Help Center> MapReduce Service> Developer Guide (Normal_Earlier Than 3.x)> Hive Application Development> Application Commissioning> Commissioning Applications on Linux> Running HCatalog and Viewing Results
Updated on 2022-06-01 GMT+08:00
View PDF

Running HCatalog and Viewing Results

  1. Run the mvn package command to generate a JAR file, for example, hive-examples-1.0.jar, and obtain it from the target directory in the project directory.
  2. Upload the hive-examples-1.0.jar package generated in the previous step to a specified path on Linux, for example, /opt/hive_examples, marked as $HCAT_CLIENT, and ensure that the client has been installed.

    export HCAT_CLIENT=/opt/hive_examples/

  3. Run the following command to configure environment variables (client installation path /opt/client is used as an example):

     
 export HADOOP_HOME=/opt/client/HDFS/hadoop 
 export HIVE_HOME=/opt/client/Hive/Beeline 
 export HCAT_HOME=$HIVE_HOME/../HCatalog 
 export LIB_JARS=$HCAT_HOME/lib/hive-hcatalog-core-1.3.0.jar,$HCAT_HOME/lib/hive-metastore-1.3.0.jar,$HIVE_HOME/lib/hive-exec-1.3.0.jar,$HCAT_HOME/lib/libfb303-0.9.3.jar,$HCAT_HOME/lib/slf4j-api-1.7.5.jar,$HCAT_HOME/lib/antlr-2.7.7.jar,$HCAT_HOME/lib/jdo-api-3.0.1.jar,$HCAT_HOME/lib/antlr-runtime-3.4.jar,$HCAT_HOME/lib/datanucleus-api-jdo-3.2.6.jar,$HCAT_HOME/lib/datanucleus-core-3.2.10.jar,$HCAT_HOME/lib/datanucleus-rdbms-3.2.9.jar 
 export HADOOP_CLASSPATH=$HCAT_HOME/lib/hive-hcatalog-core-1.3.0.jar:$HCAT_HOME/lib/hive-metastore-1.3.0.jar:$HIVE_HOME/lib/hive-exec-1.3.0.jar:$HCAT_HOME/lib/libfb303-0.9.3.jar:$HADOOP_HOME/etc/hadoop:$HCAT_HOME/conf:$HCAT_HOME/lib/slf4j-api-1.7.5.jar:$HCAT_HOME/lib/antlr-2.7.7.jar:$HCAT_HOME/lib/jdo-api-3.0.1.jar:$HCAT_HOME/lib/antlr-runtime-3.4.jar:$HCAT_HOME/lib/datanucleus-api-jdo-3.2.6.jar:$HCAT_HOME/lib/datanucleus-core-3.2.10.jar:$HCAT_HOME/lib/datanucleus-rdbms-3.2.9.jar

    Before importing the preceding environment variables, check whether the current JAR file exists. You can obtain the version number from the lib directory of Hive on the client.

  4. Prepare for the client running.

    1. If the Kerberos authentication is enabled for the current cluster, run the following command to authenticate the user. If the Kerberos authentication is disabled for the current cluster, skip this step. The current user is the development user added in Preparing a Development User.

      Human-machine user: kinit MRS cluster user

      For example, kinit hiveuser.

      Machine-machine user: kinit -kt <user.keytab path> <MRS cluster user>

      For example, kinit -kt /opt/hive_examples/conf/user.keytab hiveuser

      When connecting to a security cluster, add the following parameters to the HCatalog configuration file (for example, /opt/client/Hive/HCatalog/conf/hive-site.xml) on the Hive client:

      <property>
<name>hive.metastore.sasl.enabled</name>
<value>true</value>
</property>
    2. Use the Hive client to create source table t1 in beeline: create table t1(col1 int);

      Run the insert into t1(col1) values(X); command to insert the following data into t1. In the command, X indicates the data value to be inserted.

       
    +----------+--+ 
    | t1.col1  | 
    +----------+--+ 
    | 1        | 
    | 1        | 
    | 1        | 
    | 2        | 
    | 2        | 
    | 3        |
    3. Create destination table t2: create table t2(col1 int,col2 int);

  5. Use the YARN client to submit a task.

    yarn --config $HADOOP_HOME/etc/hadoop jar $HCAT_CLIENT/hive-examples-1.0.jar com.huawei.bigdata.hive.example.HCatalogExample -libjars $LIB_JARS t1 t2

  6. View the running result. The data in t2 is as follows:

    0: jdbc:hive2://192.168.1.18:24002,192.168.1.> select * from t2; 
 +----------+----------+--+ 
 | t2.col1  | t2.col2  | 
 +----------+----------+--+ 
 | 1        | 3        | 
 | 2        | 2        | 
 | 3        | 1        | 
 +----------+----------+--+