[ https://issues.apache.org/jira/browse/SPARK-40114?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17580731#comment-17580731 ]
Apache Spark commented on SPARK-40114: -------------------------------------- User 'HyukjinKwon' has created a pull request for this issue: https://github.com/apache/spark/pull/37553 > Arrow 9.0.0 support with SparkR > ------------------------------- > > Key: SPARK-40114 > URL: https://issues.apache.org/jira/browse/SPARK-40114 > Project: Spark > Issue Type: Bug > Components: SparkR > Affects Versions: 3.4.0 > Reporter: Hyukjin Kwon > Priority: Major > > {code} > == Failed > ====================================================================== > -- 1. Error (test_sparkSQL_arrow.R:103:3): dapply() Arrow optimization > --------- > Error in `readBin(con, raw(), as.integer(dataLen), endian = "big")`: invalid > 'n' argument > Backtrace: > 1. SparkR::collect(ret) > at test_sparkSQL_arrow.R:103:2 > 2. SparkR::collect(ret) > 3. SparkR (local) .local(x, ...) > 7. SparkR:::readRaw(conn) > 8. base::readBin(con, raw(), as.integer(dataLen), endian = "big") > -- 2. Error (test_sparkSQL_arrow.R:133:3): dapply() Arrow optimization - type > sp > Error in `readBin(con, raw(), as.integer(dataLen), endian = "big")`: invalid > 'n' argument > Backtrace: > 1. SparkR::collect(ret) > at test_sparkSQL_arrow.R:133:2 > 2. SparkR::collect(ret) > 3. SparkR (local) .local(x, ...) > 7. SparkR:::readRaw(conn) > 8. base::readBin(con, raw(), as.integer(dataLen), endian = "big") > -- 3. Error (test_sparkSQL_arrow.R:143:3): dapply() Arrow optimization - type > sp > Error in `readBin(con, raw(), as.integer(dataLen), endian = "big")`: invalid > 'n' argument > Backtrace: > 1. testthat::expect_true(all(collect(ret) == rdf)) > at test_sparkSQL_arrow.R:143:2 > 5. SparkR::collect(ret) > 6. SparkR (local) .local(x, ...) > 10. SparkR:::readRaw(conn) > 11. base::readBin(con, raw(), as.integer(dataLen), endian = "big") > -- 4. Error (test_sparkSQL_arrow.R:184:3): gapply() Arrow optimization > --------- > Error in `readBin(con, raw(), as.integer(dataLen), endian = "big")`: invalid > 'n' argument > Backtrace: > 1. SparkR::collect(ret) > at test_sparkSQL_arrow.R:184:2 > 2. SparkR::collect(ret) > 3. SparkR (local) .local(x, ...) > 7. SparkR:::readRaw(conn) > 8. base::readBin(con, raw(), as.integer(dataLen), endian = "big") > -- 5. Error (test_sparkSQL_arrow.R:217:3): gapply() Arrow optimization - type > sp > Error in `readBin(con, raw(), as.integer(dataLen), endian = "big")`: invalid > 'n' argument > Backtrace: > 1. SparkR::collect(ret) > at test_sparkSQL_arrow.R:217:2 > 2. SparkR::collect(ret) > 3. SparkR (local) .local(x, ...) > 7. SparkR:::readRaw(conn) > 8. base::readBin(con, raw(), as.integer(dataLen), endian = "big") > -- 6. Error (test_sparkSQL_arrow.R:229:3): gapply() Arrow optimization - type > sp > Error in `readBin(con, raw(), as.integer(dataLen), endian = "big")`: invalid > 'n' argument > Backtrace: > 1. testthat::expect_true(all(collect(ret) == rdf)) > at test_sparkSQL_arrow.R:229:2 > 5. SparkR::collect(ret) > 6. SparkR (local) .local(x, ...) > 10. SparkR:::readRaw(conn) > 11. base::readBin(con, raw(), as.integer(dataLen), endian = "big") > -- 7. Failure (test_sparkSQL_arrow.R:247:3): SPARK-32478: gapply() Arrow > optimiz > `count(...)` threw an error with unexpected message. > Expected match: "expected IntegerType, IntegerType, got IntegerType, > StringType" > Actual message: "org.apache.spark.SparkException: Job aborted due to stage > failure: Task 0 in stage 29.0 failed 1 times, most recent failure: Lost task > 0.0 in stage 29.0 (TID 54) (APPVYR-WIN executor driver): > org.apache.spark.SparkException: R unexpectedly exited.\nR worker produced > errors: The tzdb package is not installed. Timezones will not be available to > Arrow compute functions.\nError in arrow::write_arrow(df, raw()) : > write_arrow has been removed\nCalls: <Anonymous> -> writeRaw -> writeInt -> > writeBin -> <Anonymous>\nExecution halted\n\r\n\tat > org.apache.spark.api.r.BaseRRunner$ReaderIterator$$anonfun$1.applyOrElse(BaseRRunner.scala:144)\r\n\tat > > org.apache.spark.api.r.BaseRRunner$ReaderIterator$$anonfun$1.applyOrElse(BaseRRunner.scala:137)\r\n\tat > > scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:38)\r\n\tat > > org.apache.spark.sql.execution.r.ArrowRRunner$$anon$2.read(ArrowRRunner.scala:194)\r\n\tat > > org.apache.spark.sql.execution.r.ArrowRRunner$$anon$2.read(ArrowRRunner.scala:123)\r\n\tat > > org.apache.spark.api.r.BaseRRunner$ReaderIterator.hasNext(BaseRRunner.scala:113)\r\n\tat > scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:491)\r\n\tat > scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\r\n\tat > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.hashAgg_doAggregateWithoutKey_0$(Unknown > Source)\r\n\tat > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.processNext(Unknown > Source)\r\n\tat > org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)\r\n\tat > > org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:760)\r\n\tat > scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\r\n\tat > org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:140)\r\n\tat > > org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)\r\n\tat > > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:101)\r\n\tat > > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)\r\n\tat > org.apache.spark.scheduler.Task.run(Task.scala:139)\r\n\tat > org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:548)\r\n\tat > org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1490)\r\n\tat > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:551)\r\n\tat > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\r\n\tat > > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\r\n\tat > java.lang.Thread.run(Thread.java:748)\r\nCaused by: > java.net.SocketException: Connection reset\r\n\tat > java.net.SocketInputStream.read(SocketInputStream.java:210)\r\n\tat > java.net.SocketInputStream.read(SocketInputStream.java:141)\r\n\tat > java.io.BufferedInputStream.fill(BufferedInputStream.java:246)\r\n\tat > java.io.BufferedInputStream.read(BufferedInputStream.java:265)\r\n\tat > java.io.DataInputStream.readInt(DataInputStream.java:387)\r\n\tat > org.apache.spark.sql.execution.r.ArrowRRunner$$anon$2.read(ArrowRRunner.scala:154)\r\n\t... > 20 more\r\n\nDriver stacktrace:\r\n\tat > org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2706)\r\n\tat > > org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2642)\r\n\tat > > org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2641)\r\n\tat > > scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)\r\n\tat > > scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)\r\n\tat > scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)\r\n\tat > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2641)\r\n\tat > > org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1189)\r\n\tat > > org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1189)\r\n\tat > scala.Option.foreach(Option.scala:407)\r\n\tat > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1189)\r\n\tat > > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2897)\r\n\tat > > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2836)\r\n\tat > > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2825)\r\n\tat > org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)\r\nCaused > by: org.apache.spark.SparkException: R unexpectedly exited.\nR worker > produced errors: The tzdb package is not installed. Timezones will not be > available to Arrow compute functions.\nError in arrow::write_arrow(df, raw()) > : write_arrow has been removed\nCalls: <Anonymous> -> writeRaw -> writeInt -> > writeBin -> <Anonymous>\nExecution halted\n\r\n\tat > org.apache.spark.api.r.BaseRRunner$ReaderIterator$$anonfun$1.applyOrElse(BaseRRunner.scala:144)\r\n\tat > > org.apache.spark.api.r.BaseRRunner$ReaderIterator$$anonfun$1.applyOrElse(BaseRRunner.scala:137)\r\n\tat > > scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:38)\r\n\tat > > org.apache.spark.sql.execution.r.ArrowRRunner$$anon$2.read(ArrowRRunner.scala:194)\r\n\tat > > org.apache.spark.sql.execution.r.ArrowRRunner$$anon$2.read(ArrowRRunner.scala:123)\r\n\tat > > org.apache.spark.api.r.BaseRRunner$ReaderIterator.hasNext(BaseRRunner.scala:113)\r\n\tat > scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:491)\r\n\tat > scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\r\n\tat > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.hashAgg_doAggregateWithoutKey_0$(Unknown > Source)\r\n\tat > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage3.processNext(Unknown > Source)\r\n\tat > org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)\r\n\tat > > org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:760)\r\n\tat > scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)\r\n\tat > org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:140)\r\n\tat > > org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)\r\n\tat > > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:101)\r\n\tat > > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)\r\n\tat > org.apache.spark.scheduler.Task.run(Task.scala:139)\r\n\tat > org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:548)\r\n\tat > org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1490)\r\n\tat > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:551)\r\n\tat > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\r\n\tat > > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\r\n\tat > java.lang.Thread.run(Thread.java:748)\r\nCaused by: > java.net.SocketException: Connection reset\r\n\tat > java.net.SocketInputStream.read(SocketInputStream.java:210)\r\n\tat > java.net.SocketInputStream.read(SocketInputStream.java:141)\r\n\tat > java.io.BufferedInputStream.fill(BufferedInputStream.java:246)\r\n\tat > java.io.BufferedInputStream.read(BufferedInputStream.java:265)\r\n\tat > java.io.DataInputStream.readInt(DataInputStream.java:387)\r\n\tat > org.apache.spark.sql.execution.r.ArrowRRunner$$anon$2.read(ArrowRRunner.scala:154)\r\n\t... > 20 more\r\n" > Backtrace: > 1. testthat::expect_error(...) > at test_sparkSQL_arrow.R:247:2 > 7. SparkR::count(...) > 8. SparkR:::callJMethod(x@sdf, "count") > 9. SparkR:::invokeJava(isStatic = FALSE, objId$id, methodName, ...) > 10. SparkR:::handleErrors(returnStatus, conn) > == DONE > ======================================================================== > {code} > https://ci.appveyor.com/project/HyukjinKwon/spark/builds/44490387 -- This message was sent by Atlassian Jira (v8.20.10#820010) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org