[GitHub] [spark] SparkQA commented on issue #26915: [INFRA] Reverts commit 56dcd79 and c216ef1
SparkQA commented on issue #26915: [INFRA] Reverts commit 56dcd79 and c216ef1 URL: https://github.com/apache/spark/pull/26915#issuecomment-566350525 **[Test build #115419 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/115419/testReport)** for PR 26915 at commit [`d540e68`](https://github.com/apache/spark/commit/d540e68facff08b9f8eefba0070c232af1d3c8ed). This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] SparkQA commented on issue #26906: [SPARK-30066][SQL][FOLLOWUP] Remove size field for interval column cache
SparkQA commented on issue #26906: [SPARK-30066][SQL][FOLLOWUP] Remove size field for interval column cache URL: https://github.com/apache/spark/pull/26906#issuecomment-566350550 **[Test build #115420 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/115420/testReport)** for PR 26906 at commit [`11b7f71`](https://github.com/apache/spark/commit/11b7f718e53c17e9a7c2946bddcaf8b860562d31). This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] [spark] AmplabJenkins commented on issue #26906: [SPARK-30066][SQL][FOLLOWUP] Remove size field for interval column cache
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[GitHub] [spark] jiangxb1987 opened a new pull request #26916: [SPARK-25100][TEST][FOLLOWUP] Refactor test cases
jiangxb1987 opened a new pull request #26916: [SPARK-25100][TEST][FOLLOWUP] Refactor test cases URL: https://github.com/apache/spark/pull/26916 ### What changes were proposed in this pull request? Refactor test cases added by https://github.com/apache/spark/pull/26714, to improve code compactness. ### How was this patch tested? Tested locally. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] AmplabJenkins commented on issue #26915: [INFRA] Reverts commit 56dcd79 and c216ef1
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[GitHub] [spark] AmplabJenkins removed a comment on issue #26915: [INFRA] Reverts commit 56dcd79 and c216ef1
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[GitHub] [spark] wangyum commented on issue #26915: [INFRA] Reverts commit 56dcd79 and c216ef1
wangyum commented on issue #26915: [INFRA] Reverts commit 56dcd79 and c216ef1 URL: https://github.com/apache/spark/pull/26915#issuecomment-566350961 Sorry @srowen @HyukjinKwon @dongjoon-hyun @cloud-fan It should not add commits to master after https://github.com/apache/spark/pull/26879. Such as: [3.0.0-preview2-rc1](https://github.com/apache/spark/releases/tag/v3.0.0-preview2-rc1). But I forgot to check out the latest code. I'm very sorry about that. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] jiangxb1987 commented on a change in pull request #26916: [SPARK-25100][TEST][FOLLOWUP] Refactor test cases in `FileSuite` and `KryoSerializerSuite`
jiangxb1987 commented on a change in pull request #26916: [SPARK-25100][TEST][FOLLOWUP] Refactor test cases in `FileSuite` and `KryoSerializerSuite` URL: https://github.com/apache/spark/pull/26916#discussion_r358569006 ## File path: core/src/test/scala/org/apache/spark/FileSuite.scala ## @@ -702,32 +702,39 @@ class FileSuite extends SparkFunSuite with LocalSparkContext { assert(collectRDDAndDeleteFileBeforeCompute(true).isEmpty) } - test("SPARK-25100: Using KryoSerializer and" + - "setting registrationRequired true can lead job failed") { -val inputFile = new File(tempDir, "/input").getAbsolutePath -val textFileOutputDir = new File(tempDir, "/out1").getAbsolutePath -val dataSetDir = new File(tempDir, "/out2").getAbsolutePath - -Utils.tryWithResource(new PrintWriter(new File(inputFile))) { writer => - for (i <- 1 to 100) { + test("SPARK-25100: Support commit tasks when Kyro registration is required") { +// Prepare the input file +val inputFilePath = new File(tempDir, "/input").getAbsolutePath +Utils.tryWithResource(new PrintWriter(new File(inputFilePath))) { writer => + for (i <- 1 to 3) { writer.print(i) writer.write('\n') } } -val conf = new SparkConf(false).setMaster("local"). - set("spark.kryo.registrationRequired", "true").setAppName("test") -conf.set("spark.serializer", classOf[KryoSerializer].getName) +// Start a new SparkContext +val conf = new SparkConf(false) + .setMaster("local") + .setAppName("test") + .set("spark.kryo.registrationRequired", "true") + .set("spark.serializer", classOf[KryoSerializer].getName) +sc = new SparkContext(conf) + +// Prepare the input RDD +val pairRDD = sc.textFile(inputFilePath).map(x => (x, x)) +// Test saveAsTextFile() +val outputFilePath1 = new File(tempDir, "/out1").getAbsolutePath +pairRDD.saveAsTextFile(outputFilePath1) +assert(sc.textFile(outputFilePath1).collect() === Array("(1,1)", "(2,2)", "(3,3)")) Review comment: We should ensure the content in the output file is correct. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] AmplabJenkins removed a comment on issue #26915: [INFRA] Reverts commit 56dcd79 and c216ef1
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[GitHub] [spark] AmplabJenkins removed a comment on issue #26906: [SPARK-30066][SQL][FOLLOWUP] Remove size field for interval column cache
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[GitHub] [spark] jiangxb1987 commented on a change in pull request #26916: [SPARK-25100][TEST][FOLLOWUP] Refactor test cases in `FileSuite` and `KryoSerializerSuite`
jiangxb1987 commented on a change in pull request #26916: [SPARK-25100][TEST][FOLLOWUP] Refactor test cases in `FileSuite` and `KryoSerializerSuite` URL: https://github.com/apache/spark/pull/26916#discussion_r358569339 ## File path: core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala ## @@ -363,16 +363,14 @@ class KryoSerializerSuite extends SparkFunSuite with SharedSparkContext { val conf = new SparkConf(false) conf.set(KRYO_REGISTRATION_REQUIRED, true) -val ser = new KryoSerializer(conf).newInstance() -// In HadoopMapReduceCommitProtocol#commitTask -val addedAbsPathFiles: mutable.Map[String, String] = mutable.Map() -addedAbsPathFiles.put("test1", "test1") -addedAbsPathFiles.put("test2", "test2") +// HadoopMapReduceCommitProtocol.commitTask() returns a TaskCommitMessage containing a complex +// structure. -val partitionPaths: mutable.Set[String] = mutable.Set() -partitionPaths.add("test3") +val ser = new KryoSerializer(conf).newInstance() +val addedAbsPathFiles = Map("test1" -> "test1", "test2" -> "test2") +val partitionPaths = Set("test3") -val taskCommitMessage1 = new TaskCommitMessage(addedAbsPathFiles.toMap -> partitionPaths.toSet) +val taskCommitMessage1 = new TaskCommitMessage(addedAbsPathFiles -> partitionPaths) Review comment: We only need to test the object returned by `HadoopMapReduceCommitProtocol.commitTask()`, thus no need to create a mutable map/set then convert it. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] HyukjinKwon commented on a change in pull request #26733: [SPARK-30097][SS][SQL] - Add suport for core sinks in writeStream
HyukjinKwon commented on a change in pull request #26733: [SPARK-30097][SS][SQL] - Add suport for core sinks in writeStream URL: https://github.com/apache/spark/pull/26733#discussion_r358569445 ## File path: sql/core/src/main/scala/org/apache/spark/sql/streaming/DataStreamWriter.scala ## @@ -132,6 +132,30 @@ final class DataStreamWriter[T] private[sql](ds: Dataset[T]) { this } + def parquet(path: String): StreamingQuery = { +format("parquet") + .option("path", path) + .start() + } + + def json(path: String): StreamingQuery = { +format("json") + .option("path", path) + .start() + } + + def csv(path: String): StreamingQuery = { +format("csv") + .option("path", path) + .start() + } + + def text(path: String): StreamingQuery = { +format("text") + .option("path", path) + .start() + } Review comment: Yesh This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] HyukjinKwon commented on a change in pull request #26733: [SPARK-30097][SS][SQL] - Add suport for core sinks in writeStream
HyukjinKwon commented on a change in pull request #26733: [SPARK-30097][SS][SQL] - Add suport for core sinks in writeStream URL: https://github.com/apache/spark/pull/26733#discussion_r358569519 ## File path: sql/core/src/main/scala/org/apache/spark/sql/streaming/DataStreamWriter.scala ## @@ -132,6 +132,30 @@ final class DataStreamWriter[T] private[sql](ds: Dataset[T]) { this } + def parquet(path: String): StreamingQuery = { +format("parquet") + .option("path", path) + .start() + } + + def json(path: String): StreamingQuery = { +format("json") + .option("path", path) + .start() + } + + def csv(path: String): StreamingQuery = { +format("csv") + .option("path", path) + .start() + } + + def text(path: String): StreamingQuery = { +format("text") + .option("path", path) + .start() + } Review comment: Yeah, thanks for closing. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] jiangxb1987 commented on issue #26916: [SPARK-25100][TEST][FOLLOWUP] Refactor test cases in `FileSuite` and `KryoSerializerSuite`
jiangxb1987 commented on issue #26916: [SPARK-25100][TEST][FOLLOWUP] Refactor test cases in `FileSuite` and `KryoSerializerSuite` URL: https://github.com/apache/spark/pull/26916#issuecomment-566351638 cc @deshanxiao @HeartSaVioR @dongjoon-hyun Please take a look when you have time, thanks! This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] HyukjinKwon commented on a change in pull request #26733: [SPARK-30097][SS][SQL] - Add suport for core sinks in writeStream
HyukjinKwon commented on a change in pull request #26733: [SPARK-30097][SS][SQL] - Add suport for core sinks in writeStream URL: https://github.com/apache/spark/pull/26733#discussion_r358569445 ## File path: sql/core/src/main/scala/org/apache/spark/sql/streaming/DataStreamWriter.scala ## @@ -132,6 +132,30 @@ final class DataStreamWriter[T] private[sql](ds: Dataset[T]) { this } + def parquet(path: String): StreamingQuery = { +format("parquet") + .option("path", path) + .start() + } + + def json(path: String): StreamingQuery = { +format("json") + .option("path", path) + .start() + } + + def csv(path: String): StreamingQuery = { +format("csv") + .option("path", path) + .start() + } + + def text(path: String): StreamingQuery = { +format("text") + .option("path", path) + .start() + } Review comment: Yesh This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] SparkQA commented on issue #26916: [SPARK-25100][TEST][FOLLOWUP] Refactor test cases in `FileSuite` and `KryoSerializerSuite`
SparkQA commented on issue #26916: [SPARK-25100][TEST][FOLLOWUP] Refactor test cases in `FileSuite` and `KryoSerializerSuite` URL: https://github.com/apache/spark/pull/26916#issuecomment-566352458 **[Test build #115421 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/115421/testReport)** for PR 26916 at commit [`559c45c`](https://github.com/apache/spark/commit/559c45c697ff7b207275e6549c6b8f6396a8e32b). This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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AmplabJenkins commented on issue #26916: [SPARK-25100][TEST][FOLLOWUP] Refactor test cases in `FileSuite` and `KryoSerializerSuite` URL: https://github.com/apache/spark/pull/26916#issuecomment-566352757 Test PASSed. Refer to this link for build results (access rights to CI server needed): https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder-K8s/20224/ Test PASSed. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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AmplabJenkins removed a comment on issue #26916: [SPARK-25100][TEST][FOLLOWUP] Refactor test cases in `FileSuite` and `KryoSerializerSuite` URL: https://github.com/apache/spark/pull/26916#issuecomment-566352750 Merged build finished. Test PASSed. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] [spark] xuanyuanking opened a new pull request #26917: [SPARK-30278][SQL][DOC] Update Spark SQL document menu for new changes
