
正文
Oracle 12C In-Memory特性研究
提示:扫一扫查出行【扫一扫了解最新限行尾号】
复制提示
Oracle 12C In-Memory特性研究一、Oracle In-Memory1.1 In-Memory 开启方法1.2 开启与关闭IM column store1.3 inmemory优先级调整1.4 加载对象到IM二、In-Memory测试2.1 全字段查询2.2 索引字段比较测试2.3 批量update测试2.4 大批量insert测试2.5 大量delete测试2.6 压缩方式测试2.7 查询大量列性能测试三、评估对象在IMO大小四、参考文献
一、Oracle In-Memory
行格式与列格式:
Oracle 数据库传统上以行格式存储数据。在行格式数据库中,数据库中存储的每个新事务或新记录都表示为表中的一个新行,而在查询数据时是利用传统BUFFER CACHE。
列格式数据库将表以单独的列结构存储到内存中。列格式适用于报表类,分析,选择少量列但是查询要访问大部分的数据的场景。
一、Oracle In-Memory
行格式与列格式:
Oracle 数据库传统上以行格式存储数据。在行格式数据库中,数据库中存储的每个新事务或新记录都表示为表中的一个新行,而在查询数据时是利用传统BUFFER CACHE。
列格式数据库将表以单独的列结构存储到内存中。列格式适用于报表类,分析,选择少量列但是查询要访问大部分的数据的场景。
1.1 In-Memory 开启方法
启用IMO非常简单,12.1.0.2及之后版本下,设置INMEMORY_SIZE 为非0值便可启用IM column store特性。
INMEMORY_SIZE 是个实例级参数,默认为0,设置一个非0值时,最小值为100M。
通常情况下,sys用户下的对象及SYSTEM、SYSAUX表空间上的对象无法使用IMO特性,但通过设置“_enable_imc_sys”隐含参数也可以使用
开启DB In-Memory过程如下:
1、修改INMEMORY_SIZE参数:
SQL> ALTER SYSTEM SET INMEMORY_SIZE=1G SCOPE=SPFILE;
2、检查sga参数的设置,确保在设置完inmemroy_size参数之后数据库实例还可以正常启动。如果数据库使用了ASMM,则需要检查sga_target参数。如果使用了AMM,则需要检查MEMORY_TARGET参数,同时也需要检查SGA_MAX_TARGET(或MEMORY_MAX_TARGET)。
备注:从 12.2 开始,可以动态增加 In-Memory 区域的大小,为此,只需 通过 ALTER SYSTEM 命令增加 INMEMORY_SIZE 参数值即可
3、重启数据库实例
4、查看IM特性是否开启
SQL> SHOW PARAMETER inmemory;
NAME TYPE VALUE
------------------------------------ ----------- ------------------------------
inmemory_adg_enabled boolean TRUE
inmemory_clause_default string
inmemory_expressions_usage string ENABLE
inmemory_force string DEFAULT
inmemory_max_populate_servers integer 2
inmemory_query string ENABLE
inmemory_size big integer 1G
inmemory_trickle_repopulate_servers_ integer 1
percent
inmemory_virtual_columns string MANUAL
optimizer_inmemory_aware boolean TRUE
1234567891011121314
1.2 开启与关闭IM column store
1、TABLE 级启用:
可以通过如下初始建表或后续修改表 inmemory 属性的方式进行启用:
create table test (id number) inmemory;
alter table test inmemory;
123
2、COLUMN 级启用:
仅启用表中某列前,该表必须先设置为 inmemory 模式:
alter table imo_t1 inmemory (id) no inmemory (name,type); alter table imo_t2 inmemory (name) no inmemory (id,type);
启用IMO非常简单,12.1.0.2及之后版本下,设置INMEMORY_SIZE 为非0值便可启用IM column store特性。
INMEMORY_SIZE 是个实例级参数,默认为0,设置一个非0值时,最小值为100M。
通常情况下,sys用户下的对象及SYSTEM、SYSAUX表空间上的对象无法使用IMO特性,但通过设置“_enable_imc_sys”隐含参数也可以使用
开启DB In-Memory过程如下:
1、修改INMEMORY_SIZE参数:
SQL> ALTER SYSTEM SET INMEMORY_SIZE=1G SCOPE=SPFILE;
2、检查sga参数的设置,确保在设置完inmemroy_size参数之后数据库实例还可以正常启动。如果数据库使用了ASMM,则需要检查sga_target参数。如果使用了AMM,则需要检查MEMORY_TARGET参数,同时也需要检查SGA_MAX_TARGET(或MEMORY_MAX_TARGET)。
备注:从 12.2 开始,可以动态增加 In-Memory 区域的大小,为此,只需 通过 ALTER SYSTEM 命令增加 INMEMORY_SIZE 参数值即可
3、重启数据库实例
4、查看IM特性是否开启
SQL> SHOW PARAMETER inmemory;
NAME TYPE VALUE
------------------------------------ ----------- ------------------------------
inmemory_adg_enabled boolean TRUE
inmemory_clause_default string
inmemory_expressions_usage string ENABLE
inmemory_force string DEFAULT
inmemory_max_populate_servers integer 2
inmemory_query string ENABLE
inmemory_size big integer 1G
inmemory_trickle_repopulate_servers_ integer 1
percent
inmemory_virtual_columns string MANUAL
optimizer_inmemory_aware boolean TRUE
1234567891011121314
1.2 开启与关闭IM column store
1、TABLE 级启用:
可以通过如下初始建表或后续修改表 inmemory 属性的方式进行启用:
create table test (id number) inmemory;
alter table test inmemory;
123
2、COLUMN 级启用:
仅启用表中某列前,该表必须先设置为 inmemory 模式:
alter table imo_t1 inmemory (id) no inmemory (name,type); alter table imo_t2 inmemory (name) no inmemory (id,type);
SELECT table_name, segment_column_id seg_col_id, column_name, inmemory_compression FROM v$im_column_level WHERE owner = 'IMOTEST' and table_name in ('IMO_T1','IMO_T2') ORDER BY 1,3;
TABLE_NAME SEG_COL_ID COLUMN_NAME INMEMORY_COMPRESSION
---------- ---------- --------------- -----------------------
IMO_T1 1 ID DEFAULT
IMO_T1 2 NAME NO INMEMORY
IMO_T1 3 TYPE NO INMEMORY
IMO_T2 1 ID NO INMEMORY
IMO_T2 2 NAME DEFAULT
IMO_T2 3 TYPE NO INMEMORY
1234567891011121314
3、表空间级启用:
可以通过如下初始创建表空间或后续修改表空间 inmemory 属性的方式进行启用,在属性为 inmemory 的表空间中创建的对象自动加载 inmemory 属性,除非显示设置对象为 no inmemory:
create tablespace imotest datafile '/u01/app/oracle/oradata/orcl/imotest01.dbf' size 100M default inmemory;
或
alter tablespace imotest default inmemory;
select tablespace_name, def_inmemory from dba_tablespaces where tablespace in ('IMOTEST');
alter tablespace imotest default inmemory;
select tablespace_name, def_inmemory from dba_tablespaces where tablespace in ('IMOTEST');
TABLESPACE_NAME DEF_INMEMORY
------------------------------ ---------------
IMOTEST ENABLED
12345678910
4、如果需要知道具体哪些列开启了IM column store则需要到V$IM_COLUMN_LEVEL中进行查看
SQL> SELECT TABLE_NAME, COLUMN_NAME, INMEMORY_COMPRESSION FROM V$IM_COLUMN_LEVEL WHERE TABLE_NAME = 'TBNAME';
1
5、查询有关IM列表属性
SQL> SELECT OWNER, SEGMENT_NAME,bytes,INMEMORY_SIZE,POPULATE_STATUS, BYTES_NOT_POPULATED FROM V$IM_SEGMENTS;
------------------------------ ---------------
IMOTEST ENABLED
12345678910
4、如果需要知道具体哪些列开启了IM column store则需要到V$IM_COLUMN_LEVEL中进行查看
SQL> SELECT TABLE_NAME, COLUMN_NAME, INMEMORY_COMPRESSION FROM V$IM_COLUMN_LEVEL WHERE TABLE_NAME = 'TBNAME';
1
5、查询有关IM列表属性
SQL> SELECT OWNER, SEGMENT_NAME,bytes,INMEMORY_SIZE,POPULATE_STATUS, BYTES_NOT_POPULATED FROM V$IM_SEGMENTS;
OWNER SEGMENT_NA BYTES INMEMORY_SIZE POPULATE_STAT BYTES_NOT_POPULATED
---------- ---------- ---------- ------------- ------------- -------------------
CS MEM 391880704 52428800 COMPLETED 0
CS TEST 99426304 15138816 COMPLETED 0
CS DUP 5095424 3407872 COMPLETED 0
1234567
6、关闭inmemory
alter table test no inmemory;
1
1.3 inmemory优先级调整
启用了 IMO 的对象,会按照一定的优先级进入 SGA 中配置好的 IN-MEMORY 区域,同时,在 IN-MEMORY 区域用满后,依次置换出优先级较低的对象。下表为关于 IMO 对象优先级说明:
优先级描述
PRIORITY NONE 缺省级别;执行 SQL 引起对象扫描后,触发进入 IN-MEMORY
PRIORITY CRITICAL 最高优先级;数据库启动后立即进入 IN-MEMORY
PRIORITY HIGH 在具有 CRITICAL 优先级的对象之后进入 IN-MEMORY
PRIORITY MEDIUM 在具有 CRITICAL、HIGH 优先级的对象之后进入 IN-MEMORY
PRIORITY LOW 在具有 CRITICAL、HIGH、MEDIUM 优先级的对象之后进入 IN-MEMORY
12345
修改示例:
SQL> alter table test inmemory priority high;
---------- ---------- ---------- ------------- ------------- -------------------
CS MEM 391880704 52428800 COMPLETED 0
CS TEST 99426304 15138816 COMPLETED 0
CS DUP 5095424 3407872 COMPLETED 0
1234567
6、关闭inmemory
alter table test no inmemory;
1
1.3 inmemory优先级调整
启用了 IMO 的对象,会按照一定的优先级进入 SGA 中配置好的 IN-MEMORY 区域,同时,在 IN-MEMORY 区域用满后,依次置换出优先级较低的对象。下表为关于 IMO 对象优先级说明:
优先级描述
PRIORITY NONE 缺省级别;执行 SQL 引起对象扫描后,触发进入 IN-MEMORY
PRIORITY CRITICAL 最高优先级;数据库启动后立即进入 IN-MEMORY
PRIORITY HIGH 在具有 CRITICAL 优先级的对象之后进入 IN-MEMORY
PRIORITY MEDIUM 在具有 CRITICAL、HIGH 优先级的对象之后进入 IN-MEMORY
PRIORITY LOW 在具有 CRITICAL、HIGH、MEDIUM 优先级的对象之后进入 IN-MEMORY
12345
修改示例:
SQL> alter table test inmemory priority high;
SQL> col owner format a30
SQL> col segment_name format a30
SQL> SELECT INMEMORY,INMEMORY_PRIORITY,INMEMORY_COMPRESSION,INMEMORY_DISTRIBUTE, INMEMORY_DUPLICATE
FROM USER_TABLES WHERE TABLE_NAME = 'TEST';
INMEMORY INMEMORY INMEMORY_COMPRESS INMEMORY_DISTRI INMEMORY_DUPL
-------- -------- ----------------- --------------- -------------
ENABLED HIGH FOR QUERY LOW AUTO NO DUPLICATE
1234567891011
1.4 加载对象到IM
1、通过全表扫描objects加载数据到IM
SQL> SELECT /*+ FULL (s) */ COUNT(*) FROM table s;
查询V$IM_SEGMENTS中的数据
SQL> col owner for a10
FROM USER_TABLES WHERE TABLE_NAME = 'TEST';
INMEMORY INMEMORY INMEMORY_COMPRESS INMEMORY_DISTRI INMEMORY_DUPL
-------- -------- ----------------- --------------- -------------
ENABLED HIGH FOR QUERY LOW AUTO NO DUPLICATE
1234567891011
1.4 加载对象到IM
1、通过全表扫描objects加载数据到IM
SQL> SELECT /*+ FULL (s) */ COUNT(*) FROM table s;
查询V$IM_SEGMENTS中的数据
SQL> col owner for a10
SQL> col SEGMENT_NAME for a10
SQL> SELECT OWNER, SEGMENT_NAME, POPULATE_STATUS, BYTES_NOT_POPULATED FROM V$IM_SEGMENTS;
OWNER SEGMENT_NA POPULATE_ BYTES_NOT_POPULATED
OWNER SEGMENT_NA POPULATE_ BYTES_NOT_POPULATED
---------- ---------- --------- -------------------
CS TEST COMPLETED 0
12345678910111213
2、DBMS_INMEMORY来加载数据
DBMS_INMEMORY包提供了两个PROCEDURE来手工加载数据到IM中:
POPULATE:强制加载给定的表
REPOPULATE:强制重新加载给定的表,在该表已经至少加载过一次之后才可使用。
手工执行DBMS_INMEMORY.POPULATE procedure来加载TEST表到IM中
SQL> EXEC DBMS_INMEMORY.POPULATE('CS','TEST');
12
通过DBMS_INMEMORY.REPOPULATE prcedure及FORCE=>TRUE选项来加载TEST表到IM中。FORCE=>TRUE选项强制进行一次完整重新载入,类似于full refresh
SQL> EXEC DBMS_INMEMORY.REPOPULATE('CS','TEST', FORCE=>TRUE);
1
3、设置PRIORITY clause自动加载数据
将测试表TEST的PRIORITY级别改为HIGH。
SQL> ALTER TABLE test INMEMORY PRIORITY HIGH|MEDIUM|LOW;
1
二、In-Memory测试
2.1 全字段查询
通过CTAS方式创建表TEST,普通行式扫描与开启inmemory特性分别测试,比对执行计划。
create table test as select * from dba_objects;
1
no inmemory查询测试
set timing on
set autotrace traceonly
set pagesize 200 linesize 200
col TABLE_NAME for a20
col INMEMORY_PRIORITY for a20
col INMEMORY_DISTRIBUTE for a20
col INMEMORY_COMPRESSION for a20
1234567
全字段查询,执行计划
SQL> select count(*) from test;
COUNT(*)
----------
74329
Elapsed: 00:00:00.01
12345678910111213
2、DBMS_INMEMORY来加载数据
DBMS_INMEMORY包提供了两个PROCEDURE来手工加载数据到IM中:
POPULATE:强制加载给定的表
REPOPULATE:强制重新加载给定的表,在该表已经至少加载过一次之后才可使用。
手工执行DBMS_INMEMORY.POPULATE procedure来加载TEST表到IM中
SQL> EXEC DBMS_INMEMORY.POPULATE('CS','TEST');
12
通过DBMS_INMEMORY.REPOPULATE prcedure及FORCE=>TRUE选项来加载TEST表到IM中。FORCE=>TRUE选项强制进行一次完整重新载入,类似于full refresh
SQL> EXEC DBMS_INMEMORY.REPOPULATE('CS','TEST', FORCE=>TRUE);
1
3、设置PRIORITY clause自动加载数据
将测试表TEST的PRIORITY级别改为HIGH。
SQL> ALTER TABLE test INMEMORY PRIORITY HIGH|MEDIUM|LOW;
1
二、In-Memory测试
2.1 全字段查询
通过CTAS方式创建表TEST,普通行式扫描与开启inmemory特性分别测试,比对执行计划。
create table test as select * from dba_objects;
1
no inmemory查询测试
set timing on
set autotrace traceonly
set pagesize 200 linesize 200
col TABLE_NAME for a20
col INMEMORY_PRIORITY for a20
col INMEMORY_DISTRIBUTE for a20
col INMEMORY_COMPRESSION for a20
1234567
全字段查询,执行计划
SQL> select count(*) from test;
COUNT(*)
----------
74329
Elapsed: 00:00:00.01
Execution Plan
----------------------------------------------------------
Plan hash value: 1950795681
----------------------------------------------------------
Plan hash value: 1950795681
-------------------------------------------------------------------
| Id | Operation | Name | Rows | Cost (%CPU)| Time |
-------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 403 (1)| 00:00:01 |
| 1 | SORT AGGREGATE | | 1 | | |
| 2 | TABLE ACCESS FULL| TEST | 74329 | 403 (1)| 00:00:01 |
-------------------------------------------------------------------
| Id | Operation | Name | Rows | Cost (%CPU)| Time |
-------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 403 (1)| 00:00:01 |
| 1 | SORT AGGREGATE | | 1 | | |
| 2 | TABLE ACCESS FULL| TEST | 74329 | 403 (1)| 00:00:01 |
-------------------------------------------------------------------
Statistics
----------------------------------------------------------
0 recursive calls
5 db block gets
1460 consistent gets
0 physical reads
0 redo size
544 bytes sent via SQL*Net to client
608 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
1234567891011121314151617181920212223242526272829303132
开启in memory查询测试
SQL> alter table test inmemory;
1
SQL> select TABLE_NAME,INMEMORY_PRIORITY,INMEMORY_DISTRIBUTE,INMEMORY_COMPRESSION from user_tables;
----------------------------------------------------------
0 recursive calls
5 db block gets
1460 consistent gets
0 physical reads
0 redo size
544 bytes sent via SQL*Net to client
608 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
1234567891011121314151617181920212223242526272829303132
开启in memory查询测试
SQL> alter table test inmemory;
1
SQL> select TABLE_NAME,INMEMORY_PRIORITY,INMEMORY_DISTRIBUTE,INMEMORY_COMPRESSION from user_tables;
TABLE_NAME INMEMORY_PRIORITY INMEMORY_DISTRIBUTE INMEMORY_COMPRESSION
-------------------- -------------------- -------------------- --------------------
TEST NONE AUTO FOR QUERY LOW
-------------------- -------------------- -------------------- --------------------
TEST NONE AUTO FOR QUERY LOW
已开启inmemory
1234567
SQL> select pool,ALLOC_BYTES/1024/1024,USED_BYTES/1024/1024,POPULATE_STATUS,con_id
from V$INMEMORY_AREA;
1234567
SQL> select pool,ALLOC_BYTES/1024/1024,USED_BYTES/1024/1024,POPULATE_STATUS,con_id
from V$INMEMORY_AREA;
POOL ALLOC_BYTES/1024/1024 USED_BYTES/1024/1024 POPULATE_STATUS CON_ID
------------ ------------ --------------------- ---------- ------------------
1MB POOL 815 0 DONE 3
64KB POOL 192 0 DONE 3
--因为只是把该表设置了INMEMORY,但是未查询过,所以查询V$INMEMORY_AREA中未使用相关内存--
12345678
全字段查询,执行计划
第一次执行:
SQL> select count(*) from test;
------------ ------------ --------------------- ---------- ------------------
1MB POOL 815 0 DONE 3
64KB POOL 192 0 DONE 3
--因为只是把该表设置了INMEMORY,但是未查询过,所以查询V$INMEMORY_AREA中未使用相关内存--
12345678
全字段查询,执行计划
第一次执行:
SQL> select count(*) from test;
COUNT(*)
----------
74329
----------
74329
Elapsed: 00:00:00.05
Execution Plan
----------------------------------------------------------
Plan hash value: 1950795681
----------------------------------------------------------
Plan hash value: 1950795681
----------------------------------------------------------------------------
| Id | Operation | Name | Rows | Cost (%CPU)| Time |
----------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 403 (1)| 00:00:01 |
| 1 | SORT AGGREGATE | | 1 | | |
| 2 | TABLE ACCESS INMEMORY FULL| TEST | 74329 | 403 (1)| 00:00:01 |
----------------------------------------------------------------------------
| Id | Operation | Name | Rows | Cost (%CPU)| Time |
----------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 403 (1)| 00:00:01 |
| 1 | SORT AGGREGATE | | 1 | | |
| 2 | TABLE ACCESS INMEMORY FULL| TEST | 74329 | 403 (1)| 00:00:01 |
----------------------------------------------------------------------------
Statistics
----------------------------------------------------------
5 recursive calls
5 db block gets
1467 consistent gets
0 physical reads
0 redo size
544 bytes sent via SQL*Net to client
608 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
2 sorts (memory)
0 sorts (disk)
1 rows processed
12345678910111213141516171819202122232425262728293031323334
第二次执行:
Elapsed: 00:00:00.03
----------------------------------------------------------
5 recursive calls
5 db block gets
1467 consistent gets
0 physical reads
0 redo size
544 bytes sent via SQL*Net to client
608 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
2 sorts (memory)
0 sorts (disk)
1 rows processed
12345678910111213141516171819202122232425262728293031323334
第二次执行:
Elapsed: 00:00:00.03
Execution Plan
----------------------------------------------------------
Plan hash value: 1950795681
----------------------------------------------------------
Plan hash value: 1950795681
----------------------------------------------------------------------------
| Id | Operation | Name | Rows | Cost (%CPU)| Time |
----------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 16 (7)| 00:00:01 |
| 1 | SORT AGGREGATE | | 1 | | |
| 2 | TABLE ACCESS INMEMORY FULL| TEST | 74329 | 16 (7)| 00:00:01 |
----------------------------------------------------------------------------
| Id | Operation | Name | Rows | Cost (%CPU)| Time |
----------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 16 (7)| 00:00:01 |
| 1 | SORT AGGREGATE | | 1 | | |
| 2 | TABLE ACCESS INMEMORY FULL| TEST | 74329 | 16 (7)| 00:00:01 |
----------------------------------------------------------------------------
Statistics
----------------------------------------------------------
0 recursive calls
3 db block gets
9 consistent gets
0 physical reads
0 redo size
544 bytes sent via SQL*Net to client
608 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
12345678910111213141516171819202122232425262728
查询inmemory内存使用:
SQL> select pool,ALLOC_BYTES/1024/1024,USED_BYTES/1024/1024,POPULATE_STATUS,con_id
from V$INMEMORY_AREA;
----------------------------------------------------------
0 recursive calls
3 db block gets
9 consistent gets
0 physical reads
0 redo size
544 bytes sent via SQL*Net to client
608 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
12345678910111213141516171819202122232425262728
查询inmemory内存使用:
SQL> select pool,ALLOC_BYTES/1024/1024,USED_BYTES/1024/1024,POPULATE_STATUS,con_id
from V$INMEMORY_AREA;
POOL ALLOC_BYTES/1024/1024 USED_BYTES/1024/1024 POPULATE_STATUS CON_ID
-------------------------- --------------------- -------------------- -------------------------- ----------
1MB POOL 815 4 DONE 3
64KB POOL 192 .25 DONE 3
--再次查看,已经使用了分配的In-Memory中内存
12345678
性能比对:
-------------------------- --------------------- -------------------- -------------------------- ----------
1MB POOL 815 4 DONE 3
64KB POOL 192 .25 DONE 3
--再次查看,已经使用了分配的In-Memory中内存
12345678
性能比对:
sql plan
no-inmemory
inmemory
no-inmemory
inmemory
consistent gets
1460
9
1460
9
physical reads
0
0
0
0
Cost
403
16
403
16
结果:
开启inmemory之后性能提升162倍
2.2 索引字段比较测试
在已开启IMO特性条件下,通过给表test增加列索引,比较IM与索引执行计划
1、在object_name上创建索引
SQL> create index idx_test_OBname on test(OBJECT_NAME);
1
2、查看表TEST是否加载到IM中
col owner for a20
col SEGMENT_NAME for a20
col POPULATE_STATUS for a20
col BYTES_NOT_POPULATED for 99999
开启inmemory之后性能提升162倍
2.2 索引字段比较测试
在已开启IMO特性条件下,通过给表test增加列索引,比较IM与索引执行计划
1、在object_name上创建索引
SQL> create index idx_test_OBname on test(OBJECT_NAME);
1
2、查看表TEST是否加载到IM中
col owner for a20
col SEGMENT_NAME for a20
col POPULATE_STATUS for a20
col BYTES_NOT_POPULATED for 99999
SELECT OWNER, SEGMENT_NAME, POPULATE_STATUS, BYTES_NOT_POPULATED FROM V$IM_SEGMENTS;
OWNER SEGMENT_NAME POPULATE_STATUS BYTES_NOT_POPULATED
-------------------- -------------------- -------------------- -------------------
CS TEST COMPLETED 0
表已被加入到IM中
12345678910
3、使用索引简单列查询
SQL> set autotrace traceonly
SQL> select count(*) from test where object_name='TEST';
OWNER SEGMENT_NAME POPULATE_STATUS BYTES_NOT_POPULATED
-------------------- -------------------- -------------------- -------------------
CS TEST COMPLETED 0
表已被加入到IM中
12345678910
3、使用索引简单列查询
SQL> set autotrace traceonly
SQL> select count(*) from test where object_name='TEST';
Execution Plan
----------------------------------------------------------
Plan hash value: 3197243274
----------------------------------------------------------
Plan hash value: 3197243274
-------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 35 | 3 (0)| 00:00:01 |
| 1 | SORT AGGREGATE | | 1 | 35 | | |
|* 2 | INDEX RANGE SCAN| IDX_TEST_OBNAME | 10 | 350 | 3 (0)| 00:00:01 |
-------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 35 | 3 (0)| 00:00:01 |
| 1 | SORT AGGREGATE | | 1 | 35 | | |
|* 2 | INDEX RANGE SCAN| IDX_TEST_OBNAME | 10 | 350 | 3 (0)| 00:00:01 |
-------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
---------------------------------------------------
2 - access("OBJECT_NAME"='TEST')
Statistics
----------------------------------------------------------
2 recursive calls
0 db block gets
6 consistent gets
2 physical reads
0 redo size
542 bytes sent via SQL*Net to client
607 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
逻辑读:6
物理:2
1234567891011121314151617181920212223242526272829303132333435363738
4、强制全表扫描查询
SQL> select /*+full(s)*/count(*) from test s where object_name='test';
----------------------------------------------------------
2 recursive calls
0 db block gets
6 consistent gets
2 physical reads
0 redo size
542 bytes sent via SQL*Net to client
607 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
逻辑读:6
物理:2
1234567891011121314151617181920212223242526272829303132333435363738
4、强制全表扫描查询
SQL> select /*+full(s)*/count(*) from test s where object_name='test';
Execution Plan
----------------------------------------------------------
Plan hash value: 1950795681
----------------------------------------------------------
Plan hash value: 1950795681
------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 35 | 124 (1)| 00:00:01 |
| 1 | SORT AGGREGATE | | 1 | 35 | | |
|* 2 | TABLE ACCESS INMEMORY FULL| TEST | 9 | 315 | 124 (1)| 00:00:01 |
------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 35 | 124 (1)| 00:00:01 |
| 1 | SORT AGGREGATE | | 1 | 35 | | |
|* 2 | TABLE ACCESS INMEMORY FULL| TEST | 9 | 315 | 124 (1)| 00:00:01 |
------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
---------------------------------------------------
2 - inmemory("OBJECT_NAME"='test')
filter("OBJECT_NAME"='test')
filter("OBJECT_NAME"='test')
Statistics
----------------------------------------------------------
1 recursive calls
0 db block gets
10 consistent gets
0 physical reads
0 redo size
541 bytes sent via SQL*Net to client
607 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
逻辑读:10
物理读:0
12345678910111213141516171819202122232425262728293031323334353637
总结:在数据离散度较高,且通过索引条件过滤的扫描场景中,IM特性对性能并没有提升,传统的索引+行式存储的执行计划已经足够,在默认情况下还是会根据查询索引返回rowid的方式查找数据。
2.3 批量update测试
1、创建测试表disk、emp,分别为im表以及rows表,总数相同
SQL> create table disk as select * from dba_objects;
SQL> insert into disk select * from disk;
----------------------------------------------------------
1 recursive calls
0 db block gets
10 consistent gets
0 physical reads
0 redo size
541 bytes sent via SQL*Net to client
607 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
逻辑读:10
物理读:0
12345678910111213141516171819202122232425262728293031323334353637
总结:在数据离散度较高,且通过索引条件过滤的扫描场景中,IM特性对性能并没有提升,传统的索引+行式存储的执行计划已经足够,在默认情况下还是会根据查询索引返回rowid的方式查找数据。
2.3 批量update测试
1、创建测试表disk、emp,分别为im表以及rows表,总数相同
SQL> create table disk as select * from dba_objects;
SQL> insert into disk select * from disk;
74360 rows created.
