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HyukjinKwon commented on a change in pull request #25168: [SPARK-28276][SQL][PYTHON][TEST] Convert and port 'cross-join.sql' into UDF test base URL: https://github.com/apache/spark/pull/25168#discussion_r303757925 ## File path: sql/core/src/test/resources/sql-tests/results/udf/udf

[GitHub] [spark] HyukjinKwon closed pull request #25106: [SPARK-28345][SQL][Python] PythonUDF predicate should be able to pushdown to join

HyukjinKwon closed pull request #25106: [SPARK-28345][SQL][Python] PythonUDF predicate should be able to pushdown to join URL: https://github.com/apache/spark/pull/25106 This is an automated message from the Apache Git Servi

[GitHub] [spark] viirya commented on a change in pull request #25168: [SPARK-28276][SQL][PYTHON][TEST] Convert and port 'cross-join.sql' into UDF test base

viirya commented on a change in pull request #25168: [SPARK-28276][SQL][PYTHON][TEST] Convert and port 'cross-join.sql' into UDF test base URL: https://github.com/apache/spark/pull/25168#discussion_r303760063 ## File path: sql/core/src/test/resources/sql-tests/results/udf/udf-cros

[GitHub] [spark] jerryshao commented on issue #24909: [SPARK-28106][SQL] When Spark SQL use "add jar" , before add to SparkContext, check jar path exist first.

jerryshao commented on issue #24909: [SPARK-28106][SQL] When Spark SQL use "add jar" , before add to SparkContext, check jar path exist first. URL: https://github.com/apache/spark/pull/24909#issuecomment-511699348 Thanks for the fix, merging to master branch. ---

[GitHub] [spark] SparkQA commented on issue #25168: [SPARK-28276][SQL][PYTHON][TEST] Convert and port 'cross-join.sql' into UDF test base

SparkQA commented on issue #25168: [SPARK-28276][SQL][PYTHON][TEST] Convert and port 'cross-join.sql' into UDF test base URL: https://github.com/apache/spark/pull/25168#issuecomment-511700709 **[Test build #107727 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuil

[GitHub] [spark] dilipbiswal commented on a change in pull request #25164: [SPARK-28375] Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates if run multiple times

dilipbiswal commented on a change in pull request #25164: [SPARK-28375] Prevent the PullupCorrelatedPredicates optimizer rule from removing predicates if run multiple times URL: https://github.com/apache/spark/pull/25164#discussion_r303762504 ## File path: sql/catalyst/src/main/sc

[GitHub] [spark] jerryshao closed pull request #24909: [SPARK-28106][SQL] When Spark SQL use "add jar" , before add to SparkContext, check jar path exist first.

jerryshao closed pull request #24909: [SPARK-28106][SQL] When Spark SQL use "add jar" , before add to SparkContext, check jar path exist first. URL: https://github.com/apache/spark/pull/24909 This is an automated message

[GitHub] [spark] AmplabJenkins commented on issue #25168: [SPARK-28276][SQL][PYTHON][TEST] Convert and port 'cross-join.sql' into UDF test base

AmplabJenkins commented on issue #25168: [SPARK-28276][SQL][PYTHON][TEST] Convert and port 'cross-join.sql' into UDF test base URL: https://github.com/apache/spark/pull/25168#issuecomment-511702575 Merged build finished. Test PASSed.

[GitHub] [spark] AmplabJenkins commented on issue #25168: [SPARK-28276][SQL][PYTHON][TEST] Convert and port 'cross-join.sql' into UDF test base

AmplabJenkins commented on issue #25168: [SPARK-28276][SQL][PYTHON][TEST] Convert and port 'cross-join.sql' into UDF test base URL: https://github.com/apache/spark/pull/25168#issuecomment-511702578 Test PASSed. Refer to this link for build results (access rights to CI server needed):

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AmplabJenkins removed a comment on issue #25168: [SPARK-28276][SQL][PYTHON][TEST] Convert and port 'cross-join.sql' into UDF test base URL: https://github.com/apache/spark/pull/25168#issuecomment-511702578 Test PASSed. Refer to this link for build results (access rights to CI server nee

[GitHub] [spark] AmplabJenkins removed a comment on issue #25168: [SPARK-28276][SQL][PYTHON][TEST] Convert and port 'cross-join.sql' into UDF test base

AmplabJenkins removed a comment on issue #25168: [SPARK-28276][SQL][PYTHON][TEST] Convert and port 'cross-join.sql' into UDF test base URL: https://github.com/apache/spark/pull/25168#issuecomment-511702575 Merged build finished. Test PASSed. ---

[GitHub] [spark] hvanhovell commented on issue #24958: [SPARK-28153][PYTHON] Use AtomicReference at InputFileBlockHolder (to support input_file_name with Python UDF)

hvanhovell commented on issue #24958: [SPARK-28153][PYTHON] Use AtomicReference at InputFileBlockHolder (to support input_file_name with Python UDF) URL: https://github.com/apache/spark/pull/24958#issuecomment-511705042 Honestly, the only proper way of fixing this is to make the input file

