學習Spark——那些讓你精疲力盡的坑
作者：杰鍋鍋
這篇就介紹下自己遇到的各種坑。我不知道各位是否遇到過并能輕松解決，反正我是被這些小問題搞得精疲力盡，故在此總結以備忘。
這一個月我都干了些什么……
工作上，還是一如既往的寫bug并不亦樂乎的修bug。學習上，最近看了一些非專業書籍，寫點小感悟，我剛稍稍瞄了下，最近五篇居然都跟技術無關，看來我與本行業已經是漸行漸遠了。
所以，趁著這篇博客，重拾自己，認清自己，要時刻謹記我是一名碼農。不過，摸著良心說，最近的技術方面也是有所感悟和積累的，比如如何寫好設計文檔，如何使用延時隊列，如何使用防刷技術等等。當然了，今天我們還是沿著“學習Spark”這條路繼續走下去。
這篇就介紹下自己遇到的各種坑。我不知道各位是否遇到過并能輕松解決，反正我是被這些小問題搞得精疲力盡，故在此總結以備忘。
1.1 Scala與Intellij集成報錯
在Scala安裝成功后，準備到Intellij上寫Scala代碼，發現Scala都配好了(關于如何配置，網上資料很多)，結果運行Scala程序時報錯。
錯誤：
- Error:scalac: Multiple 'scala-library*.jar' files (scala-library.jar, scala-library.jar, scala-library.jar) in Scala compiler classpath in Scala SDK scala-sdk-2.12.2
解決方法：在OverStackflow上找到了思路。在Intellij中打開project structure，刪除已有的Scala的路徑(我的Scala是安裝在/usr/local/Cellar/scala/2.12.2路徑下的),重新添加/usr/local/Cellar/scala/2.12.2/idea/lib目錄即可。
改動前
改動后
1.2 Scala語法Intellij不認
在Intellij中寫了一個Scala的HelloWorld，代碼如下
- /**
- * Created by jackie on 17/5/7.
- */
- package com.jackie.scala.s510
- object HelloWorld {
- def main(args: Array[String]): Unit = {
- println("hello world")
- println(increaseAnother(5));
- println(Array(1,2,3,4).map{(x:Int)=>x+1}.mkString(","));
- println(Array(1,2,3,4) map{(x:Int)=>x+1} mkString(","));
- println(Array(1,2,3,4) map{(x:Int)=>x+1} mkString(","));
- // test object
- var person = new Person()
- person.name_=("john") // name_=()對應java中的setter方法
- println("Person name:" + person.name)
- person.name = "Jackie"
- println("Person name:" + person.name)
- var mp = new MyPerson()
- mp.name_("alihaha")
- println("MyPerson name:" + person.name)
- var pwp = new PersonWithParam("Jackie", 18)
- println("PersonWithParam:" + pwp.toString())
- }
- def increaseAnother(x: Int): Int = x + 1
- }
運行的時候，報錯mkString無法識別。
錯誤：mkString can't be resolved
解決方法：需要交代下我各個環境的版本參數，Intellij-14.0， jdk-8， scala-2.12.2。但是在Intellij中能選擇的Scala***版本只有2.11，所有后來將Intellij升級到2017.1版本，這時候還報錯Error:scalac: Error: org.jetbrains.jps.incremental.scala.remote.ServerException，然后在Intellij中打開project structure，將scala由2.12.2換成2.11.7，問題解決。
1.3 Spark與Intellij集成的問題
Spark環境都安裝好了，所以想在Intellij中運行Spark程序，但是在添加了Spark的相關依賴后，發現無法編譯通過。
錯誤：
- Exception NoSuchMethodError: com.google.common.collect.MapMaker.keyEquivalence
解決方法：實現聲明，之前在maven中一直引用的都是spark-core2.10，這時候報錯，我定位問題出在Guava上，然后找到所有間接依賴了Guava的jar，都exclude，問題還是沒有解決。期間添加了Spark的很多依賴，試了都不行，***試了下Spark-core2.11，問題解決(有的時候版本的兼容性真的很坑)。
1.4 hadoop上傳本地文件到HDFS
如果想將本地文件上傳到HDFS，使用hadoop fs -put localDir hdfsDir，前提是保證hadoop啟動。
錯誤：
- jackie@jackies-MacBook-Pro:~|⇒ hadoop fs -put ~/Documents/doc/README.md /
- 17/05/13 10:56:39 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
- 17/05/13 10:56:40 WARN ipc.Client: Failed to connect to server: localhost/127.0.0.1:8020: try once and fail.
