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stack commented on HBASE-20188: ------------------------------- [~eshcar] Yes to 50k recordcount. I had it at 100k but I see that letting this full set load makes it so we are mostly missing cache changing profile seen running the workloads. I upped my heap to 31G and set recordcount at 50k. > [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)