EXPDP/IMPDP中的并行度PARALLEL參數(shù)是什么

這篇文章給大家介紹EXPDP/IMPDP中的并行度PARALLEL參數(shù)是什么，內(nèi)容非常詳細(xì)，感興趣的小伙伴們可以參考借鑒，希望對(duì)大家能有所幫助。

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如果設(shè)置 EXPDP parallel=4 必須要設(shè)置4個(gè)EXPDP文件，不然PARALLEL是有問(wèn)題的，同時(shí)EXPDP會(huì)使用一個(gè)WORKER進(jìn)程導(dǎo)出METADATA，其他WORKER進(jìn)程會(huì)同時(shí)出數(shù)據(jù)，如果EXPDP作業(yè)很于250M 只會(huì)啟動(dòng)一個(gè)WORKER進(jìn)程如果是500M會(huì)啟動(dòng)2個(gè)，1000M及會(huì)啟動(dòng)4個(gè)WOKER進(jìn)程，一般來(lái)說(shuō)加上%U來(lái)設(shè)置多個(gè)文件。

而IMPDP有所不同，會(huì)先啟動(dòng)一個(gè)WOKER進(jìn)程METADATA導(dǎo)入,然后啟動(dòng)多個(gè)WORKER進(jìn)程導(dǎo)入，所以再前期只會(huì)看到WOKER在導(dǎo)入METADATA，而且IMPDP如果PARALLE=4也需要>=4個(gè)DMP文件，也可以使用%U來(lái)進(jìn)行導(dǎo)入。

nohup expdp system/**** PARALLEL=2 JOB_NAME=full_bak_job full=y dumpfile=exptest:back_%U.dmp logfile=exptest:back.log &

impdp system/*** PARALLEL=2 EXCLUDE=STATISTICS JOB_NAME=full_imp cluster=no full=y dumpfile=test:back_%U.dmp logfile=test:back_imp.log;

而在11GR2后EXPDP 和 IMDP的WORKER進(jìn)程會(huì)在多個(gè)INSTANCE啟動(dòng)，所以DIRECTORY必須在共享磁盤上，如果沒(méi)有設(shè)置共享磁盤還是指定cluster=no 來(lái)防止報(bào)錯(cuò)。

當(dāng)觀察EXPDP/IMPDP woker的時(shí)候如下：

Import> status

Job: FULL_IMP
Operation: IMPORT
Mode: FULL
State: EXECUTING
Bytes Processed: 150,300,713,536
Percent Done: 80
Current Parallelism: 6
Job Error Count: 0
Dump File: /expdp/back_%u.dmp
Dump File: /expdp/back_01.dmp
Dump File: /expdp/back_02.dmp
Dump File: /expdp/back_03.dmp
Dump File: /expdp/back_04.dmp
Dump File: /expdp/back_05.dmp
Dump File: /expdp/back_06.dmp
Dump File: /expdp/back_07.dmp
Dump File: /expdp/back_08.dmp

Worker 1 Status:
Process Name: DW00
State: EXECUTING
Object Schema: ACRUN
Object Name: T_PLY_UNDRMSG
Object Type: DATABASE_EXPORT/SCHEMA/TABLE/TABLE_DATA
Completed Objects: 3
Completed Rows: 3,856,891
Completed Bytes: 1,134,168,200
Percent Done: 83
Worker Parallelism: 1

Worker 2 Status:
Process Name: DW01
State: EXECUTING
Object Schema: ACRUN
Object Name: T_FIN_PAYDUE
Object Type: DATABASE_EXPORT/SCHEMA/TABLE/TABLE_DATA
Completed Objects: 5
Completed Rows: 2,646,941
Completed Bytes: 1,012,233,224
Percent Done: 93
Worker Parallelism: 1

Worker 3 Status:
Process Name: DW02
State: EXECUTING
Object Schema: ACRUN
Object Name: MLOG$_T_FIN_CLMDUE
Object Type: DATABASE_EXPORT/SCHEMA/TABLE/TABLE_DATA
Completed Objects: 6
Completed Bytes: 382,792,584
Worker Parallelism: 1

Worker 4 Status:
Process Name: DW03
State: EXECUTING
Object Schema: ACRUN
Object Name: T_PAY_CONFIRM_INFO
Object Type: DATABASE_EXPORT/SCHEMA/TABLE/TABLE_DATA
Completed Objects: 5
Completed Rows: 2,443,790
Completed Bytes: 943,310,104
Percent Done: 83
Worker Parallelism: 1

Worker 5 Status:
Process Name: DW04
State: EXECUTING
Object Schema: ACRUN
Object Name: T_PLY_TGT
Object Type: DATABASE_EXPORT/SCHEMA/TABLE/TABLE_DATA
Completed Objects: 6
Completed Rows: 2,285,353
Completed Bytes: 822,501,496
Percent Done: 64
Worker Parallelism: 1

Worker 6 Status:
Process Name: DW05
State: EXECUTING
Object Schema: ACRUN
Object Name: T_FIN_PREINDRCT_CLMFEE
Object Type: DATABASE_EXPORT/SCHEMA/TABLE/TABLE_DATA
Completed Objects: 5
Completed Rows: 6,042,384
Completed Bytes: 989,435,088
Percent Done: 79
Worker Parallelism: 1

英文如下：

For Data Pump Export, the value that is specified for the parallel parameter should be less than or equal to the number of files in the dump file set. Each worker or Parallel Execution Process requires exclusive access to the dump file, so having fewer dump files than the degree of parallelism will mean that some workers or PX processes will be unable to write the information they are exporting. If this occurs, the worker processes go into an idle state and will not be doing any work until more files are added to the job. See the explanation of the DUMPFILE parameter in the Database Utilities guide for details on how to specify multiple dump files for a Data Pump export job.
For Data Pump Import, the workers and PX processes can all read from the same files. However, if there are not enough dump files, the performance may not be optimal because multiple threads of execution will be trying to access the same dump file. The performance impact of multiple processes sharing the dump files depends on the I/O subsystem containing the dump files. For this reason, Data Pump Import should not have a value for the PARALLEL parameter that is significantly larger than the number of files in the dump file set.

In a typical export that includes both data and metadata, the first worker process will unload the metadata: tablespaces, schemas, grants, roles, tables, indexes, and so on. This single worker unloads the metadata, and all the rest unload the data, all at the same time. If the metadata worker finishes and there are still data objects to unload, it will start unloading the data too. The examples in this document assume that there is always one worker busy unloading metadata while the rest of the workers are busy unloading table data objects.

If the external tables method is chosen, Data Pump will determine the maximum number of PX processes that can work on a table data object. It does this by dividing the estimated size of the table data object by 250 MB and rounding the result down. If the result is zero or one, then PX processes are not used to unload the table

The PARALLEL parameter works a bit differently in Import than Export. Because there are various dependencies that exist when creating objects during import, everything must be done in order. For Import, no data loading can occur until the tables are created because data cannot be loaded into tables that do not yet exist

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