Postgres中UPDATE更新语句源码分析
PG中UPDATE源码分析
本文主要描述SQL中UPDATE语句的源码分析,代码为PG13.3版本。
整体流程分析
以update dtea set id = 1;
这条最简单的Update语句进行源码分析(dtea不是分区表,不考虑并行等,没有建立任何索引),帮助我们理解update的大致流程。
SQL流程如下:
-
parser(语法解析,生成语法解析树UpdateStmt,检查是否有语法层面的错误)
-
analyze(语义分析, UpdateStmt转为查询树Query, 会查系统表检查有无语义方面的错误)
-
rewrite(规则重写, 根据规则rules重写查询树Query, 根据事先存储在系统表中的规则进行重写,没有的话不进行重写,另外加一句,视图的实现是根据规则系统实现的,也是在这里需要进行处理)
-
optimizer(优化器:逻辑优化、物理优化、生成执行计划, 由Query生成对应的执行计划PlannedStmt, 基于代价的优化器,由最佳路径Path生成最佳执行计划Plan)
-
executor(执行器,会有各种算子,依据执行计划进行处理,火山模型,一次一元组)
-
storage(存储引擎)。中间还有事务处理。事务处理部分的代码这里不再进行分析,免得将问题复杂化。存储引擎那部分也不进行分析,重点关注解析、优化、执行这三部分。
对应的代码:
// ——- 解析器部分————–
–> pg_parse_query(query_string); //生成语法解析树
–> pg_analyze_and_rewrite(parsetree, query_string,NULL, 0, NULL); // 生成查询树Query
–> parse_analyze(parsetree, query_string, paramTypes, numParams,queryEnv); // 语义分析
–> pg_rewrite_query(query); // 规则重写
// ——–优化器———-
–> pg_plan_queries()
//——– 执行器———-
–> PortalStart(portal, NULL, 0, InvalidSnapshot);
–> PortalRun(portal,FETCH_ALL,true,true,receiver,receiver,&qc); // 执行器执行
–> PortalDrop(portal, false);
解析部分——生成语法解析树UpdateStmt
关键数据结构:UpdateStmt
、RangeVar
、ResTarget
:
typedef struct UpdateStmt
{
NodeTag type;
RangeVar *relation; /* relation to update */
List *targetList; /* the target list (of ResTarget) */ // 对应语句中的set id = 0;信息在这里
Node *whereClause; /* qualifications */
List *fromClause; /* optional from clause for more tables */
List *returningList; /* list of expressions to return */
WithClause *withClause; /* WITH clause */
} UpdateStmt;
// dtea 表
typedef struct RangeVar
{
NodeTag type;
char *catalogname; /* the catalog (database) name, or NULL */
char *schemaname; /* the schema name, or NULL */
char *relname; /* the relation/sequence name */
bool inh; /* expand rel by inheritance? recursively act
* on children? */
char relpersistence; /* see RELPERSISTENCE_* in pg_class.h */
Alias *alias; /* table alias & optional column aliases */
int location; /* token location, or -1 if unknown */
} RangeVar;
// set id = 0; 经transformTargetList() -> transformTargetEntry,会转为TargetEntry
typedef struct ResTarget
{
NodeTag type;
char *name; /* column name or NULL */ // id column
List *indirection; /* subscripts, field names, and ‘*’, or NIL */
Node *val; /* the value expression to compute or assign */ // = 1表达式节点存在这里
int location; /* token location, or -1 if unknown */
} ResTarget;
用户输入的update语句update dtea set id = 1
由字符串会转为可由数据库理解的内部数据结构语法解析树UpdateStmt
。执行逻辑在pg_parse_query(query_string);
中,需要理解flex与bison。
gram.y中Update语法的定义:
* QUERY:
* UpdateStmt (UPDATE)
*****************************************************************************/
//结合这条语句分析 update dtea set id = 0;
UpdateStmt: opt_with_clause UPDATE relation_expr_opt_alias
SET set_clause_list from_clause where_or_current_clause returning_clause
{
UpdateStmt *n = makeNode(UpdateStmt);
n->relation = $3;
n->targetList = $5;
n->fromClause = $6;
n->whereClause = $7;
n->returningList = $8;
n->withClause = $1;
$$ = (Node *)n;
}
;
set_clause_list:
set_clause { $$ = $1; }
| set_clause_list ‘,’ set_clause { $$ = list_concat($1,$3); }
;
// 对应的是 set id = 0
set_clause: // id = 0
set_target ‘=’ a_expr
{
$1->val = (Node *) $3;
$$ = list_make1($1);
}
| ‘(‘ set_target_list ‘)’ ‘=’ a_expr
{
int ncolumns = list_length($2);
int i = 1;
ListCell *col_cell;
foreach(col_cell, $2) /* Create a MultiAssignRef source for each target */
{
ResTarget *res_col = (ResTarget *) lfirst(col_cell);
MultiAssignRef *r = makeNode(MultiAssignRef);
r->source = (Node *) $5;
r->colno = i;
r->ncolumns = ncolumns;
res_col->val = (Node *) r;
i++;
}
$$ = $2;
}
;
set_target:
ColId opt_indirection
{
$$ = makeNode(ResTarget);
$$->name = $1;
$$->indirection = check_indirection($2, yyscanner);
$$->val = NULL; /* upper production sets this */
$$->location = @1;
}
;
set_target_list:
set_target { $$ = list_make1($1); }
| set_target_list ‘,’ set_target { $$ = lappend($1,$3); }
;
解析部分——生成查询树Query
生成了UpdateStmt
后, 会经由parse_analyze
语义分析,生成查询树Query
,以供后续优化器生成执行计划。主要代码在src/backent/parser/analyze.c
中
analyze.c : transform the raw parse tree into a query tree
–> transformTopLevelStmt(pstate, parseTree);
–> transformOptionalSelectInto(pstate, parseTree->stmt);
–> transformStmt(pstate, parseTree);
// transforms an update statement
–> transformUpdateStmt(pstate, (UpdateStmt *) parseTree); // 实际由UpdateStmt转为Query的处理函数
具体的我们看一下transformUpdateStmt
函数实现:
static Query *transformUpdateStmt(ParseState *pstate, UpdateStmt *stmt) {
Query *qry = makeNode(Query);
ParseNamespaceItem *nsitem;
Node *qual;
qry->commandType = CMD_UPDATE;
pstate->p_is_insert = false;
/* process the WITH clause independently of all else */
if (stmt->withClause) {
qry->hasRecursive = stmt->withClause->recursive;
qry->cteList = transformWithClause(pstate, stmt->withClause);
qry->hasModifyingCTE = pstate->p_hasModifyingCTE;
}
qry->resultRelation = setTargetTable(pstate, stmt->relation, stmt->relation->inh, true, ACL_UPDATE);
nsitem = pstate->p_target_nsitem;
/* subqueries in FROM cannot access the result relation */
nsitem->p_lateral_only = true;
nsitem->p_lateral_ok = false;
/* the FROM clause is non-standard SQL syntax. We used to be able to do this with REPLACE in POSTQUEL so we keep the feature.*/
transformFromClause(pstate, stmt->fromClause);
/* remaining clauses can reference the result relation normally */
nsitem->p_lateral_only = false;
nsitem->p_lateral_ok = true;
qual = transformWhereClause(pstate, stmt->whereClause,EXPR_KIND_WHERE, “WHERE”);
qry->returningList = transformReturningList(pstate, stmt->returningList);
/* Now we are done with SELECT-like processing, and can get on with
* transforming the target list to match the UPDATE target columns.*/
