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openGauss每日一练第19天 | 收集统计信息,打印执行计划

原创 Sean 2021-12-19
315

学习目标

学习openGauss收集统计信息、打印执行计划、垃圾收集和checkpoint

课程学习实操

连接数据库

#第一次进入等待15秒
#数据库启动中…
su - omm
gsql -r

1.准备数据

Create schema tpcds; CREATE TABLE tpcds.customer_address ( ca_address_sk integer NOT NULL , ca_address_id character(16), ca_street_number character(10) , ca_street_name character varying(60) , ca_street_type character(15) , ca_suite_number character(10) , ca_city character varying(60) , ca_county character varying(30) , ca_state character(2) , ca_zip character(10) , ca_country character varying(20) , ca_gmt_offset numeric(5,2) , ca_location_type character(20) ); insert into tpcds.customer_address values (1, 'AAAAAAAABAAAAAAA', '18', 'Jackson', 'Parkway', 'Suite 280', 'Fairfield', 'Maricopa County', 'AZ', '86192' ,'United States', -7.00, 'condo'), (2, 'AAAAAAAACAAAAAAA', '362', 'Washington 6th', 'RD', 'Suite 80', 'Fairview', 'Taos County', 'NM', '85709', 'United States', -7.00, 'condo'), (3, 'AAAAAAAADAAAAAAA', '585', 'Dogwood Washington', 'Circle', 'Suite Q', 'Pleasant Valley', 'York County', 'PA', '12477', 'United States', -5.00, 'single family'); omm=# Create schema tpcds; CREATE SCHEMA omm=# CREATE TABLE tpcds.customer_address omm-# ( omm(# ca_address_sk integer NOT NULL , omm(# ca_address_id character(16), omm(# ca_street_number character(10) , omm(# ca_street_name character varying(60) , omm(# ca_street_type character(15) , omm(# ca_suite_number character(10) , omm(# ca_city character varying(60) , omm(# ca_county character varying(30) , omm(# ca_state character(2) , omm(# ca_zip character(10) , omm(# ca_country character varying(20) , omm(# ca_gmt_offset numeric(5,2) , omm(# ca_location_type character(20) omm(# ); CREATE TABLE omm=# insert into tpcds.customer_address values omm-# (1, 'AAAAAAAABAAAAAAA', '18', 'Jackson', 'Parkway', 'Suite 280', 'Fairfield', 'Maricopa County', 'AZ', '86192' ,'United States', -7.00, 'condo'), omm-# (2, 'AAAAAAAACAAAAAAA', '362', 'Washington 6th', 'RD', 'Suite 80', 'Fairview', 'Taos County', 'NM', '85709', 'United States', -7.00, 'condo'), omm-# (3, 'AAAAAAAADAAAAAAA', '585', 'Dogwood Washington', 'Circle', 'Suite Q', 'Pleasant Valley', 'York County', 'PA', '12477', 'United States', -5.00, 'single family'); INSERT 0 3 omm=# select * from tpcds.customer_address ; ca_address_sk | ca_address_id | ca_street_number | ca_street_name | ca_street_type | ca_suite_number | ca _city | ca_county | ca_state | ca_zip | ca_country | ca_gmt_offset | ca_location_type ---------------+------------------+------------------+--------------------+-----------------+-----------------+------- ----------+-----------------+----------+------------+---------------+---------------+---------------------- 1 | AAAAAAAABAAAAAAA | 18 | Jackson | Parkway | Suite 280 | Fairfi eld | Maricopa County | AZ | 86192 | United States | -7.00 | condo 2 | AAAAAAAACAAAAAAA | 362 | Washington 6th | RD | Suite 80 | Fairvi 3 | AAAAAAAADAAAAAAA | 585 | Dogwood Washington | Circle | Suite Q | Pleasa nt Valley | York County | PA | 12477 | United States | -5.00 | single family (3 rows) ew | Taos County | NM | 85709 | United States | -7.00 | condo omm=#
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–使用序列的generate_series(1,N)函数对表插入数据

insert into tpcds.customer_address values(generate_series(10, 10000)); omm=# insert into tpcds.customer_address values(generate_series(10, 10000)); INSERT 0 9991 omm=#
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2.收集统计信息

