From issues-return-196384-archive-asf-public=cust-asf.ponee.io@spark.apache.org Tue Jul 17 15:25:05 2018 Return-Path: X-Original-To: archive-asf-public@cust-asf.ponee.io Delivered-To: archive-asf-public@cust-asf.ponee.io Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by mx-eu-01.ponee.io (Postfix) with SMTP id F19F3180600 for ; Tue, 17 Jul 2018 15:25:04 +0200 (CEST) Received: (qmail 16855 invoked by uid 500); 17 Jul 2018 13:25:04 -0000 Mailing-List: contact issues-help@spark.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Delivered-To: mailing list issues@spark.apache.org Received: (qmail 16844 invoked by uid 99); 17 Jul 2018 13:25:04 -0000 Received: from pnap-us-west-generic-nat.apache.org (HELO spamd4-us-west.apache.org) (209.188.14.142) by apache.org (qpsmtpd/0.29) with ESMTP; Tue, 17 Jul 2018 13:25:04 +0000 Received: from localhost (localhost [127.0.0.1]) by spamd4-us-west.apache.org (ASF Mail Server at spamd4-us-west.apache.org) with ESMTP id 992B8C0F5F for ; Tue, 17 Jul 2018 13:25:03 +0000 (UTC) X-Virus-Scanned: Debian amavisd-new at spamd4-us-west.apache.org X-Spam-Flag: NO X-Spam-Score: -109.501 X-Spam-Level: X-Spam-Status: No, score=-109.501 tagged_above=-999 required=6.31 tests=[ENV_AND_HDR_SPF_MATCH=-0.5, KAM_ASCII_DIVIDERS=0.8, RCVD_IN_DNSWL_MED=-2.3, SPF_PASS=-0.001, USER_IN_DEF_SPF_WL=-7.5, USER_IN_WHITELIST=-100] autolearn=disabled Received: from mx1-lw-eu.apache.org ([10.40.0.8]) by localhost (spamd4-us-west.apache.org [10.40.0.11]) (amavisd-new, port 10024) with ESMTP id uFYIJDZniaTm for ; Tue, 17 Jul 2018 13:25:02 +0000 (UTC) Received: from mailrelay1-us-west.apache.org (mailrelay1-us-west.apache.org [209.188.14.139]) by mx1-lw-eu.apache.org (ASF Mail Server at mx1-lw-eu.apache.org) with ESMTP id 3DE965F402 for ; Tue, 17 Jul 2018 13:25:01 +0000 (UTC) Received: from jira-lw-us.apache.org (unknown [207.244.88.139]) by mailrelay1-us-west.apache.org (ASF Mail Server at mailrelay1-us-west.apache.org) with ESMTP id 6231EE02BE for ; Tue, 17 Jul 2018 13:25:00 +0000 (UTC) Received: from jira-lw-us.apache.org (localhost [127.0.0.1]) by jira-lw-us.apache.org (ASF Mail Server at jira-lw-us.apache.org) with ESMTP id 1933E23F97 for ; Tue, 17 Jul 2018 13:25:00 +0000 (UTC) Date: Tue, 17 Jul 2018 13:25:00 +0000 (UTC) From: "Romeo Kienzer (JIRA)" To: issues@spark.apache.org Message-ID: In-Reply-To: References: Subject: [jira] [Commented] (SPARK-24828) Incompatible parquet formats - java.lang.UnsupportedOperationException: org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainLongDictionary MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: quoted-printable X-JIRA-FingerPrint: 30527f35849b9dde25b450d4833f0394 [ https://issues.apache.org/jira/browse/SPARK-24828?page=3Dcom.atlassia= n.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=3D165= 46602#comment-16546602 ]=20 Romeo Kienzer commented on SPARK-24828: --------------------------------------- [~q79969786]=C2=A0 [x] done > Incompatible parquet formats - java.lang.UnsupportedOperationException: o= rg.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainLongD= ictionary > -------------------------------------------------------------------------= ---------------------------------------------------------------------------= --------- > > Key: SPARK-24828 > URL: https://issues.apache.org/jira/browse/SPARK-24828 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 2.3.0 > Environment: Environment for creating the parquet file: > IBM Watson Studio Apache Spark Service, V2.1.2 > Environment for reading the parquet file: > java version "1.8.0_144" > Java(TM) SE Runtime Environment (build 1.8.0_144-b01) > Java HotSpot(TM) 64-Bit Server VM (build 25.144-b01, mixed mode) > MacOSX 10.13.3 (17D47) > Spark spark-2.1.2-bin-hadoop2.7 directly obtained from http://spark.apach= e.org/downloads.html > Reporter: Romeo Kienzer > Priority: Minor > Attachments: a2_m2.parquet.zip > > > As requested by [~hyukjin.kwon] here a new issue - related issue can be f= ound here > =C2=A0 > Using the attached parquet file from one Spark installation, reading it u= sing an installation directly obtained from [http://spark.apache.org/downlo= ads.html] yields to the following exception: > =C2=A0 > 18/07/17 07:40:38 ERROR