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https://issues.apache.org/jira/browse/HIVE-17417?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16242708#comment-16242708
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Prasanth Jayachandran edited comment on HIVE-17417 at 11/7/17 7:32 PM:
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[~ashutoshc] Here is the difference between Joda, JDK8 and SDF
{code}
Benchmark Mode Cnt
Score Error Units
TimestampFormatBenchmark.benchmarkJDK8TimestampFormatter avgt 10
274.533 ± 2.663 ns/op
TimestampFormatBenchmark.benchmarkJodaTimeTimestampFormatter avgt 10
230.096 ± 5.089 ns/op
TimestampFormatBenchmark.benchmarkSimpleDateFormatter avgt 10
543.846 ± 12.677 ns/op
{code}
On bigger scale this slight difference between joda vs jdk8 will not matter
much. Moving to native JDK8 will be better too. Will update the patch with JDK8
formatter.
was (Author: prasanth_j):
[~ashutoshc] Here is the difference between Joda, JDK8 and SDF
{code}
Benchmark Mode Cnt
Score Error Units
TimestampFormatBenchmark.benchmarkJDK8TimestampFormatter avgt 10
274.533 ± 2.663 ns/op
TimestampFormatBenchmark.benchmarkJodaTimeTimestampFormatter avgt 10
230.096 ± 5.089 ns/op
TimestampFormatBenchmark.benchmarkSimpleDateFormatter avgt 10
543.846 ± 12.677 ns/op
{code}
On bigger scale this slightly difference between joda vs jdk8 will not matter
much. Moving to native JDK8 will be better too. Will update the patch with JDK8
formatter.
> LazySimple Timestamp is very expensive
> --------------------------------------
>
> Key: HIVE-17417
> URL: https://issues.apache.org/jira/browse/HIVE-17417
> Project: Hive
> Issue Type: Bug
> Components: Serializers/Deserializers
> Affects Versions: 3.0.0, 2.4.0
> Reporter: Prasanth Jayachandran
> Assignee: Prasanth Jayachandran
> Priority: Critical
> Attachments: HIVE-17417.1.patch, HIVE-17417.2.patch,
> HIVE-17417.3.patch, HIVE-17417.4.patch, HIVE-17417.5.patch,
> date-serialize.png, timestamp-serialize.png, ts-jmh-perf.png
>
>
> In a specific case where a schema contains array<struct> with timestamp and
> date fields (array size >10000). Any access to this column very very
> expensive in terms of CPU as most of the time is serialization of timestamp
> and date. Refer attached profiles. >70% time spent in serialization +
> tostring conversions.
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