qry->targetList = transformUpdateTargetList(pstate, stmt->targetList); // 处理SQL语句中的 set id =1
qry->rtable = pstate->p_rtable;
qry->jointree = makeFromExpr(pstate->p_joinlist, qual);
qry->hasTargetSRFs = pstate->p_hasTargetSRFs;
qry->hasSubLinks = pstate->p_hasSubLinks;
assign_query_collations(pstate, qry);
return qry;
}
这里面要重点关注一下transformTargetList
,会将抽象语法树中的ResTarget
转为查询器的TargetEntry
。
{
Expr xpr;
Expr *expr; /* expression to evaluate */
AttrNumber resno; /* attribute number (see notes above) */
char *resname; /* name of the column (could be NULL) */
Index ressortgroupref; /* nonzero if referenced by a sort/group clause */
Oid resorigtbl; /* OID of column’s source table */
AttrNumber resorigcol; /* column’s number in source table */
bool resjunk; /* set to true to eliminate the attribute from final target list */
} TargetEntry;
对于其内部处理可参考源码
src/backend/parser
中的相关处理,这里不再细述。需要重点阅读一下README,PG源码中所有的README都是非常好的资料,一定要认真读。
优化器——生成执行计划
这块的内容很多,主要的逻辑是先进行逻辑优化,比如子查询、子链接、常量表达式、选择下推等等的处理,因为我们要分析的这条语句十分简单,所以逻辑优化的这部分都没有涉及到。物理优化,涉及到选择率,代价估计,索引扫描还是顺序扫描,选择那种连接方式,应用动态规划呢还是基因算法,选择nestloop-join、merge-join还是hash-join等。因为我们这个表没有建索引,更新单表也不涉及到多表连接,所以物理优化这块涉及的也不多。路径生成,生成最佳路径,再由最佳路径生成执行计划。
在路径生成这块,最基础的是对表的扫描方式,比如顺序扫描、索引扫描,再往上是连接方式,采用那种连接方式,再往上是比如排序、Limit等路径……,由底向上生成路径。我们要分析的语句很简单,没有其他处理,就顺序扫描再更新就可以了。
这里先不考虑并行执行计划。我们先看一下其执行计划结果:
QUERY PLAN
————————————————————–
Update on dtea (cost=0.00..19.00 rows=900 width=68)
-> Seq Scan on dtea (cost=0.00..19.00 rows=900 width=68)
(2 rows)
下面我们分析一下其执行计划的生成流程:
pg_plan_queries()
–> pg_plan_query()
–> planner()
–> standard_planner(Query *parse, const char *query_string, int cursorOptions,ParamListInfo boundParams)
// 由Query—> PlannerInfo
–> subquery_planner(glob, parse, NULL,false, tuple_fraction); // 涉及到很多逻辑优化的内容,很多不列出
–> pull_up_sublinks(root);
–> pull_up_subqueries(root); // 这里只列出几个重要的逻辑优化内容,其他的不再列出……
// 如果是update/delete分区表继承表则走inheritance_planner(),其他情况走grouping_planner()
–> inheritance_planner() // update/delete分区表继承表的情况
–> grouping_planner()
–> grouping_planner() // 非分区表、继承表的情况
–> preprocess_targetlist(root); // update虽然只更新一列,但是插入一条新元组的时候,需要知道其他列信息.
–> rewriteTargetListUD(parse, target_rte, target_relation);
–> expand_targetlist()
–> query_planner(root, standard_qp_callback, &qp_extra); // 重要
–> add_base_rels_to_query()
–> deconstruct_jointree(root);
–> add_other_rels_to_query(root); // 展开分区表到PlannerInfo中的相关字段中
–> expand_inherited_rtentry()
–> expand_planner_arrays(root, num_live_parts);
–> make_one_rel(root, joinlist);
–> set_base_rel_sizes(root);
–> set_rel_size();
–> set_append_rel_size(root, rel, rti, rte); // 如果是分区表或者继承走这里,否则走下面
–> set_rel_size(root, childrel, childRTindex, childRTE); // 处理子分区表
–> set_plain_rel_size(root, rel, rte);
–> set_plain_rel_size() // 如果不是分区表或者继承
–> set_baserel_size_estimates()
–> set_base_rel_pathlists(root);
–> set_rel_pathlist(root, rel, rti, root->simple_rte_array[rti]);
–> set_append_rel_pathlist(root, rel, rti, rte); // 生成各分区表的访问路径
–> make_rel_from_joinlist(root, joinlist);// 动态规划还是基因规划
–> standard_join_search() // 动态规划
–> geqo() // 基因规划与动态规划二选一
–> apply_scanjoin_target_to_paths()
–> create_modifytable_path()
// 由PlannerInfo—> RelOptInfo
–> fetch_upper_rel(root, UPPERREL_FINAL, NULL);
// 由RelOptInfo—> Path
–> get_cheapest_fractional_path(final_rel, tuple_fraction);
// 由 PlannerInfo+Path —> Plan
–> create_plan(root, best_path);
// 后续处理,由Plan —> PlannedStmt
核心数据结构:PlannedStmt、PlannerInfo、RelOptInfo(存储访问路径及其代价)、Path
Path:所有的路径都继承自Path,所以这个比较重要。
{
NodeTag type;
NodeTag pathtype; /* tag identifying scan/join method */
RelOptInfo *parent; /* the relation this path can build */
PathTarget *pathtarget; /* list of Vars/Exprs, cost, width */
ParamPathInfo *param_info; /* parameterization info, or NULL if none */
bool parallel_aware; /* engage parallel-aware logic? */
bool parallel_safe; /* OK to use as part of parallel plan? */
int parallel_workers; /* desired # of workers; 0 = not parallel */
/* estimated size/costs for path (see costsize.c for more info) */
double rows; /* estimated number of result tuples */
Cost startup_cost; /* cost expended before fetching any tuples */
Cost total_cost; /* total cost (assuming all tuples fetched) */
List *pathkeys; /* sort ordering of path’s output */
/* pathkeys is a List of PathKey nodes; see above */
} Path;
/* ModifyTablePath represents performing INSERT/UPDATE/DELETE modifications
* We represent most things that will be in the ModifyTable plan node
* literally, except we have child Path(s) not Plan(s). But analysis of the
* OnConflictExpr is deferred to createplan.c, as is collection of FDW data. */
typedef struct ModifyTablePath
{
Path path; // 可以看到ModifyTablePath继承自Path
CmdType operation; /* INSERT, UPDATE, or DELETE */
bool canSetTag; /* do we set the command tag/es_processed? */
Index nominalRelation; /* Parent RT index for use of EXPLAIN */
Index rootRelation; /* Root RT index, if target is partitioned */
bool partColsUpdated; /* some part key in hierarchy updated */
List *resultRelations; /* integer list of RT indexes */
List *subpaths; /* Path(s) producing source data */
List *subroots; /* per-target-table PlannerInfos */
List *withCheckOptionLists; /* per-target-table WCO lists */
List *returningLists; /* per-target-table RETURNING tlists */
List *rowMarks; /* PlanRowMarks (non-locking only) */
OnConflictExpr *onconflict; /* ON CONFLICT clause, or NULL */
int epqParam; /* ID of Param for EvalPlanQual re-eval */
} ModifyTablePath;
生成update执行路径,最终都是要生成ModifyTablePath,本例中路径生成过程:Path–>ProjectionPath–>ModifyTablePath,也就是先顺序扫描表,再修改表。后面由路径生成执行计划。
* Creates a pathnode that represents performing INSERT/UPDATE/DELETE mods
*