Executor: Exception in task 3.0 in stage 1.0 (TID= 4) > scala.MatchError: [1.0,null] (of class org.apache.spark.sql.catalyst.exp= ressions.GenericRowWithSchema) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.ml.evaluation.MulticlassClassific= ationEvaluator$$anonfun$1.apply(MulticlassClassificationEvaluator.scala:79) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.ml.evaluation.MulticlassClassific= ationEvaluator$$anonfun$1.apply(MulticlassClassificationEvaluator.scala:79) > =C2=A0=C2=A0 =C2=A0at scala.collection.Iterator$$anon$11.next(Iterator.s= cala:409) > =C2=A0=C2=A0 =C2=A0at scala.collection.Iterator$$anon$11.next(Iterator.s= cala:409) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.util.collection.ExternalSorter.in= sertAll(ExternalSorter.scala:193) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.shuffle.sort.SortShuffleWriter.wr= ite(SortShuffleWriter.scala:63) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.scheduler.ShuffleMapTask.runTask(= ShuffleMapTask.scala:96) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.scheduler.ShuffleMapTask.runTask(= ShuffleMapTask.scala:53) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.scheduler.Task.run(Task.scala:99) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.executor.Executor$TaskRunner.run(= Executor.scala:325) > =C2=A0=C2=A0 =C2=A0at java.util.concurrent.ThreadPoolExecutor.runWorker(= ThreadPoolExecutor.java:1149) > =C2=A0=C2=A0 =C2=A0at java.util.concurrent.ThreadPoolExecutor$Worker.run= (ThreadPoolExecutor.java:624) > =C2=A0=C2=A0 =C2=A0at java.lang.Thread.run(Thread.java:748) > 18/07/17 07:40:38 ERROR Executor: Exception in task 0.0 in stage 1.0 (TI= D 1) > java.lang.UnsupportedOperationException: org.apache.parquet.column.value= s.dictionary.PlainValuesDictionary$PlainLongDictionary > =C2=A0=C2=A0 =C2=A0at org.apache.parquet.column.Dictionary.decodeToInt(D= ictionary.java:48) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.sql.execution.vectorized.OnHeapCo= lumnVector.getInt(OnHeapColumnVector.java:233) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.sql.catalyst.expressions.Generate= dClass$GeneratedIterator.processNext(Unknown Source) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.sql.execution.BufferedRowIterator= .hasNext(BufferedRowIterator.java:43) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.sql.execution.WholeStageCodegenEx= ec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377) > =C2=A0=C2=A0 =C2=A0at scala.collection.Iterator$$anon$11.hasNext(Iterato= r.scala:408) > =C2=A0=C2=A0 =C2=A0at scala.collection.Iterator$$anon$11.hasNext(Iterato= r.scala:408) > =C2=A0=C2=A0 =C2=A0at scala.collection.Iterator$$anon$11.hasNext(Iterato= r.scala:408) > =C2=A0=C2=A0 =C2=A0at scala.collection.Iterator$$anon$11.hasNext(Iterato= r.scala:408) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.util.collection.ExternalSorter.in= sertAll(ExternalSorter.scala:191) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.shuffle.sort.SortShuffleWriter.wr= ite(SortShuffleWriter.scala:63) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.scheduler.ShuffleMapTask.runTask(= ShuffleMapTask.scala:96) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.scheduler.ShuffleMapTask.runTask(= ShuffleMapTask.scala:53) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.scheduler.Task.run(Task.scala:99) > =C2=A0=C2=A0 =C2=A0at org.apache.spark.executor.Executor$TaskRunner.run(= Executor.scala:325) > =C2=A0=C2=A0 =C2=A0at java.util.concurrent.ThreadPoolExecutor.runWorker(= ThreadPoolExecutor.java:1149) > =C2=A0=C2=A0 =C2=A0at java.util.concurrent.ThreadPoolExecutor$Worker.run= (ThreadPoolExecutor.java:624) > =C2=A0=C2=A0 =C2=A0at java.lang.Thread.run(Thread.java:748) > =C2=A0 > The file is attached [^a2_m2.parquet.zip] > =C2=A0 > The following code reproduces the error: > df =3D spark.read.parquet('a2_m2.parquet') > from pyspark.ml.evaluation import MulticlassClassificationEvaluator > binEval =3D MulticlassClassificationEvaluator().setMetricName("accuracy")= .setPredictionCol("prediction").setLabelCol("label") > accuracy =3D binEval.evaluate(df) -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org For additional commands, e-mail: issues-help@spark.apache.org