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PostgreSQL中create_sort_plan函数实现逻辑是什么
这篇文章主要讲解了“PostgreSQL中create_sort_plan函数实现逻辑是什么”，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中create_sort_plan函数实现逻辑是什么”吧！
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一、数据结构
Plan
所有计划节点通过将Plan结构作为第一个字段从Plan结构“派生”。这确保了在将节点转换为计划节点时，一切都能正常工作。(在执行器中以通用方式传递时，节点指针经常被转换为Plan *)
/* ----------------
* Plan node
*
* All plan nodes "derive" from the Plan structure by having the
* Plan structure as the first field. This ensures that everything works
* when nodes are cast to Plan's. (node pointers are frequently cast to Plan*
* when passed around generically in the executor)
* 所有计划节点通过将Plan结构作为第一个字段从Plan结构“派生”。
* 这确保了在将节点转换为计划节点时，一切都能正常工作。
* (在执行器中以通用方式传递时，节点指针经常被转换为Plan *)
*
* We never actually instantiate any Plan nodes; this is just the common
* abstract superclass for all Plan-type nodes.
* 从未实例化任何Plan节点;这只是所有Plan-type节点的通用抽象超类。
* ----------------
*/
typedef struct Plan
{
NodeTag type;//节点类型
/*
* 成本估算信息;estimated execution costs for plan (see costsize.c for more info)
*/
Cost startup_cost; /* 启动成本;cost expended before fetching any tuples */
Cost total_cost; /* 总成本;total cost (assuming all tuples fetched) */
/*
* 优化器估算信息;planner's estimate of result size of this plan step
*/
double plan_rows; /* 行数;number of rows plan is expected to emit */
int plan_width; /* 平均行大小(Byte为单位);average row width in bytes */
/*
* 并行执行相关的信息;information needed for parallel query
*/
bool parallel_aware; /* 是否参与并行执行逻辑?engage parallel-aware logic? */
bool parallel_safe; /* 是否并行安全;OK to use as part of parallel plan? */
/*
* Plan类型节点通用的信息.Common structural data for all Plan types.
*/
int plan_node_id; /* unique across entire final plan tree */
List *targetlist; /* target list to be computed at this node */
List *qual; /* implicitly-ANDed qual conditions */
struct Plan *lefttree; /* input plan tree(s) */
struct Plan *righttree;
List *initPlan; /* Init Plan nodes (un-correlated expr
* subselects) */
/*
* Information for management of parameter-change-driven rescanning
* parameter-change-driven重扫描的管理信息.
*
* extParam includes the paramIDs of all external PARAM_EXEC params
* affecting this plan node or its children. setParam params from the
* node's initPlans are not included, but their extParams are.
*
* allParam includes all the extParam paramIDs, plus the IDs of local
* params that affect the node (i.e., the setParams of its initplans).
* These are _all_ the PARAM_EXEC params that affect this node.
*/
Bitmapset *extParam;
Bitmapset *allParam;
} Plan;二、源码解读
create_plan->create_plan_recurse->create_projection_plan函数创建计划树,执行投影操作并通过递归的方式为子访问路径生成执行计划。create_sort_plan函数创建Sort计划节点。
//---------------------------------------------------------------- create_projection_plan
/*
* create_projection_plan
*
* Create a plan tree to do a projection step and (recursively) plans
* for its subpaths. We may need a Result node for the projection,
* but sometimes we can just let the subplan do the work.
* 创建计划树,执行投影操作并通过递归的方式为子访问路径生成执行计划.
* 一般来说需要一个Result节点用于投影操作,但有时候可以让子计划执行此项任务.
*/
static Plan *
create_projection_plan(PlannerInfo *root, ProjectionPath *best_path, int flags)
{
Plan *plan;
Plan *subplan;
List *tlist;
bool needs_result_node = false;
/*
* Convert our subpath to a Plan and determine whether we need a Result
* node.
* 转换subpath为Plan,并确定是否需要Result节点.
*
* In most cases where we don't need to project, creation_projection_path
* will have set dummypp, but not always. First, some createplan.c
* routines change the tlists of their nodes. (An example is that
* create_merge_append_plan might add resjunk sort columns to a
* MergeAppend.) Second, create_projection_path has no way of knowing
* what path node will be placed on top of the projection path and
* therefore can't predict whether it will require an exact tlist. For
* both of these reasons, we have to recheck here.