[GitHub] [spark] cloud-fan closed pull request #25158: [SPARK-28395][SQL] Division operator support integral division

cloud-fan closed pull request #25158: [SPARK-28395][SQL] Division operator support integral division URL: https://github.com/apache/spark/pull/25158 This is an automated message from the Apache Git Service. To respond to the

[GitHub] [spark] cloud-fan commented on issue #25165: [SPARK-28201][SQL][TEST][FOLLOWUP] Fix Integration test suite according to the new exception message

cloud-fan commented on issue #25165: [SPARK-28201][SQL][TEST][FOLLOWUP] Fix Integration test suite according to the new exception message URL: https://github.com/apache/spark/pull/25165#issuecomment-511710847 thanks, merging to master! --

[GitHub] [spark] cloud-fan closed pull request #25165: [SPARK-28201][SQL][TEST][FOLLOWUP] Fix Integration test suite according to the new exception message

cloud-fan closed pull request #25165: [SPARK-28201][SQL][TEST][FOLLOWUP] Fix Integration test suite according to the new exception message URL: https://github.com/apache/spark/pull/25165 This is an automated message from the

[GitHub] [spark] mgaido91 commented on a change in pull request #25137: [SPARK-28348][SQL] Decimal precision promotion for binary arithmetic with casted decimal type

mgaido91 commented on a change in pull request #25137: [SPARK-28348][SQL] Decimal precision promotion for binary arithmetic with casted decimal type URL: https://github.com/apache/spark/pull/25137#discussion_r303196343 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/

[GitHub] [spark] mgaido91 commented on a change in pull request #25137: [SPARK-28348][SQL] Decimal precision promotion for binary arithmetic with casted decimal type

mgaido91 commented on a change in pull request #25137: [SPARK-28348][SQL] Decimal precision promotion for binary arithmetic with casted decimal type URL: https://github.com/apache/spark/pull/25137#discussion_r303196418 ## File path: sql/catalyst/src/test/scala/org/apache/spark/sql/

[GitHub] [spark] mgaido91 commented on a change in pull request #25137: [SPARK-28348][SQL] Decimal precision promotion for binary arithmetic with casted decimal type

mgaido91 commented on a change in pull request #25137: [SPARK-28348][SQL] Decimal precision promotion for binary arithmetic with casted decimal type URL: https://github.com/apache/spark/pull/25137#discussion_r303196449 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/

[GitHub] [spark] cloud-fan commented on issue #24991: [SPARK-28188] Materialize Dataframe API

cloud-fan commented on issue #24991: [SPARK-28188] Materialize Dataframe API URL: https://github.com/apache/spark/pull/24991#issuecomment-511712741 I've spent more time understanding the use case, and think table cache should be a better choice here 1. disk vs memory: you can set the sto

[GitHub] [spark] AmplabJenkins commented on issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarInterval with Integral Type.

AmplabJenkins commented on issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarInterval with Integral Type. URL: https://github.com/apache/spark/pull/22054#issuecomment-511717918 Test PASSed. Refer to this link for build results (access rights to CI server needed):

[GitHub] [spark] AmplabJenkins commented on issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarInterval with Integral Type.

AmplabJenkins commented on issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarInterval with Integral Type. URL: https://github.com/apache/spark/pull/22054#issuecomment-511717906 Merged build finished. Test PASSed. -

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AmplabJenkins removed a comment on issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarInterval with Integral Type. URL: https://github.com/apache/spark/pull/22054#issuecomment-511717906 Merged build finished. Test PASSed. -

[GitHub] [spark] SparkQA commented on issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarInterval with Integral Type.

SparkQA commented on issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarInterval with Integral Type. URL: https://github.com/apache/spark/pull/22054#issuecomment-511718692 **[Test build #107728 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuild

[GitHub] [spark] AmplabJenkins removed a comment on issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarInterval with Integral Type.

AmplabJenkins removed a comment on issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarInterval with Integral Type. URL: https://github.com/apache/spark/pull/22054#issuecomment-511717918 Test PASSed. Refer to this link for build results (access rights to CI server neede

[GitHub] [spark] priyankagargnitk commented on issue #25022: [SPARK-24695][SQL]: To expose Calendar interval type, so that same can be returned from the UDF.

priyankagargnitk commented on issue #25022: [SPARK-24695][SQL]: To expose Calendar interval type, so that same can be returned from the UDF. URL: https://github.com/apache/spark/pull/25022#issuecomment-511720167 > I'm OK exposing it, but we need to mark that this API is not stable and will

[GitHub] [spark] AmplabJenkins commented on issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarInterval with Integral Type.

