java - 运行 Apache.Spark - log4j :WARN Please initialize the log4j system properly

Question

我在加载 Spark Framework 时遇到了问题，有这种日志。log4j 有问题，我不知道发生了什么。你能给我一些如何解决问题并正确运行的建议吗？

C:\dev\spark-1.6.0-bin-hadoop2.6\bin>spark-shell
log4j:WARN No appenders could be found for logger (org.apache.hadoop.metrics2.li
b.MutableMetricsFactory).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more in
fo.
Using Spark's repl log4j profile: org/apache/spark/log4j-defaults-repl.propertie
s
To adjust logging level use sc.setLogLevel("INFO")
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 1.6.0
      /_/

Using Scala version 2.10.5 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_73)
Type in expressions to have them evaluated.
Type :help for more information.
Spark context available as sc.
16/02/25 22:20:12 WARN General: Plugin (Bundle) "org.datanucleus" is already reg
istered. Ensure you dont have multiple JAR versions of the same plugin in the cl
asspath. The URL "file:/C:/dev/spark-1.6.0-bin-hadoop2.6/bin/../lib/datanucleus-
core-3.2.10.jar" is already registered, and you are trying to register an identi
cal plugin located at URL "file:/C:/dev/spark-1.6.0-bin-hadoop2.6/lib/datanucleu
s-core-3.2.10.jar."
16/02/25 22:20:12 WARN General: Plugin (Bundle) "org.datanucleus.store.rdbms" is
 already registered. Ensure you dont have multiple JAR versions of the same plug
in in the classpath. The URL "file:/C:/dev/spark-1.6.0-bin-hadoop2.6/lib/datanuc
leus-rdbms-3.2.9.jar" is already registered, and you are trying to register an i
dentical plugin located at URL "file:/C:/dev/spark-1.6.0-bin-hadoop2.6/bin/../li
b/datanucleus-rdbms-3.2.9.jar."
16/02/25 22:20:12 WARN General: Plugin (Bundle) "org.datanucleus.api.jdo" is alr
eady registered. Ensure you dont have multiple JAR versions of the same plugin i
n the classpath. The URL "file:/C:/dev/spark-1.6.0-bin-hadoop2.6/lib/datanucleus
-api-jdo-3.2.6.jar" is already registered, and you are trying to register an ide
ntical plugin located at URL "file:/C:/dev/spark-1.6.0-bin-hadoop2.6/bin/../lib/
datanucleus-api-jdo-3.2.6.jar."
16/02/25 22:20:13 WARN Connection: BoneCP specified but not present in CLASSPATH
 (or one of dependencies)
16/02/25 22:20:13 WARN Connection: BoneCP specified but not present in CLASSPATH
 (or one of dependencies)
16/02/25 22:20:21 WARN ObjectStore: Version information not found in metastore.
hive.metastore.schema.verification is not enabled so recording the schema versio
n 1.2.0
16/02/25 22:20:21 WARN ObjectStore: Failed to get database default, returning No
SuchObjectException
16/02/25 22:20:22 WARN : Your hostname, iMEiL resolves to a loopback/non-reachab
le address: fe80:0:0:0:19ea:ffe2:e70c:3da7%wlan1, but we couldn't find any exter
nal IP address!
java.lang.RuntimeException: java.lang.NullPointerException
        at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.jav
a:522)
        at org.apache.spark.sql.hive.client.ClientWrapper.<init>(ClientWrapper.s
cala:194)
        at org.apache.spark.sql.hive.client.IsolatedClientLoader.createClient(Is
olatedClientLoader.scala:238)
        at org.apache.spark.sql.hive.HiveContext.executionHive$lzycompute(HiveCo
ntext.scala:218)
        at org.apache.spark.sql.hive.HiveContext.executionHive(HiveContext.scala
:208)
        at org.apache.spark.sql.hive.HiveContext.functionRegistry$lzycompute(Hiv
eContext.scala:462)
        at org.apache.spark.sql.hive.HiveContext.functionRegistry(HiveContext.sc
ala:461)
        at org.apache.spark.sql.UDFRegistration.<init>(UDFRegistration.scala:40)