xuanyuanking opened a new pull request #26917: [SPARK-30278][SQL][DOC] Update Spark SQL document menu for new changes URL: https://github.com/apache/spark/pull/26917 ### What changes were proposed in this pull request? Update the Spark SQL document menu and join strategy hints. ### Why are the changes needed? - Several new changes in the Spark SQL document didn't change the menu-sql.yaml correspondingly. - Update the demo code for join strategy hints. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Document change only. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] xuanyuanking commented on issue #26917: [SPARK-30278][SQL][DOC] Update Spark SQL document menu for new changes
xuanyuanking commented on issue #26917: [SPARK-30278][SQL][DOC] Update Spark SQL document menu for new changes URL: https://github.com/apache/spark/pull/26917#issuecomment-566355307 cc @cloud-fan @gatorsmile This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] [spark] dongjoon-hyun commented on issue #26915: [INFRA] Reverts commit 56dcd79 and c216ef1
dongjoon-hyun commented on issue #26915: [INFRA] Reverts commit 56dcd79 and c216ef1 URL: https://github.com/apache/spark/pull/26915#issuecomment-566356920 You can merge this, @wangyum . This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] SparkQA commented on issue #26838: [SPARK-30144][ML][PySpark] Make MultilayerPerceptronClassificationModel extend MultilayerPerceptronParams
SparkQA commented on issue #26838: [SPARK-30144][ML][PySpark] Make MultilayerPerceptronClassificationModel extend MultilayerPerceptronParams URL: https://github.com/apache/spark/pull/26838#issuecomment-566357719 **[Test build #115423 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/115423/testReport)** for PR 26838 at commit [`7a98ffb`](https://github.com/apache/spark/commit/7a98ffbc780770bfb6454ea72a597b1c0fb168d1). This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] wangyum closed pull request #26915: [INFRA] Reverts commit 56dcd79 and c216ef1
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[GitHub] [spark] wangyum commented on issue #26915: [INFRA] Reverts commit 56dcd79 and c216ef1
wangyum commented on issue #26915: [INFRA] Reverts commit 56dcd79 and c216ef1 URL: https://github.com/apache/spark/pull/26915#issuecomment-566357813 Thank you all. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] [spark] dongjoon-hyun commented on issue #26916: [SPARK-25100][TEST][FOLLOWUP] Refactor test cases in `FileSuite` and `KryoSerializerSuite`
dongjoon-hyun commented on issue #26916: [SPARK-25100][TEST][FOLLOWUP] Refactor test cases in `FileSuite` and `KryoSerializerSuite` URL: https://github.com/apache/spark/pull/26916#issuecomment-566358336 Thank you for making a followup and pinging me, @jiangxb1987 ! This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] SparkQA commented on issue #26917: [SPARK-30278][SQL][DOC] Update Spark SQL document menu for new changes
SparkQA commented on issue #26917: [SPARK-30278][SQL][DOC] Update Spark SQL document menu for new changes URL: https://github.com/apache/spark/pull/26917#issuecomment-566358598 **[Test build #115422 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/115422/testReport)** for PR 26917 at commit [`7222fa3`](https://github.com/apache/spark/commit/7222fa3c75d829003068da1b51fe586b31d3e57b). * This patch passes all tests. * This patch merges cleanly. * This patch adds no public classes. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] [spark] srowen commented on a change in pull request #26905: [SPARK-30266][SQL] Avoid overflow and match error in ApproximatePercentile
srowen commented on a change in pull request #26905: [SPARK-30266][SQL] Avoid overflow and match error in ApproximatePercentile URL: https://github.com/apache/spark/pull/26905#discussion_r358578200 ## File path: sql/core/src/test/scala/org/apache/spark/sql/ApproximatePercentileQuerySuite.scala ## @@ -182,7 +182,7 @@ class ApproximatePercentileQuerySuite extends QueryTest with SharedSparkSession spark.sql( s"""SELECT | key, - | percentile_approx(null, 0.5) + | percentile_approx(cast(null as int), 0.5) Review comment: It doesn't make much sense, yeah. I am not sure whether we generally return null or an error in a case like this. Following Hive seems like a reasonable guide. It could be OK to change behavior if there's a release note attached to the JIRA, and if we think it's more bug fix than anything This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] cloud-fan closed pull request #26894: [SPARK-30094][SQL] Apply current namespace for the single-part table name
cloud-fan closed pull request #26894: [SPARK-30094][SQL] Apply current namespace for the single-part table name URL: https://github.com/apache/spark/pull/26894 This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] cloud-fan commented on issue #26894: [SPARK-30094][SQL] Apply current namespace for the single-part table name
