Question

我们有两个节点hadoop纱线群集，它是hadoop 2.2，我们已经使用oozie在一个工作流程中安排了两个动作，第一个动作是 python map-reduce流动作 ，第二个是 sqoop export 作业，它实际上将map-reduce流动作的输出传输到mysql数据库。

成功执行流式传输操作，这将导致sqoop作业的启动，该作业将一直运行。

stdout 会产生以下结果。

Sqoop command arguments :
         export
         --connect
         jdbc:mysql://localhost/database
         --username
         root
         --password
         root
         --table
         tableName
         --direct
         --export-dir
        /user/hduser/oozieProject/workflow/output

 =================================================================
Invoking Sqoop command line now >>>

2137 [main] WARN  org.apache.sqoop.tool.SqoopTool  - $SQOOP_CONF_DIR has not been set in the environment. Cannot check for additional configuration.
2158 [main] INFO  org.apache.sqoop.Sqoop  - Running Sqoop version: 1.4.4.2.0.6.1-102
2170 [main] WARN  org.apache.sqoop.tool.BaseSqoopTool  - Setting your password on the command-line is insecure. Consider using -P instead.
2178 [main] WARN  org.apache.sqoop.ConnFactory  - $SQOOP_CONF_DIR has not been set in the environment. Cannot check for additional configuration.
2197 [main] INFO  org.apache.sqoop.manager.MySQLManager  - Preparing to use a MySQL streaming resultset.
2197 [main] INFO  org.apache.sqoop.tool.CodeGenTool  - Beginning code generation
2464 [main] INFO  org.apache.sqoop.manager.SqlManager  - Executing SQL statement:     SELECT t.* FROM `missedCalls` AS t LIMIT 1
2483 [main] INFO  org.apache.sqoop.manager.SqlManager  - Executing SQL statement: SELECT t.* FROM `missedCalls` AS t LIMIT 1
2485 [main] INFO  org.apache.sqoop.orm.CompilationManager  - HADOOP_MAPRED_HOME is /usr/local/hadoop
3838 [main] INFO  org.apache.sqoop.orm.CompilationManager  - Writing jar file: /tmp/sqoop-hduser/compile/21bd1d5fe13adeed4f46a09f8b3d38fe/missedCalls.jar
3847 [main] INFO  org.apache.sqoop.mapreduce.ExportJobBase  - Beginning export of missedCalls
Heart beat
Heart beat
Heart beat
Heart beat
Heart beat
Heart beat
Heart beat
Heart beat

作业属性如下

nameNode=hdfs://master:54310
jobTracker=master:8035
queueName=default

oozie.libpath=${nameNode}/user/hduser/share/lib
oozie.use.system.libpath=true
oozie.wf.rerun.failnodes=true

oozieProjectRoot=${nameNode}/user/hduser/oozieProject
appPath=${oozieProjectRoot}/workflow
oozie.wf.application.path=${appPath}
oozieLibPath=${oozie.libpath}

mapred.tasktracker.map.tasks.maximum=4
mapred.tasktracker.reduce.tasks.maximum=4

inputDir=${oozieProjectRoot}/data/*
outputDir=${appPath}/output

工作流程xml如下

<!--Oozie workflow file: workflow.xml --> 
<workflow-app name="WorkflowStreamingMRAction-Python" xmlns="uri:oozie:workflow:0.1">
<start to="streamingaAction"/>
<action name="streamingaAction">
    <map-reduce>
        <job-tracker>${jobTracker}</job-tracker>
        <name-node>${nameNode}</name-node>
        <prepare>
            <delete path="${outputDir}"/>
        </prepare>
        <streaming>
            <mapper>python mapper.py</mapper>
            <reducer>python reducer.py</reducer>
        </streaming>
        <configuration>
            <property>
                <name>oozie.libpath</name>
                <value>${oozieLibPath}/mapreduce-streaming</value>
            </property>
            <property>
                <name>mapred.input.dir</name>
                <value>${inputDir}</value>
            </property>
            <property>
                <name>mapred.output.dir</name>
                <value>${outputDir}</value>
            </property>
            <property>
                <name>mapred.reduce.tasks</name>
                <value>4</value>
            </property>
        </configuration>
        <file>${appPath}/mapper.py#mapper.py</file>
        <file>${appPath}/reducer.py#reducer.py</file>
    </map-reduce>
    <ok to="sqoopAction"/>
    <error to="killJobAction"/>
    </action>

    <action name="sqoopAction">
        <sqoop xmlns="uri:oozie:sqoop-action:0.2">
            <job-tracker>${jobTracker}</job-tracker>
            <name-node>${nameNode}</name-node>
            <command>export --connect jdbc:mysql://localhost/database --username root --password myPwd --table tableName --direct --export-dir /user/hduser/oozieProject/workflow/output</command>
        </sqoop>        
    <ok to="end"/>
    <error to="killJobAction"/>
    </action>
<kill name="killJobAction">
<message>"Killed job due to error: ${wf:errorMessage(wf:lastErrorNode())}"</message>
</kill>
<end name="end" />

请告知可能出错的地方？

谢谢

Answer 1

它没有永远运行。你只需要等待。

首先，您在上面看到的Sqoop出口工作只是一个Oozie计划工作。 Heart beat表示它现在正在运行。你只需要等待。实际上你可以进入YARN资源管理器页面（通常是http：// $ namenode：8088 / cluster），然后你可以找到＆＃34; real＆＃34; Sqoop出口工作。（我想默认的映射器数量是4。）

其次，Sqoop执行＆＃34; export＆＃34;通过使用INSERT语句，所以它相对较慢。当表很大时，我建议不要使用Sqoop导出，例如，当它有超过100万个条目时。

第三，既然我注意到你试图导出到MySQL，你可以尝试批处理模式，它以这种方式运行INSERT查询：INSERT INTO <TABLE> VALUES (<ROW1>), (<ROW2>), etc.

因此您可以将命令更改为： sqoop export -D sqoop.export.records.per.statement=1000 --connect jdbc:mysql://localhost/database --username root --password myPwd --table tableName --direct --export-dir /user/hduser/oozieProject/workflow/output --batch

Sqoop工作永远使用Oozie运行

1 个答案: