本文共 8431 字，大约阅读时间需要 28 分钟。
使用greenplum时，如果需要调用一个函数，这个函数很可能就在master执行，而不会跑到segment上去执行。
例如 random()函数。 通过select random()来调用的话，不需要将这条SQL发送到segment节点，所以执行计划如下，没有gather motion的过程。postgres=# explain analyze select random(); QUERY PLAN ---------------------------------------------------------------------------------------- Result (cost=0.01..0.02 rows=1 width=0) Rows out: 1 rows with 0.017 ms to end, start offset by 0.056 ms. InitPlan -> Result (cost=0.00..0.01 rows=1 width=0) Rows out: 1 rows with 0.004 ms to end of 2 scans, start offset by 0.059 ms. Slice statistics: (slice0) Executor memory: 29K bytes. (slice1) Executor memory: 29K bytes. Statement statistics: Memory used: 128000K bytes Total runtime: 0.074 ms (11 rows)
如果要让这个函数在segment执行，怎么办呢？
通过gp_dist_random('gp_id')来调用，gp_dist_random的参数是一个可查询的视图，或表。postgres=# explain analyze select random() from gp_dist_random('gp_id'); QUERY PLAN ----------------------------------------------------------------------------------------------------------------------------------------- Gather Motion 240:1 (slice1; segments: 240) (cost=0.00..4.00 rows=240 width=0) Rows out: 240 rows at destination with 6.336 ms to first row, 59 ms to end, start offset by 4195 ms. -> Seq Scan on gp_id (cost=0.00..4.00 rows=1 width=0) Rows out: Avg 1.0 rows x 240 workers. Max 1 rows (seg0) with 0.073 ms to first row, 0.075 ms to end, start offset by 4207 ms. Slice statistics: (slice0) Executor memory: 471K bytes. (slice1) Executor memory: 163K bytes avg x 240 workers, 163K bytes max (seg0). Statement statistics: Memory used: 128000K bytes Total runtime: 4279.445 ms (10 rows) gp_id在每个segment中都有一条记录，所以以上SQL会在每个SEGMENT中调用一次random()并返回所有结果，例如我的测试环境中有240个segment, 那么以上SQL将返回240条记录。
在gp_id的定义中，介绍了gp_dist_random用它可以做一些管理的工作：
譬如查询数据库的大小，查询表的大小，其实都是这样统计的。 src/backend/catalog/postgres_bki_srcs/*------------------------------------------------------------------------- * * gp_id.h * definition of the system "database identifier" relation (gp_dbid) * along with the relation's initial contents. * * Copyright (c) 2009-2010, Greenplum inc * * NOTES * Historically this table was used to supply every segment with its * identification information. However in the 4.0 release when the file * replication feature was added it could no longer serve this purpose * because it became a requirement for all tables to have the same physical * contents on both the primary and mirror segments. To resolve this the * information is now passed to each segment on startup based on the * gp_segment_configuration (stored on the master only), and each segment * has a file in its datadirectory (gp_dbid) that uniquely identifies the * segment. * * The contents of the table are now irrelevant, with the exception that * several tools began relying on this table for use as a method of remote * function invocation via gp_dist_random('gp_id') due to the fact that this * table was guaranteed of having exactly one row on every segment. The * contents of the row have no defined meaning, but this property is still * relied upon. */ #ifndef _GP_ID_H_ #define _GP_ID_H_ #include "catalog/genbki.h" /* * Defines for gp_id table */ #define GpIdRelationName "gp_id" /* TIDYCAT_BEGINFAKEDEF CREATE TABLE gp_id with (shared=true, oid=false, relid=5001, content=SEGMENT_LOCAL) ( gpname name , numsegments smallint , dbid smallint , content smallint ); TIDYCAT_ENDFAKEDEF */ 查询数据库大小的GP函数
