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Posted to issues@spark.apache.org by "Dongjoon Hyun (JIRA)" <ji...@apache.org> on 2019/02/20 06:13:00 UTC
[jira] [Commented] (SPARK-26937) Build Spark 2.4 Support Hadoop-3.1
faild
[ https://issues.apache.org/jira/browse/SPARK-26937?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16772650#comment-16772650 ]
Dongjoon Hyun commented on SPARK-26937:
---------------------------------------
Thank you for reporting, [~xujiang].
BTW, please see the PR description of SPARK-23807 for the workaround.
- https://github.com/apache/spark/pull/20923
There are many efforts for this, but the key issue is SPARK-23534. I close this as a duplicate of SPARK-23534.
> Build Spark 2.4 Support Hadoop-3.1 faild
> ----------------------------------------
>
> Key: SPARK-26937
> URL: https://issues.apache.org/jira/browse/SPARK-26937
> Project: Spark
> Issue Type: Bug
> Components: Build
> Affects Versions: 2.4.0
> Environment: h2. Hi, my environmental information is as follows：
> Operating System
> {code:java}
> CentOS Linux release 7.4.1708 (Core)
> Linux e26cf748c48f 4.9.87-linuxkit-aufs #1 SMP Fri Mar 16 18:16:33 UTC 2018 x86_64 x86_64 x86_64 GNU/Linux
> {code}
> Maven
> {code:java}
> Apache Maven 3.5.4 (1edded0938998edf8bf061f1ceb3cfdeccf443fe; 2018-06-17T18:33:14Z)
> Maven home: /usr/local/maven
> Java version: 1.8.0_151, vendor: Oracle Corporation, runtime: /usr/lib/jvm/java-1.8.0-openjdk-1.8.0.151-1.b12.el7_4.x86_64/jre
> Default locale: en_US, platform encoding: UTF-8
> OS name: "linux", version: "4.9.87-linuxkit-aufs", arch: "amd64", family: "unix"{code}
> R version
> {code:java}
> R version 3.5.1 (2018-07-02) – "Feather Spray"
> Copyright (C) 2018 The R Foundation for Statistical Computing
> Platform: x86_64-redhat-linux-gnu (64-bit){code}
> Allocation of resources
> {code:java}
> Mem: 5957M
> Swap: 2047M
> Cpus: 3{code}
> Reporter: Xu Jiang
> Priority: Major
> Labels: build
>
> The build command I am running is：
> {code:java}
> ./dev/make-distribution.sh --name jdp-spark --tgz --pip --r -Psparkr -Phadoop-3.1 -Phive -Phive-thriftserver -Pmesos -Pyarn -Pkubernetes -DskipTests{code}
> The main reason is that the package that relies on hive-exec-*.jar does not support Hadoop 3.1.0.
> {code:java}
> {{org.apache.spark.sql.api.r.SQLUtils.getOrCreateSparkSession(SQLUtils.scala)
> ... 36 more
> Caused by: java.lang.IllegalArgumentException:{color:red} Unrecognized Hadoop major version number: 3.1.0{color}
> at org.apache.hadoop.hive.shims.ShimLoader.getMajorVersion(ShimLoader.java:174)}}{code}
> Detailed error：
> {code:java}
> {{+ SPARK_JARS_DIR=/ws/jdp-package/dl/spark2-2.4.0-src/assembly/target/scala-2.11/jars
> + '[' -d /ws/jdp-package/dl/spark2-2.4.0-src/assembly/target/scala-2.11/jars ']'
> + SPARK_HOME=/ws/jdp-package/dl/spark2-2.4.0-src
> + /usr/bin/R CMD build /ws/jdp-package/dl/spark2-2.4.0-src/R/pkg
> checking for file ‘/ws/jdp-package/dl/spark2-2.4.0-src/R/pkg/DESCRIPTION’ ... OK preparing ‘SparkR’: checking DESCRIPTION meta-information ... OK installing the package to build vignettes creating vignettes ... ERROR
> Attaching package: 'SparkR'
> The following objects are masked from 'package:stats':
> cov, filter, lag, na.omit, predict, sd, var, window
> The following objects are masked from 'package:base':
> as.data.frame, colnames, colnames<-, drop, endsWith,
> intersect, rank, rbind, sample, startsWith, subset, summary,
> transform, union
> Picked up _JAVA_OPTIONS: -XX:-UsePerfData
> Picked up _JAVA_OPTIONS: -XX:-UsePerfData
> 2019-02-20 01:00:07 WARN NativeCodeLoader:60 - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
> Setting default log level to "WARN".