SQL> /
148720 rows created.
SQL> /
297440 rows created.
SQL> /
594880 rows created.
SQL> /
1189760 rows created.
SQL> commit;
Commit complete.
SQL> select count(*) from disk;
COUNT(*)
----------
2379520
SQL> create table mem as select * from disk inmemory;
1234567891011121314151617181920212223242526272829303132
更新磁盘表
update disk set owner=‘tom’;
更新内存表
update mem set owner=‘tom’;
普通表:
时间:14.49
逻辑读:3202294+894128
物理读:5602
cost:403
IM表:
时间:18.94
逻辑读:3231179+254
物理读:92476
cost:483
总结:IM特性在update性能有所下降
2.4 大批量insert测试
从磁盘插到磁盘
insert into disk select * from cs;
从磁盘插到内存
insert into mem select * from cs;
普通表:
时间:0.13
逻辑读:9332+2903
物理读:2895
cost:404
IM表:
时间:0.17
逻辑读:3231179+254
物理读:92476
cost:483
2.5 大量delete测试
delete from disk where rownum <10000;
delete from mem where rownum <10000;
普通表:
时间:0.08
逻辑读:11470+202
物理读:253
cost:12986
IM表:
时间:0.07
逻辑读:11472+9
物理读:0
cost:493
2.6 压缩方式测试
----------
2379520
SQL> create table mem as select * from disk inmemory;
1234567891011121314151617181920212223242526272829303132
更新磁盘表
update disk set owner=‘tom’;
更新内存表
update mem set owner=‘tom’;
普通表:
时间:14.49
逻辑读:3202294+894128
物理读:5602
cost:403
IM表:
时间:18.94
逻辑读:3231179+254
物理读:92476
cost:483
总结:IM特性在update性能有所下降
2.4 大批量insert测试
从磁盘插到磁盘
insert into disk select * from cs;
从磁盘插到内存
insert into mem select * from cs;
普通表:
时间:0.13
逻辑读:9332+2903
物理读:2895
cost:404
IM表:
时间:0.17
逻辑读:3231179+254
物理读:92476
cost:483
2.5 大量delete测试
delete from disk where rownum <10000;
delete from mem where rownum <10000;
普通表:
时间:0.08
逻辑读:11470+202
物理读:253
cost:12986
IM表:
时间:0.07
逻辑读:11472+9
物理读:0
cost:493
2.6 压缩方式测试
压缩方式
描述
描述
NO MEMCOMPRESS
IMO 中存储无压缩
IMO 中存储无压缩
MEMCOMPRESS FOR DML
最小化压缩,优化 DML 操作
最小化压缩,优化 DML 操作
MEMCOMPRESS FOR QUERY LOW
缺省方式:查询性能最优、空间压缩效果好于DML方式
缺省方式:查询性能最优、空间压缩效果好于DML方式
MEMCOMPRESS FOR QUERY HIGH
查询性能次优(excellent)、空间压缩效果好于 QUERY LOW
查询性能次优(excellent)、空间压缩效果好于 QUERY LOW
MEMCOMPRESS FOR CAPACITY LOW
查询性能良好(good)、空间压缩效果好于 QUERY HIGH
查询性能良好(good)、空间压缩效果好于 QUERY HIGH
MEMCOMPRESS FOR CAPACITY HIGH
缺省设置、空间压缩效果最优
缺省设置、空间压缩效果最优
查看压缩比
col owner for a5
col SEGMENT_NAME for a10
col POPULATE_STATUS for a10
col INMEMORY_COMPRESSION for a10
SQL> SELECT V.OWNER, V.SEGMENT_NAME,V.BYTES/1024/1024 ORIG_SIZE_MB,V.INMEMORY_SIZE/1024/1024 IN_MEM_SIZE_MB,BYTES_NOT_POPULATED,POPULATE_STATUS status,INMEMORY_COMPRESSION,V.BYTES/V.INMEMORY_SIZE COMP_RATIO FROM V$IM_SEGMENTS V WHERE SEGMENT_NAME = 'TEST';
col owner for a5
col SEGMENT_NAME for a10
col POPULATE_STATUS for a10
col INMEMORY_COMPRESSION for a10
SQL> SELECT V.OWNER, V.SEGMENT_NAME,V.BYTES/1024/1024 ORIG_SIZE_MB,V.INMEMORY_SIZE/1024/1024 IN_MEM_SIZE_MB,BYTES_NOT_POPULATED,POPULATE_STATUS status,INMEMORY_COMPRESSION,V.BYTES/V.INMEMORY_SIZE COMP_RATIO FROM V$IM_SEGMENTS V WHERE SEGMENT_NAME = 'TEST';
OWNER SEGMENT_NAME ORIG_SIZE_MB IN_MEM_SIZE_MB BYTES_NOT_POPULATED STATUS INMEMORY_COMPRESS COMP_RATIO
----- -------------------- ------------ -------------- ------------------- -------------------- ----------------- ----------
CS TEST 1466.78125 110.625 0 COMPLETED FOR QUERY LOW 13.2590395
123456789
表TEST在磁盘上占用1466MB,采用默认压缩方式,内存中占用110.625MB,压缩比为13.26:1
压缩比测试:
表TEST大小1466.78125MB,数据行9514112
1、NO MEMCOMPRESS:
alter table test inmemory MEMCOMPRESS NO MEMCOMPRESS;
逻辑读:14
物理读:0
COST: 126
时间: 0.01
压缩比:1.19
123456
2、MEMCOMPRESS FOR DML:
alter table test inmemory MEMCOMPRESS FOR DML;
逻辑读:14
物理读:0
COST: 126
时间:0.01
压缩比:1.22
123456
3、MEMCOMPRESS FOR QUERY LOW:
alter table test inmemory MEMCOMPRESS FOR QUERY LOW;
逻辑读:14
物理读:0
COST:125
时间:0.01
压缩比:7.20
123456
4、MEMCOMPRESS FOR QUERY HIGH:
alter table test inmemory MEMCOMPRESS FOR QUERY high;
逻辑读:14
物理读:0
COST: 125
时间:0.01
压缩比:9.67
123456
5、MEMCOMPRESS FOR CAPACITY LOW:
alter table test inmemory MEMCOMPRESS FOR CAPACITY LOW;
逻辑读:14
物理读:0
COST: 125
时间:0.01
压缩比:12.91
123456
6、MEMCOMPRESS FOR CAPACITY HIGH:
alter table test inmemory MEMCOMPRESS FOR CAPACITY HIGH;
逻辑读:14
物理读:0
COST: 25
时间:0.01
压缩比:19.14
----- -------------------- ------------ -------------- ------------------- -------------------- ----------------- ----------
CS TEST 1466.78125 110.625 0 COMPLETED FOR QUERY LOW 13.2590395
123456789
表TEST在磁盘上占用1466MB,采用默认压缩方式,内存中占用110.625MB,压缩比为13.26:1
压缩比测试:
表TEST大小1466.78125MB,数据行9514112
1、NO MEMCOMPRESS:
alter table test inmemory MEMCOMPRESS NO MEMCOMPRESS;
逻辑读:14
物理读:0
COST: 126
时间: 0.01
压缩比:1.19
123456
2、MEMCOMPRESS FOR DML:
alter table test inmemory MEMCOMPRESS FOR DML;
逻辑读:14
物理读:0
COST: 126
时间:0.01
压缩比:1.22
123456
3、MEMCOMPRESS FOR QUERY LOW:
alter table test inmemory MEMCOMPRESS FOR QUERY LOW;
逻辑读:14
物理读:0
COST:125
时间:0.01
压缩比:7.20
123456
4、MEMCOMPRESS FOR QUERY HIGH:
alter table test inmemory MEMCOMPRESS FOR QUERY high;
逻辑读:14
物理读:0
COST: 125
时间:0.01
压缩比:9.67
123456
5、MEMCOMPRESS FOR CAPACITY LOW:
alter table test inmemory MEMCOMPRESS FOR CAPACITY LOW;
逻辑读:14
物理读:0
COST: 125
时间:0.01
压缩比:12.91
123456
6、MEMCOMPRESS FOR CAPACITY HIGH:
alter table test inmemory MEMCOMPRESS FOR CAPACITY HIGH;
逻辑读:14
物理读:0