cloud-fan commented on issue #26894: [SPARK-30094][SQL] Apply current namespace for the single-part table name URL: https://github.com/apache/spark/pull/26894#issuecomment-566361014 thanks, merging to master! This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] yaooqinn commented on a change in pull request #26905: [SPARK-30266][SQL] Avoid overflow and match error in ApproximatePercentile
yaooqinn commented on a change in pull request #26905: [SPARK-30266][SQL] Avoid overflow and match error in ApproximatePercentile URL: https://github.com/apache/spark/pull/26905#discussion_r358579502 ## File path: sql/core/src/test/scala/org/apache/spark/sql/ApproximatePercentileQuerySuite.scala ## @@ -182,7 +182,7 @@ class ApproximatePercentileQuerySuite extends QueryTest with SharedSparkSession spark.sql( s"""SELECT | key, - | percentile_approx(null, 0.5) + | percentile_approx(cast(null as int), 0.5) Review comment: Agreed. I'll updated this change in the PR description. And I guess the author's original purpose of these tests here are to verify the null handling of the non-null types, not `NullType` This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] cloud-fan commented on a change in pull request #26905: [SPARK-30266][SQL] Avoid overflow and match error in ApproximatePercentile
cloud-fan commented on a change in pull request #26905: [SPARK-30266][SQL] Avoid overflow and match error in ApproximatePercentile URL: https://github.com/apache/spark/pull/26905#discussion_r358580862 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala ## @@ -83,32 +83,37 @@ case class ApproximatePercentile( } // Mark as lazy so that accuracyExpression is not evaluated during tree transformation. - private lazy val accuracy: Int = accuracyExpression.eval().asInstanceOf[Int] - - override def inputTypes: Seq[AbstractDataType] = { -// Support NumericType, DateType and TimestampType since their internal types are all numeric, -// and can be easily cast to double for processing. -Seq(TypeCollection(NumericType, DateType, TimestampType), - TypeCollection(DoubleType, ArrayType(DoubleType)), IntegerType) - } + private lazy val accuracy: Long = accuracyExpression.eval().asInstanceOf[Number].longValue() // Mark as lazy so that percentageExpression is not evaluated during tree transformation. private lazy val (returnPercentileArray: Boolean, percentages: Array[Double]) = -percentageExpression.eval() match { - // Rule ImplicitTypeCasts can cast other numeric types to double - case num: Double => (false, Array(num)) - case arrayData: ArrayData => (true, arrayData.toDoubleArray()) +percentageExpression.dataType match { + case DoubleType => (false, Array(percentageExpression.eval().asInstanceOf[Double])) + case _: NumericType => Review comment: Why would it overflow? The type coercion should cast `accuracyExpression` to int type. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] yaooqinn commented on a change in pull request #26905: [SPARK-30266][SQL] Avoid overflow and match error in ApproximatePercentile
yaooqinn commented on a change in pull request #26905: [SPARK-30266][SQL] Avoid overflow and match error in ApproximatePercentile URL: https://github.com/apache/spark/pull/26905#discussion_r358581552 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala ## @@ -83,32 +83,37 @@ case class ApproximatePercentile( } // Mark as lazy so that accuracyExpression is not evaluated during tree transformation. - private lazy val accuracy: Int = accuracyExpression.eval().asInstanceOf[Int] - - override def inputTypes: Seq[AbstractDataType] = { -// Support NumericType, DateType and TimestampType since their internal types are all numeric, -// and can be easily cast to double for processing. -Seq(TypeCollection(NumericType, DateType, TimestampType), - TypeCollection(DoubleType, ArrayType(DoubleType)), IntegerType) - } + private lazy val accuracy: Long = accuracyExpression.eval().asInstanceOf[Number].longValue() // Mark as lazy so that percentageExpression is not evaluated during tree transformation. private lazy val (returnPercentileArray: Boolean, percentages: Array[Double]) = -percentageExpression.eval() match { - // Rule ImplicitTypeCasts can cast other numeric types to double - case num: Double => (false, Array(num)) - case arrayData: ArrayData => (true, arrayData.toDoubleArray()) +percentageExpression.dataType match { + case DoubleType => (false, Array(percentageExpression.eval().asInstanceOf[Double])) + case _: NumericType => Review comment: If we specify a accuracy value greater than Int.MaxValue This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] HeartSaVioR commented on issue #26723: [SPARK-27523][CORE] - Resolve scheme-less event log directory relative to default filesystem
HeartSaVioR commented on issue #26723: [SPARK-27523][CORE] - Resolve scheme-less event log directory relative to default filesystem URL: https://github.com/apache/spark/pull/26723#issuecomment-566364451 What about explicitly documenting this behavior in configuration.md? I'm now a bit confused which configurations use which one for schema-less directory configuration, but it might worth to mention when we won't follow default filesystem. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] SparkQA commented on issue #26910: [SPARK-30154][ML] PySpark UDF to convert MLlib vectors to dense arrays
SparkQA commented on issue #26910: [SPARK-30154][ML] PySpark UDF to convert MLlib vectors to dense arrays URL: https://github.com/apache/spark/pull/26910#issuecomment-566364589 **[Test build #115424 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/115424/testReport)** for PR 26910 at commit [`e2bb6c0`](https://github.com/apache/spark/commit/e2bb6c098198f611c3b74289cb53be9a1e187de1). This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] AmplabJenkins commented on issue #26910: [SPARK-30154][ML] PySpark UDF to convert MLlib vectors to dense arrays
