spark git commit: [SPARK-15206][SQL] add testcases for distinct aggregate in having clause

Repository: spark Updated Branches: refs/heads/branch-2.0 9c20c7a33 -> 9a08c9f1c [SPARK-15206][SQL] add testcases for distinct aggregate in having clause ## What changes were proposed in this pull request? Add new test cases for including distinct aggregate in having clause in 2.0 branch.

spark git commit: [SPARK-15206][SQL] add testcases for distinct aggregate in having clause

Repository: spark Updated Branches: refs/heads/master 8f0a3d5bc -> df9adb5ec [SPARK-15206][SQL] add testcases for distinct aggregate in having clause ## What changes were proposed in this pull request? Add new test cases for including distinct aggregate in having clause in 2.0 branch. This

spark git commit: [SPARK-15330][SQL] Implement Reset Command

Repository: spark Updated Branches: refs/heads/branch-2.0 6871deb93 -> 9c20c7a33 [SPARK-15330][SQL] Implement Reset Command What changes were proposed in this pull request? Like `Set` Command in Hive, `Reset` is also supported by Hive. See the link:

spark git commit: [SPARK-15330][SQL] Implement Reset Command

Repository: spark Updated Branches: refs/heads/master c18fa464f -> 8f0a3d5bc [SPARK-15330][SQL] Implement Reset Command What changes were proposed in this pull request? Like `Set` Command in Hive, `Reset` is also supported by Hive. See the link:

spark git commit: [SPARK-15280] Input/Output] Refactored OrcOutputWriter and moved serialization to a new class.

Repository: spark Updated Branches: refs/heads/master 201a51f36 -> c18fa464f [SPARK-15280] Input/Output] Refactored OrcOutputWriter and moved serialization to a new class. ## What changes were proposed in this pull request? Refactoring: Separated ORC serialization logic from OrcOutputWriter

spark git commit: [SPARK-15280] Input/Output] Refactored OrcOutputWriter and moved serialization to a new class.

Repository: spark Updated Branches: refs/heads/branch-2.0 4148a9c2c -> 6871deb93 [SPARK-15280] Input/Output] Refactored OrcOutputWriter and moved serialization to a new class. ## What changes were proposed in this pull request? Refactoring: Separated ORC serialization logic from

spark git commit: [SPARK-15452][SQL] Mark aggregator API as experimental

Repository: spark Updated Branches: refs/heads/master 5e1ee2898 -> 201a51f36 [SPARK-15452][SQL] Mark aggregator API as experimental ## What changes were proposed in this pull request? The Aggregator API was introduced in 2.0 for Dataset. All typed Dataset APIs should still be marked as

spark git commit: [SPARK-15452][SQL] Mark aggregator API as experimental

Repository: spark Updated Branches: refs/heads/branch-2.0 d7bf318a0 -> 4148a9c2c [SPARK-15452][SQL] Mark aggregator API as experimental ## What changes were proposed in this pull request? The Aggregator API was introduced in 2.0 for Dataset. All typed Dataset APIs should still be marked as

[3/3] spark git commit: [SPARK-15078] [SQL] Add all TPCDS 1.4 benchmark queries for SparkSQL

[SPARK-15078] [SQL] Add all TPCDS 1.4 benchmark queries for SparkSQL Now that SparkSQL supports all TPC-DS queries, this patch adds all 99 benchmark queries inside SparkSQL. Benchmark only Author: Sameer Agarwal Closes #13188 from sameeragarwal/tpcds-all. (cherry

[2/3] spark git commit: [SPARK-15078] [SQL] Add all TPCDS 1.4 benchmark queries for SparkSQL

http://git-wip-us.apache.org/repos/asf/spark/blob/d7bf318a/sql/core/src/test/resources/tpcds/q49.sql -- diff --git a/sql/core/src/test/resources/tpcds/q49.sql b/sql/core/src/test/resources/tpcds/q49.sql new file mode 100755 index

[1/3] spark git commit: [SPARK-15078] [SQL] Add all TPCDS 1.4 benchmark queries for SparkSQL

Repository: spark Updated Branches: refs/heads/branch-2.0 9a8df0c9a -> d7bf318a0 http://git-wip-us.apache.org/repos/asf/spark/blob/d7bf318a/sql/core/src/test/resources/tpcds/q85.sql -- diff --git

spark git commit: [SPARK-15114][SQL] Column name generated by typed aggregate is super verbose

Repository: spark Updated Branches: refs/heads/branch-2.0 69f39552d -> 9a8df0c9a [SPARK-15114][SQL] Column name generated by typed aggregate is super verbose ## What changes were proposed in this pull request? Generate a shorter default alias for `AggregateExpression `, In this PR,

spark git commit: [SPARK-15114][SQL] Column name generated by typed aggregate is super verbose

Repository: spark Updated Branches: refs/heads/master f39621c99 -> 5e1ee2898 [SPARK-15114][SQL] Column name generated by typed aggregate is super verbose ## What changes were proposed in this pull request? Generate a shorter default alias for `AggregateExpression `, In this PR, aggregate

spark git commit: [SPARK-15462][SQL][TEST] unresolved === false` is enough in testcases.

Repository: spark Updated Branches: refs/heads/branch-2.0 a93f04dd4 -> 69f39552d [SPARK-15462][SQL][TEST] unresolved === false` is enough in testcases. ## What changes were proposed in this pull request? In only `catalyst` module, there exists 8 evaluation test cases on unresolved

spark git commit: [SPARK-15462][SQL][TEST] unresolved === false` is enough in testcases.

Repository: spark Updated Branches: refs/heads/master 666bf2e83 -> f39621c99 [SPARK-15462][SQL][TEST] unresolved === false` is enough in testcases. ## What changes were proposed in this pull request? In only `catalyst` module, there exists 8 evaluation test cases on unresolved expressions.

spark git commit: [SPARK-15445][SQL] Build fails for java 1.7 after adding java.mathBigInteger support

Repository: spark Updated Branches: refs/heads/branch-2.0 c0cc921a5 -> a93f04dd4 [SPARK-15445][SQL] Build fails for java 1.7 after adding java.mathBigInteger support ## What changes were proposed in this pull request? Using longValue() and then checking whether the value is in the range for

spark git commit: [SPARK-15445][SQL] Build fails for java 1.7 after adding java.mathBigInteger support

Repository: spark Updated Branches: refs/heads/master 45b7557e6 -> 666bf2e83 [SPARK-15445][SQL] Build fails for java 1.7 after adding java.mathBigInteger support ## What changes were proposed in this pull request? Using longValue() and then checking whether the value is in the range for a