- java.net.ConnectException: Connection refused
- at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
- at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
- at org.apache.hadoop.net.SocketIOWithTimeout.connect(SocketIOWithTimeout.java:206)
- at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:531)
- at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:495)
- at org.apache.hadoop.ipc.Client$Connection.setupConnection(Client.java:681)
- at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:777)
- at org.apache.hadoop.ipc.Client$Connection.access$3500(Client.java:409)
- at org.apache.hadoop.ipc.Client.getConnection(Client.java:1542)
- at org.apache.hadoop.ipc.Client.call(Client.java:1373)
- at org.apache.hadoop.ipc.Client.call(Client.java:1337)
- at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:227)
- at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:116)
- at com.sun.proxy.$Proxy10.getFileInfo(Unknown Source)
- at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.getFileInfo(ClientNamenodeProtocolTranslatorPB.java:787)
- 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.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:398)
- at org.apache.hadoop.io.retry.RetryInvocationHandler$Call.invokeMethod(RetryInvocationHandler.java:163)
- at org.apache.hadoop.io.retry.RetryInvocationHandler$Call.invoke(RetryInvocationHandler.java:155)
- at org.apache.hadoop.io.retry.RetryInvocationHandler$Call.invokeOnce(RetryInvocationHandler.java:95)
- at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:335)
- at com.sun.proxy.$Proxy11.getFileInfo(Unknown Source)
- at org.apache.hadoop.hdfs.DFSClient.getFileInfo(DFSClient.java:1700)
- at org.apache.hadoop.hdfs.DistributedFileSystem$27.doCall(DistributedFileSystem.java:1436)
- at org.apache.hadoop.hdfs.DistributedFileSystem$27.doCall(DistributedFileSystem.java:1433)
- at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
- at org.apache.hadoop.hdfs.DistributedFileSystem.getFileStatus(DistributedFileSystem.java:1433)
- at org.apache.hadoop.fs.Globber.getFileStatus(Globber.java:64)
- at org.apache.hadoop.fs.Globber.doGlob(Globber.java:282)
- at org.apache.hadoop.fs.Globber.glob(Globber.java:148)
- at org.apache.hadoop.fs.FileSystem.globStatus(FileSystem.java:1685)
- at org.apache.hadoop.fs.shell.PathData.expandAsGlob(PathData.java:326)
- at org.apache.hadoop.fs.shell.CommandWithDestination.getRemoteDestination(CommandWithDestination.java:195)
- at org.apache.hadoop.fs.shell.CopyCommands$Put.processOptions(CopyCommands.java:256)
- at org.apache.hadoop.fs.shell.Command.run(Command.java:164)
- at org.apache.hadoop.fs.FsShell.run(FsShell.java:315)
- at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:76)
- at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:90)
- at org.apache.hadoop.fs.FsShell.main(FsShell.java:378)
- put: Call From jackies-macbook-pro.local/192.168.73.56 to localhost:8020 failed on connection exception: java.net.ConnectException: Connection refused; For more details see: http://wiki.apache.org/hadoop/ConnectionRefused
解決方法：進入hadoop安裝目錄(我的是/usr/local/Cellar/hadoop)進入sbin下執行./start-all.sh啟動hadoop服務。
1.5 Spark啟動
上篇在配置Spark時沒有配置spark-defaults.conf文件，所以在Spark安裝目錄下(我的是/usr/local/Spark)啟動./start-all.sh出錯。
錯誤：
- spark-shell
- Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
- Setting default log level to "WARN".
- To adjust logging level use sc.setLogLevel(newLevel).
