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Monica Liu updated SPARK-10981:
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Description:
I am using SparkR from RStudio, and I ran into an error with the join function
that I
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Reynold Xin updated SPARK-10909:
Labels: (was: jdbc newbie sql)
> Spark sql jdbc fails for Oracle NUMBER type columns
>
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Andrew Or updated SPARK-10956:
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Affects Version/s: (was: 1.0.0)
> Introduce common memory management interface for execution and
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Yin Huai resolved SPARK-10941.
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Resolution: Fixed
Fix Version/s: 1.6.0
Issue resolved by pull request 8973
Monica Liu created SPARK-10981:
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Summary: R semijoin leads to Java errors, R leftsemi leads to
Spark errors
Key: SPARK-10981
URL: https://issues.apache.org/jira/browse/SPARK-10981
Project: Spark
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Andrew Or updated SPARK-1:
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Description:
Memory management in Spark is currently broken down into two disjoint regions:
one for
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Andrew Or updated SPARK-1:
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Attachment: unified-memory-management-spark-1.pdf
> Consolidate cache memory management and
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Reynold Xin resolved SPARK-10679.
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Resolution: Fixed
Fix Version/s: 1.6.0
> javax.jdo.JDOFatalUserException in executor
>
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Reynold Xin updated SPARK-10914:
Description:
Using an inner join, to match together two integer columns, I generally get no
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Reynold Xin commented on SPARK-10914:
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I don't think size estimator would impact the result.
If I
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Josh Rosen resolved SPARK-10982.
Resolution: Fixed
Fix Version/s: 1.6.0
Issue resolved by pull request 9013
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Xiangrui Meng updated SPARK-10490:
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Assignee: Yanbo Liang
> Consolidate the Cholesky solvers in WeightedLeastSquares and ALS
>
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Xiangrui Meng updated SPARK-10875:
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Shepherd: Xiangrui Meng
Target Version/s: 1.6.0
> RowMatrix.computeCovariance()
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Marcelo Vanzin commented on SPARK-10987:
Hmm. I think I know what's going on, just not how. In
Andrew Or created SPARK-10985:
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Summary: Avoid passing evicted blocks throughout BlockManager /
CacheManager
Key: SPARK-10985
URL: https://issues.apache.org/jira/browse/SPARK-10985
Project: Spark
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Reynold Xin updated SPARK-7869:
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Assignee: Alexey Grishchenko
> Spark Data Frame Fails to Load Postgres Tables with JSONB DataType
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Reynold Xin updated SPARK-7869:
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Target Version/s: 1.6.0
> Spark Data Frame Fails to Load Postgres Tables with JSONB DataType Columns
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Joseph Wu updated SPARK-10986:
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Description:
When running an example task on a Mesos cluster (local master, local agent),
any Spark
Joseph Wu created SPARK-10986:
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Summary: ClassNotFoundException when running on Client mode, with
a Mesos master.
Key: SPARK-10986
URL: https://issues.apache.org/jira/browse/SPARK-10986
Project: Spark
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Huaxin Gao commented on SPARK-8386:
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If the above fix is correct, can I have a pull request to check in
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Yin Huai updated SPARK-9702:
Assignee: Josh Rosen
> Repartition operator should use Exchange to perform its shuffle
>
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Reynold Xin commented on SPARK-1:
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[~bowenzhangusa] thanks for the interest. This task is pretty
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Bowen Zhang commented on SPARK-1:
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[~rxin], sounds good.
> Consolidate cache memory management
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Marcelo Vanzin commented on SPARK-10987:
It may not be cluster mode per se; I ran the tests
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Andrew Or updated SPARK-1:
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Summary: Consolidate storage and execution memory management (was:
Consolidate cache memory
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Davies Liu updated SPARK-10980:
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Description: Decimal(100L, 20, 2) will become
100 instead of
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Joseph K. Bradley resolved SPARK-10779.
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Resolution: Fixed
Fix Version/s: 1.6.0
Issue resolved by pull request 8967
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Marcelo Vanzin commented on SPARK-10987:
The {{ExecutorRunnable}} process (client-mode AM) was
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Xiangrui Meng resolved SPARK-10738.
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Resolution: Fixed
Fix Version/s: 1.6.0
Issue resolved by pull request 8853
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Davies Liu resolved SPARK-10917.
Resolution: Fixed
Fix Version/s: 1.6.0
Issue resolved by pull request 8971
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Marcelo Vanzin updated SPARK-10987:
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Summary: yarn-client mode misbehaving with netty-based RPC backend (was:
yarn-cluster mode
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Apache Spark reassigned SPARK-10980:
Assignee: Davies Liu (was: Apache Spark)
> Create wrong decimal if unscaled > 1e18 and
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Apache Spark commented on SPARK-10980:
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User 'davies' has created a pull request for this issue:
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Sean Owen commented on SPARK-10942:
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I tried this on master in spark-shell:
{code}
import
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Apache Spark reassigned SPARK-10980:
Assignee: Apache Spark (was: Davies Liu)
> Create wrong decimal if unscaled > 1e18 and
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Marcelo Vanzin resolved SPARK-10300.
