expression(root,
(Node *) rte->tablesample,
EXPRKIND_TABLESAMPLE);//数据表采样语句
}
else if (rte->rtekind == RTE_SUBQUERY)//子查询
{
/*
* We don't want to do all preprocessing yet on the subquery's
* expressions, since that will happen when we plan it. But if it
* contains any join aliases of our level, those have to get
* expanded now, because planning of the subquery won't do it.
* That's only possible if the subquery is LATERAL.
* 我们还不想对子查询的表达式进行预处理，因为这将在计划时发生。
* 但是，如果它包含当前级别的任何连接别名，那么现在就必须扩展这些别名，
* 因为子查询的计划无法做到这一点。只有在子查询是LATERAL的情况下才有可能。
*/
if (rte->lateral && root->hasJoinRTEs)
rte->subquery = (Query *)
flatten_join_alias_vars(root, (Node *) rte->subquery);
}
else if (rte->rtekind == RTE_FUNCTION)//函数
{
/* Preprocess the function expression(s) fully */
//预处理函数表达式
kind = rte->lateral ? EXPRKIND_RTFUNC_LATERAL : EXPRKIND_RTFUNC;
rte->functions = (List *)
preprocess_expression(root, (Node *) rte->functions, kind);
}
else if (rte->rtekind == RTE_TABLEFUNC)//TABLE FUNC
{
/* Preprocess the function expression(s) fully */
kind = rte->lateral ? EXPRKIND_TABLEFUNC_LATERAL : EXPRKIND_TABLEFUNC;
rte->tablefunc = (TableFunc *)
preprocess_expression(root, (Node *) rte->tablefunc, kind);
}
else if (rte->rtekind == RTE_VALUES)//VALUES子句
{
/* Preprocess the values lists fully */
kind = rte->lateral ? EXPRKIND_VALUES_LATERAL : EXPRKIND_VALUES;
rte->values_lists = (List *)
preprocess_expression(root, (Node *) rte->values_lists, kind);
}
/*
* Process each element of the securityQuals list as if it were a
* separate qual expression (as indeed it is). We need to do it this
* way to get proper canonicalization of AND/OR structure. Note that
* this converts each element into an implicit-AND sublist.
* 处理securityQuals列表的每个元素，就好像它是一个单独的qual表达式(事实也是如此)。
* 之所以这样做，是因为需要获得适当的规范化AND/OR结构。
* 注意，这将把每个元素转换为隐含的子列表。
*/
foreach(lcsq, rte->securityQuals)
{
lfirst(lcsq) = preprocess_expression(root,
(Node *) lfirst(lcsq),
EXPRKIND_QUAL);
}
}
/*
* Now that we are done preprocessing expressions, and in particular done
* flattening join alias variables, get rid of the joinaliasvars lists.
* They no longer match what expressions in the rest of the tree look
* like, because we have not preprocessed expressions in those lists (and
* do not want to; for example, expanding a SubLink there would result in
* a useless unreferenced subplan). Leaving them in place simply creates
* a hazard for later scans of the tree. We could try to prevent that by
* using QTW_IGNORE_JOINALIASES in every tree scan done after this point,
* but that doesn't sound very reliable.
* 现在，已经完成了预处理表达式，特别是扁平化连接别名变量，现在可以去掉joinaliasvars链表了。
* 它们不再匹配树中其他部分中的表达式，因为我们没有在那些链表中预处理表达式
* (而且是不希望这样做,例如，在那里展开一个SubLink将导致无用的未引用的子计划)。
* 把它们放在链表中只会给以后扫描树造成问题。
* 我们可以在这之后的每一次树扫描中使用QTW_IGNORE_JOINALIASES来防止这种情况，虽然这听起来不太可靠。
*/
if (root->hasJoinRTEs)
{
foreach(l, parse->rtable)
{
RangeTblEntry *rte = lfirst_node(RangeTblEntry, l);
rte->joinaliasvars = NIL;
}
}
/*
* In some cases we may want to transfer a HAVING clause into WHERE. We
* cannot do so if the HAVING clause contains aggregates (obviously) or
* volatile functions (since a HAVING clause is supposed to be executed
* only once per group). We also can't do this if there are any nonempty
* grouping sets; moving such a clause into WHERE would potentially change
* the results, if any referenced column isn't present in all the grouping
* sets. (If there are only empty grouping sets, then the HAVING clause
* must be degenerate as discussed below.)
* 在某些情况下，我们可能想把“HAVING”条件转移到WHERE子句中。
* 如果HAVING子句包含聚合(显式的)或易变volatile函数(因为每个GROUP只执行一次HAVING子句)，就不能这样做。
* 如果有任何非空GROUPING SET，也不能这样做;
* 如果在所有GROUPING SET中没有出现任何引用列，将这样的子句移动到WHERE可能会改变结果。
* (如果只有空的GROUP SET分组集，则可以按照下面讨论的那样简化HAVING子句->WHERE中。)
*
* Also, it may be that the clause is so expensive to execute that we're
* better off doing it only once per group, despite the loss of
* selectivity. This is hard to estimate short of doing the entire
* planning process twice, so we use a heuristic: clauses containing
* subplans are left in HAVING. Otherwise, we move or copy the HAVING
* clause into WHERE, in hopes of eliminating tuples before aggregation
* instead of after.