COST: 25
时间:0.01
压缩比:19.14
1234567
测试结果汇总:
测试结果汇总:
压缩方式
压缩比
压缩比
NO MEMCOMPRESS
1.19
1.19
MEMCOMPRESS FOR DML
1.22
1.22
MEMCOMPRESS FOR QUERY LOW
7.20
7.20
MEMCOMPRESS FOR QUERY HIGH
9.67
9.67
MEMCOMPRESS FOR CAPACITY LOW
12.91
12.91
MEMCOMPRESS FOR CAPACITY HIGH
19.14
19.14
总结:压缩方式不同,表加载到IM中的时间也会不一样。压缩比越大加载到内存中的时间越长。而对于select查询消耗时间不影响。
2.7 查询大量列性能测试
三、评估对象在IMO大小
DBMS_COMPRESSION.GET_COMPRESSION_RATIO
在对一张表使用COMPRESSION clause进行IM压缩级别设置之前,我们可以通过Oracle的COMPRESSION ADVISOR对表放入到IM中的大小进行提前计算。
SET SERVEROUTPUT ON
2.7 查询大量列性能测试
三、评估对象在IMO大小
DBMS_COMPRESSION.GET_COMPRESSION_RATIO
在对一张表使用COMPRESSION clause进行IM压缩级别设置之前,我们可以通过Oracle的COMPRESSION ADVISOR对表放入到IM中的大小进行提前计算。
SET SERVEROUTPUT ON
DECLARE
l_blkcnt_cmp PLS_INTEGER;
l_blkcnt_uncmp PLS_INTEGER;
l_row_cmp PLS_INTEGER;
l_row_uncmp PLS_INTEGER;
l_cmp_ratio PLS_INTEGER;
l_comptype_str VARCHAR2(100);
BEGIN
dbms_compression.get_compression_ratio (
-- Input parameters
scratchtbsname => 'CS',
ownname => 'CS',
objname => 'TEST',
subobjname => NULL,
comptype => dbms_compression.comp_inmemory_QUERY_LOW,
-- Output parameter
blkcnt_cmp => l_blkcnt_cmp,
blkcnt_uncmp => l_blkcnt_uncmp,
row_cmp => l_row_cmp,
row_uncmp => l_row_uncmp,
cmp_ratio => l_cmp_ratio,
comptype_str => l_comptype_str,
subset_numrows => dbms_compression.comp_ratio_allrows);
dbms_output.put_line('Comp. ratio (QUERY LOW):'||l_cmp_ratio);
END;
/
1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253
Comp. ratio (QUERY LOW):7
估计结果压缩比7,实际压缩比为7.20
#五、RAC环境测试
rac环境独有参数DUPLICATE clause、DISTRIBUTE clause:
DUPLICATE clause:
此参数为EXADATA一体机专用,在RAC环境中,每个节点拥有自己的IM Area。一个objects根据DUPLICATE clause的设置将一样的数据加载到多个IM Area中。
默认是NO DUPLICATE设置,表示在数据库的IM中对一个objects在所有节点中合起来只保存一份。举例说明,比如三节点的RAC中,对于分区表SALES来讲可能2012年份的数据在1节点,2013年份的数据在2节点,2014年份的数据在3节点,每个分区只保存在一个节点上。
为了提升可用性,也可以设置为DUPLICAET ALL,在每个节点上都保存一份。举例说明,还是刚才那个SALES表的请款下,1,2,3三个节点各保存一份完整sales表数据到各自的IM中。在任意一个节点上都可以获取查询需要的数据。
在设置为DUPLICATE ALL的情况下
DISTRIBUTE clause:
如果一个objects因为太大无法被加载到一个IM Area中,还可以通过DISTRIBUTE clause的设置将它分成几个数据片分别加载到不同的节点中。
默认情况下DISTRIBUTE clause的默认值为AUTO-DISTRIBUTE,这时候是否将objects分布式分布在不同的节点上由Oracle内部算法决定。这个参数对于单实例没有影响,在RAC环境中,默认存在IM中的表会分布在各个节点之中。
RAC环境并不像单实例一样只需修改表的IM属性即可启用,如果要使用IMO,必须在系统层面修改“并行度策略”为自动。下面对参数“parallel_degree_policy”,分别测试2个场景
1、先查看要测试的表TEST是否已加载到IM STORE
col SEGMENT_NAME for a5
col POPULATE_STATUS for a10
col INMEMORY_DISTRIBUTE for a10
col INMEMORY_DUPLICATE for a20
1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253
Comp. ratio (QUERY LOW):7
估计结果压缩比7,实际压缩比为7.20
#五、RAC环境测试
rac环境独有参数DUPLICATE clause、DISTRIBUTE clause:
DUPLICATE clause:
此参数为EXADATA一体机专用,在RAC环境中,每个节点拥有自己的IM Area。一个objects根据DUPLICATE clause的设置将一样的数据加载到多个IM Area中。
默认是NO DUPLICATE设置,表示在数据库的IM中对一个objects在所有节点中合起来只保存一份。举例说明,比如三节点的RAC中,对于分区表SALES来讲可能2012年份的数据在1节点,2013年份的数据在2节点,2014年份的数据在3节点,每个分区只保存在一个节点上。
为了提升可用性,也可以设置为DUPLICAET ALL,在每个节点上都保存一份。举例说明,还是刚才那个SALES表的请款下,1,2,3三个节点各保存一份完整sales表数据到各自的IM中。在任意一个节点上都可以获取查询需要的数据。
在设置为DUPLICATE ALL的情况下
DISTRIBUTE clause:
如果一个objects因为太大无法被加载到一个IM Area中,还可以通过DISTRIBUTE clause的设置将它分成几个数据片分别加载到不同的节点中。
默认情况下DISTRIBUTE clause的默认值为AUTO-DISTRIBUTE,这时候是否将objects分布式分布在不同的节点上由Oracle内部算法决定。这个参数对于单实例没有影响,在RAC环境中,默认存在IM中的表会分布在各个节点之中。
RAC环境并不像单实例一样只需修改表的IM属性即可启用,如果要使用IMO,必须在系统层面修改“并行度策略”为自动。下面对参数“parallel_degree_policy”,分别测试2个场景
1、先查看要测试的表TEST是否已加载到IM STORE
col SEGMENT_NAME for a5
col POPULATE_STATUS for a10
col INMEMORY_DISTRIBUTE for a10
col INMEMORY_DUPLICATE for a20
SQL> select INST_ID,SEGMENT_NAME,INMEMORY_SIZE/1024/1024,BYTES/1024/1024,BYTES_NOT_POPULATED/1024/1024,INMEMORY_DISTRIBUTE,INMEMORY_DUPLICATE,POPULATE_STATUS from gv$im_segments;
INST_ID SEGME INMEMORY_SIZE/1024/1024 BYTES/1024/1024 BYTES_NOT_POPULATED/1024/1024 INMEMORY_D INMEMORY_DUPLICATE POPULATE_S
---------- ----- ----------------------- --------------- ----------------------------- ---------- -------------------- ----------
2 TEST 9.125 192 123.53125 AUTO NO DUPLICATE COMPLETED
1 TEST 16.1875 192 66.9140625 AUTO NO DUPLICATE COMPLETED
1234567891011
1、开启AUTO DOP
alter system set parallel_degree_policy=AUTO sid='*';
alter system set parallel_force_local=false sid='*';
alter system flush buffer_cache;
alter system flush shared_pool;
1234
2、查看执行计划
SQL> select /*+ parallel */count(*) from test;
---------- ----- ----------------------- --------------- ----------------------------- ---------- -------------------- ----------
2 TEST 9.125 192 123.53125 AUTO NO DUPLICATE COMPLETED
1 TEST 16.1875 192 66.9140625 AUTO NO DUPLICATE COMPLETED
1234567891011
1、开启AUTO DOP
alter system set parallel_degree_policy=AUTO sid='*';
alter system set parallel_force_local=false sid='*';
alter system flush buffer_cache;
alter system flush shared_pool;
1234
2、查看执行计划
SQL> select /*+ parallel */count(*) from test;
COUNT(*)
----------
1455168
----------
1455168
Execution Plan
----------------------------------------------------------
Plan hash value: 2661943167
----------------------------------------------------------
