最近集群准备升级到cdh5.2.0，并使用tez，在测试集群cdh5.2.0已经稳定运行了很长时间，因此开始折腾hive on tez了，期间遇到不少问题，这里记录下。
hive on tez的部署比较简单，可以参考wiki.主要注意几个地方
1.编译的时候
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mvn clean
package
-Dtar -DskipTests=
true
-Dmaven.javadoc.skip=
true
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2.需要将tez相关的包upload到hdfs中，并设置tez-site.xml
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<property>
<name>tez.lib.uris<
/name
>
<value>${fs.defaultFS}
/tez
,${fs.defaultFS}
/tez/lib
<
/value
>
<
/property
>
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设置mapred-site.xml
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<property>
<name>mapreduce.framework.name<
/name
>
<value>yarn-tez<
/value
>
<
/property
>
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3.注意更新hadoop-env.sh中classpath的设置
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export
TEZ_HOME=
/home/vipshop/platform/tez
for
jar
in
`
ls
$TEZ_HOME |
grep
jar`;
do
export
HADOOP_CLASSPATH=$HADOOP_CLASSPATH:$TEZ_HOME/$jar
done
for
jar
in
`
ls
$TEZ_HOME
/lib
`;
do
export
HADOOP_CLASSPATH=$HADOOP_CLASSPATH:$TEZ_HOME
/lib/
$jar
done
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否则会报如下错误（加载不到对应的tez相关类，导致Cluster 初始化时失败）:
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java.io.IOException: Cannot initialize Cluster. Please check your configuration
for
mapreduce.framework.name and the correspond server addresses.
at org.apache.hadoop.mapreduce.Cluster.initialize(Cluster.java:120)
at org.apache.hadoop.mapreduce.Cluster.<init>(Cluster.java:82)
at org.apache.hadoop.mapreduce.Cluster.<init>(Cluster.java:75)
at org.apache.hadoop.mapreduce.Job$9.run(Job.java:1265)
at org.apache.hadoop.mapreduce.Job$9.run(Job.java:1261)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:396)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1614)
at org.apache.hadoop.mapreduce.Job.connect(Job.java:1260)
at org.apache.hadoop.mapreduce.Job.submit(Job.java:1289)
at org.apache.hadoop.mapreduce.Job.waitForCompletion(Job.java:1313)
at org.apache.hadoop.mapreduce.SleepJob.run(SleepJob.java:261)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)
at org.apache.hadoop.mapreduce.SleepJob.main(SleepJob.java:194)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
at java.lang.reflect.Method.invoke(Method.java:597)
at org.apache.hadoop.util.ProgramDriver$ProgramDescription.invoke(ProgramDriver.java:72)
at org.apache.hadoop.util.ProgramDriver.run(ProgramDriver.java:145)
at org.apache.hadoop.
test
.MapredTestDriver.run(MapredTestDriver.java:118)
at org.apache.hadoop.
test
.MapredTestDriver.main(MapredTestDriver.java:126)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
at java.lang.reflect.Method.invoke(Method.java:597)
at org.apache.hadoop.util.RunJar.main(RunJar.java:212)
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部署完毕后，使用hadoop jar提交tez job运行正常，测试hive on tez:
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hive -hiveconf hive.execution.engine=tez -hiveconf hive.root.logger=DEBUG,console
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出现如下报错：
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Exception
in
thread
"main"
java.lang.NoSuchMethodError:
org.apache.tez.mapreduce.hadoop.MRHelpers.updateEnvironmentForMRAM(Lorg
/apache/hadoop/conf/Configuration
;Ljava
/util/Map
;)V
at org.apache.hadoop.hive.ql.
exec
.tez.TezSessionState.
open
(TezSessionState.java:182)
at org.apache.hadoop.hive.ql.
exec
.tez.TezSessionState.
open
(TezSessionState.java:123)
at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:355)
at org.apache.hadoop.hive.cli.CliDriver.run(CliDriver.java:681)
at org.apache.hadoop.hive.cli.CliDriver.main(CliDriver.java:625)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
at java.lang.reflect.Method.invoke(Method.java:597)
at org.apache.hadoop.util.RunJar.main(RunJar.java:212)
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从堆栈上来看是由于session初始化异常导致，
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org.apache.hadoop.hive.cli.CliDriver.main->org.apache.hadoop.hive.cli.CliDriver.run->
org.apache.hadoop.hive.ql.session.SessionState.start
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在SessionState.start方法中:
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if
(HiveConf.getVar(startSs.getConf(), HiveConf.ConfVars.HIVE_EXECUTION_ENGINE)
.equals(
"tez"
) && (startSs.isHiveServerQuery ==
false
)) {
//如果设置hive.execution.engine为tez（默认为mr）
try
{
if
(startSs.tezSessionState ==
null
) {
startSs.tezSessionState =
new
TezSessionState(startSs.getSessionId());
//实例化一个TezSessionState对象
}
startSs.tezSessionState.open(startSs.conf );
//调用TezSessionState.open方法
}
catch
(Exception e) {
throw
new
RuntimeException(e);
}
}
else
{
LOG.info(
"No Tez session required at this point. hive.execution.engine=mr."
