[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Guanghao Zhang updated HBASE-20188: --- Fix Version/s: (was: 2.2.0) 2.3.0 > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Priority: Blocker > Fix For: 3.0.0, 2.3.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188-xac.sh, > HBASE-20188.sh, HBase 2.0 performance evaluation - 8GB(1).pdf, HBase 2.0 > performance evaluation - 8GB.pdf, HBase 2.0 performance evaluation - Basic vs > None_ system settings.pdf, HBase 2.0 performance evaluation - throughput > SSD_HDD.pdf, ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, hbase-env.sh, hbase-site.xml, > hbase-site.xml, hits.png, hits_with_fp_scheduler.png, > lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, perregion.png, run_ycsb.sh, > total.png, tree.txt, workloadx, workloadx > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Duo Zhang updated HBASE-20188: -- Fix Version/s: (was: 2.1.0) 2.2.0 > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Priority: Blocker > Fix For: 3.0.0, 2.2.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188-xac.sh, > HBASE-20188.sh, HBase 2.0 performance evaluation - 8GB(1).pdf, HBase 2.0 > performance evaluation - 8GB.pdf, HBase 2.0 performance evaluation - Basic vs > None_ system settings.pdf, HBase 2.0 performance evaluation - throughput > SSD_HDD.pdf, ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, hbase-env.sh, hbase-site.xml, > hbase-site.xml, hits.png, hits_with_fp_scheduler.png, > lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, perregion.png, run_ycsb.sh, > total.png, tree.txt, workloadx, workloadx > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Eshcar Hillel updated HBASE-20188: -- Attachment: HBase 2.0 performance evaluation - throughput SSD_HDD.pdf > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 3.0.0, 2.1.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188-xac.sh, > HBASE-20188.sh, HBase 2.0 performance evaluation - 8GB(1).pdf, HBase 2.0 > performance evaluation - 8GB.pdf, HBase 2.0 performance evaluation - Basic vs > None_ system settings.pdf, HBase 2.0 performance evaluation - throughput > SSD_HDD.pdf, ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, hbase-env.sh, hbase-site.xml, > hbase-site.xml, hits.png, hits_with_fp_scheduler.png, > lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, perregion.png, run_ycsb.sh, > total.png, tree.txt, workloadx, workloadx > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Fix Version/s: 2.1.0 > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 3.0.0, 2.1.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188-xac.sh, > HBASE-20188.sh, HBase 2.0 performance evaluation - 8GB(1).pdf, HBase 2.0 > performance evaluation - 8GB.pdf, HBase 2.0 performance evaluation - Basic vs > None_ system settings.pdf, ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, hbase-env.sh, hbase-site.xml, > hbase-site.xml, hits.png, hits_with_fp_scheduler.png, > lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, perregion.png, run_ycsb.sh, > total.png, tree.txt, workloadx, workloadx > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Fix Version/s: (was: 2.0.0) 3.0.0 > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 3.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188-xac.sh, > HBASE-20188.sh, HBase 2.0 performance evaluation - 8GB(1).pdf, HBase 2.0 > performance evaluation - 8GB.pdf, HBase 2.0 performance evaluation - Basic vs > None_ system settings.pdf, ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, hbase-env.sh, hbase-site.xml, > hbase-site.xml, hits.png, hits_with_fp_scheduler.png, > lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, perregion.png, run_ycsb.sh, > total.png, tree.txt, workloadx, workloadx > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: (was: HBASE-20188.branch-2.0.001.patch) > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188-xac.sh, > HBASE-20188.sh, HBase 2.0 performance evaluation - 8GB(1).pdf, HBase 2.0 > performance evaluation - 8GB.pdf, HBase 2.0 performance evaluation - Basic vs > None_ system settings.pdf, ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, hbase-env.sh, hbase-site.xml, > hbase-site.xml, hits.png, hits_with_fp_scheduler.png, > lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, perregion.png, run_ycsb.sh, > total.png, tree.txt, workloadx, workloadx > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: HBASE-20188.branch-2.0.001.patch > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188-xac.sh, > HBASE-20188.branch-2.0.001.patch, HBASE-20188.sh, HBase 