* ‘rel’ is the parent relation associated with the result
* ‘resultRelations’ is an integer list of actual RT indexes of target rel(s)
* ‘subpaths’ is a list of Path(s) producing source data (one per rel)
* ‘subroots’ is a list of PlannerInfo structs (one per rel)*/
ModifyTablePath *create_modifytable_path(PlannerInfo *root, RelOptInfo *rel,
CmdType operation, bool canSetTag,
Index nominalRelation, Index rootRelation,
bool partColsUpdated,
List *resultRelations, List *subpaths,
List *subroots,
List *withCheckOptionLists, List *returningLists,
List *rowMarks, OnConflictExpr *onconflict,
int epqParam)
{
ModifyTablePath *pathnode = makeNode(ModifyTablePath);
double total_size;
ListCell *lc;
Assert(list_length(resultRelations) == list_length(subpaths));
Assert(list_length(resultRelations) == list_length(subroots));
Assert(withCheckOptionLists == NIL || list_length(resultRelations) == list_length(withCheckOptionLists));
Assert(returningLists == NIL || list_length(resultRelations) == list_length(returningLists));
pathnode->path.pathtype = T_ModifyTable;
pathnode->path.parent = rel;
pathnode->path.pathtarget = rel->reltarget; /* pathtarget is not interesting, just make it minimally valid */
/* For now, assume we are above any joins, so no parameterization */
pathnode->path.param_info = NULL;
pathnode->path.parallel_aware = false;
pathnode->path.parallel_safe = false;
pathnode->path.parallel_workers = 0;
pathnode->path.pathkeys = NIL;
/** Compute cost & rowcount as sum of subpath costs & rowcounts.
*
* Currently, we don’t charge anything extra for the actual table
* modification work, nor for the WITH CHECK OPTIONS or RETURNING
* expressions if any. It would only be window dressing, since
* ModifyTable is always a top-level node and there is no way for the
* costs to change any higher-level planning choices. But we might want
* to make it look better sometime.*/
pathnode->path.startup_cost = 0;
pathnode->path.total_cost = 0;
pathnode->path.rows = 0;
total_size = 0;
foreach(lc, subpaths)
{
Path *subpath = (Path *) lfirst(lc);
if (lc == list_head(subpaths)) /* first node? */
pathnode->path.startup_cost = subpath->startup_cost;
pathnode->path.total_cost += subpath->total_cost;
pathnode->path.rows += subpath->rows;
total_size += subpath->pathtarget->width * subpath->rows;
}
/* Set width to the average width of the subpath outputs. XXX this is
* totally wrong: we should report zero if no RETURNING, else an average
* of the RETURNING tlist widths. But it’s what happened historically,
* and improving it is a task for another day.*/
if (pathnode->path.rows > 0)
total_size /= pathnode->path.rows;
pathnode->path.pathtarget->width = rint(total_size);
pathnode->operation = operation;
pathnode->canSetTag = canSetTag;
pathnode->nominalRelation = nominalRelation;
pathnode->rootRelation = rootRelation;
pathnode->partColsUpdated = partColsUpdated;
pathnode->resultRelations = resultRelations;
pathnode->subpaths = subpaths;
pathnode->subroots = subroots;
pathnode->withCheckOptionLists = withCheckOptionLists;
pathnode->returningLists = returningLists;
pathnode->rowMarks = rowMarks;
pathnode->onconflict = onconflict;
pathnode->epqParam = epqParam;
return pathnode;
}
现在我们生成了最优的update路径,需要由路径生成执行计划:
{
Plan *plan;
Assert(root->plan_params == NIL); /* plan_params should not be in use in current query level */
/* Initialize this module’s workspace in PlannerInfo */
root->curOuterRels = NULL;
root->curOuterParams = NIL;
/* Recursively process the path tree, demanding the correct tlist result */
plan = create_plan_recurse(root, best_path, CP_EXACT_TLIST); // 实际实现是在这里
/** Make sure the topmost plan node’s targetlist exposes the original
* column names and other decorative info. Targetlists generated within
* the planner don’t bother with that stuff, but we must have it on the
* top-level tlist seen at execution time. However, ModifyTable plan
* nodes don’t have a tlist matching the querytree targetlist.*/
if (!IsA(plan, ModifyTable))
apply_tlist_labeling(plan->targetlist, root->processed_tlist);
/** Attach any initPlans created in this query level to the topmost plan
* node. (In principle the initplans could go in any plan node at or
* above where they’re referenced, but there seems no reason to put them
* any lower than the topmost node for the query level. Also, see
* comments for SS_finalize_plan before you try to change this.)*/
SS_attach_initplans(root, plan);
/* Check we successfully assigned all NestLoopParams to plan nodes */
if (root->curOuterParams != NIL)
elog(ERROR, “failed to assign all NestLoopParams to plan nodes”);
/** Reset plan_params to ensure param IDs used for nestloop params are not re-used later*/
root->plan_params = NIL;
return plan;
}
// 由最佳路径生成最佳执行计划
static ModifyTable *create_modifytable_plan(PlannerInfo *root, ModifyTablePath *best_path)
{
ModifyTable *plan;
List *subplans = NIL;
ListCell *subpaths,
*subroots;
/* Build the plan for each input path */
forboth(subpaths, best_path->subpaths, subroots, best_path->subroots)
{
Path *subpath = (Path *) lfirst(subpaths);
PlannerInfo *subroot = (PlannerInfo *) lfirst(subroots);
Plan *subplan;
/* In an inherited UPDATE/DELETE, reference the per-child modified
* subroot while creating Plans from Paths for the child rel. This is
* a kluge, but otherwise it’s too hard to ensure that Plan creation
* functions (particularly in FDWs) don’t depend on the contents of
* “root” matching what they saw at Path creation time. The main
* downside is that creation functions for Plans that might appear
* below a ModifyTable cannot expect to modify the contents of “root”
* and have it “stick” for subsequent processing such as setrefs.c.
