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https://issues.apache.org/jira/browse/HDFS-17639?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated HDFS-17639:
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    Labels: pull-request-available  (was: )

> Lock contention for hasStorageType when the number of storage nodes is large
> ----------------------------------------------------------------------------
>
>                 Key: HDFS-17639
>                 URL: https://issues.apache.org/jira/browse/HDFS-17639
>             Project: Hadoop HDFS
>          Issue Type: Improvement
>          Components: datanode, server
>    Affects Versions: 3.4.0
>            Reporter: goaymode
>            Priority: Minor
>              Labels: pull-request-available
>
> I was looking into methods associated with storages and storageTypes. I found 
> [DatanodeDescriptor.hasStorageType|https://github.com/apache/hadoop/blob/2f0dd7c4feb1e482d47786d26d6d32483f39414b/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/blockmanagement/DatanodeDescriptor.java#L1138]
>  could be a source of  bottlenecks. To check whether a specific storage type 
> exists among the storage locations associated with a DatanodeDescriptor, 
> [hasStorageType|https://github.com/apache/hadoop/blob/2f0dd7c4feb1e482d47786d26d6d32483f39414b/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/blockmanagement/DatanodeDescriptor.java#L1138]
>  iterates over an array of DatanodeStorageInfos returned by 
> [getStorageInfos()|https://github.com/apache/hadoop/blob/2f0dd7c4feb1e482d47786d26d6d32483f39414b/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/blockmanagement/DatanodeDescriptor.java#L305].
>  This retrieves the storage information from a storageMap and converts it to 
> an array while under a lock. As the system scales and the size of storageMap 
> grows with more datanodes, the duration spent in the synchronized block will 
> increase. This issue could become more significant when hasStorageType is 
> called  in methods like 
> [DatanodeDescriptor.pruneStorageMap|https://github.com/apache/hadoop/blob/49a495803a9451850b8982317e277b605c785587/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/blockmanagement/DatanodeDescriptor.java#L568]
>  that could iterate (resulting in a form of nested iteration) over a large 
> data structure. The combination of a repeated linear search (within 
> hasStorageType) and the iteration within a lock can lead to a significant 
> complexity (potentially quadratic) and significant synchronization bottlenecks
>  
> [DFSNetworkTopology.chooseRandomWithStorageType|https://github.com/apache/hadoop/blob/2f0dd7c4feb1e482d47786d26d6d32483f39414b/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/net/DFSNetworkTopology.java#L180]
>  and [DFSNetworkTopology. 
> chooseRandomWithStorageTypeTwoTrial|https://github.com/apache/hadoop/blob/2f0dd7c4feb1e482d47786d26d6d32483f39414b/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/net/DFSNetworkTopology.java#L107]
>  are affected because they both invoke hasStorageType. Additionally, 
> [INodeFile.assertAllBlocksComplete|https://github.com/apache/hadoop/blob/2f0dd7c4feb1e482d47786d26d6d32483f39414b/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/INodeFile.java#L345]
>  and 
> [BlockManager.checkRedundancy()|https://github.com/apache/hadoop/blob/6be04633b55bbd67c2875e39977cd9d2308dc1d1/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/blockmanagement/BlockManager.java#L5018]
>  faces a similar issue 
> ([FSNamesystem.finalizeINodeFileUnderConstruction|https://github.com/apache/hadoop/blob/2f0dd7c4feb1e482d47786d26d6d32483f39414b/hadoop-hdfs-project/hadoop-hdfs/src/main/java/org/apache/hadoop/hdfs/server/namenode/FSNamesystem.java#L3908]
>  invokes both methods under a writeLock)
> This appears to be a similar issue with 
> https://issues.apache.org/jira/browse/HDFS-17638 . I’m curious to know if my 
> analysis is wrong and if there is anything that can be done to reduce the 
> impact of these issues



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