2.0 performance > evaluation - 8GB(1).pdf, HBase 2.0 performance evaluation - 8GB.pdf, HBase > 2.0 performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, hbase-env.sh, hbase-site.xml, > hbase-site.xml, hits.png, hits_with_fp_scheduler.png, > lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, perregion.png, run_ycsb.sh, > total.png, tree.txt, workloadx, workloadx > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: hits_with_fp_scheduler.png > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188-xac.sh, > HBASE-20188.sh, HBase 2.0 performance evaluation - 8GB(1).pdf, HBase 2.0 > performance evaluation - 8GB.pdf, HBase 2.0 performance evaluation - Basic vs > None_ system settings.pdf, ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, hbase-env.sh, hbase-site.xml, > hbase-site.xml, hits.png, hits_with_fp_scheduler.png, > lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, perregion.png, run_ycsb.sh, > total.png, tree.txt, workloadx, workloadx > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: total.png perregion.png hits.png > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188-xac.sh, > HBASE-20188.sh, HBase 2.0 performance evaluation - 8GB(1).pdf, HBase 2.0 > performance evaluation - 8GB.pdf, HBase 2.0 performance evaluation - Basic vs > None_ system settings.pdf, ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, hbase-env.sh, hbase-site.xml, > hbase-site.xml, hits.png, lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, perregion.png, run_ycsb.sh, > total.png, tree.txt, workloadx, workloadx > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Eshcar Hillel updated HBASE-20188: -- Attachment: workloadx > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188-xac.sh, > HBASE-20188.sh, HBase 2.0 performance evaluation - 8GB(1).pdf, HBase 2.0 > performance evaluation - 8GB.pdf, HBase 2.0 performance evaluation - Basic vs > None_ system settings.pdf, ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, hbase-env.sh, hbase-site.xml, > hbase-site.xml, lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, run_ycsb.sh, tree.txt, workloadx, > workloadx > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Eshcar Hillel updated HBASE-20188: -- Attachment: HBase 2.0 performance evaluation - 8GB(1).pdf > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188-xac.sh, > HBASE-20188.sh, HBase 2.0 performance evaluation - 8GB(1).pdf, HBase 2.0 > performance evaluation - 8GB.pdf, HBase 2.0 performance evaluation - Basic vs > None_ system settings.pdf, ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, hbase-env.sh, hbase-site.xml, > hbase-site.xml, lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, run_ycsb.sh, tree.txt, workloadx > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Eshcar Hillel updated HBASE-20188: -- Attachment: hbase-site.xml workloadx HBASE-20188-xac.sh > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188-xac.sh, > HBASE-20188.sh, HBase 2.0 performance evaluation - 8GB.pdf, HBase 2.0 > performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, hbase-env.sh, hbase-site.xml, > hbase-site.xml, lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, run_ycsb.sh, tree.txt, workloadx > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Eshcar Hillel updated HBASE-20188: -- Attachment: HBase 2.0 performance evaluation - 8GB.pdf > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188.sh, HBase 2.0 > performance evaluation - 8GB.pdf, HBase 2.0 performance evaluation - Basic vs > None_ system settings.pdf, ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, hbase-env.sh, hbase-site.xml, > lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, run_ycsb.sh, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: hbase-env.sh > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188.sh, HBase 2.0 > performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, hbase-env.sh, hbase-site.xml, > lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, run_ycsb.sh, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: run_ycsb.sh hbase-site.xml > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188.sh, HBase 2.0 > performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, hbase-site.xml, > lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, run_ycsb.sh, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: (was: misses.127.workloadc.20180402T200918Z.svg) > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188.sh, HBase 2.0 > performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, > lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: lock.127.workloadc.20180402T200918Z.svg > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188.sh, HBase 2.0 > performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, > lock.127.workloadc.20180402T200918Z.svg, > lock.2.memsize2.c.20180403T160257Z.