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https://issues.apache.org/jira/browse/HADOOP-15933?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Pranay Singh updated HADOOP-15933:
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Description:
The usage of HDFS has changed from being used as a map-reduce filesystem, now
it's becoming more of like a general purpose filesystem. In most of the cases
there are issues with the Namenode so we have metrics to know the workload or
stress on Namenode.
However, there is a need to have more statistics collected for different
operations/RPCs in DFSClient to know which RPC operations are taking longer
time or to know what is the frequency of the operation.These statistics can be
exposed to the users of DFS Client and they can periodically log or do some
sort of flow control if the response is slow. This will also help to isolate
HDFS issue in a mixed environment where on a node say we have Spark, HBase and
Impala running together. We can check the throughput of different operation
across client and isolate the problem caused because of noisy neighbor or
network congestion or shared JVM.
We have dealt with several problems from the field for which there is no
conclusive evidence as to what caused the problem. If we had metrics or stats
in DFSClient we would be better equipped to solve such complex problems.
List of jiras for reference:
-------------------------
HADOOP-15538 HADOOP-15530 ( client side deadlock)
was:
The usage of HDFS has changed from being used as a map-reduce filesystem, now
it's becoming more of like a general purpose filesystem. In most of the cases
there are issues with the Namenode so we have metrics to know the workload or
stress on Namenode.
However, there is a need to have more statistics collected for different
operations/RPCs in DFSClient to know which RPC operations are taking longer
time or to know what is the frequency of the operation.These statistics can be
exposed to the users of DFS Client and they can periodically log or do some
sort of flow control if the response is slow. This will also help to isolate
HDFS issue in a mixed environment where on a node we have HBase and Impala
running together. We can check the throughput of different operation across
client and isolate the problem caused because of noisy neighbor or network
congestion or shared JVM.
We have dealt with several problems from the field for which there is no
conclusive evidence as to what caused the problem. If we had metrics or stats
in DFSClient we would be better equipped to solve such complex problems.
List of jiras for reference:
-------------------------
HADOOP-15538 HADOOP-15530 ( client side deadlock)
> Need for more stats in DFSClient
> --------------------------------
>
> Key: HADOOP-15933
> URL: https://issues.apache.org/jira/browse/HADOOP-15933
> Project: Hadoop Common
> Issue Type: Improvement
> Reporter: Pranay Singh
> Assignee: Pranay Singh
> Priority: Major
>
> The usage of HDFS has changed from being used as a map-reduce filesystem, now
> it's becoming more of like a general purpose filesystem. In most of the cases
> there are issues with the Namenode so we have metrics to know the workload or
> stress on Namenode.
> However, there is a need to have more statistics collected for different
> operations/RPCs in DFSClient to know which RPC operations are taking longer
> time or to know what is the frequency of the operation.These statistics can
> be exposed to the users of DFS Client and they can periodically log or do
> some sort of flow control if the response is slow. This will also help to
> isolate HDFS issue in a mixed environment where on a node say we have Spark,
> HBase and Impala running together. We can check the throughput of different
> operation across client and isolate the problem caused because of noisy
> neighbor or network congestion or shared JVM.
> We have dealt with several problems from the field for which there is no
> conclusive evidence as to what caused the problem. If we had metrics or stats
> in DFSClient we would be better equipped to solve such complex problems.
> List of jiras for reference:
> -------------------------
> HADOOP-15538 HADOOP-15530 ( client side deadlock)
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