Query Apache Hive through the JDBC driver in HDInsight
Learn how to use the JDBC driver from a Java application to submit Apache Hive queries to Apache Hadoop in Azure HDInsight. The information in this document demonstrates how to connect programmatically and from the SQuirrel SQL client.
For more information on the Hive JDBC Interface, see HiveJDBCInterface.
A Hadoop on HDInsight cluster.
Linux is the only operating system used on HDInsight version 3.4 or greater. For more information, see HDInsight 3.3 retirement.
SQuirreL SQL. SQuirreL is a JDBC client application.
The Java Developer Kit (JDK) version 7 or higher.
Apache Maven. Maven is a project build system for Java projects that is used by the project associated with this article.
JDBC connection string
JDBC connections to an HDInsight cluster on Azure are made over 443, and the traffic is secured using SSL. The public gateway that the clusters sit behind redirects the traffic to the port that HiveServer2 is actually listening on. The following connection string shows the format to use for HDInsight:
CLUSTERNAME with the name of your HDInsight cluster.
When establishing the connection, you must use the HDInsight cluster admin name and password to authenticate to the cluster gateway. When connecting from JDBC clients such as SQuirreL SQL, you must enter the admin name and password in client settings.
From a Java application, you must use the name and password when establishing a connection. For example, the following Java code opens a new connection using the connection string, admin name, and password:
Connect with SQuirreL SQL client
SQuirreL SQL is a JDBC client that can be used to remotely run Hive queries with your HDInsight cluster. The following steps assume that you have already installed SQuirreL SQL.
Create a directory that contains the files. For example,
From a command line, use the following commands to copy the files from the HDInsight cluster:
scp USERNAME@CLUSTERNAME:/usr/hdp/current/hadoop-client/hadoop-common.jar . scp USERNAME@CLUSTERNAME:/usr/hdp/current/hadoop-client/hadoop-auth.jar . scp USERNAME@CLUSTERNAME:/usr/hdp/current/hadoop-client/lib/log4j-*.jar . scp USERNAME@CLUSTERNAME:/usr/hdp/current/hadoop-client/lib/slf4j-*.jar . scp USERNAME@CLUSTERNAME:/usr/hdp/current/hive-client/lib/hive-*-1.2*.jar . scp USERNAME@CLUSTERNAME:/usr/hdp/current/hive-client/lib/httpclient-*.jar . scp USERNAME@CLUSTERNAME:/usr/hdp/current/hive-client/lib/httpcore-*.jar . scp USERNAME@CLUSTERNAME:/usr/hdp/current/hive-client/lib/libthrift-*.jar . scp USERNAME@CLUSTERNAME:/usr/hdp/current/hive-client/lib/libfb*.jar . scp USERNAME@CLUSTERNAME:/usr/hdp/current/hive-client/lib/commons-logging-*.jar .
USERNAMEwith the SSH user account name for the cluster. Replace
CLUSTERNAMEwith the HDInsight cluster name.
Start the SQuirreL SQL application. From the left of the window, select Drivers.
From the icons at the top of the Drivers dialog, select the + icon to create a driver.
In the Add Driver dialog, add the following information:
- Name: Hive
- Example URL:
- Extra Class Path: Use the Add button to add the all of jar files downloaded earlier
- Class Name: org.apache.hive.jdbc.HiveDriver
Click OK to save these settings.
On the left of the SQuirreL SQL window, select Aliases. Then click the + icon to create a connection alias.
Use the following values for the Add Alias dialog.
Name: Hive on HDInsight
Driver: Use the dropdown to select the Hive driver
Replace CLUSTERNAME with the name of your HDInsight cluster.
User Name: The cluster login account name for your HDInsight cluster. The default is
Password: The password for the cluster login account.
Use the Test button to verify that the connection works. When Connect to: Hive on HDInsight dialog appears, select Connect to perform the test. If the test succeeds, you see a Connection successful dialog. If an error occurs, see Troubleshooting.
To save the connection alias, use the Ok button at the bottom of the Add Alias dialog.
From the Connect to dropdown at the top of SQuirreL SQL, select Hive on HDInsight. When prompted, select Connect.
Once connected, enter the following query into the SQL query dialog, and then select the Run icon. The results area should show the results of the query.
select * from hivesampletable limit 10;
Connect from an example Java application
An example of using a Java client to query Hive on HDInsight is available at https://github.com/Azure-Samples/hdinsight-java-hive-jdbc. Follow the instructions in the repository to build and run the sample.
Unexpected Error occurred attempting to open an SQL connection
Symptoms: When connecting to an HDInsight cluster that is version 3.3 or greater, you may receive an error that an unexpected error occurred. The stack trace for this error begins with the following lines:
java.util.concurrent.ExecutionException: java.lang.RuntimeException: java.lang.NoSuchMethodError: org.apache.commons.codec.binary.Base64.<init>(I)V at java.util.concurrent.FutureTas...(FutureTask.java:122) at java.util.concurrent.FutureTask.get(FutureTask.java:206)
Cause: This error is caused by an older version commons-codec.jar file included with SQuirreL.
Resolution: To fix this error, use the following steps:
Download the commons-codec jar file from your HDInsight cluster.
scp USERNAME@CLUSTERNAME:/usr/hdp/current/hive-client/lib/commons-codec*.jar ./commons-codec.jar
Exit SQuirreL, and then go to the directory where SQuirreL is installed on your system. In the SquirreL directory, under the
libdirectory, replace the existing commons-codec.jar with the one downloaded from the HDInsight cluster.
Restart SQuirreL. The error should no longer occur when connecting to Hive on HDInsight.
Now that you have learned how to use JDBC to work with Hive, use the following links to explore other ways to work with Azure HDInsight.
- Visualize Hive data with Microsoft Power BI in Azure HDInsight.
- Visualize Interactive Query Hive data with Power BI in Azure HDInsight.
- Use Zeppelin to run Hive queries in Azure HDInsight.
- Connect Excel to HDInsight with the Microsoft Hive ODBC Driver.
- Connect Excel to Hadoop by using Power Query.
- Connect to Azure HDInsight and run Hive queries using Data Lake Tools for Visual Studio.
- Use Azure HDInsight Tool for Visual Studio Code.
- Upload data to HDInsight
- Use Hive with HDInsight
- Use Pig with HDInsight
- Use MapReduce jobs with HDInsight