        at org.apache.spark.sql.SQLContext.<init>(SQLContext.scala:330)
        at org.apache.spark.sql.hive.HiveContext.<init>(HiveContext.scala:90)
        at org.apache.spark.sql.hive.HiveContext.<init>(HiveContext.scala:101)
        at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)

        at sun.reflect.NativeConstructorAccessorImpl.newInstance(Unknown Source)

        at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(Unknown Sou
rce)
        at java.lang.reflect.Constructor.newInstance(Unknown Source)
        at org.apache.spark.repl.SparkILoop.createSQLContext(SparkILoop.scala:10
28)
        at $iwC$$iwC.<init>(<console>:15)
        at $iwC.<init>(<console>:24)
        at <init>(<console>:26)
        at .<init>(<console>:30)
        at .<clinit>(<console>)
        at .<init>(<console>:7)
        at .<clinit>(<console>)
        at $print(<console>)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
        at java.lang.reflect.Method.invoke(Unknown Source)
        at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:
1065)
        at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:
1346)
        at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840
)
        at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
        at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
        at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:8
57)
        at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.sca
la:902)
        at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
        at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply
(SparkILoopInit.scala:132)
        at org.apache.spark.repl.SparkILoopInit$$anonfun$initializeSpark$1.apply
(SparkILoopInit.scala:124)
        at org.apache.spark.repl.SparkIMain.beQuietDuring(SparkIMain.scala:324)
        at org.apache.spark.repl.SparkILoopInit$class.initializeSpark(SparkILoop
Init.scala:124)
        at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:64)

        at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$Spark
ILoop$$process$1$$anonfun$apply$mcZ$sp$5.apply$mcV$sp(SparkILoop.scala:974)
        at org.apache.spark.repl.SparkILoopInit$class.runThunks(SparkILoopInit.s
cala:159)
        at org.apache.spark.repl.SparkILoop.runThunks(SparkILoop.scala:64)
        at org.apache.spark.repl.SparkILoopInit$class.postInitialization(SparkIL
oopInit.scala:108)
        at org.apache.spark.repl.SparkILoop.postInitialization(SparkILoop.scala:
64)
        at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$Spark
ILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:991)
        at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$Spark
ILoop$$process$1.apply(SparkILoop.scala:945)
        at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$Spark
ILoop$$process$1.apply(SparkILoop.scala:945)
        at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClass
Loader.scala:135)
        at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$pr
ocess(SparkILoop.scala:945)
        at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
        at org.apache.spark.repl.Main$.main(Main.scala:31)
        at org.apache.spark.repl.Main.main(Main.scala)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
        at java.lang.reflect.Method.invoke(Unknown Source)
        at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSub
mit$$runMain(SparkSubmit.scala:731)
        at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:18
1)
        at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
        at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
        at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.NullPointerException
        at java.lang.ProcessBuilder.start(Unknown Source)
        at org.apache.hadoop.util.Shell.runCommand(Shell.java:482)
        at org.apache.hadoop.util.Shell.run(Shell.java:455)
        at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:
715)
        at org.apache.hadoop.util.Shell.execCommand(Shell.java:808)
        at org.apache.hadoop.util.Shell.execCommand(Shell.java:791)
        at org.apache.hadoop.fs.FileUtil.execCommand(FileUtil.java:1097)
        at org.apache.hadoop.fs.RawLocalFileSystem$DeprecatedRawLocalFileStatus.
loadPermissionInfo(RawLocalFileSystem.java:582)
        at org.apache.hadoop.fs.RawLocalFileSystem$DeprecatedRawLocalFileStatus.
getPermission(RawLocalFileSystem.java:557)
        at org.apache.hadoop.hive.ql.session.SessionState.createRootHDFSDir(Sess
ionState.java:599)
        at org.apache.hadoop.hive.ql.session.SessionState.createSessionDirs(Sess
ionState.java:554)
        at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.jav
a:508)
        ... 62 more

<console>:16: error: not found: value sqlContext
         import sqlContext.implicits._
                ^
<console>:16: error: not found: value sqlContext
         import sqlContext.sql
                ^

Answer 1

Spark 使用 log4j 进行日志记录，但是，它需要进行配置，因此您会收到这些警告。您可以通过在 conf 目录中添加一个 log4j.properties 文件来配置它。在同一目录中应该有一个 log4j.properties.template，您需要将 log4j.jar 下载到您的 Java 类路径。