[jira] [Updated] (HDFS-15382) Split DataNode FsDatasetImpl lock to blockpool volume lock
[ https://issues.apache.org/jira/browse/HDFS-15382?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Aiphago updated HDFS-15382: --- Attachment: image-2020-06-02-1.png > Split DataNode FsDatasetImpl lock to blockpool volume lock > --- > > Key: HDFS-15382 > URL: https://issues.apache.org/jira/browse/HDFS-15382 > Project: Hadoop HDFS > Issue Type: Improvement >Reporter: Aiphago >Assignee: Aiphago >Priority: Major > Fix For: 3.2.1 > > Attachments: image-2020-06-02-1.png > > > In HDFS-15180 we split lock to blockpool grain size.But when one volume is in > heavy load and will block other request which in same blockpool but different > volume.So we split lock to two leval to avoid this happend.And to improve > datanode performance. -- 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-15382) Split DataNode FsDatasetImpl lock to blockpool volume lock
[ https://issues.apache.org/jira/browse/HDFS-15382?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Aiphago updated HDFS-15382: --- Affects Version/s: (was: 3.2.1) (was: 2.9.2) > Split DataNode FsDatasetImpl lock to blockpool volume lock > --- > > Key: HDFS-15382 > URL: https://issues.apache.org/jira/browse/HDFS-15382 > Project: Hadoop HDFS > Issue Type: Improvement >Reporter: Aiphago >Assignee: Aiphago >Priority: Major > Fix For: 3.2.1 > > > In HDFS-15180 we split lock to blockpool grain size.But when one volume is in > heavy load and will block other request which in same blockpool but different > volume.So we split lock to two leval to avoid this happend.And to improve > datanode performance. -- 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-15382) Split DataNode FsDatasetImpl lock to blockpool volume lock
[ https://issues.apache.org/jira/browse/HDFS-15382?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Aiphago updated HDFS-15382: --- Target Version/s: (was: 3.2.0, 2.9.2) > Split DataNode FsDatasetImpl lock to blockpool volume lock > --- > > Key: HDFS-15382 > URL: https://issues.apache.org/jira/browse/HDFS-15382 > Project: Hadoop HDFS > Issue Type: Improvement >Affects Versions: 2.9.2, 3.2.1 >Reporter: Aiphago >Assignee: Aiphago >Priority: Major > Fix For: 3.2.1 > > > In HDFS-15180 we split lock to blockpool grain size.But when one volume is in > heavy load and will block other request which in same blockpool but different > volume.So we split lock to two leval to avoid this happend.And to improve > datanode performance. -- 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-15382) Split DataNode FsDatasetImpl lock to blockpool volume lock
[ https://issues.apache.org/jira/browse/HDFS-15382?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Aiphago updated HDFS-15382: --- Attachment: (was: image-2020-06-02.png) > Split DataNode FsDatasetImpl lock to blockpool volume lock > --- > > Key: HDFS-15382 > URL: https://issues.apache.org/jira/browse/HDFS-15382 > Project: Hadoop HDFS > Issue Type: Improvement >Affects Versions: 2.9.2, 3.2.1 >Reporter: Aiphago >Assignee: Aiphago >Priority: Major > Fix For: 3.2.1 > > > In HDFS-15180 we split lock to blockpool grain size.But when one volume is in > heavy load and will block other request which in same blockpool but different > volume.So we split lock to two leval to avoid this happend.And to improve > datanode performance. -- 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-15382) Split DataNode FsDatasetImpl lock to blockpool volume lock
[ https://issues.apache.org/jira/browse/HDFS-15382?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Aiphago updated HDFS-15382: --- Attachment: image-2020-06-02.png > Split DataNode FsDatasetImpl lock to blockpool volume lock > --- > > Key: HDFS-15382 > URL: https://issues.apache.org/jira/browse/HDFS-15382 > Project: Hadoop HDFS > Issue Type: Improvement >Affects Versions: 2.9.2, 3.2.1 >Reporter: Aiphago >Assignee: Aiphago >Priority: Major > Fix For: 3.2.1 > > Attachments: image-2020-06-02.png > > > In HDFS-15180 we split lock to blockpool grain size.But when one volume is in > heavy load and will block other request which in same blockpool but different > volume.So we split lock to two leval to avoid this happend.And to improve > datanode performance. -- 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-15382) Split DataNode FsDatasetImpl lock to blockpool volume lock
[ https://issues.apache.org/jira/browse/HDFS-15382?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Aiphago updated HDFS-15382: --- Affects Version/s: 2.9.2 3.2.1 > Split DataNode FsDatasetImpl lock to blockpool volume lock > --- > > Key: HDFS-15382 > URL: https://issues.apache.org/jira/browse/HDFS-15382 > Project: Hadoop HDFS > Issue Type: Improvement >Affects Versions: 2.9.2, 3.2.1 >Reporter: Aiphago >Assignee: Aiphago >Priority: Major > Fix For: 3.2.1 > > > In HDFS-15180 we split lock to blockpool grain size.But when one volume is in > heavy load and will block other request which in same blockpool but different > volume.So we split lock to two leval to avoid this happend.And to improve > datanode performance. -- 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-15382) Split DataNode FsDatasetImpl lock to blockpool volume lock
[ https://issues.apache.org/jira/browse/HDFS-15382?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Aiphago updated HDFS-15382: --- Fix Version/s: 2.9.2 3.2.1 > Split DataNode FsDatasetImpl lock to blockpool volume lock > --- > > Key: HDFS-15382 > URL: https://issues.apache.org/jira/browse/HDFS-15382 > Project: Hadoop HDFS > Issue Type: Improvement >Reporter: Aiphago >Assignee: Aiphago >Priority: Major > Fix For: 2.9.2, 3.2.1 > > > In HDFS-15180 we split lock to blockpool grain size.But when one volume is in > heavy load and will block other request which in same blockpool but different > volume.So we split lock to two leval to avoid this happend.And to improve > datanode performance. -- 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-15382) Split DataNode FsDatasetImpl lock to blockpool volume lock
[ https://issues.apache.org/jira/browse/HDFS-15382?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Aiphago updated HDFS-15382: --- Fix Version/s: (was: 2.9.2) > Split DataNode FsDatasetImpl lock to blockpool volume lock > --- > > Key: HDFS-15382 > URL: https://issues.apache.org/jira/browse/HDFS-15382 > Project: Hadoop HDFS > Issue Type: Improvement >Reporter: Aiphago >Assignee: Aiphago >Priority: Major > Fix For: 3.2.1 > > > In HDFS-15180 we split lock to blockpool grain size.But when one volume is in > heavy load and will block other request which in same blockpool but different > volume.So we split lock to two leval to avoid this happend.And to improve > datanode performance. -- 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