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: (was: cpu.127.workloadc.20180402T200918Z.svg) > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188.sh, HBase 2.0 > performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, > lock.2.memsize2.c.20180403T160257Z.svg, > misses.127.workloadc.20180402T200918Z.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: (was: cpu.127.workloadc.20180402T200918Z.svg) > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188.sh, HBase 2.0 > performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, > lock.2.memsize2.c.20180403T160257Z.svg, > misses.127.workloadc.20180402T200918Z.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: (was: cpu.2.memsize2.c.20180403T160257Z.svg) > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188.sh, HBase 2.0 > performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > cpu.127.workloadc.20180402T200918Z.svg, > cpu.127.workloadc.20180402T200918Z.svg, flamegraph-1072.1.svg, > flamegraph-1072.2.svg, lock.2.memsize2.c.20180403T160257Z.svg, > misses.127.workloadc.20180402T200918Z.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: cpu.127.workloadc.20180402T200918Z.svg > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188.sh, HBase 2.0 > performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > cpu.127.workloadc.20180402T200918Z.svg, > cpu.127.workloadc.20180402T200918Z.svg, flamegraph-1072.1.svg, > flamegraph-1072.2.svg, lock.2.memsize2.c.20180403T160257Z.svg, > misses.127.workloadc.20180402T200918Z.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: (was: cpu.127.workloadc.20180402T200918Z.svg) > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188.sh, HBase 2.0 > performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > cpu.127.workloadc.20180402T200918Z.svg, > cpu.127.workloadc.20180402T200918Z.svg, flamegraph-1072.1.svg, > flamegraph-1072.2.svg, lock.2.memsize2.c.20180403T160257Z.svg, > misses.127.workloadc.20180402T200918Z.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: cpu.127.workloadc.20180402T200918Z.svg > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188.sh, HBase 2.0 > performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > cpu.127.workloadc.20180402T200918Z.svg, > cpu.127.workloadc.20180402T200918Z.svg, > cpu.2.memsize2.c.20180403T160257Z.svg, flamegraph-1072.1.svg, > flamegraph-1072.2.svg, lock.2.memsize2.c.20180403T160257Z.svg, > misses.127.workloadc.20180402T200918Z.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: cpu.127.workloadc.20180402T200918Z.svg > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188.sh, HBase 2.0 > performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > cpu.127.workloadc.20180402T200918Z.svg, > cpu.2.memsize2.c.20180403T160257Z.svg, flamegraph-1072.1.svg, > flamegraph-1072.2.svg, lock.2.memsize2.c.20180403T160257Z.svg, > misses.127.workloadc.20180402T200918Z.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: lock.2.memsize2.c.20180403T160257Z.svg > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188.sh, HBase 2.0 > performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > cpu.2.memsize2.c.20180403T160257Z.svg, flamegraph-1072.1.svg, > flamegraph-1072.2.svg, lock.2.memsize2.c.20180403T160257Z.svg, > misses.127.workloadc.20180402T200918Z.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: cpu.2.memsize2.c.20180403T160257Z.svg > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188.sh, HBase 2.0 > performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > cpu.2.memsize2.c.20180403T160257Z.svg, flamegraph-1072.1.svg, > flamegraph-1072.2.svg, lock.2.memsize2.c.20180403T160257Z.svg, > misses.127.workloadc.20180402T200918Z.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: misses.127.workloadc.20180402T200918Z.svg > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188.sh, HBase 2.0 > performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, > misses.127.workloadc.20180402T200918Z.