postgres=# \df+ pg_database_size List of functions Schema | Name | Result data type | Argument data types | Type | Data access | Volatility | Owner | Language | Source code | Description ------------+------------------+------------------+---------------------+--------+----------------+------------+----------+----------+-----------------------+------------------------------------------------------------- pg_catalog | pg_database_size | bigint | name | normal | reads sql data | volatile | dege.zzz | internal | pg_database_size_name | Calculate total disk space usage for the specified database pg_catalog | pg_database_size | bigint | oid | normal | reads sql data | volatile | dege.zzz | internal | pg_database_size_oid | Calculate total disk space usage for the specified database (2 rows)
其中pg_database_size_name 的源码如下：
很明显，在统计数据库大小时也用到了select sum(pg_database_size('%s'))::int8 from gp_dist_random('gp_id');Datum pg_database_size_name(PG_FUNCTION_ARGS) { int64 size = 0; Name dbName = PG_GETARG_NAME(0); Oid dbOid = get_database_oid(NameStr(*dbName)); if (!OidIsValid(dbOid)) ereport(ERROR, (errcode(ERRCODE_UNDEFINED_DATABASE), errmsg("database \"%s\" does not exist", NameStr(*dbName)))); size = calculate_database_size(dbOid); if (Gp_role == GP_ROLE_DISPATCH) { StringInfoData buffer; initStringInfo(&buffer); appendStringInfo(&buffer, "select sum(pg_database_size('%s'))::int8 from gp_dist_random('gp_id');", NameStr(*dbName)); size += get_size_from_segDBs(buffer.data); } PG_RETURN_INT64(size); } 不信我们可以直接查询这个SQL，和使用pg_database_size函数得到的结果几乎是一样的，只差了calculate_database_size的部分。
postgres=# select sum(pg_database_size('postgres'))::int8 from gp_dist_random('gp_id'); sum ---------------- 16006753522624 (1 row) postgres=# select pg_database_size('postgres'); pg_database_size ------------------ 16006763924106 (1 row) gp_dist_random('gp_id')本质上就是在所有节点查询gp_id，
gp_dist_random('pg_authid')就是在所有节点查询pg_authid， 例如：postgres=# select * from gp_dist_random('gp_id'); gpname | numsegments | dbid | content -----------+-------------+------+--------- Greenplum | -1 | -1 | -1 Greenplum | -1 | -1 | -1 Greenplum | -1 | -1 | -1 Greenplum | -1 | -1 | -1 Greenplum | -1 | -1 | -1 Greenplum | -1 | -1 | -1 Greenplum | -1 | -1 | -1 Greenplum | -1 | -1 | -1 Greenplum | -1 | -1 | -1 Greenplum | -1 | -1 | -1 。。。。。。 如果不想返回太多记录，可以使用limit 来过滤，但是执行还是会在所有的segment都执行，如下：
postgres=# explain analyze select random() from gp_dist_random('gp_id') limit 1; QUERY PLAN ----------------------------------------------------------------------------------------------------------------------------------------------- Limit (cost=0.00..0.04 rows=1 width=0) Rows out: 1 rows with 5.865 ms to first row, 5.884 ms to end, start offset by 4212 ms. -> Gather Motion 240:1 (slice1; segments: 240) (cost=0.00..0.04 rows=1 width=0) Rows out: 1 rows at destination with 5.857 ms to end, start offset by 4212 ms. -> Limit (cost=0.00..0.02 rows=1 width=0) Rows out: Avg 1.0 rows x 240 workers. Max 1 rows (seg0) with 0.062 ms to first row, 0.063 ms to end, start offset by 4228 ms. -> Seq Scan on gp_id (cost=0.00..4.00 rows=1 width=0) Rows out: Avg 1.0 rows x 240 workers. Max 1 rows (seg0) with 0.060 ms to end, start offset by 4228 ms. Slice statistics: (slice0) Executor memory: 463K bytes. (slice1) Executor memory: 163K bytes avg x 240 workers, 163K bytes max (seg0). Statement statistics: Memory used: 128000K bytes Total runtime: 4288.007 ms (14 rows) 转载地址：http://xehca.baihongyu.com/