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Posted to issues@hbase.apache.org by "Weichen Ye (JIRA)" <ji...@apache.org> on 2014/11/03 02:07:34 UTC
[jira] [Updated] (HBASE-12394) Support multiple regions as input to
each mapper in map/reduce jobs
[ https://issues.apache.org/jira/browse/HBASE-12394?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Weichen Ye updated HBASE-12394:
-------------------------------
Description:
For Hadoop cluster, a job with large HBase table as input always consumes a large amount of computing resources. For example, we need to create a job with 1000 mappers to scan a table with 1000 regions. This patch is to support one mapper using multiple regions as input.
The following new files are included in this patch:
TableMultiRegionInputFormat.java
TableMultiRegionInputFormatBase.java
TableMultiRegionMapReduceUtil.java
*TestTableMultiRegionInputFormatScan1.java
*TestTableMultiRegionInputFormatScan2.java
*TestTableMultiRegionInputFormatScanBase.java
*TestTableMultiRegionMapReduceUtil.java
The files start with * are tests.
In order to support multiple regions for one mapper, we need a new property in configuration--"hbase.mapreduce.scan.regionspermapper"
hbase.mapreduce.scan.regionspermapper controls how many regions used as input for one mapper. For example,if we have an HBase table with 300 regions, and we set hbase.mapreduce.scan.regionspermapper = 3. Then we run a job to scan the table, the job will use only 300/3=100 mappers.
In this way, we can control the number of mappers using the following formula.
Number of Mappers = (Total region numbers) / hbase.mapreduce.scan.regionspermapper
This is an example of the configuration.
<property>
<name>hbase.mapreduce.scan.regionspermapper</name>
<value>3</value>
</property>
This is an example for Java code:
TableMultiRegionMapReduceUtil.initTableMapperJob(tablename, scan, Map.class, Text.class, Text.class, job);
was:
For Hadoop cluster, a job with large HBase table as input always consumes a large amount of computing resources. For example, we need to create a job with 1000 mappers to scan a table with 1000 regions. This patch is to support one mapper using multiple regions as input.
The following new files are included in this patch:
TableMultiRegionInputFormat.java
TableMultiRegionInputFormatBase.java
TableMultiRegionMapReduceUtil.java
*TestTableMultiRegionInputFormatScan1.java
*TestTableMultiRegionInputFormatScan2.java
*TestTableMultiRegionInputFormatScanBase.java
*TestTableMultiRegionMapReduceUtil.java
The files start with * are tests.
In order to support multiple regions for one mapper, we need a new property in configuration--"hbase.mapreduce.scan.regionspermapper"
This is an example,which means each mapper has 3 regions as input.
<property>
<name>hbase.mapreduce.scan.regionspermapper</name>
<value>3</value>
</property>
This is an example for Java code:
TableMultiRegionMapReduceUtil.initTableMapperJob(tablename, scan, Map.class, Text.class, Text.class, job);
> Support multiple regions as input to each mapper in map/reduce jobs
> -------------------------------------------------------------------
>
> Key: HBASE-12394
> URL: https://issues.apache.org/jira/browse/HBASE-12394
> Project: HBase
> Issue Type: Improvement
> Components: mapreduce
> Affects Versions: 2.0.0, 0.98.6.1
> Reporter: Weichen Ye
> Attachments: HBASE-12394.patch
>
>
> For Hadoop cluster, a job with large HBase table as input always consumes a large amount of computing resources. For example, we need to create a job with 1000 mappers to scan a table with 1000 regions. This patch is to support one mapper using multiple regions as input.
>
> The following new files are included in this patch:
> TableMultiRegionInputFormat.java
> TableMultiRegionInputFormatBase.java
> TableMultiRegionMapReduceUtil.java
> *TestTableMultiRegionInputFormatScan1.java
> *TestTableMultiRegionInputFormatScan2.java
> *TestTableMultiRegionInputFormatScanBase.java
> *TestTableMultiRegionMapReduceUtil.java
>
> The files start with * are tests.
> In order to support multiple regions for one mapper, we need a new property in configuration--"hbase.mapreduce.scan.regionspermapper"
> hbase.mapreduce.scan.regionspermapper controls how many regions used as input for one mapper. For example,if we have an HBase table with 300 regions, and we set hbase.mapreduce.scan.regionspermapper = 3. Then we run a job to scan the table, the job will use only 300/3=100 mappers.
> In this way, we can control the number of mappers using the following formula.
> Number of Mappers = (Total region numbers) / hbase.mapreduce.scan.regionspermapper
> This is an example of the configuration.
> <property>
> <name>hbase.mapreduce.scan.regionspermapper</name>
> <value>3</value>
> </property>
> This is an example for Java code:
> TableMultiRegionMapReduceUtil.initTableMapperJob(tablename, scan, Map.class, Text.class, Text.class, job);
>
>
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