* 在大多数情况下，我们不需要投影运算，creation_projection_path将设置dummypp标志，但并不总是如此。
* 首先,一些createplan.c中的函数更改其节点的tlist。
* (例如，create_merge_append_plan可能会向MergeAppend添加resjunk sort列)。
* 其次，create_projection_path无法知道将在投影路径顶部放置哪些路径节点，因此无法预测它是否需要一个确切的tlist。
* 由于这两个原因，我们不得不在这里重新检查。
*/
if (use_physical_tlist(root, &best_path->path, flags))
{
/*
* Our caller doesn't really care what tlist we return, so we don't
* actually need to project. However, we may still need to ensure
* proper sortgroupref labels, if the caller cares about those.
* 如果我们的调用者并不关心返回的结果tlist，所以实际上不需要投影运算。
* 然而，如果调用者关心sortgroupref标签，可能仍然需要确保正确的sortgroupref数据。
*/
subplan = create_plan_recurse(root, best_path->subpath, 0);
tlist = subplan->targetlist;
if (flags & CP_LABEL_TLIST)
apply_pathtarget_labeling_to_tlist(tlist,
best_path->path.pathtarget);
}
else if (is_projection_capable_path(best_path->subpath))
{
/*
* Our caller requires that we return the exact tlist, but no separate
* result node is needed because the subpath is projection-capable.
* Tell create_plan_recurse that we're going to ignore the tlist it
* produces.
* 调用者要求返回精确的tlist，但是不需要单独的Result节点，因为子路径支持投影。
* 调用create_plan_recurse时忽略它生成的tlist。
*/
subplan = create_plan_recurse(root, best_path->subpath,
CP_IGNORE_TLIST);
tlist = build_path_tlist(root, &best_path->path);
}
else
{
/*
* It looks like we need a result node, unless by good fortune the
* requested tlist is exactly the one the child wants to produce.
* 看起来需要一个Result节点，除非幸运的是，请求的tlist正是子节点想要生成的。
*/
subplan = create_plan_recurse(root, best_path->subpath, 0);
tlist = build_path_tlist(root, &best_path->path);
needs_result_node = !tlist_same_exprs(tlist, subplan->targetlist);
}
/*
* If we make a different decision about whether to include a Result node
* than create_projection_path did, we'll have made slightly wrong cost
* estimates; but label the plan with the cost estimates we actually used,
* not "corrected" ones. (XXX this could be cleaned up if we moved more
* of the sortcolumn setup logic into Path creation, but that would add
* expense to creating Paths we might end up not using.)
* 如果我们对是否包含一个Result节点做出与create_projection_path不同的决定，
* 我们就会做出略微错误的成本估算;
* 但是在这个计划上标上我们实际使用的成本估算，而不是“修正的”成本估算。
* (如果我们将更多的sortcolumn设置逻辑移到路径创建中，这个问题就可以解决了，
* 但是这会增加创建路径的成本，而最终可能不会使用这些路径。)
*/
if (!needs_result_node)
{
/* Don't need a separate Result, just assign tlist to subplan */
//不需要单独的Result节点,把tlist赋值给subplan
plan = subplan;
plan->targetlist = tlist;
/* Label plan with the estimated costs we actually used */
//标记估算成本
plan->startup_cost = best_path->path.startup_cost;
plan->total_cost = best_path->path.total_cost;
plan->plan_rows = best_path->path.rows;
plan->plan_width = best_path->path.pathtarget->width;
plan->parallel_safe = best_path->path.parallel_safe;
/* ... but don't change subplan's parallel_aware flag */
}
else
{
/* We need a Result node */
//需要Result节点
plan = (Plan *) make_result(tlist, NULL, subplan);
copy_generic_path_info(plan, (Path *) best_path);
}
return plan;
}
//---------------------------------------------------------------- create_sort_plan
/*
* create_sort_plan
*
* Create a Sort plan for 'best_path' and (recursively) plans
* for its subpaths.
* 创建Sort计划节点
*/
static Sort *
create_sort_plan(PlannerInfo *root, SortPath *best_path, int flags)
{
Sort *plan;
Plan *subplan;
/*
* We don't want any excess columns in the sorted tuples, so request a
* smaller tlist. Otherwise, since Sort doesn't project, tlist
* requirements pass through.
* 我们不希望在排序元组中有任何多余的列，所以希望得到一个更小的tlist。
* 否则，由于Sort不执行投影运算，tlist就会通过完整的保留传递。
*/
subplan = create_plan_recurse(root, best_path->subpath,
flags | CP_SMALL_TLIST);
/*
* make_sort_from_pathkeys() indirectly calls find_ec_member_for_tle(),
* which will ignore any child EC members that don't belong to the given
* relids. Thus, if this sort path is based on a child relation, we must
* pass its relids.