AmplabJenkins commented on issue #26910: [SPARK-30154][ML] PySpark UDF to convert MLlib vectors to dense arrays URL: https://github.com/apache/spark/pull/26910#issuecomment-566364920 Test PASSed. Refer to this link for build results (access rights to CI server needed): https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder-K8s/20227/ Test PASSed. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] yaooqinn commented on a change in pull request #26905: [SPARK-30266][SQL] Avoid overflow and match error in ApproximatePercentile
yaooqinn commented on a change in pull request #26905: [SPARK-30266][SQL] Avoid overflow and match error in ApproximatePercentile URL: https://github.com/apache/spark/pull/26905#discussion_r358582153 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala ## @@ -83,32 +83,37 @@ case class ApproximatePercentile( } // Mark as lazy so that accuracyExpression is not evaluated during tree transformation. - private lazy val accuracy: Int = accuracyExpression.eval().asInstanceOf[Int] - - override def inputTypes: Seq[AbstractDataType] = { -// Support NumericType, DateType and TimestampType since their internal types are all numeric, -// and can be easily cast to double for processing. -Seq(TypeCollection(NumericType, DateType, TimestampType), - TypeCollection(DoubleType, ArrayType(DoubleType)), IntegerType) - } + private lazy val accuracy: Long = accuracyExpression.eval().asInstanceOf[Number].longValue() // Mark as lazy so that percentageExpression is not evaluated during tree transformation. private lazy val (returnPercentileArray: Boolean, percentages: Array[Double]) = -percentageExpression.eval() match { - // Rule ImplicitTypeCasts can cast other numeric types to double - case num: Double => (false, Array(num)) - case arrayData: ArrayData => (true, arrayData.toDoubleArray()) +percentageExpression.dataType match { + case DoubleType => (false, Array(percentageExpression.eval().asInstanceOf[Double])) + case _: NumericType => Review comment: I don't mean a overflow exception here, just the value here is not right. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] AmplabJenkins commented on issue #26910: [SPARK-30154][ML] PySpark UDF to convert MLlib vectors to dense arrays
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[GitHub] [spark] maropu opened a new pull request #26918: [SPARK-30279][SQL] Support 32 or more grouping attributes for GROUPING_ID
maropu opened a new pull request #26918: [SPARK-30279][SQL] Support 32 or more grouping attributes for GROUPING_ID URL: https://github.com/apache/spark/pull/26918 ### What changes were proposed in this pull request? This pr intends to support 32 or more grouping attributes for GROUPING_ID. In the current master, an integer overflow can occur to compute grouping IDs; https://github.com/apache/spark/blob/e75d9afb2f282ce79c9fd8bce031287739326a4f/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala#L613 For example, the query below generates wrong grouping IDs in the master; ``` scala> val numCols = 32 // or, 31 scala> val cols = (0 until numCols).map { i => s"c$i" } scala> sql(s"create table test_$numCols (${cols.map(c => s"$c int").mkString(",")}, v int) using parquet") scala> val insertVals = (0 until numCols).map { _ => 1 }.mkString(",") scala> sql(s"insert into test_$numCols values ($insertVals,3)") scala> sql(s"select grouping_id(), sum(v) from test_$numCols group by grouping sets ((${cols.mkString(",")}), (${cols.init.mkString(",")}))").show(10, false) scala> sql(s"drop table test_$numCols") // numCols = 32 +-+--+ |grouping_id()|sum(v)| +-+--+ |0|3 | |0|3 | // Wrong Grouping ID +-+--+ // numCols = 31 +-+--+ |grouping_id()|sum(v)| +-+--+ |0|3 | |1|3 | +-+--+ ``` To fix this issue, this pr generates string grouping IDs instead of integer IDs for that case. ### Why are the changes needed? To support more cases in `GROUPING_ID`. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Added unit tests. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] SparkQA commented on issue #26918: [SPARK-30279][SQL] Support 32 or more grouping attributes for GROUPING_ID
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[GitHub] [spark] AmplabJenkins commented on issue #26918: [SPARK-30279][SQL] Support 32 or more grouping attributes for GROUPING_ID
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[GitHub] [spark] JkSelf commented on a change in pull request #26434: [SPARK-29544] [SQL] optimize skewed partition based on data size
JkSelf commented on a change in pull request #26434: [SPARK-29544] [SQL] optimize skewed partition based on data size URL: https://github.com/apache/spark/pull/26434#discussion_r358583953 ## File path: sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/ReduceNumShufflePartitions.scala ## @@ -145,39 +156,36 @@ case class ReduceNumShufflePartitions(conf: SQLConf) extends Rule[SparkPlan] { distinctNumPreShufflePartitions.length == 1, "There should be only one distinct value of the number pre-shuffle partitions " + "among registered Exchange operator.") -val numPreShufflePartitions = distinctNumPreShufflePartitions.head val partitionStartIndices = ArrayBuffer[Int]() -// The first element of partitionStartIndices is always 0. -partitionStartIndices += 0 - -var postShuffleInputSize = 0L - -var i = 0 -while (i < numPreShufflePartitions) { - // We calculate the total size of ith pre-shuffle partitions from all pre-shuffle