Resolution: Fixed
Second time is the charm?
> Use tags to control which tests to run
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Andrew Or updated SPARK-1:
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Description:
Memory management in Spark is currently broken down into two disjoint regions:
one for
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Reynold Xin edited comment on SPARK-10914 at 10/7/15 10:22 PM:
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Thanks for
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Xiangrui Meng resolved SPARK-10490.
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Resolution: Fixed
Fix Version/s: 1.6.0
Issue resolved by pull request 8936
Davies Liu created SPARK-10980:
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Summary: Create wrong decimal with unscaled value and precision >
18
Key: SPARK-10980
URL: https://issues.apache.org/jira/browse/SPARK-10980
Project: Spark
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Davies Liu updated SPARK-10980:
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Affects Version/s: 1.2.2
1.3.1
1.4.1
> Create wrong
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Davies Liu updated SPARK-10980:
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Summary: Create wrong decimal if unscaled > 1e18 and scale > 0 (was:
Create wrong decimal with
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Reynold Xin commented on SPARK-10342:
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[~fxing] thanks a lot for the interest. Since this is your
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Huaxin Gao commented on SPARK-8386:
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I looked the code, it has this
@deprecated("Use write.jdbc()",
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Xiangrui Meng updated SPARK-10959:
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Assignee: Bryan Cutler
> PySpark StreamingLogisticRegressionWithSGD does not train with given
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Davies Liu resolved SPARK-10980.
Resolution: Fixed
Fix Version/s: 1.2.3
1.5.2
1.3.2
Reynold Xin created SPARK-10982:
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Summary: Rename ExpressionAggregate -> DeclarativeAggregate
Key: SPARK-10982
URL: https://issues.apache.org/jira/browse/SPARK-10982
Project: Spark
Issue Type:
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Andrew Or updated SPARK-10956:
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Description:
The first step towards implementing a solution for SPARK-1 is to refactor
the
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Andrew Or updated SPARK-10956:
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Description:
The first step towards implementing a solution for SPARK-1 is to refactor
the
Andrew Or created SPARK-10984:
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Summary: Simplify *MemoryManager class structure
Key: SPARK-10984
URL: https://issues.apache.org/jira/browse/SPARK-10984
Project: Spark
Issue Type: Sub-task
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Andrew Or updated SPARK-10956:
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Priority: Major (was: Critical)
> Introduce common memory management interface for execution and
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Joseph K. Bradley updated SPARK-10779:
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Assignee: Evan Chen
> Set initialModel for KMeans model in PySpark (spark.mllib)
>
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Reynold Xin edited comment on SPARK-10914 at 10/7/15 10:12 PM:
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I just ran
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Reynold Xin updated SPARK-10914:
Description:
Using an inner join, to match together two integer columns, I generally get no
Marcelo Vanzin created SPARK-10987:
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Summary: yarn-cluster mode misbehaving with netty-based RPC backend
Key: SPARK-10987
URL: https://issues.apache.org/jira/browse/SPARK-10987
Project: Spark
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Joseph K. Bradley updated SPARK-10919:
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Summary: Association rules class should return the support of each rule
(was:
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Joseph K. Bradley commented on SPARK-10919:
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Would you be interested in sending a PR for this?
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Yin Huai resolved SPARK-9702.
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Resolution: Fixed
Fix Version/s: 1.6.0
Issue resolved by pull request 8083
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Xiangrui Meng updated SPARK-10875:
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Assignee: Nick Pritchard
> RowMatrix.computeCovariance() result is not exactly symmetric
>
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Apache Spark commented on SPARK-10982:
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User 'rxin' has created a pull request for this issue:
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Apache Spark reassigned SPARK-10982:
Assignee: Reynold Xin (was: Apache Spark)
> Rename ExpressionAggregate ->
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Apache Spark reassigned SPARK-10982:
Assignee: Apache Spark (was: Reynold Xin)
> Rename ExpressionAggregate ->
Andrew Or created SPARK-10983:
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Summary: Implement unified memory manager
Key: SPARK-10983
URL: https://issues.apache.org/jira/browse/SPARK-10983
Project: Spark
Issue Type: Sub-task
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Reynold Xin resolved SPARK-10856.
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Resolution: Fixed
Assignee: Liang-Chi Hsieh
Fix Version/s: 1.6.0
> SQL Server
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Reynold Xin updated SPARK-7869:
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Description:
Most of our tables load into dataframes just fine with postgres. However we
have a
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Reynold Xin updated SPARK-10186:
Labels: (was: array json postgres sql struct)
> Add support for more postgres column types
>
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Xiangrui Meng updated SPARK-10959:
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Target Version/s: 1.5.2, 1.6.0
> PySpark StreamingLogisticRegressionWithSGD does not train
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Xiangrui Meng updated SPARK-10959:
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Shepherd: Xiangrui Meng
> PySpark StreamingLogisticRegressionWithSGD does not train with given
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Huaxin Gao commented on SPARK-8386:
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Actually I can also recreate the problem in the other two cases.
