
|
Available Workflow Actions
|
|
If you were logged in you would be able to see more operations.
|
|
|
|
File Attachments:
|
|
|
Issue Links:
|
Reference
|
|
This issue relates to:
|
|
|
HDFS-738 Improve the disk utilization of HDFS
|
|
|
|
|
|
HDFS-284 dfs.data.dir syntax needs revamping: multiple percentages and weights
|
|
|
|
|
|
This issue is related to:
|
|
HADOOP-2437
final map output not evenly distributed across multiple disks
|
|
|
|
|
dependent
|
|
|
|
|
|
When multiple file system partitions are configured for the data storage of a data node,
it uses a strict round robin policy to decide which partition to use for writing the next block.
This may result in anormaly cases in which the blocks of a file are not evenly distributed across
the partitions. For example, when we use distcp to copy files with each node have 4 mappers running concurrently,
those 4 mappers are writing to DFS at about the same rate. Thus, it is possible that the 4 mappers write out
blocks interleavingly. If there are 4 file system partitions configured for the local data node, it is possible that each mapper will
continue to write its blocks on to the same file system partition.
A simple random placement policy will avoid such anormaly cases, and does not have any obvious drawbacks.
|
|
Description
|
When multiple file system partitions are configured for the data storage of a data node,
it uses a strict round robin policy to decide which partition to use for writing the next block.
This may result in anormaly cases in which the blocks of a file are not evenly distributed across
the partitions. For example, when we use distcp to copy files with each node have 4 mappers running concurrently,
those 4 mappers are writing to DFS at about the same rate. Thus, it is possible that the 4 mappers write out
blocks interleavingly. If there are 4 file system partitions configured for the local data node, it is possible that each mapper will
continue to write its blocks on to the same file system partition.
A simple random placement policy will avoid such anormaly cases, and does not have any obvious drawbacks.
|
Show » |
| No work has yet been logged on this issue.
|
|