–查看系统表中表的统计信息

select relname, relpages, reltuples from pg_class where relname = 'customer_address'; omm=# select relname, relpages, reltuples from pg_class where relname = 'customer_address'; relname | relpages | reltuples ------------------+----------+----------- customer_address | 0 | 0 (1 row) omm=#
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—使用ANALYZE VERBOSE语句更新统计信息,并输出表的相关信息

analyze VERBOSE tpcds.customer_address; omm=# analyze VERBOSE tpcds.customer_address; INFO: analyzing "tpcds.customer_address"(gaussdb pid=1) INFO: ANALYZE INFO : "customer_address": scanned 55 of 55 pages, containing 9994 live rows and 0 dead rows; 9994 rows in sample, 9994 estimated total rows(gaussdb pid=1) ANALYZE omm=#
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–查看系统表中表的统计信息

select relname, relpages, reltuples from pg_class where relname = 'customer_address'; omm=# select relname, relpages, reltuples from pg_class where relname = 'customer_address'; relname | relpages | reltuples ------------------+----------+----------- customer_address | 55 | 9994 (1 row) omm=#
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3.打印执行计划

–使用默认的打印格式

SET explain_perf_mode=normal;
–显示表简单查询的执行计划

EXPLAIN SELECT * FROM tpcds.customer_address; omm=# SET explain_perf_mode=normal; SET omm=# EXPLAIN SELECT * FROM tpcds.customer_address; QUERY PLAN ----------------------------------------------------------------------- Seq Scan on customer_address (cost=0.00..154.94 rows=9994 width=151) (1 row)
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–以JSON格式输出的执行计划(explain_perf_mode为normal时)

EXPLAIN(FORMAT JSON) SELECT * FROM tpcds.customer_address; omm=# EXPLAIN(FORMAT JSON) SELECT * FROM tpcds.customer_address; QUERY PLAN -------------------------------------------- [ + { + "Plan": { + "Node Type": "Seq Scan", + "Relation Name": "customer_address",+ "Alias": "customer_address", + "Startup Cost": 0.00, + "Total Cost": 154.94, + "Plan Rows": 9994, + "Plan Width": 151 + } + } + ] (1 row)
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–禁止开销估计的执行计划

EXPLAIN(COSTS FALSE)SELECT * FROM tpcds.customer_address; omm=# EXPLAIN(COSTS FALSE)SELECT * FROM tpcds.customer_address; QUERY PLAN ------------------------------ Seq Scan on customer_address (1 row)
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–带有聚集函数查询的执行计划

EXPLAIN SELECT SUM(ca_address_sk) FROM tpcds.customer_address WHERE ca_address_sk<100; omm=# EXPLAIN SELECT SUM(ca_address_sk) FROM tpcds.customer_address WHERE ca_address_sk<100; QUERY PLAN ------------------------------------------------------------------------- Aggregate (cost=180.16..180.17 rows=1 width=12) -> Seq Scan on customer_address (cost=0.00..179.93 rows=94 width=4) Filter: (ca_address_sk < 100) (3 rows) omm=#
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–有索引条件的执行计划

create index customer_address_idx on tpcds.customer_address(ca_address_sk); EXPLAIN SELECT * FROM tpcds.customer_address WHERE ca_address_sk<100; omm=# create index customer_address_idx on tpcds.customer_address(ca_address_sk); CREATE INDEX omm=# EXPLAIN SELECT * FROM tpcds.customer_address WHERE ca_address_sk<100; omm=# QUERY PLAN ------------------------------------------------------------------------------------------------ [Bypass] Index Scan using customer_address_idx on customer_address (cost=0.00..9.90 rows=94 width=151) Index Cond: (ca_address_sk < 100) (3 rows) omm=#
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4.垃圾收集