stages. - // Then, we add the total size to postShuffleInputSize. - var nextShuffleInputSize = 0L - var j = 0 - while (j < mapOutputStatistics.length) { -nextShuffleInputSize += mapOutputStatistics(j).bytesByPartitionId(i) -j += 1 - } - - // If including the nextShuffleInputSize would exceed the target partition size, then start a - // new partition. - if (i > 0 && postShuffleInputSize + nextShuffleInputSize > targetPostShuffleInputSize) { -partitionStartIndices += i -// reset postShuffleInputSize. -postShuffleInputSize = nextShuffleInputSize - } else { -postShuffleInputSize += nextShuffleInputSize - } - - i += 1 +val partitionEndIndices = ArrayBuffer[Int]() +val numPartitions = mapOutputStatistics.map(stats => stats.bytesByPartitionId.length).head +val includedPartitions = (0 until numPartitions).filter(!excludedPartitions.contains(_)) +val firstStartIndex = includedPartitions(0) +partitionStartIndices += firstStartIndex +var postShuffleInputSize = mapOutputStatistics.map(_.bytesByPartitionId(firstStartIndex)).sum +var i = firstStartIndex +includedPartitions.filter(_ != firstStartIndex).foreach { + nextPartitionIndices => +var nextShuffleInputSize = + mapOutputStatistics.map(_.bytesByPartitionId(nextPartitionIndices)).sum +// If nextPartitionIndices is skewed and omitted, or including +// the nextShuffleInputSize would exceed the target partition size, +// then start a new partition. +if (nextPartitionIndices != i + 1 || Review comment: The `nextPartitionIndices ` is excluded. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] JkSelf commented on a change in pull request #26434: [SPARK-29544] [SQL] optimize skewed partition based on data size
JkSelf commented on a change in pull request #26434: [SPARK-29544] [SQL] optimize skewed partition based on data size URL: https://github.com/apache/spark/pull/26434#discussion_r358584117 ## File path: sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/OptimizeSkewedPartitions.scala ## @@ -0,0 +1,313 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + *http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.execution.adaptive + +import scala.collection.mutable +import scala.collection.mutable.ArrayBuffer +import scala.concurrent.duration.Duration + +import org.apache.spark.{MapOutputStatistics, MapOutputTrackerMaster, SparkEnv} +import org.apache.spark.rdd.RDD +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.catalyst.expressions.Attribute +import org.apache.spark.sql.catalyst.plans._ +import org.apache.spark.sql.catalyst.plans.physical.{Partitioning, UnknownPartitioning} +import org.apache.spark.sql.catalyst.rules.Rule +import org.apache.spark.sql.execution._ +import org.apache.spark.sql.execution.joins.SortMergeJoinExec +import org.apache.spark.sql.internal.SQLConf +import org.apache.spark.util.ThreadUtils + +case class OptimizeSkewedPartitions(conf: SQLConf) extends Rule[SparkPlan] { + + private val supportedJoinTypes = +Inner :: Cross :: LeftSemi :: LeftAnti :: LeftOuter :: RightOuter :: Nil + + /** + * A partition is considered as a skewed partition if its size is larger than the median + * partition size * spark.sql.adaptive.skewedPartitionFactor and also larger than + * spark.sql.adaptive.skewedPartitionSizeThreshold. + */ + private def isSkewed( + stats: MapOutputStatistics, + partitionId: Int, + medianSize: Long): Boolean = { +val size = stats.bytesByPartitionId(partitionId) +size > medianSize * conf.getConf(SQLConf.ADAPTIVE_EXECUTION_SKEWED_PARTITION_FACTOR) && + size > conf.getConf(SQLConf.ADAPTIVE_EXECUTION_SKEWED_PARTITION_SIZE_THRESHOLD) + } + + private def medianSize(stats: MapOutputStatistics): Long = { +val numPartitions = stats.bytesByPartitionId.length +val bytes = stats.bytesByPartitionId.sorted +if (bytes(numPartitions / 2) > 0) bytes(numPartitions / 2) else 1 + } + + /** + * Get all the map data size for specific reduce partitionId. + */ + def getMapSizeForSpecificPartition(partitionId: Int, shuffleId: Int): Array[Long] = { +val mapOutputTracker = SparkEnv.get.mapOutputTracker.asInstanceOf[MapOutputTrackerMaster] +mapOutputTracker.shuffleStatuses.get(shuffleId). + get.mapStatuses.map{_.getSizeForBlock(partitionId)} + } + + /** + * Split the partition into the number of mappers. Each split read data from each mapper. + */ + private def estimateMapStartIndices( + stage: QueryStageExec, + partitionId: Int, + medianSize: Long): Array[Int] = { +val dependency = ShuffleQueryStageExec.getShuffleStage(stage).plan.shuffleDependency +val numMappers = dependency.rdd.partitions.length +// TODO: split the partition based on the size +(0 until numMappers).toArray + } + + private def getStatistics(queryStage: QueryStageExec): MapOutputStatistics = { +val shuffleStage = ShuffleQueryStageExec.getShuffleStage(queryStage) +val metrics = shuffleStage.plan.mapOutputStatisticsFuture +assert(metrics.isCompleted, + "ShuffleQueryStageExec should already be ready when executing OptimizeSkewedPartitions rule") +ThreadUtils.awaitResult(metrics, Duration.Zero) + } + + /** + * Base optimization support check: the join type is supported. + * Note that for some join types(like left outer), whether a certain partition can be optimized + * also depends on the filed isSkewAndSupportsSplit. + */ + private def supportOptimization( + joinType: JoinType, + leftStage: QueryStageExec, + rightStage: QueryStageExec): Boolean = { +val joinTypeSupported = supportedJoinTypes.contains(joinType) +val shuffleStageCheck = ShuffleQueryStageExec.isShuffleQueryStageExec(leftStage) && + ShuffleQueryStageExec.isShuffleQueryStageExec(rightStage) +joinTypeSupported && shuffleStageCheck + } + + private def supportSplitOnLeftPartition(joinType: JoinType)
