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=#
复制
–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=#
复制
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=#
复制
—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=#
复制
–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=#
复制
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)
复制
–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)
复制
–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)
复制
–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=#
复制
–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=#
复制
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=#
复制
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
复制
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=#
复制
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=#
复制
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=#
复制
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=#
复制
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=#
复制
5.清理数据
omm=# drop table partition_table;
DROP TABLE
omm=#
复制
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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