* make_sort_from_pathkeys()间接调用find_ec_member_for_tle()，它将忽略不属于给定relid的任何子EC成员。
* 因此，如果这个排序路径是基于子关系的，我们必须传递它的relids。
*/
plan = make_sort_from_pathkeys(subplan, best_path->path.pathkeys,
IS_OTHER_REL(best_path->subpath->parent) ?
best_path->path.parent->relids : NULL);
copy_generic_path_info(&plan->plan, (Path *) best_path);
return plan;
}
//------------------------------------------------ build_path_tlist
/*
* Build a target list (ie, a list of TargetEntry) for the Path's output.
* 构建用于输出的target链表(比如TargetEntry节点链表)
*
* This is almost just make_tlist_from_pathtarget(), but we also have to
* deal with replacing nestloop params.
* 该函数几乎就是make_tlist_from_pathtarget()的实现逻辑，但还必须处理替换nestloop参数。
*/
static List *
build_path_tlist(PlannerInfo *root, Path *path)
{
List *tlist = NIL;
Index *sortgrouprefs = path->pathtarget->sortgrouprefs;
int resno = 1;
ListCell *v;
foreach(v, path->pathtarget->exprs)
{
Node *node = (Node *) lfirst(v);
TargetEntry *tle;
/*
* If it's a parameterized path, there might be lateral references in
* the tlist, which need to be replaced with Params. There's no need
* to remake the TargetEntry nodes, so apply this to each list item
* separately.
* 如果是参数化路径，那么tlist中可能有横向引用，需要用Params替换。
* 不需要重新构建TargetEntry节点，因此可以将其单独应用于每个链表项。
*/
if (path->param_info)
node = replace_nestloop_params(root, node);
tle = makeTargetEntry((Expr *) node,
resno,
NULL,
false);
if (sortgrouprefs)
tle->ressortgroupref = sortgrouprefs[resno - 1];
tlist = lappend(tlist, tle);
resno++;
}
return tlist;
}三、跟踪分析
测试脚本如下
testdb=# explain select dw.*,grjf.grbh,grjf.xm,grjf.ny,grjf.je testdb-# from t_dwxx dw,lateral (select gr.grbh,gr.xm,jf.ny,jf.je testdb(# from t_grxx gr inner join t_jfxx jf testdb(# on gr.dwbh = dw.dwbh testdb(# and gr.grbh = jf.grbh) grjf testdb-# order by dw.dwbh; QUERY PLAN ------------------------------------------------------------------------------------------ Sort (cost=20070.93..20320.93 rows=100000 width=47) Sort Key: dw.dwbh -> Hash Join (cost=3754.00..8689.61 rows=100000 width=47) Hash Cond: ((gr.dwbh)::text = (dw.dwbh)::text) -> Hash Join (cost=3465.00..8138.00 rows=100000 width=31) Hash Cond: ((jf.grbh)::text = (gr.grbh)::text) -> Seq Scan on t_jfxx jf (cost=0.00..1637.00 rows=100000 width=20) -> Hash (cost=1726.00..1726.00 rows=100000 width=16) -> Seq Scan on t_grxx gr (cost=0.00..1726.00 rows=100000 width=16) -> Hash (cost=164.00..164.00 rows=10000 width=20) -> Seq Scan on t_dwxx dw (cost=0.00..164.00 rows=10000 width=20) (11 rows)
启动gdb,设置断点,进入create_projection_plan函数
(gdb) b create_projection_plan Breakpoint 2 at 0x7b95a8: file createplan.c, line 1627. (gdb) c Continuing. Breakpoint 2, create_projection_plan (root=0x26c1258, best_path=0x2722d00, flags=1) at createplan.c:1627 1627 bool needs_result_node = false;
转换subpath为Plan,并确定是否需要Result节点,并且判断是否需要生成Result节点
... (gdb) n 1642 if (use_physical_tlist(root, &best_path->path, flags)) (gdb) n 1655 else if (is_projection_capable_path(best_path->subpath)) (gdb) 1673 subplan = create_plan_recurse(root, best_path->subpath, 0);
查看best_path&best_path->subpath变量
(gdb) p *best_path
$3 = {path = {type = T_ProjectionPath, pathtype = T_Result, parent = 0x2722998, pathtarget = 0x27226f8, param_info = 0x0,
parallel_aware = false, parallel_safe = true, parallel_workers = 0, rows = 100000, startup_cost = 20070.931487218411,
total_cost = 20320.931487218411, pathkeys = 0x26cfe98}, subpath = 0x2722c68, dummypp = true}