> To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
> 2019-02-20 01:00:14 ERROR RBackendHandler:91 - getOrCreateSparkSession on org.apache.spark.sql.api.r.SQLUtils failed
> java.lang.reflect.InvocationTargetException
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at org.apache.spark.api.r.RBackendHandler.handleMethodCall(RBackendHandler.scala:167)
> at org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:108)
> at org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:40)
> at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105)
> at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:362)
> at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:348)
> at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:340)
> at io.netty.handler.timeout.IdleStateHandler.channelRead(IdleStateHandler.java:286)
> at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:362)
> at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:348)
> at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:340)
> at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:102)
> at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:362)
> at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:348)
> at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:340)
> at io.netty.handler.codec.ByteToMessageDecoder.fireChannelRead(ByteToMessageDecoder.java:310)
> at io.netty.handler.codec.ByteToMessageDecoder.channelRead(ByteToMessageDecoder.java:284)
> at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:362)
> at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:348)
> at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:340)
> at io.netty.channel.DefaultChannelPipeline$HeadContext.channelRead(DefaultChannelPipeline.java:1359)
> at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:362)
> at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:348)
> at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:935)
> at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:138)
> at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:645)
> at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:580)
> at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:497)
> at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:459)
> at io.netty.util.concurrent.SingleThreadEventExecutor$5.run(SingleThreadEventExecutor.java:858)
> at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:138)
> at java.lang.Thread.run(Thread.java:748)
> Caused by: java.lang.ExceptionInInitializerError
> at org.apache.hadoop.hive.conf.HiveConf.<clinit>(HiveConf.java:105)
> at java.lang.Class.forName0(Native Method)
> at java.lang.Class.forName(Class.java:348)
> at org.apache.spark.util.Utils$.classForName(Utils.scala:238)
> at org.apache.spark.sql.SparkSession$.hiveClassesArePresent(SparkSession.scala:1117)
> at org.apache.spark.sql.api.r.SQLUtils$.getOrCreateSparkSession(SQLUtils.scala:52)
> at org.apache.spark.sql.api.r.SQLUtils.getOrCreateSparkSession(SQLUtils.scala)
> ... 36 more
> Caused by: java.lang.IllegalArgumentException: Unrecognized Hadoop major version number: 3.1.0
> at org.apache.hadoop.hive.shims.ShimLoader.getMajorVersion(ShimLoader.java:174)
> at org.apache.hadoop.hive.shims.ShimLoader.loadShims(ShimLoader.java:139)
> at org.apache.hadoop.hive.shims.ShimLoader.getHadoopShims(ShimLoader.java:100)
> at org.apache.hadoop.hive.conf.HiveConf$ConfVars.<clinit>(HiveConf.java:368)
> ... 43 more
> Quitting from lines 65-67 (sparkr-vignettes.Rmd)
> Error: processing vignette 'sparkr-vignettes.Rmd' failed with diagnostics:
> java.lang.ExceptionInInitializerError
> at org.apache.hadoop.hive.conf.HiveConf.<clinit>(HiveConf.java:105)
> at java.lang.Class.forName0(Native Method)
> at java.lang.Class.forName(Class.java:348)
> at org.apache.spark.util.Utils$.classForName(Utils.scala:238)
> at org.apache.spark.sql.SparkSession$.hiveClassesArePresent(SparkSession.scala:1117)
> at org.apache.spark.sql.api.r.SQLUtils$.getOrCreateSparkSession(SQLUtils.scala:52)
> at org.apache.spark.sql.api.r.SQLUtils.getOrCreateSparkSession(SQLUtils.scala)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at org.apache.spark.api.r.RBackendHandler.handleMethodCall(RBackendHandler.scala:167)
> at org.apache.spark.api.r.RBackendHandl
> Execution halted}}
> {code}
>
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