–VACUUM回收表或B-Tree索引中已经删除的行所占据的存储空间

update tpcds.customer_address set ca_address_sk = ca_address_sk + 1 where ca_address_sk <100; VACUUM (VERBOSE, ANALYZE) tpcds.customer_address; omm=# update tpcds.customer_address set ca_address_sk = ca_address_sk + 1 where ca_address_sk <100; UPDATE 93 omm=# VACUUM (VERBOSE, ANALYZE) tpcds.customer_address; INFO: vacuuming "tpcds.customer_address"(gaussdb pid=1) INFO: index "customer_address_idx" now contains 10087 row versions in 31 pages(gaussdb pid=1) DETAIL: 0 index row versions were removed. 0 index pages have been deleted, 0 are currently reusable. CPU 0.00s/0.00u sec elapsed 0.00 sec. INFO: "customer_address": found 0 removable, 10087 nonremovable row versions in 55 out of 55 pages(gaussdb pid=1) DETAIL: 93 dead row versions cannot be removed yet. There were 0 unused item pointers. 0 pages are entirely empty. CPU 0.00s/0.00u sec elapsed 0.00 sec. INFO: analyzing "tpcds.customer_address"(gaussdb pid=1) INFO: ANALYZE INFO : "customer_address": scanned 55 of 55 pages, containing 9994 live rows and 93 dead rows; 9994 rows in sample, 9994 estimated total rows(gaussdb pid=1) VACUUM omm=#
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5.事务日志检查点

–检查点(CHECKPOINT)是一个事务日志中的点,所有数据文件都在该点被更新以反映日志中的信息,所有数据文件都将被刷新到磁盘

CHECKPOINT; omm=# CHECKPOINT; CHECKPOINT
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6.清理数据

drop schema tpcds cascade; omm=# drop schema tpcds cascade; NOTICE: drop cascades to table tpcds.customer_address DROP SCHEMA omm=#
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课后作业

1.创建分区表,并用generate_series(1,N)函数对表插入数据

omm=# create table partition_table omm-# ( omm(# c1 int, omm(# c2 CHAR(2) omm(# ) omm-# partition by range (c1) omm-# ( omm(# partition partition_table_p0 values less than (10000), omm(# partition partition_table_p1 values less than (20000), omm(# partition partition_table_p2 values less than (30000) omm(# ); CREATE TABLE omm=# insert into partition_table values(generate_series(1, 29999)); INSERT 0 29999 omm=#
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2.收集表统计信息

omm=# select relname, relpages, reltuples from pg_class where relname = 'partition_table'; relname | relpages | reltuples -----------------+----------+----------- partition_table | 0 | 0 (1 row) omm=# analyze VERBOSE partition_table; INFO: analyzing "public.partition_table"(gaussdb pid=1) INFO: ANALYZE INFO : "partition_table": scanned 45 of 45 pages, containing 9999 live rows and 0 dead rows; 9999 rows in sample, 9999 estimated total rows(gaussdb pid=1) INFO: ANALYZE INFO : "partition_table": scanned 45 of 45 pages, containing 10000 live rows and 0 dead rows; 10000 rows in sample, 10000 estimated total rows(gaussdb pid=1) INFO: ANALYZE INFO : "partition_table": scanned 45 of 45 pages, containing 10000 live rows and 0 dead rows; 10000 rows in sample, 10000 estimated total rows(gaussdb pid=1) ANALYZE omm=# omm=# select relname, relpages, reltuples from pg_class where relname = 'partition_table'; relname | relpages | reltuples -----------------+----------+----------- partition_table | 135 | 29999 (1 row) omm=#
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3.显示简单查询的执行计划;建立索引并显示有索引条件的执行计划

