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Posted to dev@crunch.apache.org by "Josh Wills (JIRA)" <ji...@apache.org> on 2012/07/06 00:12:33 UTC
[jira] [Created] (CRUNCH-3) Replicated ("map-side") joins
Josh Wills created CRUNCH-3:
-------------------------------
Summary: Replicated ("map-side") joins
Key: CRUNCH-3
URL: https://issues.apache.org/jira/browse/CRUNCH-3
Project: Crunch
Issue Type: New Feature
Components: MapReduce Patterns
Reporter: Josh Wills
Replicated joins are a common way to improve performance when joining a large dataset with a small one. The smaller dataset is loaded into memory in the mapper/reducer tasks, and is then joined with the larger dataset as the large one is processed by the MapReduce job itself.
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[jira] [Updated] (CRUNCH-3) Replicated ("map-side") joins
Posted by "Gabriel Reid (JIRA)" <ji...@apache.org>.
[ https://issues.apache.org/jira/browse/CRUNCH-3?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Gabriel Reid updated CRUNCH-3:
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Attachment: mapside-joins.patch
Patch to implement map side joins -- added after the commit was done, only for completeness.
> Replicated ("map-side") joins
> -----------------------------
>
> Key: CRUNCH-3
> URL: https://issues.apache.org/jira/browse/CRUNCH-3
> Project: Crunch
> Issue Type: New Feature
> Components: MapReduce Patterns
> Reporter: Josh Wills
> Assignee: Gabriel Reid
> Attachments: mapside-joins.patch
>
>
> Replicated joins are a common way to improve performance when joining a large dataset with a small one. The smaller dataset is loaded into memory in the mapper/reducer tasks, and is then joined with the larger dataset as the large one is processed by the MapReduce job itself.
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[jira] [Updated] (CRUNCH-3) Replicated ("map-side") joins
Posted by "Gabriel Reid (JIRA)" <ji...@apache.org>.
[ https://issues.apache.org/jira/browse/CRUNCH-3?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Gabriel Reid updated CRUNCH-3:
------------------------------
Fix Version/s: 0.3.0
Patch applied in 0.3.0
> Replicated ("map-side") joins
> -----------------------------
>
> Key: CRUNCH-3
> URL: https://issues.apache.org/jira/browse/CRUNCH-3
> Project: Crunch
> Issue Type: New Feature
> Components: MapReduce Patterns
> Reporter: Josh Wills
> Assignee: Gabriel Reid
> Fix For: 0.3.0
>
> Attachments: mapside-joins.patch
>
>
> Replicated joins are a common way to improve performance when joining a large dataset with a small one. The smaller dataset is loaded into memory in the mapper/reducer tasks, and is then joined with the larger dataset as the large one is processed by the MapReduce job itself.
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[jira] [Resolved] (CRUNCH-3) Replicated ("map-side") joins
Posted by "Gabriel Reid (JIRA)" <ji...@apache.org>.
[ https://issues.apache.org/jira/browse/CRUNCH-3?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Gabriel Reid resolved CRUNCH-3.
-------------------------------
Resolution: Fixed
> Replicated ("map-side") joins
> -----------------------------
>
> Key: CRUNCH-3
> URL: https://issues.apache.org/jira/browse/CRUNCH-3
> Project: Crunch
> Issue Type: New Feature
> Components: MapReduce Patterns
> Reporter: Josh Wills
> Assignee: Gabriel Reid
> Fix For: 0.3.0
>
> Attachments: mapside-joins.patch
>
>
> Replicated joins are a common way to improve performance when joining a large dataset with a small one. The smaller dataset is loaded into memory in the mapper/reducer tasks, and is then joined with the larger dataset as the large one is processed by the MapReduce job itself.
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[jira] [Assigned] (CRUNCH-3) Replicated ("map-side") joins
Posted by "Josh Wills (JIRA)" <ji...@apache.org>.
[ https://issues.apache.org/jira/browse/CRUNCH-3?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Josh Wills reassigned CRUNCH-3:
-------------------------------
Assignee: Gabriel Reid
> Replicated ("map-side") joins
> -----------------------------
>
> Key: CRUNCH-3
> URL: https://issues.apache.org/jira/browse/CRUNCH-3
> Project: Crunch
> Issue Type: New Feature
> Components: MapReduce Patterns
> Reporter: Josh Wills
> Assignee: Gabriel Reid
>
> Replicated joins are a common way to improve performance when joining a large dataset with a small one. The smaller dataset is loaded into memory in the mapper/reducer tasks, and is then joined with the larger dataset as the large one is processed by the MapReduce job itself.
--
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