- 17/05/13 13:42:49 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
- 17/05/13 13:42:51 WARN StandaloneAppClient$ClientEndpoint: Failed to connect to master 192.168.73.56:7077
- org.apache.spark.SparkException: Exception thrown in awaitResult
- at org.apache.spark.rpc.RpcTimeout$$anonfun$1.applyOrElse(RpcTimeout.scala:77)
- at org.apache.spark.rpc.RpcTimeout$$anonfun$1.applyOrElse(RpcTimeout.scala:75)
- at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:36)
- at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
- at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
- at scala.PartialFunction$OrElse.apply(PartialFunction.scala:167)
- at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:83)
- at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:88)
- at org.apache.spark.rpc.RpcEnv.setupEndpointRef(RpcEnv.scala:96)
- at org.apache.spark.deploy.client.StandaloneAppClient$ClientEndpoint$$anonfun$tryRegisterAllMasters$1$$anon$1.run(StandaloneAppClient.scala:106)
- at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
- at java.util.concurrent.FutureTask.run(FutureTask.java:266)
- at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
- at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
- at java.lang.Thread.run(Thread.java:745)
- Caused by: java.io.IOException: Failed to connect to /192.168.73.56:7077
解決方法：將Spark安裝目錄下的conf中的spark-defaults.conf.template拷貝一份出來，重命名為spark-defaults.conf，按照https://sanwen8.cn/p/3bac5Bj.html配置好，再啟動Spark，發現還是報錯
- https://sanwen8.cn/p/3bac5Bj.html Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
- Setting default log level to "WARN".
- To adjust logging level use sc.setLogLevel(newLevel).
- 17/05/13 14:19:12 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
- 17/05/13 14:19:15 ERROR SparkContext: Error initializing SparkContext.
- java.net.ConnectException: Call From jackies-MacBook-Pro.local/192.168.73.56 to 192.168.73.56:8021 failed on connection exception: java.net.ConnectException: Connection refused; For more details see: http://wiki.apache.org/hadoop/ConnectionRefused
- at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
于是按照StackOverflow，將spark-defaults.conf中的spark.eventLog.enabled由true改為false，之后再啟動成功。
注意：這里我反復配置了localhost和自己的ip，來回切換，最終證明只要在/etc/hosts中配置好ip對應映射的名稱，可以直接用名稱即可，不用寫ip，而且要保持hadoop中的配置文件和spark中的配置文件要一致，否則針對會精疲力盡。
1.6 將運算任務交給Spark運行的報錯
運行下面的一個Demo程序
- package com.jackie.scala.s513;
- import org.apache.spark.SparkConf;
- import org.apache.spark.api.java.JavaPairRDD;
- import org.apache.spark.api.java.JavaRDD;
- import org.apache.spark.api.java.JavaSparkContext;
- import org.apache.spark.api.java.function.FlatMapFunction;
- import org.apache.spark.api.java.function.Function2;
- import org.apache.spark.api.java.function.PairFunction;
- import scala.Tuple2;
- import java.util.Arrays;
- import java.util.Iterator;
- import java.util.List;
- import java.util.regex.Pattern;
- /**
- * Created by jackie on 17/5/13.