[GitHub] [spark] SparkQA commented on issue #26416: [SPARK-29779][CORE] Compact old event log files and cleanup
SparkQA commented on issue #26416: [SPARK-29779][CORE] Compact old event log files and cleanup URL: https://github.com/apache/spark/pull/26416#issuecomment-566367616 **[Test build #115414 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/115414/testReport)** for PR 26416 at commit [`23ce9d7`](https://github.com/apache/spark/commit/23ce9d7e8d47205d8bc6f6a8a050965aa00229d8). * This patch passes all tests. * This patch merges cleanly. * This patch adds the following public classes _(experimental)_: * ` case class FilterStatistic(` * `class EventLogFileCompactor(` * `class FilteredEventLogFileRewriter(` * `class CompactedEventLogFileWriter(` This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] [spark] WangGuangxin commented on a change in pull request #26899: [SPARK-28332][SQL] Reserve init value -1 only when do min max statistics in SQLMetrics
WangGuangxin commented on a change in pull request #26899: [SPARK-28332][SQL] Reserve init value -1 only when do min max statistics in SQLMetrics URL: https://github.com/apache/spark/pull/26899#discussion_r358586175 ## File path: sql/core/src/main/scala/org/apache/spark/sql/execution/metric/SQLMetrics.scala ## @@ -67,7 +67,9 @@ class SQLMetric(val metricType: String, initValue: Long = 0L) extends Accumulato def +=(v: Long): Unit = _value += v - override def value: Long = _value + def getRawValue(): Long = _value + + override def value: Long = Math.max(_value, 0) Review comment: What I want to do here is when we want to distinguish an uninitialized metric by -1, then we can use `SQLMetric.getRawValue`(It's the same with what current SQLMetric does without this PR). Otherwise use `SQLMetrics.value` to make sure it returns at least 0 (It's the same with initializing SQLMetric to 0). It's a bit tricky. `SQLMetric.getRawValue` was called in `SQLAppStatusListener.onTaskEnd` and `SQLMetrics.postDriverMetricUpdates`. The metric values in these two places eventually go to `LiveStageMetrics` used by `SQLAppStatusListener.aggregateMetrics` and then aggregated in `SQLMetrics.stringValue`. If a SQLMetric is initialized by -1 and it was not got updated in executors, then this metric value is -1 and can be filtered by logic in `SQLMetrics.stringValue`. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] SparkQA commented on issue #26914: [SPARK-30274][Core] Avoid BytesToBytesMap lookup hang forever when holding keys reaching max capacity
SparkQA commented on issue #26914: [SPARK-30274][Core] Avoid BytesToBytesMap lookup hang forever when holding keys reaching max capacity URL: https://github.com/apache/spark/pull/26914#issuecomment-566371745 **[Test build #115418 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/115418/testReport)** for PR 26914 at commit [`d5a1ec2`](https://github.com/apache/spark/commit/d5a1ec2c78f520792c580a3174d13aace59c7fb2). * This patch passes all tests. * This patch merges cleanly. * This patch adds no public classes. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] SparkQA removed a comment on issue #26914: [SPARK-30274][Core] Avoid BytesToBytesMap lookup hang forever when holding keys reaching max capacity
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[GitHub] [spark] SparkQA commented on issue #26416: [SPARK-29779][CORE] Compact old event log files and cleanup
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[GitHub] [spark] attilapiros commented on a change in pull request #26869: [SPARK-30235][CORE] Switching off host local disk reading of shuffle blocks in case of useOldFetchProtocol
attilapiros commented on a change in pull request #26869: [SPARK-30235][CORE] Switching off host local disk reading of shuffle blocks in case of useOldFetchProtocol URL: https://github.com/apache/spark/pull/26869#discussion_r358589382 ## File path: core/src/main/scala/org/apache/spark/internal/config/package.scala ## @@ -1097,9 +1097,9 @@ package object config { private[spark] val SHUFFLE_HOST_LOCAL_DISK_READING_ENABLED = ConfigBuilder("spark.shuffle.readHostLocalDisk.enabled") - .doc("If enabled, shuffle blocks requested from those block managers which are running on " + -"the same host are read from the disk directly instead of being fetched as remote blocks " + -"over the network.") + .doc("If enabled (and `spark.shuffle.useOldFetchProtocol` is disabled), shuffle blocks " + Review comment: Transforming the first part to string interpolation has not been forgotten. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] [spark] cloud-fan closed pull request #26831: [SPARK-30201][SQL] HiveOutputWriter standardOI should use ObjectInspectorCopyOption.DEFAULT
cloud-fan closed pull request #26831: [SPARK-30201][SQL] HiveOutputWriter standardOI should use ObjectInspectorCopyOption.DEFAULT URL: https://github.com/apache/spark/pull/26831 This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] [spark] cloud-fan commented on issue #26831: [SPARK-30201][SQL] HiveOutputWriter standardOI should use ObjectInspectorCopyOption.DEFAULT
cloud-fan commented on issue #26831: [SPARK-30201][SQL] HiveOutputWriter standardOI should use ObjectInspectorCopyOption.DEFAULT URL: https://github.com/apache/spark/pull/26831#issuecomment-566373038 thanks, merging to master! This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] attilapiros commented on a change in pull request #26869: [SPARK-30235][CORE] Switching off host local disk reading of shuffle blocks in case of useOldFetchProtocol