Josh Rosen created SPARK-10988:
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Summary: Reduce duplication in Aggregate2's expression rewriting
logic
Key: SPARK-10988
URL: https://issues.apache.org/jira/browse/SPARK-10988
Project: Spark
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RaviShankar KS updated SPARK-10967:
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Attachment: CreateDF_sparkshell_jira.scala
run in spark shell
> Incorrect Join behavior in
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RaviShankar KS updated SPARK-10968:
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Attachment: CreateDF_sparkshell_jira.scala
> Incorrect Join behavior in filter conditions
>
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Sean Owen commented on SPARK-10965:
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You don't need it to be assigned to you, just go ahead. I will add
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RaviShankar KS updated SPARK-10967:
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Description:
We notice that the join conditions are not working as expected in the case of
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RaviShankar KS closed SPARK-10967.
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Resolution: Invalid
Target Version/s: 1.5.1, 1.4.1 (was: 1.4.1, 1.5.1)
> ignore -
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RaviShankar KS updated SPARK-10967:
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Attachment: (was: CreateDF_sparkshell_jira.scala)
> Incorrect UNION ALL behavior
>
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RaviShankar KS updated SPARK-10967:
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Description: IGNORE (was: We notice that the join conditions are not
working as expected in
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RaviShankar KS updated SPARK-10967:
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Summary: ignore - Incorrect UNION ALL behavior (was: Incorrect UNION ALL
behavior)
>
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RaviShankar KS commented on SPARK-10968:
not actually incorrect.
DataFrame d5.value has fields
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Liang-Chi Hsieh commented on SPARK-10968:
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Is it incorrect? Because d5.value and d5_opp.value are
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Apache Spark reassigned SPARK-10988:
Assignee: Apache Spark (was: Josh Rosen)
> Reduce duplication in Aggregate2's expression
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Joseph K. Bradley resolved SPARK-10064.
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Resolution: Fixed
Fix Version/s: 1.6.0
Issue resolved by pull request 8246
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Apache Spark reassigned SPARK-10992:
Assignee: Apache Spark
> Partial Aggregation Support for Hive UDAF
>
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Apache Spark commented on SPARK-10992:
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User 'chenghao-intel' has created a pull request for this
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Apache Spark reassigned SPARK-10992:
Assignee: (was: Apache Spark)
> Partial Aggregation Support for Hive UDAF
>
Marcelo Vanzin created SPARK-10997:
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Summary: Netty-based RPC env should support a "client-only" mode.
Key: SPARK-10997
URL: https://issues.apache.org/jira/browse/SPARK-10997
Project: Spark
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Peter Haumer commented on SPARK-8386:
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Huaxin Gao, sorry for not replying earlier. It slipped through
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https://issues.apache.org/jira/browse/SPARK-10988?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14947817#comment-14947817
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Apache Spark commented on SPARK-10988:
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User 'JoshRosen' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-10988?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-10988:
Assignee: Josh Rosen (was: Apache Spark)
> Reduce duplication in Aggregate2's expression
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https://issues.apache.org/jira/browse/SPARK-10940?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14947836#comment-14947836
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Sandeep Pal commented on SPARK-10940:
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I rebooted all the machines and issue is not reproduced.
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https://issues.apache.org/jira/browse/SPARK-10990?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14947838#comment-14947838
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Apache Spark commented on SPARK-10990:
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User 'davies' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-10990?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-10990:
Assignee: Davies Liu (was: Apache Spark)
> Avoid the serialization multiple times during
Davies Liu created SPARK-10990:
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Summary: Avoid the serialization multiple times during unrolling
of complex types
Key: SPARK-10990
URL: https://issues.apache.org/jira/browse/SPARK-10990
Project: Spark
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https://issues.apache.org/jira/browse/SPARK-10987?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14947893#comment-14947893
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Marcelo Vanzin commented on SPARK-10987:
Anyway, here's what I found so far.
Driver launches AM;
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https://issues.apache.org/jira/browse/SPARK-10989?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-10989:
Assignee: Apache Spark
> Add the dot and hadamard products to the Vectors object
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Yang Yang created SPARK-10994:
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Summary: Local clustering coefficient computation in GraphX
Key: SPARK-10994
URL: https://issues.apache.org/jira/browse/SPARK-10994
Project: Spark
Issue Type: New
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https://issues.apache.org/jira/browse/SPARK-10989?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-10989:
Assignee: (was: Apache Spark)
> Add the dot and hadamard products to the Vectors
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https://issues.apache.org/jira/browse/SPARK-10998?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14948007#comment-14948007
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Apache Spark commented on SPARK-10998:
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User 'marmbrus' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-10998?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-10998:
Assignee: Michael Armbrust (was: Apache Spark)
> Show non-children in default
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https://issues.apache.org/jira/browse/SPARK-10767?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-10767:
Assignee: (was: Apache Spark)
> Make pyspark shared params codegen more consistent
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