[GitHub] [spark] SparkQA commented on pull request #31305: [SPARK-34213][SQL][3.0] Refresh cached data of v1 table in `LOAD DATA`

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[GitHub] [spark] MaxGekk commented on pull request #31304: [SPARK-34213][SQL] Refresh cached data of v1 table in `LOAD DATA`

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MaxGekk commented on pull request #31304: URL: https://github.com/apache/spark/pull/31304#issuecomment-766303721 Here is the backport to `branch-3.0`: https://github.com/apache/spark/pull/31305 This is an automated message

[GitHub] [spark] MaxGekk opened a new pull request #31305: [SPARK-34213][SQL][3.0] Refresh cached data of v1 table in `LOAD DATA`

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MaxGekk opened a new pull request #31305: URL: https://github.com/apache/spark/pull/31305 ### What changes were proposed in this pull request? Invoke `CatalogImpl.refreshTable()` instead of `SessionCatalog.refreshTable` in v1 implementation of the `LOAD DATA` command.

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[GitHub] [spark] viirya commented on pull request #31296: [SPARK-34205][SQL][SS] Add pipe to Dataset to enable Streaming Dataset pipe

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viirya commented on pull request #31296: URL: https://github.com/apache/spark/pull/31296#issuecomment-766292873 BTW, I know PipedRDD (RDD.pipe) is widely used. At least I heard many times people use pipe to adapt existing program with Spark.

[GitHub] [spark] viirya commented on pull request #31296: [SPARK-34205][SQL][SS] Add pipe to Dataset to enable Streaming Dataset pipe

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viirya commented on pull request #31296: URL: https://github.com/apache/spark/pull/31296#issuecomment-766292712 > Also, when they can do arbitrary aggregation in forked process per partition, the aggregation is only bound to the micro-batch, even only bound to the single partition, which

[GitHub] [spark] viirya edited a comment on pull request #31296: [SPARK-34205][SQL][SS] Add pipe to Dataset to enable Streaming Dataset pipe

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viirya edited a comment on pull request #31296: URL: https://github.com/apache/spark/pull/31296#issuecomment-766291831 > I understand the functionality is lacking on SS. There's a workaround like foreachBatch -> toRDD -> pipe but streaming operations can't be added after calling pipe. So

[GitHub] [spark] viirya commented on pull request #31296: [SPARK-34205][SQL][SS] Add pipe to Dataset to enable Streaming Dataset pipe

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viirya commented on pull request #31296: URL: https://github.com/apache/spark/pull/31296#issuecomment-766291831 > I understand the functionality is lacking on SS. There's a workaround like foreachBatch -> toRDD -> pipe but streaming operations can't be added after calling pipe. So I'd

[GitHub] [spark] wangyum commented on a change in pull request #31303: [SPARK-34211][SQL][TESTS] Benchmark TPC-DS with 1GB scale factor

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wangyum commented on a change in pull request #31303: URL: https://github.com/apache/spark/pull/31303#discussion_r563236578 ## File path: .github/workflows/build_and_test.yml ## @@ -430,3 +430,38 @@ jobs: - name: Build with SBT run: | ./build/sbt -Pyarn

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[GitHub] [spark] HyukjinKwon commented on pull request #31218: [SPARK-34147][SQL][TEST] Keep table partitioning in TPCDSQueryBenchmak when CBO is enabled

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HyukjinKwon commented on pull request #31218: URL: https://github.com/apache/spark/pull/31218#issuecomment-766288411 @maropu can you take a quick look for doubly sure when you find some time? This is an automated message

[GitHub] [spark] HyukjinKwon commented on a change in pull request #31218: [SPARK-34147][SQL][TEST] Keep table partitioning in TPCDSQueryBenchmak when CBO is enabled

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HyukjinKwon commented on a change in pull request #31218: URL: https://github.com/apache/spark/pull/31218#discussion_r563234527 ## File path: sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/TPCDSQueryBenchmark.scala ## @@ -70,11 +67,13 @@ object

[GitHub] [spark] HyukjinKwon closed pull request #31243: [SPARK-34155][SQL][TEST] Add partition columns for TPCDS tables

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[GitHub] [spark] HyukjinKwon commented on a change in pull request #31271: [SPARK-34185][DOCS] Review and fix issues in API docs

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HyukjinKwon commented on a change in pull request #31271: URL: https://github.com/apache/spark/pull/31271#discussion_r563233910 ## File path: project/SparkBuild.scala ## @@ -910,7 +910,7 @@ object Unidoc {

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[GitHub] [spark] HyukjinKwon closed pull request #31300: [SPARK-34052][SQL][3.1] store SQL text for a temp view created using "CACHE TABLE .. AS SELECT ..."

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[GitHub] [spark] HyukjinKwon closed pull request #31290: [SPARK-33813][SQL][3.0] Fix the issue that JDBC source can't treat MS SQL Server's spatial types

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[GitHub] [spark] HyukjinKwon commented on pull request #31298: [SPARK-34193][CORE] TorrentBroadcast block manager decommissioning race fix

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HyukjinKwon commented on pull request #31298: URL: https://github.com/apache/spark/pull/31298#issuecomment-766285048 cc @Ngone51 who also works on decommissioning and torrent broadcast stuff. This is an automated message

[GitHub] [spark] HyukjinKwon commented on pull request #31300: [SPARK-34052][SQL][3.1] store SQL text for a temp view created using "CACHE TABLE .. AS SELECT ..."

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[GitHub] [spark] HyukjinKwon closed pull request #29178: [SPARK-32380][SQL] fixed spark3.0 access hive table while data in hbase problem

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[GitHub] [spark] HyukjinKwon closed pull request #31302: [SPARK-34210][SQL] After upgrading 3.0.1, Spark SQL access hive on HBase table access exception

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HyukjinKwon commented on pull request #31302: URL: https://github.com/apache/spark/pull/31302#issuecomment-766284757 Is this a duplicate of https://github.com/apache/spark/pull/29178 and https://github.com/apache/spark/pull/31147? I have the same question

[GitHub] [spark] HyukjinKwon closed pull request #31147: [SPARK-32380][SQL]fixed spark3.0 access hive table while data in hbase problem

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[GitHub] [spark] HeartSaVioR edited a comment on pull request #31296: [SPARK-34205][SQL][SS] Add pipe to Dataset to enable Streaming Dataset pipe

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HeartSaVioR edited a comment on pull request #31296: URL: https://github.com/apache/spark/pull/31296#issuecomment-766278704 Also, when they can do arbitrary aggregation in forked process per partition, the aggregation is only bound to the micro-batch, even only bound to the single

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HeartSaVioR edited a comment on pull request #31296: URL: https://github.com/apache/spark/pull/31296#issuecomment-766278704 Also, when they can do arbitrary aggregation in forked process per partition, the aggregation is only bound to the micro-batch, even only bound to the single

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HeartSaVioR commented on pull request #31296: URL: https://github.com/apache/spark/pull/31296#issuecomment-766278704 Also, when they can do arbitrary aggregation in forked process per partition, the aggregation is only bound to the micro-batch, even only bound to the single partition,

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HeartSaVioR commented on pull request #31296: URL: https://github.com/apache/spark/pull/31296#issuecomment-766276315 I understand the functionality is lacking on SS. There's a workaround like foreachBatch -> toRDD -> pipe but streaming operations can't be added after calling pipe. So I'd

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