* 而且，执行子句的成本非常高，所以最好每组只执行一次，尽管这样会导致选择性selectivity。
* 如果不把整个规划过程重复一遍，这是很难估计的，因此我们使用启发式的方法:
* 包含子计划的条款在HAVING的后面。
* 否则，我们将把HAVING子句移动到WHERE中，希望在聚合之前而不是聚合之后消除元组。
*
* If the query has explicit grouping then we can simply move such a
* clause into WHERE; any group that fails the clause will not be in the
* output because none of its tuples will reach the grouping or
* aggregation stage. Otherwise we must have a degenerate (variable-free)
* HAVING clause, which we put in WHERE so that query_planner() can use it
* in a gating Result node, but also keep in HAVING to ensure that we
* don't emit a bogus aggregated row. (This could be done better, but it
* seems not worth optimizing.)
* 如果查询有显式分组，那么可以简单地将这样的子句移动到WHERE中;
* 任何失败的GROUP子句都不会出现在输出中，因为它的元组不会到达分组或聚合阶段。
* 否则，我们必须有一个退化的(无变量的)HAVING子句，把它放在WHERE中，
* 以便query_planner()可以在一个控制结果节点中使用它，但同时还要确保不会发出一个伪造的聚合行。
* (这本来可以做得更好，但似乎不值得继续深入优化。)
*
* Note that both havingQual and parse->jointree->quals are in
* implicitly-ANDed-list form at this point, even though they are declared
* as Node *.
* 请注意，现在不管是qual还是parse->jointree->quals，即使它们被声明为节点 *，
* 但它们在这个点上都是都是隐式的链表形式。
*/
newHaving = NIL;
foreach(l, (List *) parse->havingQual)
{
Node *havingclause = (Node *) lfirst(l);
if ((parse->groupClause && parse->groupingSets) ||
contain_agg_clause(havingclause) ||
contain_volatile_functions(havingclause) ||
contain_subplans(havingclause))
{
/* keep it in HAVING */
newHaving = lappend(newHaving, havingclause);
}
else if (parse->groupClause && !parse->groupingSets)
{
/* move it to WHERE */
parse->jointree->quals = (Node *)
lappend((List *) parse->jointree->quals, havingclause);
}
else
{
/* put a copy in WHERE, keep it in HAVING */
parse->jointree->quals = (Node *)
lappend((List *) parse->jointree->quals,
copyObject(havingclause));
newHaving = lappend(newHaving, havingclause);
}
}
parse->havingQual = (Node *) newHaving;
/* Remove any redundant GROUP BY columns */
//移除多余的GROUP BY 列
remove_useless_groupby_columns(root);
/*
* If we have any outer joins, try to reduce them to plain inner joins.
* This step is most easily done after we've done expression
* preprocessing.
* 如果存在外连接，则尝试将它们转换为普通的内部连接。
* 在我们完成表达式预处理之后，这个步骤相对容易完成。
*/
if (hasOuterJoins)
reduce_outer_joins(root);
/*
* Do the main planning. If we have an inherited target relation, that
* needs special processing, else go straight to grouping_planner.
* 执行主要的计划过程。
* 如果存在继承的目标关系，则需要特殊处理，否则直接执行grouping_planner。
*/
if (parse->resultRelation &&
rt_fetch(parse->resultRelation, parse->rtable)->inh)
inheritance_planner(root);
else
grouping_planner(root, false, tuple_fraction);
/*
* Capture the set of outer-level param IDs we have access to, for use in
* extParam/allParam calculations later.
* 获取我们可以访问的outer-level的参数IDs,以便稍后在extParam/allParam计算中使用。
*/
SS_identify_outer_params(root);
/*
* If any initPlans were created in this query level, adjust the surviving
* Paths' costs and parallel-safety flags to account for them. The
* initPlans won't actually get attached to the plan tree till
* create_plan() runs, but we must include their effects now.
* 如果在此查询级别中创建了initplan，则调整现存的访问路径成本和并行安全标志，以反映这些成本。
* 在create_plan()运行之前，initPlans实际上不会被附加到计划树中，但是我们现在必须包含它们的效果。
*/
final_rel = fetch_upper_rel(root, UPPERREL_FINAL, NULL);
SS_charge_for_initplans(root, final_rel);
/*
* Make sure we've identified the cheapest Path for the final rel. (By
* doing this here not in grouping_planner, we include initPlan costs in
* the decision, though it's unlikely that will change anything.)
* 确保我们已经为最终的关系确定了成本最低的路径
* (我们没有在grouping_planner中这样做，而是在最终决定中加入了initPlan的成本，尽管这不太可能改变任何事情)。
*/
set_cheapest(final_rel);
return root;
}“PostgreSQL中Review subquery_planner函数的实现逻辑是什么”的内容就介绍到这里了，感谢大家的阅读。如果想了解更多行业相关的知识可以关注亿速云网站，小编将为大家输出更多高质量的实用文章！
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