AmplabJenkins commented on issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarInterval with Integral Type. URL: https://github.com/apache/spark/pull/22054#issuecomment-511720931 Merged build finished. Test PASSed. -

[GitHub] [spark] AmplabJenkins commented on issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarInterval with Integral Type.

AmplabJenkins commented on issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarInterval with Integral Type. URL: https://github.com/apache/spark/pull/22054#issuecomment-511720937 Test PASSed. Refer to this link for build results (access rights to CI server needed):

[GitHub] [spark] gaborgsomogyi commented on a change in pull request #25135: [SPARK-28367][SS] Use new KafkaConsumer.poll API in Kafka connector

gaborgsomogyi commented on a change in pull request #25135: [SPARK-28367][SS] Use new KafkaConsumer.poll API in Kafka connector URL: https://github.com/apache/spark/pull/25135#discussion_r303786627 ## File path: external/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/K

[GitHub] [spark] AmplabJenkins removed a comment on issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarInterval with Integral Type.

AmplabJenkins removed a comment on issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarInterval with Integral Type. URL: https://github.com/apache/spark/pull/22054#issuecomment-511720937 Test PASSed. Refer to this link for build results (access rights to CI server neede

[GitHub] [spark] gaborgsomogyi commented on issue #21861: [SPARK-24907][SQL][WIP] Migrate JDBC DataSource to JDBCDataSourceV2 Read using DataSourceV2 API

gaborgsomogyi commented on issue #21861: [SPARK-24907][SQL][WIP] Migrate JDBC DataSource to JDBCDataSourceV2 Read using DataSourceV2 API URL: https://github.com/apache/spark/pull/21861#issuecomment-511722470 @shivsood thanks for considering me as collaborator. Since I'm mainly in the strea

[GitHub] [spark] wangyum opened a new pull request #25170: [SPARK-28343][FOLLOW-UP][SQL][TEST] Enable spark.sql.function.preferIntegralDivision for PostgreSQL testing

wangyum opened a new pull request #25170: [SPARK-28343][FOLLOW-UP][SQL][TEST] Enable spark.sql.function.preferIntegralDivision for PostgreSQL testing URL: https://github.com/apache/spark/pull/25170 ## What changes were proposed in this pull request? This PR enables `spark.sql.functio

[GitHub] [spark] SparkQA commented on issue #25170: [SPARK-28343][FOLLOW-UP][SQL][TEST] Enable spark.sql.function.preferIntegralDivision for PostgreSQL testing

SparkQA commented on issue #25170: [SPARK-28343][FOLLOW-UP][SQL][TEST] Enable spark.sql.function.preferIntegralDivision for PostgreSQL testing URL: https://github.com/apache/spark/pull/25170#issuecomment-511724645 **[Test build #107729 has started](https://amplab.cs.berkeley.edu/jenkins/jo

[GitHub] [spark] HeartSaVioR commented on a change in pull request #25135: [SPARK-28367][SS] Use new KafkaConsumer.poll API in Kafka connector

HeartSaVioR commented on a change in pull request #25135: [SPARK-28367][SS] Use new KafkaConsumer.poll API in Kafka connector URL: https://github.com/apache/spark/pull/25135#discussion_r303792433 ## File path: external/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/Kaf

[GitHub] [spark] HyukjinKwon commented on issue #25168: [SPARK-28276][SQL][PYTHON][TEST] Convert and port 'cross-join.sql' into UDF test base

HyukjinKwon commented on issue #25168: [SPARK-28276][SQL][PYTHON][TEST] Convert and port 'cross-join.sql' into UDF test base URL: https://github.com/apache/spark/pull/25168#issuecomment-511726635 Looks good .. but let's get #25130 first .. just in case that causes some changes in those PRs

[GitHub] [spark] AmplabJenkins removed a comment on issue #25170: [SPARK-28343][FOLLOW-UP][SQL][TEST] Enable spark.sql.function.preferIntegralDivision for PostgreSQL testing

AmplabJenkins removed a comment on issue #25170: [SPARK-28343][FOLLOW-UP][SQL][TEST] Enable spark.sql.function.preferIntegralDivision for PostgreSQL testing URL: https://github.com/apache/spark/pull/25170#issuecomment-511726821 Test PASSed. Refer to this link for build results (access r

[GitHub] [spark] AmplabJenkins commented on issue #25170: [SPARK-28343][FOLLOW-UP][SQL][TEST] Enable spark.sql.function.preferIntegralDivision for PostgreSQL testing

AmplabJenkins commented on issue #25170: [SPARK-28343][FOLLOW-UP][SQL][TEST] Enable spark.sql.function.preferIntegralDivision for PostgreSQL testing URL: https://github.com/apache/spark/pull/25170#issuecomment-511726821 Test PASSed. Refer to this link for build results (access rights to

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