* That’s not great, but it seems better than the alternative.*/
subplan = create_plan_recurse(subroot, subpath, CP_EXACT_TLIST);
/* Transfer resname/resjunk labeling, too, to keep executor happy */
apply_tlist_labeling(subplan->targetlist, subroot->processed_tlist);
subplans = lappend(subplans, subplan);
}
plan = make_modifytable(root,best_path->operation,best_path->canSetTag,
best_path->nominalRelation,best_path->rootRelation,
best_path->partColsUpdated,best_path->resultRelations,
subplans,best_path->subroots,best_path->withCheckOptionLists,
best_path->returningLists,best_path->rowMarks,
best_path->onconflict,best_path->epqParam);
copy_generic_path_info(&plan->plan, &best_path->path);
return plan;
}
最终的执行计划是ModifyTable:
* ModifyTable node –
* Apply rows produced by subplan(s) to result table(s),
* by inserting, updating, or deleting.
*
* If the originally named target table is a partitioned table, both
* nominalRelation and rootRelation contain the RT index of the partition
* root, which is not otherwise mentioned in the plan. Otherwise rootRelation
* is zero. However, nominalRelation will always be set, as it’s the rel that
* EXPLAIN should claim is the INSERT/UPDATE/DELETE target.
*
* Note that rowMarks and epqParam are presumed to be valid for all the
* subplan(s); they can’t contain any info that varies across subplans.
* —————-*/
typedef struct ModifyTable
{
Plan plan;
CmdType operation; /* INSERT, UPDATE, or DELETE */
bool canSetTag; /* do we set the command tag/es_processed? */
Index nominalRelation; /* Parent RT index for use of EXPLAIN */
Index rootRelation; /* Root RT index, if target is partitioned */
bool partColsUpdated; /* some part key in hierarchy updated */
List *resultRelations; /* integer list of RT indexes */
int resultRelIndex; /* index of first resultRel in plan’s list */
int rootResultRelIndex; /* index of the partitioned table root */
List *plans; /* plan(s) producing source data */
List *withCheckOptionLists; /* per-target-table WCO lists */
List *returningLists; /* per-target-table RETURNING tlists */
List *fdwPrivLists; /* per-target-table FDW private data lists */
Bitmapset *fdwDirectModifyPlans; /* indices of FDW DM plans */
List *rowMarks; /* PlanRowMarks (non-locking only) */
int epqParam; /* ID of Param for EvalPlanQual re-eval */
OnConflictAction onConflictAction; /* ON CONFLICT action */
List *arbiterIndexes; /* List of ON CONFLICT arbiter index OIDs */
List *onConflictSet; /* SET for INSERT ON CONFLICT DO UPDATE */
Node *onConflictWhere; /* WHERE for ON CONFLICT UPDATE */
Index exclRelRTI; /* RTI of the EXCLUDED pseudo relation */
List *exclRelTlist; /* tlist of the EXCLUDED pseudo relation */
} ModifyTable;
执行器
根据上面的执行计划,去执行。主要是各种算子的实现,其中要理解执行器的运行原理,主要是火山模型,一次一元组。我们看一下其调用过程。
关键数据结构:
typedef struct ModifyTableState
{
PlanState ps; /* its first field is NodeTag */
CmdType operation; /* INSERT, UPDATE, or DELETE */
bool canSetTag; /* do we set the command tag/es_processed? */
bool mt_done; /* are we done? */
PlanState **mt_plans; /* subplans (one per target rel) */
int mt_nplans; /* number of plans in the array */
int mt_whichplan; /* which one is being executed (0..n-1) */
TupleTableSlot **mt_scans; /* input tuple corresponding to underlying
* plans */
ResultRelInfo *resultRelInfo; /* per-subplan target relations */
ResultRelInfo *rootResultRelInfo; /* root target relation (partitioned
* table root) */
List **mt_arowmarks; /* per-subplan ExecAuxRowMark lists */
EPQState mt_epqstate; /* for evaluating EvalPlanQual rechecks */
bool fireBSTriggers; /* do we need to fire stmt triggers? */
/* Slot for storing tuples in the root partitioned table’s rowtype during
* an UPDATE of a partitioned table. */
TupleTableSlot *mt_root_tuple_slot;
struct PartitionTupleRouting *mt_partition_tuple_routing; /* Tuple-routing support info */
struct TransitionCaptureState *mt_transition_capture; /* controls transition table population for specified operation */
/* controls transition table population for INSERT…ON CONFLICT UPDATE */
struct TransitionCaptureState *mt_oc_transition_capture;
/* Per plan map for tuple conversion from child to root */
TupleConversionMap **mt_per_subplan_tupconv_maps;
} ModifyTableState;
核心执行算子实现:
* ExecModifyTable
*
* Perform table modifications as required, and return RETURNING results
* if needed.