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Eshcar Hillel updated HBASE-20188: -- Attachment: HBASE-20188.sh > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBASE-20188.sh, HBase 2.0 > performance evaluation - Basic vs None_ system settings.pdf, > ITBLL2.5B_1.2.7vs2.0.0_cpu.png, ITBLL2.5B_1.2.7vs2.0.0_gctime.png, > ITBLL2.5B_1.2.7vs2.0.0_iops.png, ITBLL2.5B_1.2.7vs2.0.0_load.png, > ITBLL2.5B_1.2.7vs2.0.0_memheap.png, ITBLL2.5B_1.2.7vs2.0.0_memstore.png, > ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Eshcar Hillel updated HBASE-20188: -- Attachment: HBase 2.0 performance evaluation - Basic vs None_ system settings.pdf > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, HBase 2.0 performance evaluation - > Basic vs None_ system settings.pdf, ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Anastasia Braginsky updated HBASE-20188: Attachment: CAM-CONFIG-V01.patch > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Assignee: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: CAM-CONFIG-V01.patch, ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Mike Drob updated HBASE-20188: -- Priority: Blocker (was: Critical) > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Priority: Blocker > Fix For: 2.0.0 > > Attachments: ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: YCSB_IN_MEMORY_COMPACTION=NONE.ops.png > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Priority: Critical > Fix For: 2.0.0 > > Attachments: ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_IN_MEMORY_COMPACTION=NONE.ops.png, YCSB_MEMSTORE.png, > YCSB_OPs.png, YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: YCSB_in-memory-compaction=NONE.ops.png > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Priority: Critical > Fix For: 2.0.0 > > Attachments: ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_MEMSTORE.png, YCSB_OPs.png, > YCSB_in-memory-compaction=NONE.ops.png, YCSB_load.png, flamegraph-1072.1.svg, > flamegraph-1072.2.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: YCSB_OPs.png YCSB_MEMSTORE.png YCSB_GC_TIME.png YCSB_CPU.png YCSB_load.png > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Priority: Critical > Fix For: 2.0.0 > > Attachments: ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, YCSB_CPU.png, > YCSB_GC_TIME.png, YCSB_MEMSTORE.png, YCSB_OPs.png, YCSB_load.png, > flamegraph-1072.1.svg, flamegraph-1072.2.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png ITBLL2.5B_1.2.7vs2.0.0_memstore.png ITBLL2.5B_1.2.7vs2.0.0_ops.png ITBLL2.5B_1.2.7vs2.0.0_iops.png ITBLL2.5B_1.2.7vs2.0.0_memheap.png ITBLL2.5B_1.2.7vs2.0.0_gctime.png ITBLL2.5B_1.2.7vs2.0.0_cpu.png ITBLL2.5B_1.2.7vs2.0.0_load.png > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Priority: Critical > Fix For: 2.0.0 > > Attachments: ITBLL2.5B_1.2.7vs2.0.0_cpu.png, > ITBLL2.5B_1.2.7vs2.0.0_gctime.png, ITBLL2.5B_1.2.7vs2.0.0_iops.png, > ITBLL2.5B_1.2.7vs2.0.0_load.png, ITBLL2.5B_1.2.7vs2.0.0_memheap.png, > ITBLL2.5B_1.2.7vs2.0.0_memstore.png, ITBLL2.5B_1.2.7vs2.0.0_ops.png, > ITBLL2.5B_1.2.7vs2.0.0_ops_NOT_summing_regions.png, flamegraph-1072.1.svg, > flamegraph-1072.2.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: tree.txt > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Priority: Critical > Fix For: 2.0.0 > > Attachments: flamegraph-1072.1.svg, flamegraph-1072.2.svg, tree.txt > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Attachment: flamegraph-1072.1.svg flamegraph-1072.2.svg > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Priority: Critical > Fix For: 2.0.0 > > Attachments: flamegraph-1072.1.svg, flamegraph-1072.2.svg > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Priority: Critical (was: Major) > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Priority: Critical > Fix For: 2.0.0 > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (HBASE-20188) [TESTING] Performance
[ https://issues.apache.org/jira/browse/HBASE-20188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] stack updated HBASE-20188: -- Fix Version/s: 2.0.0 > [TESTING] Performance > - > > Key: HBASE-20188 > URL: https://issues.apache.org/jira/browse/HBASE-20188 > Project: HBase > Issue Type: Umbrella > Components: Performance >Reporter: stack >Priority: Major > Fix For: 2.0.0 > > > How does 2.0.0 compare to old versions? Is it faster, slower? There is rumor > that it is much slower, that the problem is the asyncwal writing. Does > in-memory compaction slow us down or speed us up? What happens when you > enable offheaping? > Keep notes here in this umbrella issue. Need to be able to say something > about perf when 2.0.0 ships. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