omm=# SET explain_perf_mode=normal; SET omm=# EXPLAIN SELECT * FROM partition_table; QUERY PLAN ---------------------------------------------------------------------------------------- Partition Iterator (cost=0.00..434.99 rows=29999 width=16) Iterations: 3 -> Partitioned Seq Scan on partition_table (cost=0.00..434.99 rows=29999 width=16) Selected Partitions: 1..3 (4 rows) omm=# omm=# create index idx_c1 on partition_table(c1); CREATE INDEX omm=# explain select * from partition_table where c1=25; QUERY PLAN ------------------------------------------------------------------------------- Index Scan using idx_c1 on partition_table (cost=0.00..8.27 rows=1 width=16) Index Cond: (c1 = 25) (2 rows) omm=#
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4.更新表数据,并做垃圾收集

omm=# update partition_table set c1 = c1 + 1 where c1 < 10000; UPDATE 9999 omm=# VACUUM (VERBOSE, ANALYZE) partition_table; INFO: vacuuming "public.partition_table"(gaussdb pid=1) INFO: index "idx_c1" now contains 19997 row versions in 140 pages(gaussdb pid=1) DETAIL: 0 index row versions were removed. 0 index pages have been deleted, 0 are currently reusable. CPU 0.00s/0.00u sec elapsed 0.00 sec. INFO: "partition_table": found 0 removable, 19997 nonremovable row versions in 89 out of 89 pages(gaussdb pid=1) DETAIL: 9999 dead row versions cannot be removed yet. There were 0 unused item pointers. 0 pages are entirely empty. CPU 0.00s/0.00u sec elapsed 0.00 sec. INFO: vacuuming "public.partition_table"(gaussdb pid=1) INFO: index "idx_c1" now contains 10001 row versions in 140 pages(gaussdb pid=1) DETAIL: 0 index row versions were removed. 0 index pages have been deleted, 0 are currently reusable. CPU 0.00s/0.00u sec elapsed 0.00 sec. INFO: "partition_table": found 0 removable, 10001 nonremovable row versions in 45 out of 45 pages(gaussdb pid=1) DETAIL: 0 dead row versions cannot be removed yet. There were 0 unused item pointers. 0 pages are entirely empty. CPU 0.00s/0.00u sec elapsed 0.00 sec. INFO: vacuuming "public.partition_table"(gaussdb pid=1) INFO: index "idx_c1" now contains 10000 row versions in 140 pages(gaussdb pid=1) DETAIL: 0 index row versions were removed. 0 index pages have been deleted, 0 are currently reusable. CPU 0.00s/0.00u sec elapsed 0.00 sec. INFO: "partition_table": found 0 removable, 10000 nonremovable row versions in 45 out of 45 pages(gaussdb pid=1) DETAIL: 0 dead row versions cannot be removed yet. There were 0 unused item pointers. 0 pages are entirely empty. CPU 0.00s/0.00u sec elapsed 0.00 sec. INFO: scanned index "idx_c1" to remove 0.000000 invisible rows(gaussdb pid=1) DETAIL: CPU 0.00s/0.00u sec elapsed 0.00 sec. INFO: analyzing "public.partition_table"(gaussdb pid=1) INFO: ANALYZE INFO : "partition_table": scanned 89 of 89 pages, containing 9998 live rows and 9999 dead rows; 9998 rows in sample, 9998 estimated total rows(gaussdb pid=1) INFO: ANALYZE INFO : "partition_table": scanned 45 of 45 pages, containing 10001 live rows and 0 dead rows; 7542 rows in sample, 10001 estimated total rows(gaussdb pid=1) INFO: ANALYZE INFO : "partition_table": scanned 45 of 45 pages, containing 10000 live rows and 0 dead rows; 7542 rows in sample, 10000 estimated total rows(gaussdb pid=1) VACUUM omm=#
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5.清理数据

omm=# drop table partition_table; DROP TABLE omm=#
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学习总结

通过本节课的学习,我掌握了统计信息的收集方法,SQL执行计划的查看方法,垃圾的回收的方法和检查点的使用。

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