* —————————————————————- */
static TupleTableSlot *ExecModifyTable(PlanState *pstate)
{
ModifyTableState *node = castNode(ModifyTableState, pstate);
PartitionTupleRouting *proute = node->mt_partition_tuple_routing;
EState *estate = node->ps.state;
CmdType operation = node->operation;
ResultRelInfo *saved_resultRelInfo;
ResultRelInfo *resultRelInfo;
PlanState *subplanstate;
JunkFilter *junkfilter;
TupleTableSlot *slot;
TupleTableSlot *planSlot;
ItemPointer tupleid;
ItemPointerData tuple_ctid;
HeapTupleData oldtupdata;
HeapTuple oldtuple;
CHECK_FOR_INTERRUPTS();
/* This should NOT get called during EvalPlanQual; we should have passed a
* subplan tree to EvalPlanQual, instead. Use a runtime test not just
* Assert because this condition is easy to miss in testing. */
if (estate->es_epq_active != NULL)
elog(ERROR, “ModifyTable should not be called during EvalPlanQual”);
/* If we’ve already completed processing, don’t try to do more. We need
* this test because ExecPostprocessPlan might call us an extra time, and
* our subplan’s nodes aren’t necessarily robust against being called
* extra times.*/
if (node->mt_done)
return NULL;
/* On first call, fire BEFORE STATEMENT triggers before proceeding.*/
if (node->fireBSTriggers)
{
fireBSTriggers(node);
node->fireBSTriggers = false;
}
/* Preload local variables */
resultRelInfo = node->resultRelInfo + node->mt_whichplan;
subplanstate = node->mt_plans[node->mt_whichplan];
junkfilter = resultRelInfo->ri_junkFilter;
/* es_result_relation_info must point to the currently active result relation while we are within this ModifyTable node.
* Even though ModifyTable nodes can’t be nested statically, they can be nested
* dynamically (since our subplan could include a reference to a modifying
* CTE). So we have to save and restore the caller’s value.*/
saved_resultRelInfo = estate->es_result_relation_info;
estate->es_result_relation_info = resultRelInfo;
/* Fetch rows from subplan(s), and execute the required table modification for each row.*/
for (;;)
{
/* Reset the per-output-tuple exprcontext. This is needed because
* triggers expect to use that context as workspace. It’s a bit ugly
* to do this below the top level of the plan, however. We might need to rethink this later.*/
ResetPerTupleExprContext(estate);
/* Reset per-tuple memory context used for processing on conflict and
* returning clauses, to free any expression evaluation storage allocated in the previous cycle. */
if (pstate->ps_ExprContext)
ResetExprContext(pstate->ps_ExprContext);
planSlot = ExecProcNode(subplanstate);
if (TupIsNull(planSlot))
{
/* advance to next subplan if any */
node->mt_whichplan++; // 分区表的update,每个分区分布对应一个subplan,当执行完一个分区再执行下一个分区
if (node->mt_whichplan < node->mt_nplans)
{
resultRelInfo++;
subplanstate = node->mt_plans[node->mt_whichplan];
junkfilter = resultRelInfo->ri_junkFilter;
estate->es_result_relation_info = resultRelInfo;
EvalPlanQualSetPlan(&node->mt_epqstate, subplanstate->plan, node->mt_arowmarks[node->mt_whichplan]);
/* Prepare to convert transition tuples from this child. */
if (node->mt_transition_capture != NULL) {
node->mt_transition_capture->tcs_map = tupconv_map_for_subplan(node, node->mt_whichplan);
}
if (node->mt_oc_transition_capture != NULL) {
node->mt_oc_transition_capture->tcs_map = tupconv_map_for_subplan(node, node->mt_whichplan);
}
continue;
}
else
break;
}
/* Ensure input tuple is the right format for the target relation.*/
if (node->mt_scans[node->mt_whichplan]->tts_ops != planSlot->tts_ops) {
ExecCopySlot(node->mt_scans[node->mt_whichplan], planSlot);
planSlot = node->mt_scans[node->mt_whichplan];
}
/* If resultRelInfo->ri_usesFdwDirectModify is true, all we need to do here is compute the RETURNING expressions.*/
if (resultRelInfo->ri_usesFdwDirectModify)
{
Assert(resultRelInfo->ri_projectReturning);
slot = ExecProcessReturning(resultRelInfo->ri_projectReturning, RelationGetRelid(resultRelInfo->ri_RelationDesc), NULL, planSlot);
estate->es_result_relation_info = saved_resultRelInfo;
return slot;
}
EvalPlanQualSetSlot(&node->mt_epqstate, planSlot);
slot = planSlot;
tupleid = NULL;
oldtuple = NULL;
if (junkfilter != NULL)
{
/* extract the ‘ctid’ or ‘wholerow’ junk attribute.*/
if (operation == CMD_UPDATE || operation == CMD_DELETE)
{
char relkind;
Datum datum;
bool isNull;
relkind = resultRelInfo->ri_RelationDesc->rd_rel->relkind;
if (relkind == RELKIND_RELATION || relkind == RELKIND_MATVIEW)
{
datum = ExecGetJunkAttribute(slot,junkfilter->jf_junkAttNo,&isNull);
/* shouldn’t ever get a null result… */
if (isNull)
elog(ERROR, “ctid is NULL”);
tupleid = (ItemPointer) DatumGetPointer(datum);
tuple_ctid = *tupleid; /* be sure we don’t free ctid!! */
tupleid = &tuple_ctid;
}
/* Use the wholerow attribute, when available, to reconstruct the old relation tuple.*/
else if (AttributeNumberIsValid(junkfilter->jf_junkAttNo))
{
datum = ExecGetJunkAttribute(slot,junkfilter->jf_junkAttNo,&isNull);
/* shouldn’t ever get a null result… */
if (isNull)
elog(ERROR, “wholerow is NULL”);
oldtupdata.t_data = DatumGetHeapTupleHeader(datum);