(gdb) p *(SortPath *)best_path->subpath
$16 = {path = {type = T_SortPath, pathtype = T_Sort, parent = 0x2722998, pathtarget = 0x27212d8, param_info = 0x0,
parallel_aware = false, parallel_safe = true, parallel_workers = 0, rows = 100000, startup_cost = 20070.931487218411,
total_cost = 20320.931487218411, pathkeys = 0x26cfe98}, subpath = 0x2721e60}创建subpath(SortPath)的执行计划
(gdb) step create_plan_recurse (root=0x26c1258, best_path=0x2722c68, flags=0) at createplan.c:364 364 check_stack_depth(); (gdb) n 366 switch (best_path->pathtype) (gdb) 447 plan = (Plan *) create_sort_plan(root,
进入create_sort_plan
(gdb) step create_sort_plan (root=0x26c1258, best_path=0x2722c68, flags=0) at createplan.c:1759 1759 subplan = create_plan_recurse(root, best_path->subpath,
SortPath的subpath是HashPath
(gdb) p best_path->subpath->type
$17 = T_HashPath
(gdb) p *(HashPath *)best_path->subpath
$18 = {jpath = {path = {type = T_HashPath, pathtype = T_HashJoin, parent = 0x27210c0, pathtarget = 0x27212d8,
param_info = 0x0, parallel_aware = false, parallel_safe = true, parallel_workers = 0, rows = 100000,
startup_cost = 3754, total_cost = 8689.6112499999999, pathkeys = 0x0}, jointype = JOIN_INNER, inner_unique = true,
outerjoinpath = 0x2720f68, innerjoinpath = 0x26d0598, joinrestrictinfo = 0x2722068}, path_hashclauses = 0x27223c0,
num_batches = 1, inner_rows_total = 10000}完成SortPath执行计划的构建
(gdb)
1774 return plan;
(gdb)
1775 }
(gdb) p *plan
$20 = {plan = {type = T_Sort, startup_cost = 20070.931487218411, total_cost = 20320.931487218411, plan_rows = 100000,
plan_width = 47, parallel_aware = false, parallel_safe = true, plan_node_id = 0, targetlist = 0x2723208, qual = 0x0,
lefttree = 0x27243d0, righttree = 0x0, initPlan = 0x0, extParam = 0x0, allParam = 0x0}, numCols = 1,
sortColIdx = 0x27222a0, sortOperators = 0x2724468, collations = 0x2724488, nullsFirst = 0x27244a8}回到上一层
(gdb) n create_plan_recurse (root=0x26c1258, best_path=0x2722c68, flags=0) at createplan.c:450 450 break;
回到create_projection_plan函数
(gdb) n 504 return plan; (gdb) 505 } (gdb) create_projection_plan (root=0x26c1258, best_path=0x2722d00, flags=1) at createplan.c:1674 1674 tlist = build_path_tlist(root, &best_path->path);
执行完毕,返回create_plan,结果,最外层的Plan为Sort
(gdb)
1708 return plan;
(gdb)
1709 }
(gdb) p *plan
$22 = {type = T_Sort, startup_cost = 20070.931487218411, total_cost = 20320.931487218411, plan_rows = 100000,
plan_width = 47, parallel_aware = false, parallel_safe = true, plan_node_id = 0, targetlist = 0x2724548, qual = 0x0,
lefttree = 0x27243d0, righttree = 0x0, initPlan = 0x0, extParam = 0x0, allParam = 0x0}
(gdb) n
create_plan_recurse (root=0x26c1258, best_path=0x2722d00, flags=1) at createplan.c:504
504 return plan;
(gdb) p *plan
$23 = {type = T_Sort, startup_cost = 20070.931487218411, total_cost = 20320.931487218411, plan_rows = 100000,
plan_width = 47, parallel_aware = false, parallel_safe = true, plan_node_id = 0, targetlist = 0x2724548, qual = 0x0,
lefttree = 0x27243d0, righttree = 0x0, initPlan = 0x0, extParam = 0x0, allParam = 0x0}
(gdb) n
505 }
(gdb)
create_plan (root=0x26c1258, best_path=0x2722d00) at createplan.c:329
329 if (!IsA(plan, ModifyTable))感谢各位的阅读，以上就是“PostgreSQL中create_sort_plan函数实现逻辑是什么”的内容了，经过本文的学习后，相信大家对PostgreSQL中create_sort_plan函数实现逻辑是什么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！
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