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Wang, Gang edited comment on SPARK-13004 at 1/27/16 5:34 AM:
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Yes, That is
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Wang, Gang closed SPARK-13004.
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Resolution: Later
Preparing actionable items so close it temporarily as Sean Owen suggested.
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Wang, Gang commented on SPARK-13004:
I have closed it according to your advice, Thanks.
> Support
Wang, Gang created SPARK-13004:
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Summary: Support Non-Volatile Data and Operations
Key: SPARK-13004
URL: https://issues.apache.org/jira/browse/SPARK-13004
Project: Spark
Issue Type: Epic
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Wang, Gang updated SPARK-13004:
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Description:
Based on our experiments, the SerDe-like operations have some significant
negative
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Wang, Gang updated SPARK-13004:
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Description:
Based on our experiments, the SerDe-like operations have some significant
negative
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Wang, Gang updated SPARK-13004:
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Description:
Based on our experiments, the SerDe-like operations have some significant
negative
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Wang, Gang commented on SPARK-13004:
Yes, That is one of prototype for concept of proof. We are
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Wang, Gang edited comment on SPARK-13004 at 1/27/16 12:44 AM:
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Yes, That is
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Wang, Gang commented on SPARK-13004:
Yes, That is one of our prototypes for concept of proof. We are
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Wang, Gang updated SPARK-13004:
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Comment: was deleted
(was: Yes, That is one of our prototypes for concept of proof. We are preparing
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Wang, Gang updated SPARK-23373:
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Issue Type: Bug (was: New Feature)
> Can not execute "count distinct" queries on parquet formatted
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Wang, Gang updated SPARK-23373:
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Description:
I failed to run sql "select count(distinct n_name) from nation", table nation
is
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Wang, Gang updated SPARK-23373:
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Description:
I failed to run sql "select count(distinct n_name) from nation", table nation
is
Wang, Gang created SPARK-23373:
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Summary: Can not execute "count distinct" queries on parquet
formatted table
Key: SPARK-23373
URL: https://issues.apache.org/jira/browse/SPARK-23373
Project: Spark
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Wang, Gang edited comment on SPARK-23373 at 2/9/18 1:01 PM:
Yes. Seems
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Wang, Gang commented on SPARK-23373:
Yes. Seems related to my test environment.
While, I tried in a
Wang, Gang created SPARK-25401:
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Summary: Reorder the required ordering to match the table's output
ordering for bucket join
Key: SPARK-25401
URL: https://issues.apache.org/jira/browse/SPARK-25401
Wang, Gang created SPARK-25411:
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Summary: Implement range partition in Spark
Key: SPARK-25411
URL: https://issues.apache.org/jira/browse/SPARK-25411
Project: Spark
Issue Type: New Feature
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Wang, Gang commented on SPARK-23839:
Good point! Currently, Spark just take data size into
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Wang, Gang commented on SPARK-25411:
[~cloud_fan] How do you think of this feature? In our inner
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Wang, Gang commented on SPARK-17570:
Any update?
> Avoid Hash and Exchange in Sort Merge join if
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Wang, Gang updated SPARK-25411:
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Attachment: range partition design doc.pdf
> Implement range partition in Spark
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Wang, Gang commented on SPARK-25411:
Add a design doc, please help to review.
> Implement range
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Wang, Gang updated SPARK-25411:
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Attachment: range partition design doc.pdf
> Implement range partition in Spark
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Wang, Gang updated SPARK-25411:
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Attachment: (was: range partition design doc.pdf)
> Implement range partition in Spark
>
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Wang, Gang updated SPARK-26672:
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Summary: SinglePartition may not satisfies
HashClusteredDistribution/OrderedDistribution (was:
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Wang, Gang updated SPARK-26672:
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Description:
If we are loading data to a *bucketed table* TEST_TABLE of which bucket number
is not
Wang, Gang created SPARK-26672:
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Summary: SinglePartition should not satisfies
HashClusteredDistribution/OrderedDistribution
Key: SPARK-26672
URL: https://issues.apache.org/jira/browse/SPARK-26672
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Wang, Gang closed SPARK-26672.
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> SinglePartition may not satisfies
> HashClusteredDistribution/OrderedDistribution
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Wang, Gang resolved SPARK-26672.
Resolution: Not A Problem
This is only a bug in our inner Spark version. It's ok in community
Wang, Gang created SPARK-26375:
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Summary: Rule PruneFileSourcePartitions should be fired before any
other rules based on data size
Key: SPARK-26375
URL: https://issues.apache.org/jira/browse/SPARK-26375
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Wang, Gang updated SPARK-26375:
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Summary: Rule PruneFileSourcePartitions should be fired before any other
rules based on table
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Wang, Gang updated SPARK-26375:
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Description: In catalyst, some optimize rules are base on table statistics,
like rule ReorderJoin,
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Wang, Gang commented on SPARK-25401:
Yeah. I think so.
And please make sure the outputOrdering of
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Wang, Gang updated SPARK-25411:
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Description:
In our PROD environment, there are some partitioned fact tables, which are all
quite
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Wang, Gang updated SPARK-25411:
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Description:
In our product environment, there are some partitioned fact tables, which are
all
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Wang, Gang resolved SPARK-26375.
Resolution: Not A Problem
> Rule PruneFileSourcePartitions should be fired before any other rules
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Wang, Gang commented on SPARK-26375:
Should be okay, filter on partition columns is also regarded as
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Wang, Gang commented on SPARK-25411:
I referred to ORACLE DDLs, quite close to PG.
> Implement
Wang, Gang created SPARK-29189:
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Summary: Add an option to ignore block locations when listing file
Key: SPARK-29189
URL: https://issues.apache.org/jira/browse/SPARK-29189
Project: Spark
Issue
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Wang, Gang updated SPARK-29189:
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Description:
In our PROD env, we have a pure Spark cluster, I think this is also pretty
common,
Wang, Gang created SPARK-32464:
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Summary: Support skew handling on join with one side that has no
query stage
Key: SPARK-32464
URL: https://issues.apache.org/jira/browse/SPARK-32464
Project: Spark
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Wang, Gang updated SPARK-32464:
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Summary: Support skew handling on join that has one side with no query
stage (was: Support skew
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Wang, Gang commented on SPARK-32464:
A PR [https://github.com/apache/spark/pull/29266]
> Support
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