attilapiros commented on a change in pull request #26869: [SPARK-30235][CORE] Switching off host local disk reading of shuffle blocks in case of useOldFetchProtocol URL: https://github.com/apache/spark/pull/26869#discussion_r358589705 ## File path: docs/sql-migration-guide.md ## @@ -97,7 +97,7 @@ license: | - Since Spark 3.0, when Avro files are written with user provided non-nullable schema, even the catalyst schema is nullable, Spark is still able to write the files. However, Spark will throw runtime NPE if any of the records contains null. - - Since Spark 3.0, we use a new protocol for fetching shuffle blocks, for external shuffle service users, we need to upgrade the server correspondingly. Otherwise, we'll get the error message `UnsupportedOperationException: Unexpected message: FetchShuffleBlocks`. If it is hard to upgrade the shuffle service right now, you can still use the old protocol by setting `spark.shuffle.useOldFetchProtocol` to `true`. + - Since Spark 3.0, we use a new protocol for fetching shuffle blocks, for external shuffle service users, we need to upgrade the server correspondingly. Otherwise, we'll get the error message `IllegalArgumentException: Unexpected message type: `. If it is hard to upgrade the shuffle service right now, you can still use the old protocol by setting `spark.shuffle.useOldFetchProtocol` to `true`. Review comment: I have moved it to core migration guide and removed the "Since Spark 3.0, " as having subsections with the Spark versions. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] [spark] cloud-fan commented on a change in pull request #26905: [SPARK-30266][SQL] Avoid overflow and match error in ApproximatePercentile
cloud-fan commented on a change in pull request #26905: [SPARK-30266][SQL] Avoid overflow and match error in ApproximatePercentile URL: https://github.com/apache/spark/pull/26905#discussion_r358590272 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala ## @@ -83,32 +83,37 @@ case class ApproximatePercentile( } // Mark as lazy so that accuracyExpression is not evaluated during tree transformation. - private lazy val accuracy: Int = accuracyExpression.eval().asInstanceOf[Int] - - override def inputTypes: Seq[AbstractDataType] = { -// Support NumericType, DateType and TimestampType since their internal types are all numeric, -// and can be easily cast to double for processing. -Seq(TypeCollection(NumericType, DateType, TimestampType), - TypeCollection(DoubleType, ArrayType(DoubleType)), IntegerType) - } + private lazy val accuracy: Long = accuracyExpression.eval().asInstanceOf[Number].longValue() // Mark as lazy so that percentageExpression is not evaluated during tree transformation. private lazy val (returnPercentileArray: Boolean, percentages: Array[Double]) = -percentageExpression.eval() match { - // Rule ImplicitTypeCasts can cast other numeric types to double - case num: Double => (false, Array(num)) - case arrayData: ArrayData => (true, arrayData.toDoubleArray()) +percentageExpression.dataType match { + case DoubleType => (false, Array(percentageExpression.eval().asInstanceOf[Double])) + case _: NumericType => Review comment: shall we simply update `inputTypes` to replace `IntegerType` with `LongType`? This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] SparkQA commented on issue #26869: [SPARK-30235][CORE] Switching off host local disk reading of shuffle blocks in case of useOldFetchProtocol
SparkQA commented on issue #26869: [SPARK-30235][CORE] Switching off host local disk reading of shuffle blocks in case of useOldFetchProtocol URL: https://github.com/apache/spark/pull/26869#issuecomment-566374349 **[Test build #115426 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/115426/testReport)** for PR 26869 at commit [`69459e7`](https://github.com/apache/spark/commit/69459e73457650ae43e08ef783b67cdf31b0d46f). This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] cloud-fan commented on a change in pull request #26917: [SPARK-30278][SQL][DOC] Update Spark SQL document menu for new changes
cloud-fan commented on a change in pull request #26917: [SPARK-30278][SQL][DOC] Update Spark SQL document menu for new changes URL: https://github.com/apache/spark/pull/26917#discussion_r358590782 ## File path: docs/sql-performance-tuning.md ## @@ -158,7 +155,7 @@ broadcast(spark.table("src")).join(spark.table("records"), "key").show() {% highlight r %} src <- sql("SELECT * FROM src") records <- sql("SELECT * FROM records") -head(join(broadcast(src), records, src$key == records$key)) Review comment: did we remove the `broadcast` method? This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] SparkQA removed a comment on issue #26869: [SPARK-30235][CORE] Switching off host local disk reading of shuffle blocks in case of useOldFetchProtocol
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[GitHub] [spark] SparkQA commented on issue #26869: [SPARK-30235][CORE] Switching off host local disk reading of shuffle blocks in case of useOldFetchProtocol
SparkQA commented on issue #26869: [SPARK-30235][CORE] Switching off host local disk reading of shuffle blocks in case of useOldFetchProtocol URL: https://github.com/apache/spark/pull/26869#issuecomment-566375345 **[Test build #115426 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/115426/testReport)** for PR 26869 at commit [`69459e7`](https://github.com/apache/spark/commit/69459e73457650ae43e08ef783b67cdf31b0d46f). * This patch **fails to build**. * This patch merges cleanly. * This patch adds no public classes. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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