- */
- public class Simple
- {
- private static final Pattern SPACE = Pattern.compile(" ");
- public static void main(String[] args) throws Exception {
- //創建一個RDD對象
- SparkConf conf=new SparkConf().setAppName("Simple").setMaster("local");
- //創建spark上下文對象，是數據的入口
- JavaSparkContext spark=new JavaSparkContext(conf);
- //獲取數據源
- JavaRDD<String> lines = spark.textFile("hdfs://jackie:8020/");
- /**
- * 對于從數據源得到的DStream，用戶可以在其基礎上進行各種操作，
- * 對于當前時間窗口內從數據源得到的數據首先進行分割，
- * 然后利用Map和ReduceByKey方法進行計算，當然***還有使用print()方法輸出結果；
- */
- JavaRDD<String> words = lines.flatMap(new FlatMapFunction<String, String>() {
- @Override
- public Iterator<String> call(String s) {
- return Arrays.asList(SPACE.split(s)).iterator();
- }
- });
- //使用RDD的map和reduce方法進行計算
- JavaPairRDD<String, Integer> ones = words.mapToPair(
- new PairFunction<String, String, Integer>() {
- @Override
- public Tuple2<String, Integer> call(String s) {
- return new Tuple2<String, Integer>(s, 1);
- }
- });
- JavaPairRDD<String, Integer> counts = ones.reduceByKey(
- new Function2<Integer, Integer, Integer>() {
- @Override
- public Integer call(Integer i1, Integer i2) {
- return i1 + i2;
- }
- });
- List<Tuple2<String, Integer>> output = counts.collect();
- for (Tuple2<?,?> tuple : output) {
- //輸出計算結果
- System.out.println(tuple._1() + ": " + tuple._2());
- }
- spark.stop();
- }
- }
這個程序需要讀取HDFS上根目錄下的README.md文件，但是在此之前我執行了"hadoop namenode -format"(注意，這個操作引起了后面的一系列問題)。所以就準備重新使用hadoop fs -put localDir hdfsDir上傳README.md，結果這時候報錯
錯誤：
- hadoop fs -put /Users/jackie/Documents/doc/README.md /
- 17/05/13 15:47:15 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
- 17/05/13 15:47:16 WARN hdfs.DataStreamer: DataStreamer Exception
- org.apache.hadoop.ipc.RemoteException(java.io.IOException): File /README.md._COPYING_ could only be replicated to 0 nodes instead of minReplication (=1). There are 0 datanode(s) running and no node(s) are excluded in this operation.
- at org.apache.hadoop.hdfs.server.blockmanagement.BlockManager.chooseTarget4NewBlock(BlockManager.java:1733)
- at org.apache.hadoop.hdfs.server.namenode.FSDirWriteFileOp.chooseTargetForNewBlock(FSDirWriteFileOp.java:265)
- at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getAdditionalBlock(FSNamesystem.java:2496)
- at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.addBlock(NameNodeRpcServer.java:828)
后來發現是datanode沒有啟動，然后開始找datanode沒有啟動的原因，在這里http://www.aboutyun.com/thread-7931-1-1.html
文中解釋：當我們執行文件系統格式化時，會在namenode數據文件夾(即配置文件中dfs.name.dir在本地系統的路徑)中保存一個current/VERSION文件，記錄namespaceID，標識了所格式化的 namenode的版本。如果我們頻繁的格式化namenode，那么datanode中保存(即配置文件中dfs.data.dir在本地系統的路徑)的current/VERSION文件只是你***次格式化時保存的namenode的ID，因此就會造成datanode與namenode之間的id不一致。
解決方法：采取的做法是根據執行hadoop namenode –format得到成功的提示。
這時候再執行jps命令，我們就可以看到datanode了
類似的，同樣是在執行hadoop fs -put /Users/jackie/Documents/doc/README.md /是報錯如下
- hadoop fs -put /Users/jackie/Documents/doc/README.md /
- 17/05/15 09:51:04 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
- 17/05/15 09:51:05 WARN ipc.Client: Failed to connect to server: jackie/192.168.73.56:8020: try once and fail.
- java.net.ConnectException: Connection refused
- at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
- at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
- at org.apache.hadoop.net.SocketIOWithTimeout.connect(SocketIOWithTimeout.java:206)
- at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:531)
- at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:495)
- at org.apache.hadoop.ipc.Client$Connection.setupConnection(Client.java:681)
- at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:777)
- at org.apache.hadoop.ipc.Client$Connection.access$3500(Client.java:409)
一開始以為是ip的配置問題，但是反復修改無果，后來發現使用jps時，沒有啟動namenode，于是在網上找http://blog.csdn.net/bychjzh/article/details/7830508
于是在/usr/local/Cellar/hadoop/hdfs下刪除原來在core-site.xml中配置的tmp目錄，然后新建了hadoop_tmp目錄，并在core-site.xml中修改成
- <property>
- <name>hadoop.tmp.dir</name>
- <value>/usr/local/Cellar/hadoop/hdfs/hadoop_tmp</value>
- <description>A base for other temporary directories.</description>
- </property>
并執行hadoop namenode –format，***在使用start-all.sh啟動所有的服務，執行上傳文件成功
責任編輯：武曉燕
來源：
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