oldtupdata.t_len = HeapTupleHeaderGetDatumLength(oldtupdata.t_data);
ItemPointerSetInvalid(&(oldtupdata.t_self));
/* Historically, view triggers see invalid t_tableOid. */
oldtupdata.t_tableOid = (relkind == RELKIND_VIEW) ? InvalidOid : RelationGetRelid(resultRelInfo->ri_RelationDesc);
oldtuple = &oldtupdata;
}
else
Assert(relkind == RELKIND_FOREIGN_TABLE);
}
/* apply the junkfilter if needed. */
if (operation != CMD_DELETE)
slot = ExecFilterJunk(junkfilter, slot);
}
switch (operation)
{
case CMD_INSERT:
if (proute) /* Prepare for tuple routing if needed. */
slot = ExecPrepareTupleRouting(node, estate, proute, resultRelInfo, slot);
slot = ExecInsert(node, slot, planSlot, NULL, estate->es_result_relation_info, estate, node->canSetTag);
if (proute) /* Revert ExecPrepareTupleRouting’s state change. */
estate->es_result_relation_info = resultRelInfo;
break;
case CMD_UPDATE:
slot = ExecUpdate(node, tupleid, oldtuple, slot, planSlot,
&node->mt_epqstate, estate, node->canSetTag);
break;
case CMD_DELETE:
slot = ExecDelete(node, tupleid, oldtuple, planSlot,
&node->mt_epqstate, estate,
true, node->canSetTag, false /* changingPart */ , NULL, NULL);
break;
default:
elog(ERROR, “unknown operation”);
break;
}
/* If we got a RETURNING result, return it to caller. We’ll continue the work on next call.*/
if (slot) {
estate->es_result_relation_info = saved_resultRelInfo;
return slot;
}
}
estate->es_result_relation_info = saved_resultRelInfo; /* Restore es_result_relation_info before exiting */
fireASTriggers(node); /* We’re done, but fire AFTER STATEMENT triggers before exiting.*/
node->mt_done = true;
return NULL;
}
我们看一下具体执行Update的实现
/* —————————————————————-
* ExecUpdate
*
* note: we can’t run UPDATE queries with transactions off because UPDATEs are actually INSERTs and our
* scan will mistakenly loop forever, updating the tuple it just inserted.. This should be fixed but until it
* is, we don’t want to get stuck in an infinite loop which corrupts your database..
*
* When updating a table, tupleid identifies the tuple to update and oldtuple is NULL.
*
* Returns RETURNING result if any, otherwise NULL.
* —————————————————————-*/
static TupleTableSlot *
ExecUpdate(ModifyTableState *mtstate,
ItemPointer tupleid,
HeapTuple oldtuple,
TupleTableSlot *slot,
TupleTableSlot *planSlot,
EPQState *epqstate,
EState *estate,
bool canSetTag)
{
ResultRelInfo *resultRelInfo;
Relation resultRelationDesc;
TM_Result result;
TM_FailureData tmfd;
List *recheckIndexes = NIL;
TupleConversionMap *saved_tcs_map = NULL;
/* abort the operation if not running transactions*/
if (IsBootstrapProcessingMode())
elog(ERROR, “cannot UPDATE during bootstrap”);
ExecMaterializeSlot(slot);
/* get information on the (current) result relation*/
resultRelInfo = estate->es_result_relation_info;
resultRelationDesc = resultRelInfo->ri_RelationDesc;
/* BEFORE ROW UPDATE Triggers */
if (resultRelInfo->ri_TrigDesc && resultRelInfo->ri_TrigDesc->trig_update_before_row)
{
if (!ExecBRUpdateTriggers(estate, epqstate, resultRelInfo, tupleid, oldtuple, slot))
return NULL; /* “do nothing” */
}
/* INSTEAD OF ROW UPDATE Triggers */
if (resultRelInfo->ri_TrigDesc && resultRelInfo->ri_TrigDesc->trig_update_instead_row)
{
if (!ExecIRUpdateTriggers(estate, resultRelInfo, oldtuple, slot))
return NULL; /* “do nothing” */
}
else if (resultRelInfo->ri_FdwRoutine)
{
/* Compute stored generated columns*/
if (resultRelationDesc->rd_att->constr && resultRelationDesc->rd_att->constr->has_generated_stored)
ExecComputeStoredGenerated(estate, slot, CMD_UPDATE);
/* update in foreign table: let the FDW do it*/
slot = resultRelInfo->ri_FdwRoutine->ExecForeignUpdate(estate, resultRelInfo, slot, planSlot);
if (slot == NULL) /* “do nothing” */
return NULL;
/* AFTER ROW Triggers or RETURNING expressions might reference the
* tableoid column, so (re-)initialize tts_tableOid before evaluating them. */
slot->tts_tableOid = RelationGetRelid(resultRelationDesc);
}
else
{
LockTupleMode lockmode;
bool partition_constraint_failed;
bool update_indexes;
/* Constraints might reference the tableoid column, so (re-)initialize
* tts_tableOid before evaluating them.*/
slot->tts_tableOid = RelationGetRelid(resultRelationDesc);
/* Compute stored generated columns*/
if (resultRelationDesc->rd_att->constr && resultRelationDesc->rd_att->constr->has_generated_stored)
ExecComputeStoredGenerated(estate, slot, CMD_UPDATE);
/*
* Check any RLS UPDATE WITH CHECK policies
*
* If we generate a new candidate tuple after EvalPlanQual testing, we
* must loop back here and recheck any RLS policies and constraints.
* (We don’t need to redo triggers, however. If there are any BEFORE
* triggers then trigger.c will have done table_tuple_lock to lock the
* correct tuple, so there’s no need to do them again.) */
lreplace:;
/* ensure slot is independent, consider e.g. EPQ */
ExecMaterializeSlot(slot);
/* If partition constraint fails, this row might get moved to another
* partition, in which case we should check the RLS CHECK policy just
* before inserting into the new partition, rather than doing it here.
