HBase
  1. HBase
  2. HBASE-8089 Add type support
  3. HBASE-8694

Performance evaluation of encoding implementations

        Details

        • Type: Sub-task Sub-task
        • Status: Open
        • Priority: Major Major
        • Resolution: Unresolved
        • Affects Version/s: None
        • Fix Version/s: None
        • Component/s: Client
        • Labels:
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          Description

          This ticket encapsulates a micro-benchmark of serialization implementation and any performance enhancements that fall out. Specifically, the implementation posted in HBASE-8201 should be compared to the performance of Phoenix's PDataType implementations.

            Activity

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            Nick Dimiduk created issue -
            Nick Dimiduk made changes -
            Field Original Value New Value
            Fix Version/s 0.95.2 [ 12320040 ]
            Nick Dimiduk made changes -
            Description This ticket encapsulates a micro-benchmark of serialization implementation and any performance enhancements that fall out. This ticket encapsulates a micro-benchmark of serialization implementation and any performance enhancements that fall out. Specifically, the implementation posted in HBASE-8201 should be compared to the performance of Phoenix's [PDataType|https://github.com/forcedotcom/phoenix/blob/master/src/main/java/com/salesforce/phoenix/schema/PDataType.java] implementations.
            Nick Dimiduk made changes -
            Assignee Nick Dimiduk [ ndimiduk ]
            Nick Dimiduk made changes -
            Summary Performance evaluation of serialization strategies Performance evaluation of encoding implementations
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            Nick Dimiduk added a comment -

            Here's the output of an initial benchmark suite over Long and Double encodings. This is vs. code from yesterday; it does not include today's refactor to ByteRange or the introduction of Guava Precondition checking. Benchmark code is in a repository on github and include basic instructions for reproduction.

            Preliminary results indicate Phoenix's DECIMAL is ~2x faster and uses ~3x fewer heap objects than my Numeric implementation. Nice job James Taylor! I'll look into cribbing off of your implementation tomorrow In the mean time, have a look at the implementations and make sure I'm doing the other encoding libraries justice.

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            Nick Dimiduk added a comment - Here's the output of an initial benchmark suite over Long and Double encodings. This is vs. code from yesterday; it does not include today's refactor to ByteRange or the introduction of Guava Precondition checking. Benchmark code is in a repository on github and include basic instructions for reproduction. Preliminary results indicate Phoenix's DECIMAL is ~2x faster and uses ~3x fewer heap objects than my Numeric implementation. Nice job James Taylor ! I'll look into cribbing off of your implementation tomorrow In the mean time, have a look at the implementations and make sure I'm doing the other encoding libraries justice.
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            stack added a comment -

            Moving this improvement out of 0.95/0.96. Pull back if I have it wrong.

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            stack added a comment - Moving this improvement out of 0.95/0.96. Pull back if I have it wrong.
            stack made changes -
            Fix Version/s 0.95.2 [ 12320040 ]

              People

              • Assignee:
                Nick Dimiduk
                Reporter:
                Nick Dimiduk
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                Dates

                • Created:
                  Updated:

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