[jira] [Updated] (HDFS-7784) load fsimage in parallel
[ https://issues.apache.org/jira/browse/HDFS-7784?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Wei-Chiu Chuang updated HDFS-7784: -- Target Version/s: (was: ) Resolution: Duplicate Status: Resolved (was: Patch Available) I'm going to resolve this one since HDFS-14617 took large part of the code from here and merged in the codebase. > load fsimage in parallel > > > Key: HDFS-7784 > URL: https://issues.apache.org/jira/browse/HDFS-7784 > Project: Hadoop HDFS > Issue Type: Improvement > Components: namenode >Reporter: Walter Su >Assignee: Walter Su >Priority: Minor > Labels: BB2015-05-TBR > Attachments: HDFS-7784.001.patch, test-20150213.pdf > > > When single Namenode has huge amount of files, without using federation, the > startup/restart speed is slow. The fsimage loading step takes the most of the > time. fsimage loading can seperate to two parts, deserialization and object > construction(mostly map insertion). Deserialization takes the most of CPU > time. So we can do deserialization in parallel, and add to hashmap in serial. > It will significantly reduce the NN start time. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: hdfs-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: hdfs-issues-h...@hadoop.apache.org
[jira] [Updated] (HDFS-7784) load fsimage in parallel
[ https://issues.apache.org/jira/browse/HDFS-7784?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Allen Wittenauer updated HDFS-7784: --- Labels: BB2015-05-TBR (was: ) > load fsimage in parallel > > > Key: HDFS-7784 > URL: https://issues.apache.org/jira/browse/HDFS-7784 > Project: Hadoop HDFS > Issue Type: Improvement > Components: namenode >Reporter: Walter Su >Assignee: Walter Su >Priority: Minor > Labels: BB2015-05-TBR > Attachments: HDFS-7784.001.patch, test-20150213.pdf > > > When single Namenode has huge amount of files, without using federation, the > startup/restart speed is slow. The fsimage loading step takes the most of the > time. fsimage loading can seperate to two parts, deserialization and object > construction(mostly map insertion). Deserialization takes the most of CPU > time. So we can do deserialization in parallel, and add to hashmap in serial. > It will significantly reduce the NN start time. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (HDFS-7784) load fsimage in parallel
[ https://issues.apache.org/jira/browse/HDFS-7784?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Walter Su updated HDFS-7784: Priority: Minor (was: Major) > load fsimage in parallel > > > Key: HDFS-7784 > URL: https://issues.apache.org/jira/browse/HDFS-7784 > Project: Hadoop HDFS > Issue Type: Improvement > Components: namenode >Reporter: Walter Su >Assignee: Walter Su >Priority: Minor > Attachments: HDFS-7784.001.patch, test-20150213.pdf > > > When single Namenode has huge amount of files, without using federation, the > startup/restart speed is slow. The fsimage loading step takes the most of the > time. fsimage loading can seperate to two parts, deserialization and object > construction(mostly map insertion). Deserialization takes the most of CPU > time. So we can do deserialization in parallel, and add to hashmap in serial. > It will significantly reduce the NN start time. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (HDFS-7784) load fsimage in parallel
[ https://issues.apache.org/jira/browse/HDFS-7784?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Walter Su updated HDFS-7784: Attachment: test-20150213.pdf > load fsimage in parallel > > > Key: HDFS-7784 > URL: https://issues.apache.org/jira/browse/HDFS-7784 > Project: Hadoop HDFS > Issue Type: Improvement > Components: namenode >Reporter: Walter Su >Assignee: Walter Su > Attachments: HDFS-7784.001.patch, test-20150213.pdf > > > When single Namenode has huge amount of files, without using federation, the > startup/restart speed is slow. The fsimage loading step takes the most of the > time. fsimage loading can seperate to two parts, deserialization and object > construction(mostly map insertion). Deserialization takes the most of CPU > time. So we can do deserialization in parallel, and add to hashmap in serial. > It will significantly reduce the NN start time. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (HDFS-7784) load fsimage in parallel
[ https://issues.apache.org/jira/browse/HDFS-7784?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Walter Su updated HDFS-7784: Attachment: HDFS-7784.001.patch compatible with the old fsimage file. > load fsimage in parallel > > > Key: HDFS-7784 > URL: https://issues.apache.org/jira/browse/HDFS-7784 > Project: Hadoop HDFS > Issue Type: Improvement > Components: namenode >Reporter: Walter Su >Assignee: Walter Su > Attachments: HDFS-7784.001.patch > > > When single Namenode has huge amount of files, without using federation, the > startup/restart speed is slow. The fsimage loading step takes the most of the > time. fsimage loading can seperate to two parts, deserialization and object > construction(mostly map insertion). Deserialization takes the most of CPU > time. So we can do deserialization in parallel, and add to hashmap in serial. > It will significantly reduce the NN start time. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (HDFS-7784) load fsimage in parallel
[ https://issues.apache.org/jira/browse/HDFS-7784?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Walter Su updated HDFS-7784: Target Version/s: 3.0.0 Status: Patch Available (was: Open) > load fsimage in parallel > > > Key: HDFS-7784 > URL: https://issues.apache.org/jira/browse/HDFS-7784 > Project: Hadoop HDFS > Issue Type: Improvement > Components: namenode >Reporter: Walter Su >Assignee: Walter Su > > When single Namenode has huge amount of files, without using federation, the > startup/restart speed is slow. The fsimage loading step takes the most of the > time. fsimage loading can seperate to two parts, deserialization and object > construction(mostly map insertion). Deserialization takes the most of CPU > time. So we can do deserialization in parallel, and add to hashmap in serial. > It will significantly reduce the NN start time. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (HDFS-7784) load fsimage in parallel
[ https://issues.apache.org/jira/browse/HDFS-7784?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Walter Su updated HDFS-7784: Description: When single Namenode has huge amount of files, without using federation, the startup/restart speed is slow. The fsimage loading step takes the most of the time. fsimage loading can seperate to two parts, deserialization and object construction(mostly map insertion). Deserialization takes the most of CPU time. So we can do deserialization in parallel, and add to hashmap in serial. It will significantly reduce the NN start time. (was: When single Namenode has huge amount of files, without using federation, the startup/restart speed is slow. The fsimage loading step takes the most of the time. fsimage loading can seperate to two parts, deserialization and object construction(mostly map insertion). Deserialization takes the most of CPU time. So we can do deserialization in parallel, and add to hashmap in parallel. It will significantly reduce the NN start time.) > load fsimage in parallel > > > Key: HDFS-7784 > URL: https://issues.apache.org/jira/browse/HDFS-7784 > Project: Hadoop HDFS > Issue Type: Improvement > Components: namenode >Reporter: Walter Su > > When single Namenode has huge amount of files, without using federation, the > startup/restart speed is slow. The fsimage loading step takes the most of the > time. fsimage loading can seperate to two parts, deserialization and object > construction(mostly map insertion). Deserialization takes the most of CPU > time. So we can do deserialization in parallel, and add to hashmap in serial. > It will significantly reduce the NN start time. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