* This is because a trigger on that partition might again change the
* row. So skip the WCO checks if the partition constraint fails. */
partition_constraint_failed = resultRelInfo->ri_PartitionCheck && !ExecPartitionCheck(resultRelInfo, slot, estate, false);
if (!partition_constraint_failed && resultRelInfo->ri_WithCheckOptions != NIL)
{
/* ExecWithCheckOptions() will skip any WCOs which are not of the kind we are looking for at this point. */
ExecWithCheckOptions(WCO_RLS_UPDATE_CHECK, resultRelInfo, slot, estate);
}
/* If a partition check failed, try to move the row into the right partition.*/
if (partition_constraint_failed)
{
bool tuple_deleted;
TupleTableSlot *ret_slot;
TupleTableSlot *orig_slot = slot;
TupleTableSlot *epqslot = NULL;
PartitionTupleRouting *proute = mtstate->mt_partition_tuple_routing;
int map_index;
TupleConversionMap *tupconv_map;
/* Disallow an INSERT ON CONFLICT DO UPDATE that causes the
* original row to migrate to a different partition. Maybe this
* can be implemented some day, but it seems a fringe feature with
* little redeeming value.*/
if (((ModifyTable *) mtstate->ps.plan)->onConflictAction == ONCONFLICT_UPDATE)
ereport(ERROR,
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
errmsg(“invalid ON UPDATE specification”),
errdetail(“The result tuple would appear in a different partition than the original tuple.”)));
/* When an UPDATE is run on a leaf partition, we will not have
* partition tuple routing set up. In that case, fail with
* partition constraint violation error.*/
if (proute == NULL)
ExecPartitionCheckEmitError(resultRelInfo, slot, estate);
/* Row movement, part 1. Delete the tuple, but skip RETURNING
* processing. We want to return rows from INSERT.*/
ExecDelete(mtstate, tupleid, oldtuple, planSlot, epqstate, estate, false, false /* canSetTag */ , true /* changingPart */ , &tuple_deleted, &epqslot);
/* For some reason if DELETE didn’t happen (e.g. trigger prevented
* it, or it was already deleted by self, or it was concurrently
* deleted by another transaction), then we should skip the insert
* as well; otherwise, an UPDATE could cause an increase in the
* total number of rows across all partitions, which is clearly wrong.
*
* For a normal UPDATE, the case where the tuple has been the
* subject of a concurrent UPDATE or DELETE would be handled by
* the EvalPlanQual machinery, but for an UPDATE that we’ve
* translated into a DELETE from this partition and an INSERT into
* some other partition, that’s not available, because CTID chains
* can’t span relation boundaries. We mimic the semantics to a
* limited extent by skipping the INSERT if the DELETE fails to
* find a tuple. This ensures that two concurrent attempts to
* UPDATE the same tuple at the same time can’t turn one tuple
* into two, and that an UPDATE of a just-deleted tuple can’t resurrect it.*/
if (!tuple_deleted)
{
/*
* epqslot will be typically NULL. But when ExecDelete()
* finds that another transaction has concurrently updated the
* same row, it re-fetches the row, skips the delete, and
* epqslot is set to the re-fetched tuple slot. In that case,
* we need to do all the checks again.
*/
if (TupIsNull(epqslot))
return NULL;
else
{
slot = ExecFilterJunk(resultRelInfo->ri_junkFilter, epqslot);
goto lreplace;
}
}
/* Updates set the transition capture map only when a new subplan
* is chosen. But for inserts, it is set for each row. So after
* INSERT, we need to revert back to the map created for UPDATE;
* otherwise the next UPDATE will incorrectly use the one created
* for INSERT. So first save the one created for UPDATE. */
if (mtstate->mt_transition_capture)
saved_tcs_map = mtstate->mt_transition_capture->tcs_map;
/* resultRelInfo is one of the per-subplan resultRelInfos. So we
* should convert the tuple into root’s tuple descriptor, since
* ExecInsert() starts the search from root. The tuple conversion
* map list is in the order of mtstate->resultRelInfo[], so to
* retrieve the one for this resultRel, we need to know the
* position of the resultRel in mtstate->resultRelInfo[]. */
map_index = resultRelInfo – mtstate->resultRelInfo;
Assert(map_index >= 0 && map_index < mtstate->mt_nplans);
tupconv_map = tupconv_map_for_subplan(mtstate, map_index);
if (tupconv_map != NULL)
slot = execute_attr_map_slot(tupconv_map->attrMap, slot, mtstate->mt_root_tuple_slot);
/* Prepare for tuple routing, making it look like we’re inserting into the root. */
Assert(mtstate->rootResultRelInfo != NULL);
slot = ExecPrepareTupleRouting(mtstate, estate, proute, mtstate->rootResultRelInfo, slot);
ret_slot = ExecInsert(mtstate, slot, planSlot,
orig_slot, resultRelInfo,
estate, canSetTag);
/* Revert ExecPrepareTupleRouting’s node change. */
estate->es_result_relation_info = resultRelInfo;
if (mtstate->mt_transition_capture)
{
mtstate->mt_transition_capture->tcs_original_insert_tuple = NULL;
mtstate->mt_transition_capture->tcs_map = saved_tcs_map;
}
return ret_slot;
}
/* Check the constraints of the tuple. We’ve already checked the
* partition constraint above; however, we must still ensure the tuple
* passes all other constraints, so we will call ExecConstraints() and
* have it validate all remaining checks.*/
if (resultRelationDesc->rd_att->constr)
ExecConstraints(resultRelInfo, slot, estate);
/* replace the heap tuple
*
* Note: if es_crosscheck_snapshot isn’t InvalidSnapshot, we check
* that the row to be updated is visible to that snapshot, and throw a
* can’t-serialize error if not. This is a special-case behavior
* needed for referential integrity updates in transaction-snapshot mode transactions. */
result = table_tuple_update(resultRelationDesc, tupleid, slot, estate->es_output_cid,
estate->es_snapshot, estate->es_crosscheck_snapshot, true /* wait for commit */ ,&tmfd, &lockmode, &update_indexes);
switch (result)
{
case TM_SelfModified:
/* The target tuple was already updated or deleted by the
* current command, or by a later command in the current
* transaction. The former case is possible in a join UPDATE
* where multiple tuples join to the same target tuple. This
* is pretty questionable, but Postgres has always allowed it:
* we just execute the first update action and ignore
* additional update attempts.
*
* The latter case arises if the tuple is modified by a
* command in a BEFORE trigger, or perhaps by a command in a
* volatile function used in the query. In such situations we
* should not ignore the update, but it is equally unsafe to
* proceed. We don’t want to discard the original UPDATE
* while keeping the triggered actions based on it; and we
* have no principled way to merge this update with the
* previous ones. So throwing an error is the only safe
* course.