Plan hash value: 2661943167
-----------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Cost (%CPU)| Time | TQ |IN-OUT| PQ Distrib |
-----------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 9 (0)| 00:00:01 | | | |
| 1 | SORT AGGREGATE | | 1 | | | | | |
| 2 | PX COORDINATOR | | | | | | | |
| 3 | PX SEND QC (RANDOM) | :TQ10000 | 1 | | | Q1,00 | P->S | QC (RAND) |
| 4 | SORT AGGREGATE | | 1 | | | Q1,00 | PCWP | |
| 5 | PX BLOCK ITERATOR | | 90948 | 9 (0)| 00:00:01 | Q1,00 | PCWC | |
| 6 | TABLE ACCESS INMEMORY FULL| TEST | 90948 | 9 (0)| 00:00:01 | Q1,00 | PCWP | |
-----------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Cost (%CPU)| Time | TQ |IN-OUT| PQ Distrib |
-----------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 9 (0)| 00:00:01 | | | |
| 1 | SORT AGGREGATE | | 1 | | | | | |
| 2 | PX COORDINATOR | | | | | | | |
| 3 | PX SEND QC (RANDOM) | :TQ10000 | 1 | | | Q1,00 | P->S | QC (RAND) |
| 4 | SORT AGGREGATE | | 1 | | | Q1,00 | PCWP | |
| 5 | PX BLOCK ITERATOR | | 90948 | 9 (0)| 00:00:01 | Q1,00 | PCWC | |
| 6 | TABLE ACCESS INMEMORY FULL| TEST | 90948 | 9 (0)| 00:00:01 | Q1,00 | PCWP | |
-----------------------------------------------------------------------------------------------------------------
Note
-----
- automatic DOP: Computed Degree of Parallelism is 2
- parallel scans affinitized for inmemory
-----
- automatic DOP: Computed Degree of Parallelism is 2
- parallel scans affinitized for inmemory
Statistics
----------------------------------------------------------
232 recursive calls
4 db block gets
163 consistent gets
15 physical reads
0 redo size
545 bytes sent via SQL*Net to client
551 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
16 sorts (memory)
0 sorts (disk)
1 rows processed
123456789101112131415161718192021222324252627282930313233343536373839404142
逻辑读:163
物理读:15
12
3、不使用并行查询查询
SQL> select count(*) from test;
----------------------------------------------------------
232 recursive calls
4 db block gets
163 consistent gets
15 physical reads
0 redo size
545 bytes sent via SQL*Net to client
551 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
16 sorts (memory)
0 sorts (disk)
1 rows processed
123456789101112131415161718192021222324252627282930313233343536373839404142
逻辑读:163
物理读:15
12
3、不使用并行查询查询
SQL> select count(*) from test;
COUNT(*)
----------
1455168
----------
1455168
Execution Plan
----------------------------------------------------------
Plan hash value: 1950795681
----------------------------------------------------------
Plan hash value: 1950795681
----------------------------------------------------------------------------
| Id | Operation | Name | Rows | Cost (%CPU)| Time |
----------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 16 (0)| 00:00:01 |
| 1 | SORT AGGREGATE | | 1 | | |
| 2 | TABLE ACCESS INMEMORY FULL| TEST | 90948 | 16 (0)| 00:00:01 |
----------------------------------------------------------------------------
| Id | Operation | Name | Rows | Cost (%CPU)| Time |
----------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 16 (0)| 00:00:01 |
| 1 | SORT AGGREGATE | | 1 | | |
| 2 | TABLE ACCESS INMEMORY FULL| TEST | 90948 | 16 (0)| 00:00:01 |
----------------------------------------------------------------------------
Note
-----
- automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation
-----
- automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation
Statistics
----------------------------------------------------------
3 recursive calls
0 db block gets
9081 consistent gets
9077 physical reads
0 redo size
545 bytes sent via SQL*Net to client
551 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
12345678910111213141516171819202122232425262728293031323334353637
逻辑读:9081
物理读:9077
12
4、关闭AUTO DOP
alter system set parallel_degree_policy=MANUAL sid='*';
alter system set parallel_force_local=false sid='*';
alter system flush buffer_cache;
alter system flush shared_pool;
1234
5、查看执行计划
SQL> select /*+ parallel */count(*) from test;
----------------------------------------------------------
3 recursive calls
0 db block gets
9081 consistent gets
9077 physical reads
0 redo size
545 bytes sent via SQL*Net to client
551 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
12345678910111213141516171819202122232425262728293031323334353637
逻辑读:9081
物理读:9077
12
4、关闭AUTO DOP
alter system set parallel_degree_policy=MANUAL sid='*';
alter system set parallel_force_local=false sid='*';
alter system flush buffer_cache;
alter system flush shared_pool;
1234
5、查看执行计划
SQL> select /*+ parallel */count(*) from test;
COUNT(*)
----------
1455168
----------
1455168
Execution Plan
----------------------------------------------------------
Plan hash value: 2661943167
----------------------------------------------------------
Plan hash value: 2661943167
-----------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Cost (%CPU)| Time | TQ |IN-OUT| PQ Distrib |
