You are viewing a plain text version of this content. The canonical link for it is here.
Posted to common-issues@hadoop.apache.org by GitBox <gi...@apache.org> on 2019/08/08 13:39:00 UTC

[GitHub] [hadoop] elek opened a new pull request #1255: HDDS-1935. Improve the visibility with Ozone Insight tool

elek opened a new pull request #1255: HDDS-1935. Improve the visibility with Ozone Insight tool
URL: https://github.com/apache/hadoop/pull/1255
 
 
   Visibility is a key aspect for the operation of any Ozone cluster. We need better visibility to improve correctnes and performance. While the distributed tracing is a good tool for improving the visibility of performance we have no powerful tool which can be used to check the internal state of the Ozone cluster and debug certain correctness issues.
   
   To improve the visibility of the internal components I propose to introduce a new command line application `ozone insight`.
   
   The new tool will show the selected metrics / logs / configuration for any of the internal components (like replication-manager, pipeline, etc.).
   
   For each insight points we can define the required logs and log levels, metrics and configuration and the tool can display only the component specific information during the debug.
   
   h2. Usage
   
   First we can check the available insight point:
   
   {code}
   bash-4.2$ ozone insight list
   Available insight points:
   
   
     scm.node-manager                     SCM Datanode management related information.
     scm.replica-manager                  SCM closed container replication manager
     scm.event-queue                      Information about the internal async event delivery
     scm.protocol.block-location          SCM Block location protocol endpoint
     scm.protocol.container-location      Planned insight point which is not yet implemented.
     scm.protocol.datanode                Planned insight point which is not yet implemented.
     scm.protocol.security                Planned insight point which is not yet implemented.
     scm.http                             Planned insight point which is not yet implemented.
     om.key-manager                       OM Key Manager
     om.protocol.client                   Ozone Manager RPC endpoint
     om.http                              Planned insight point which is not yet implemented.
     datanode.pipeline[id]                More information about one ratis datanode ring.
     datanode.rocksdb                     More information about one ratis datanode ring.
     s3g.http                             Planned insight point which is not yet implemented.
   {code}
   
   Insight points can define configuration, metrics and/or logs. Configuration can be displayed based on the configuration objects:
   
   {code}
   ozone insight config scm.protocol.block-location
   Configuration for `scm.protocol.block-location` (SCM Block location protocol endpoint)
   
   >>> ozone.scm.block.client.bind.host
          default: 0.0.0.0
          current: 0.0.0.0
   
   The hostname or IP address used by the SCM block client  endpoint to bind
   
   
   >>> ozone.scm.block.client.port
          default: 9863
          current: 9863
   
   The port number of the Ozone SCM block client service.
   
   
   >>> ozone.scm.block.client.address
          default: ${ozone.scm.client.address}
          current: scm
   
   The address of the Ozone SCM block client service. If not defined value of ozone.scm.client.address is used
   
   {code}
   
   Metrics can be retrieved from the prometheus entrypoint:
   
   {code}
   ozone insight metrics scm.protocol.block-location
   Metrics for `scm.protocol.block-location` (SCM Block location protocol endpoint)
   
   RPC connections
   
     Open connections: 0
     Dropped connections: 0
     Received bytes: 0
     Sent bytes: 0
   
   
   RPC queue
   
     RPC average queue time: 0.0
     RPC call queue length: 0
   
   
   RPC performance
   
     RPC processing time average: 0.0
     Number of slow calls: 0
   
   
   Message type counters
   
     Number of AllocateScmBlock: 0
     Number of DeleteScmKeyBlocks: 0
     Number of GetScmInfo: 2
     Number of SortDatanodes: 0
   {code}
   
   Log levels can be adjusted with the existing logLevel servlet and can be collected / streamd via a simple logstream servlet:
   
   {code}
   ozone insight log scm.node-manager
   [SCM] 2019-08-08 12:42:37,392 [DEBUG|org.apache.hadoop.hdds.scm.node.SCMNodeManager|SCMNodeManager] Processing node report from [datanode=ozone_datanode_1.ozone_default]
   [SCM] 2019-08-08 12:43:37,392 [DEBUG|org.apache.hadoop.hdds.scm.node.SCMNodeManager|SCMNodeManager] Processing node report from [datanode=ozone_datanode_1.ozone_default]
   [SCM] 2019-08-08 12:44:37,392 [DEBUG|org.apache.hadoop.hdds.scm.node.SCMNodeManager|SCMNodeManager] Processing node report from [datanode=ozone_datanode_1.ozone_default]
   [SCM] 2019-08-08 12:45:37,393 [DEBUG|org.apache.hadoop.hdds.scm.node.SCMNodeManager|SCMNodeManager] Processing node report from [datanode=ozone_datanode_1.ozone_default]
   [SCM] 2019-08-08 12:46:37,392 [DEBUG|org.apache.hadoop.hdds.scm.node.SCMNodeManager|SCMNodeManager] Processing node report from [datanode=ozone_datanode_1.ozone_default]
   {code}
   
   The verbose mode can display the raw messages as well:
   
   {code}
   [SCM] 2019-08-08 13:16:37,398 [DEBUG|org.apache.hadoop.hdds.scm.node.SCMNodeManager|SCMNodeManager] Processing node report from [datanode=ozone_datanode_1.ozone_default]
   [SCM] 2019-08-08 13:16:37,400 [TRACE|org.apache.hadoop.hdds.scm.node.SCMNodeManager|SCMNodeManager] HB is received from [datanode=ozone_datanode_1.ozone_default]: 
   storageReport {
     storageUuid: "DS-bffe6bee-1166-4502-acf5-57fc16c5aa98"
     storageLocation: "/data/hdds"
     capacity: 470282264576
     scmUsed: 16384
     remaining: 205695963136
     storageType: DISK
     failed: false
   }
   
   {code}
   
   h2. Use cases
   
   Ozone insight can be used for any kind of debuging. Some problem examples from my yesterday
   
    1. Due to a cache problem the volumes were created twice without any error at the second time. With this tool I can check the state of the internal cache, or check if the volume is added to the rocksdb itself.
   
    2. After fixing this problem we found an DNS caching issue. The OM responded with an error but it was not clear where the error was propagated from (it was created in OzoneManagerProtocolClientSideTranslatorPB.handleError). With checking the traffic between SCM and OM it can be easy to track the origin of a specific error.
    
    4. After fixing this problem we found some pipline problem (reported later at HDDS-1933). With this tool I could check the content of the reports and messages to the pipeline manager.
   
    
   
   
   h2. Implementation
   
   We can implement the tool without any significant code change as it uses existing features:
   
    * Metrics can be downloaded from the `/prom` endpoint
    * Log Level can be set with the existing `/logLevel` servlet endpoint (from hadoop-common)
    * Log lines can be streamed with a very simple new servlet
    * Configuration can be displayed based on configuration points
   
   A new interface can be introduced for `InsightPoint`s where all the affected logs/levels, metrics and config classes can be defined for each components.
   
   Prometheus servlet endpoint can be changed to be turned on by default.
   
   See: https://issues.apache.org/jira/browse/HDDS-1935

----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
 
For queries about this service, please contact Infrastructure at:
users@infra.apache.org


With regards,
Apache Git Services

---------------------------------------------------------------------
To unsubscribe, e-mail: common-issues-unsubscribe@hadoop.apache.org
For additional commands, e-mail: common-issues-help@hadoop.apache.org