);
}
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TezSessionState.open中，首先使用createTezDir创建临时文件目录
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// create the tez tmp dir
tezScratchDir = createTezDir(sessionId);
String dir = tezScratchDir.toString();
// Localize resources to session scratch dir
localizedResources = utils.localizeTempFilesFromConf(dir, conf);
//DagUtils.localizeTempFilesFromConf方法
List<LocalResource> handlerLr = utils.localizeTempFiles(dir, conf, additionalFiles);
// DagUtils.localizeTempFiles方法
if
(handlerLr !=
null
) {
if
(localizedResources ==
null
) {
localizedResources = handlerLr;
}
else
{
localizedResources.addAll(handlerLr);
}
additionalFilesNotFromConf =
new
HashSet<String>();
for
(String originalFile : additionalFiles) {
additionalFilesNotFromConf.add(originalFile);
}
}
// generate basic tez config
TezConfiguration tezConfig =
new
TezConfiguration(conf);
//然后实例化一个TezConfiguration对象
tezConfig.set(TezConfiguration.TEZ_AM_STAGING_DIR, tezScratchDir.toUri().toString());
//设置tez的staging目录，设置项为tez.staging-dir，默认值为/tmp/tez/staging
//这里默认最终为"/tmp/hive-" + System. getProperty( "user.name")/_tez_session_dir/sessionId
appJarLr = createJarLocalResource(utils.getExecJarPathLocal());
//localize hive-exec.jar
// configuration for the application master
Map<String, LocalResource> commonLocalResources =
new
HashMap<String, LocalResource>();
commonLocalResources.put( utils.getBaseName( appJarLr), appJarLr );
if
(localizedResources !=
null
) {
for
(LocalResource lr : localizedResources) {
commonLocalResources.put( utils.getBaseName(lr), lr);
}
}
// Create environment for AM.
Map<String, String> amEnv =
new
HashMap<String, String>();
MRHelpers.updateEnvironmentForMRAM(conf, amEnv);
//调用MRHelpers类的updateEnvironmentForMRAM方法
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对于org.apache.tez.mapreduce.hadoop.MRHelpers类来说，在0.5.0中，这个updateEnvironmentForMRAM方法是不存在的，对应存在updateEnvBasedOnMRTaskEnv（配置Mappers和Reducers的环境变量）和updateEnvBasedOnMRAMEnv（配置am的环境变量）
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public
static
void
updateEnvBasedOnMRAMEnv(Configuration conf, Map<String, String> environment) {
TezYARNUtils.appendToEnvFromInputString(environment, conf.get(MRJobConfig.MR_AM_ADMIN_USER_ENV),
File.pathSeparator);
TezYARNUtils.appendToEnvFromInputString(environment, conf.get(MRJobConfig.MR_AM_ENV),
File.pathSeparator);
}
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而在0.4.1-incubating中是有updateEnvironmentForMRAM这个方法的：
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public
static
void
updateEnvironmentForMRAM(Configuration conf, Map<String, String> environment) {
TezYARNUtils.setEnvFromInputString(environment, conf.get(MRJobConfig.MR_AM_ADMIN_USER_ENV),
File.pathSeparator);
TezYARNUtils.setEnvFromInputString(environment, conf.get(MRJobConfig.MR_AM_ENV),
File.pathSeparator);
}
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对应的hive中：
hive0.13中：
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// Create environment for AM.
Map<String, String> amEnv =
new
HashMap<String, String>();
MRHelpers.updateEnvironmentForMRAM(conf, amEnv);
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hive0.14中：
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// Create environment for AM.
Map<String, String> amEnv =
new
HashMap<String, String>();
MRHelpers.updateEnvBasedOnMRAMEnv(conf, amEnv);
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可以看到0.4.x到0.5.x版本的tez api变动比较大，0.5.x的tez已经和hive0.13.x不能兼容了，要想使用tez-0.5.x版本，必须使用hive0.14.x版本。
在github下载hive0.14的源码，编译并测试运行hive on tez:
https://codeload.github.com/apache/hive/zip/branch-0.14
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mvn clean
package
-DskipTests -Phadoop-
2
-Pdist
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本文转自菜菜光 51CTO博客，原文链接：http://blog.51cto.com/caiguangguang/1604087，如需转载请自行联系原作者
