[jira] [Updated] (HBASE-4114) Metrics for HFile HDFS block locality

["Ming Ma (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/HBASE-4114?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Ming Ma updated HBASE-4114:
---------------------------

    Description: 
Normally, when we put hbase and HDFS in the same cluster ( e.g., region server runs on the datenode ), we have a reasonably good data locality, as explained by Lars. Also Work has been done by Jonathan to address the startup situation.

There are scenarios where regions can be on a different machine from the machines that hold the underlying HFile blocks, at least for some period of time. This will have performance impact on whole table scan operation and map reduce job during that time.

1.	After load balancer moves the region and before compaction (thus generate HFile on the new region server ) on that region, HDFS block can be remote.
2.	When a new machine is added, or removed, Hbase's region assignment policy is different from HDFS's block reassignment policy.
3.	Even if there is no much hbase activity, HDFS can load balance HFile blocks as other non-hbase applications push other data to HDFS.

Lots has been or will be done in load balancer, as summarized by Ted. I am curious if HFile HDFS block locality should be used as another factor here.

I have done some experiments on how HDFS block locality can impact map reduce latency. First we need to define a metrics to measure HFile data locality.

Metrics defintion:

For a given table, or a region server, or a region, we can define the following. The higher the value, the more local HFile is from region server's point of view.

HFile locality index = ( Total number of HDFS blocks that can be retrieved locally by the region server ) / ( Total number of HDFS blocks for all HFiles )

Test Results:
This is to show how HFile locality can impact the latency. It is based on a table with 1M rows, 36KB per row; regions are distributed in balance. The map job is RowCounter.

HFile Locality Index	Map job latency ( in sec )
28%	                157
36%	                150
47%	                142
61%	                133
73%	                122
89%	                103
99%	                95

So the first suggestion is to expose HFile locality index as a new region server metrics. It will be ideal if we can somehow measure HFile locality index on a per map job level.

Regarding if/when we should include that as another factor for load balancer, that will be a different work item. It is unclear how load balancer can take various factors into account to come up with the best load balancer strategy.
    Environment:     (was: Normally, when we put hbase and HDFS in the same cluster ( e.g., region server runs on the datenode ), we have a reasonably good data locality, as explained by Lars. Also Work has been done by Jonathan to address the startup situation.

There are scenarios where regions can be on a different machine from the machines that hold the underlying HFile blocks, at least for some period of time. This will have performance impact on whole table scan operation and map reduce job during that time.

1.	After load balancer moves the region and before compaction (thus generate HFile on the new region server ) on that region, HDFS block can be remote.
2.	When a new machine is added, or removed, Hbase's region assignment policy is different from HDFS's block reassignment policy.
3.	Even if there is no much hbase activity, HDFS can load balance HFile blocks as other non-hbase applications push other data to HDFS.

Lots has been or will be done in load balancer, as summarized by Ted. I am curious if HFile HDFS block locality should be used as another factor here.

I have done some experiments on how HDFS block locality can impact map reduce latency. First we need to define a metrics to measure HFile data locality.

Metrics defintion:

For a given table, or a region server, or a region, we can define the following. The higher the value, the more local HFile is from region server's point of view.

HFile locality index = ( Total number of HDFS blocks that can be retrieved locally by the region server ) / ( Total number of HDFS blocks for all HFiles )

Test Results:
This is to show how HFile locality can impact the latency. It is based on a table with 1M rows, 36KB per row; regions are distributed in balance. The map job is RowCounter.

HFile Locality Index	Map job latency ( in sec )
28%	                157
36%	                150
47%	                142
61%	                133
73%	                122
89%	                103
99%	                95

So the first suggestion is to expose HFile locality index as a new region server metrics. It will be ideal if we can somehow measure HFile locality index on a per map job level.

Regarding if/when we should include that as another factor for load balancer, that will be a different work item. It is unclear how load balancer can take various factors into account to come up with the best load balancer strategy.)

> Metrics for HFile HDFS block locality
> -------------------------------------
>
>                 Key: HBASE-4114
>                 URL: https://issues.apache.org/jira/browse/HBASE-4114
>             Project: HBase
>          Issue Type: Improvement
>          Components: metrics, regionserver
>            Reporter: Ming Ma
>            Assignee: Ming Ma
>
> Normally, when we put hbase and HDFS in the same cluster ( e.g., region server runs on the datenode ), we have a reasonably good data locality, as explained by Lars. Also Work has been done by Jonathan to address the startup situation.
> There are scenarios where regions can be on a different machine from the machines that hold the underlying HFile blocks, at least for some period of time. This will have performance impact on whole table scan operation and map reduce job during that time.
> 1.	After load balancer moves the region and before compaction (thus generate HFile on the new region server ) on that region, HDFS block can be remote.
> 2.	When a new machine is added, or removed, Hbase's region assignment policy is different from HDFS's block reassignment policy.
> 3.	Even if there is no much hbase activity, HDFS can load balance HFile blocks as other non-hbase applications push other data to HDFS.
> Lots has been or will be done in load balancer, as summarized by Ted. I am curious if HFile HDFS block locality should be used as another factor here.
> I have done some experiments on how HDFS block locality can impact map reduce latency. First we need to define a metrics to measure HFile data locality.
> Metrics defintion:
> For a given table, or a region server, or a region, we can define the following. The higher the value, the more local HFile is from region server's point of view.
> HFile locality index = ( Total number of HDFS blocks that can be retrieved locally by the region server ) / ( Total number of HDFS blocks for all HFiles )
> Test Results:
> This is to show how HFile locality can impact the latency. It is based on a table with 1M rows, 36KB per row; regions are distributed in balance. The map job is RowCounter.
> HFile Locality Index	Map job latency ( in sec )
> 28%	                157
> 36%	                150
> 47%	                142
> 61%	                133
> 73%	                122
> 89%	                103
> 99%	                95
> So the first suggestion is to expose HFile locality index as a new region server metrics. It will be ideal if we can somehow measure HFile locality index on a per map job level.
> Regarding if/when we should include that as another factor for load balancer, that will be a different work item. It is unclear how load balancer can take various factors into account to come up with the best load balancer strategy.

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