*
* If a trigger actually intends this type of interaction, it
* can re-execute the UPDATE (assuming it can figure out how)
* and then return NULL to cancel the outer update.*/
if (tmfd.cmax != estate->es_output_cid)
ereport(ERROR,(errcode(ERRCODE_TRIGGERED_DATA_CHANGE_VIOLATION),
errmsg(“tuple to be updated was already modified by an operation triggered by the current command”),
errhint(“Consider using an AFTER trigger instead of a BEFORE trigger to propagate changes to other rows.”)));
/* Else, already updated by self; nothing to do */
return NULL;
case TM_Ok:
break;
case TM_Updated:
{
TupleTableSlot *inputslot;
TupleTableSlot *epqslot;
if (IsolationUsesXactSnapshot())
ereport(ERROR,(errcode(ERRCODE_T_R_SERIALIZATION_FAILURE),errmsg(“could not serialize access due to concurrent update”)));
/* Already know that we’re going to need to do EPQ, so fetch tuple directly into the right slot. */
inputslot = EvalPlanQualSlot(epqstate, resultRelationDesc,resultRelInfo->ri_RangeTableIndex);
result = table_tuple_lock(resultRelationDesc, tupleid, estate->es_snapshot,inputslot, estate->es_output_cid, lockmode, LockWaitBlock, TUPLE_LOCK_FLAG_FIND_LAST_VERSION,&tmfd);
switch (result)
{
case TM_Ok:
Assert(tmfd.traversed);
epqslot = EvalPlanQual(epqstate, resultRelationDesc, resultRelInfo->ri_RangeTableIndex, inputslot);
if (TupIsNull(epqslot))
/* Tuple not passing quals anymore, exiting… */
return NULL;
slot = ExecFilterJunk(resultRelInfo->ri_junkFilter, epqslot);
goto lreplace;
case TM_Deleted:
/* tuple already deleted; nothing to do */
return NULL;
case TM_SelfModified:
/*
* This can be reached when following an update chain from a tuple updated by another session,
* reaching a tuple that was already updated in this transaction. If previously modified by
* this command, ignore the redundant update, otherwise error out.
*
* See also TM_SelfModified response to table_tuple_update() above.*/
if (tmfd.cmax != estate->es_output_cid)
ereport(ERROR,(errcode(ERRCODE_TRIGGERED_DATA_CHANGE_VIOLATION),
errmsg(“tuple to be updated was already modified by an operation triggered by the current command”),errhint(“Consider using an AFTER trigger instead of a BEFORE trigger to propagate changes to other rows.”)));
return NULL;
default:
/* see table_tuple_lock call in ExecDelete() */
elog(ERROR, “unexpected table_tuple_lock status: %u”, result);
return NULL;
}
}
break;
case TM_Deleted:
if (IsolationUsesXactSnapshot())
ereport(ERROR,(errcode(ERRCODE_T_R_SERIALIZATION_FAILURE),errmsg(“could not serialize access due to concurrent delete”)));
/* tuple already deleted; nothing to do */
return NULL;
default:
elog(ERROR, “unrecognized table_tuple_update status: %u”,
result);
return NULL;
}
/* insert index entries for tuple if necessary */
if (resultRelInfo->ri_NumIndices > 0 && update_indexes)
recheckIndexes = ExecInsertIndexTuples(slot, estate, false, NULL, NIL);
}
if (canSetTag)
(estate->es_processed)++;
/* AFTER ROW UPDATE Triggers */
ExecARUpdateTriggers(estate, resultRelInfo, tupleid, oldtuple, slot,recheckIndexes,mtstate->operation == CMD_INSERT ?mtstate->mt_oc_transition_capture : mtstate->mt_transition_capture);
list_free(recheckIndexes);
/* Check any WITH CHECK OPTION constraints from parent views. We are
* required to do this after testing all constraints and uniqueness
* violations per the SQL spec, so we do it after actually updating the
* record in the heap and all indexes.
*
* ExecWithCheckOptions() will skip any WCOs which are not of the kind we
* are looking for at this point. */
if (resultRelInfo->ri_WithCheckOptions != NIL)
ExecWithCheckOptions(WCO_VIEW_CHECK, resultRelInfo, slot, estate);
if (resultRelInfo->ri_projectReturning) /* Process RETURNING if present */
return ExecProcessReturning(resultRelInfo->ri_projectReturning,RelationGetRelid(resultRelationDesc),slot, planSlot);
return NULL;
}
再往下就是涉及到存储引擎的部分了,我们重点看一下其对外的接口输入参数。重点是这4个参数:
-
relation – table to be modified (caller must hold suitable lock) (要更新的那个表)
-
otid – TID of old tuple to be replaced (要更新的元组ID,对应的是老的元组,更新后相当于是插入一条新元组,老元组的tid值要更新为新的tid值)
-
slot – newly constructed tuple data to store (新元组的值)
-
cid – update command ID (used for visibility test, and stored into cmax/cmin if successful) (cid值,事务相关) 执行器层面的更新算子是建立在存储引擎提供的底层table_tuple_update接口之上的。是我们编写ExecUpdate以及ExecModifyTable的基础。
* Update a tuple.
* Input parameters:
* relation – table to be modified (caller must hold suitable lock)
* otid – TID of old tuple to be replaced
* slot – newly constructed tuple data to store
* cid – update command ID (used for visibility test, and stored into cmax/cmin if successful)
* crosscheck – if not InvalidSnapshot, also check old tuple against this
* wait – true if should wait for any conflicting update to commit/abort
* Output parameters:
* tmfd – filled in failure cases (see below)
* lockmode – filled with lock mode acquired on tuple
* update_indexes – in success cases this is set to true if new index entries are required for this tuple
*
* Normal, successful return value is TM_Ok, which means we did actually update it. */
static inline TM_Result
table_tuple_update(Relation rel, ItemPointer otid, TupleTableSlot *slot, CommandId cid,
Snapshot snapshot, Snapshot crosscheck, bool wait, TM_FailureData *tmfd, LockTupleMode *lockmode, bool *update_indexes)
{
return rel->rd_tableam->tuple_update(rel, otid, slot, cid,
snapshot, crosscheck, wait, tmfd, lockmode, update_indexes);
}
事务
这一块主要是要理解PG中update语句并不是原地更新元组,而是插入一条新元组。因为PG实现MVCC与Mysql,Oracle的实现方式有所不同,并不是通过undo日志实现的,相当于把undo日志记录到了原有的表中,并不是单独存放在一个地方。具体的不再细述,内容太多了,以后再分析事务部分。
好了,内容很多,分析源码的时候,涉及到的知识点以及逻辑是非常多的,我们最好每次分析只抓一个主干,不然每个都分析,最后就会比较乱。就先分析到这里吧。
总结
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