-----------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 9 (0)| 00:00:01 | | | |
| 1 | SORT AGGREGATE | | 1 | | | | | |
| 2 | PX COORDINATOR | | | | | | | |
| 3 | PX SEND QC (RANDOM) | :TQ10000 | 1 | | | Q1,00 | P->S | QC (RAND) |
| 4 | SORT AGGREGATE | | 1 | | | Q1,00 | PCWP | |
| 5 | PX BLOCK ITERATOR | | 90948 | 9 (0)| 00:00:01 | Q1,00 | PCWC | |
| 6 | TABLE ACCESS INMEMORY FULL| TEST | 90948 | 9 (0)| 00:00:01 | Q1,00 | PCWP | |
-----------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Cost (%CPU)| Time | TQ |IN-OUT| PQ Distrib |
-----------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 9 (0)| 00:00:01 | | | |
| 1 | SORT AGGREGATE | | 1 | | | | | |
| 2 | PX COORDINATOR | | | | | | | |
| 3 | PX SEND QC (RANDOM) | :TQ10000 | 1 | | | Q1,00 | P->S | QC (RAND) |
| 4 | SORT AGGREGATE | | 1 | | | Q1,00 | PCWP | |
| 5 | PX BLOCK ITERATOR | | 90948 | 9 (0)| 00:00:01 | Q1,00 | PCWC | |
| 6 | TABLE ACCESS INMEMORY FULL| TEST | 90948 | 9 (0)| 00:00:01 | Q1,00 | PCWP | |
-----------------------------------------------------------------------------------------------------------------
Note
-----
- automatic DOP: Computed Degree of Parallelism is 2
- parallel scans affinitized for inmemory
-----
- automatic DOP: Computed Degree of Parallelism is 2
- parallel scans affinitized for inmemory
Statistics
----------------------------------------------------------
209 recursive calls
4 db block gets
17909 consistent gets
17766 physical reads
0 redo size
545 bytes sent via SQL*Net to client
551 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
16 sorts (memory)
0 sorts (disk)
1 rows processed
123456789101112131415161718192021222324252627282930313233343536373839404142
逻辑读:17909
物理读:17766
12
总结:
1、调整系统参数(parallel_degree_policy)之后,rac环境下的IM列查询大幅降低了逻辑读与物理读。
2、在多实例的并发查询中实例之间传输的并不是IMCU,而是每个节点都会对本节点的数据运行相同的sql语句,之后把自己的结果集发送给发起sql语句的实例,组成最终的结果返回给用户。
----------------------------------------------------------
209 recursive calls
4 db block gets
17909 consistent gets
17766 physical reads
0 redo size
545 bytes sent via SQL*Net to client
551 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
16 sorts (memory)
0 sorts (disk)
1 rows processed
123456789101112131415161718192021222324252627282930313233343536373839404142
逻辑读:17909
物理读:17766
12
总结:
1、调整系统参数(parallel_degree_policy)之后,rac环境下的IM列查询大幅降低了逻辑读与物理读。
2、在多实例的并发查询中实例之间传输的并不是IMCU,而是每个节点都会对本节点的数据运行相同的sql语句,之后把自己的结果集发送给发起sql语句的实例,组成最终的结果返回给用户。
parallel_degree_policy
AUTO
MANUAL
AUTO
MANUAL
逻辑读
163
17909
163
17909
物理读
15
17766
15
17766
备注:
在没有显式使用并行sql时,rac环境im全表扫描并没有使用并行。oracle的优化器会通过一系列的计算比较cost。
SQL> select count(*) from test;
执行计划Note
-----
automatic DOP:
Computed Degree of Parallelism is 1 because of no expensive parallel operation
12345
In some cases, even with Auto DOP set correctly, the optimizer may calculate the cost of a serial access to be less than the cost of a parallel access. This has been identified as bug 18960760, and will usually only happen when very smalltables in the IM column store are involved in the query.
来自Oracle Blog
https://blogs.oracle.com/in-memory/oracle-database-in-memory-on-rac-part-i
12
四、参考文献
1、Oracle Database In-Memory on RAC - Part I
https://blogs.oracle.com/in-memory/oracle-database-in-memory-on-rac-part-i
2、Oracle 12c DB In-Memory入门实验手册
https://blog.csdn.net/badly9/article/details/49777993
3、Oracle12c IMO 测试
https://www.jianshu.com/p/966ee0182e1c
4、rac并行查询
http://blog.sina.com.cn/s/blog_74a7d3390102wegl.html
5、Oracle In-Memory白皮书
http://www.oracle.com/technetwork/cn/database/in-memory/overview/twp-oracle-database-in-memory-2245633-zhs.pdf
————————————————
版权声明:本文为CSDN博主「iverycd」的原创文章,遵循 CC 4.0 BY-SA 版权协议,转载请附上原文出处链接及本声明。
原文链接:https://blog.csdn.net/kiral07/article/details/86768842
在没有显式使用并行sql时,rac环境im全表扫描并没有使用并行。oracle的优化器会通过一系列的计算比较cost。
SQL> select count(*) from test;
执行计划Note
-----
automatic DOP:
Computed Degree of Parallelism is 1 because of no expensive parallel operation
12345
In some cases, even with Auto DOP set correctly, the optimizer may calculate the cost of a serial access to be less than the cost of a parallel access. This has been identified as bug 18960760, and will usually only happen when very smalltables in the IM column store are involved in the query.
来自Oracle Blog
https://blogs.oracle.com/in-memory/oracle-database-in-memory-on-rac-part-i
12
四、参考文献
1、Oracle Database In-Memory on RAC - Part I
https://blogs.oracle.com/in-memory/oracle-database-in-memory-on-rac-part-i
2、Oracle 12c DB In-Memory入门实验手册
https://blog.csdn.net/badly9/article/details/49777993
3、Oracle12c IMO 测试
https://www.jianshu.com/p/966ee0182e1c
4、rac并行查询
http://blog.sina.com.cn/s/blog_74a7d3390102wegl.html
5、Oracle In-Memory白皮书
http://www.oracle.com/technetwork/cn/database/in-memory/overview/twp-oracle-database-in-memory-2245633-zhs.pdf
————————————————
版权声明:本文为CSDN博主「iverycd」的原创文章,遵循 CC 4.0 BY-SA 版权协议,转载请附上原文出处链接及本声明。
原文链接:https://blog.csdn.net/kiral07/article/details/86768842







