EXPDP/IMPDP 中的並行度PARALLEL引數
如果設定 EXPDP parallel=4 必須要設定4個EXPDP檔案,不然PARALLEL是有問題的,同時EXPDP會使用一個WORKER程式匯出METADATA,其他WORKER程式會同時出資料,如果EXPDP作業很於250M 只會啟動一個WORKER程式如果是500M會啟動2個,1000M及會啟動4個WOKER程式,一般來說加上%U來設定多個檔案。
而IMPDP有所不同,會先啟動一個WOKER程式METADATA匯入,然後啟動多個WORKER程式匯入,所以再前期只會看到WOKER在匯入METADATA,而且IMPDP如果PARALLE=4也需要>=4個DMP檔案,也可以使用%U來進行匯入。
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後EXPDP 和 IMDP的WORKER程式會在多個INSTANCE啟動,所以DIRECTORY必須在共享磁碟上,如果沒有設定共享磁碟還是指定cluster=no 來防止報錯。
當觀察EXPDP/IMPDP woker的時候如下:
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$_T_FIN_CLMDUE
Object Type: DATABASE_EXPORT/SCHEMA/TABLE/TABLE_DATA
Completed Objects: 6
Completed Bytes: 382,792,584
Worker Parallelism: 1
Worker 4 Status:
Process Name: DW03
State: EXECUTING
Object Schema: ACRUN
Object Name: T_PAY_CONFIRM_INFO
Object Type: DATABASE_EXPORT/SCHEMA/TABLE/TABLE_DATA
Completed Objects: 5
Completed Rows: 2,443,790
Completed Bytes: 943,310,104
Percent Done: 83
Worker Parallelism: 1
Worker 5 Status:
Process Name: DW04
State: EXECUTING
Object Schema: ACRUN
Object Name: T_PLY_TGT
Object Type: DATABASE_EXPORT/SCHEMA/TABLE/TABLE_DATA
Completed Objects: 6
Completed Rows: 2,285,353
Completed Bytes: 822,501,496
Percent Done: 64
Worker Parallelism: 1
Worker 6 Status:
Process Name: DW05
State: EXECUTING
Object Schema: ACRUN
Object Name: T_FIN_PREINDRCT_CLMFEE
Object Type: DATABASE_EXPORT/SCHEMA/TABLE/TABLE_DATA
Completed Objects: 5
Completed Rows: 6,042,384
Completed Bytes: 989,435,088
Percent Done: 79
Worker Parallelism: 1
Operation: IMPORT
Mode: FULL
State: EXECUTING
Bytes Processed: 150,300,713,536
Percent Done: 80
Current Parallelism: 6
Job Error Count: 0
Dump File: /expdp/back_%u.dmp
Dump File: /expdp/back_01.dmp
Dump File: /expdp/back_02.dmp
Dump File: /expdp/back_03.dmp
Dump File: /expdp/back_04.dmp
Dump File: /expdp/back_05.dmp
Dump File: /expdp/back_06.dmp
Dump File: /expdp/back_07.dmp
Dump File: /expdp/back_08.dmp
Worker 1 Status:
Process Name: DW00
State: EXECUTING
Object Schema: ACRUN
Object Name: T_PLY_UNDRMSG
Object Type: DATABASE_EXPORT/SCHEMA/TABLE/TABLE_DATA
Completed Objects: 3
Completed Rows: 3,856,891
Completed Bytes: 1,134,168,200
Percent Done: 83
Worker Parallelism: 1
Worker 2 Status:
Process Name: DW01
State: EXECUTING
Object Schema: ACRUN
Object Name: T_FIN_PAYDUE
Object Type: DATABASE_EXPORT/SCHEMA/TABLE/TABLE_DATA
Completed Objects: 5
Completed Rows: 2,646,941
Completed Bytes: 1,012,233,224
Percent Done: 93
Worker Parallelism: 1
Worker 3 Status:
Process Name: DW02
State: EXECUTING
Object Schema: ACRUN
Object Name: MLOG$_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.
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
來自 “ ITPUB部落格 ” ,連結:http://blog.itpub.net/29067253/viewspace-2135448/,如需轉載,請註明出處,否則將追究法律責任。
相關文章
- EXPDP的parallel引數Parallel
- impdp hangs,慎用impdp parallel引數Parallel
- parallel並行度的相關操作、概念、引數解釋Parallel並行
- oracle parallel並行_引數parameter_parallel_max_serverOracleParallel並行Server
- Oracle expdp impdp dump引數介紹Oracle
- oracle expdp中的parallelOracleParallel
- 【impdp】IMPDP中的TRANSFORM引數--【資料泵】EXPDP匯出表結構(真實案例)後傳ORM
- 【EXPDP】運用PARALLEL 和FILESIZE引數提高備份效率Parallel
- expdp/impdp 使用version引數跨版本資料遷移
- 並行(Parallel)並行Parallel
- 10G資料泵載入命令expdp/impdp的引數說明
- impdp/expdp 示例
- oracle expdp and impdpOracle
- EXPDP/IMPDP工具的使用
- Expdp,impdp工具的使用
- ORACLE EXPDP IMPDP 中停止和啟動Oracle
- Oracle 11.2中控制並行的新引數Oracle並行
- 【EXPDP/IMPDP】使用 EXPDP/IMPDP工具“模糊”匯出和匯入
- Parallel 並行技術Parallel並行
- oracle的Parallel 並行技術OracleParallel並行
- Expdp Impdp詳解
- oracle expdp/impdp用法Oracle
- impdp和expdp的總結
- impdp的remap_schema引數REM
- expdp = exp + direct mode + parallel ?Parallel
- parallel rollback引數總結Parallel
- Oracle並行操作——並行查詢(Parallel Query)Oracle並行Parallel
- expdp/impdp 用法詳解
- expdp/impdp操作例項
- expdp, impdp characteristic 特性--索引索引
- ORACLE expdp/impdp詳解Oracle
- Oracle expdp/impdp 使用示例Oracle
- 將partition expdp後impdp
- expdp/impdp用法詳解
- expdp/impdp 使用總結
- oracle資料庫的impdp,expdpOracle資料庫
- expdp/impdp的原理及使用(轉)
- 終止imp/exp和expdp/impdp程式執行的方法