Apache Spark SQL (with Hive Metastore)

Apache Spark is a computing system with APIs in Java, Scala and Python. It allows fast processing and analasis of large chunks of data thanks to parralleled computing paradigm.

In order to query data stored in HDFS Apache Spark connects to a Hive Metastore. If Spark instances use External Hive Metastore Dataedo can be used to document that data.

Connector

Supported Versions

Hive Metastore 3.x

Supported Metadata

• Tables
  • Table type:
    • Managed Table
    • Index Table
    • External Table
  • Columns:
    • Data type
    • Nullable
    • Default value
    • Check constraint
    • Unqiue constraint
  • Primary keys
    • Columns
  • Foreign keys
    • Columns
  • Relations
• Views
  • View type:
    • Materialized view
    • Virtual view
  • Columns (see Tables)

Connect to Apache Spark with External Hive Metastore

Get connection details

If Spark uses an external Hive Metastore you will find hive-site.xml file, which contains a configuration of Hive Metastore database connection, in conf directory in Spark catalog. In this file you need to look for properties:

• javax.jdo.option.ConnectionURL
• javax.jdo.option.ConnectionUserName
• javax.jdo.option.ConnectionPassword

or, in case if your Spark instance connects to a Hive Metastore Service:

• hive.metastore.uris

In both cases you will find the properties in configuration element of hive-site.xml file.

<configuration>
...
...
...
<property>
    <name>javax.jdo.option.ConnectionURL</name>
    <value>jdbc:mysql://10.10.10.10:3306/hive_metastore?createDatabaseIfNotExist=true</value>
</property>

<property>
    <name>javax.jdo.option.ConnectionUserName</name>
    <value>Hive</value>
</property>

<property>
    <name>javax.jdo.option.ConnectionPassword</name>
    <value>verySecurePassword</value>
</property>
....
....
....
</configuration>

or

<configuration>
....
....
....
<property>
    <name>hive.metastore.uris</name>
    <value></value>
    <description>Thrift uri for the remote metastore. Used by metastore client to connect to remote metastore</description>
</property>
....
....
....
</configuration>

Once you have all the properties, you need to get the connection details. If your Spark instance connects to Hive Metastore Service, connect to a server to which uri points and follow the Hive Metastore connector instruction. Otherwise extract the details as follows:

• javax.jdo.option.ConnectionUserName - Dataedo username.
• javax.jdo.option.ConnectionPassword - Dataedo password.
• javax.jdo.option.ConnectionURL - here you need to extract infromation from jdbc connection string which has format: jdbc:[database_engine]://[database_address]:[database_port]/[metastore_database]?others_options. Previous example of configuration uses MySQL jdbc connector, although others database engines also follow the convention.

In our example, collected data is:

• database: mysql
• host: 10.10.10.10
• port: 3306
• user: Hive
• password: verySecurePassword
• metastore_database: hive_metastore

Add new connection

To connect to Hive Metastore and create new documentation by clicking Add documentation and choosing Database connection.

On the connection screen choose Apache Spark (with external Hive Metastore) as DBMS.

You need to select database engine hosting Hive Metastore:

Connection details

Then you need to provide connection details accordingly for selected database:

• Connect to Azure SQL
• Connect to MariaDB
• Connect to Postgres
• Connect to MySQL
• Connect to SQL Server

Following connection example will be based on MySQL, although others databases will have similar fields required for connection:

• Host - hostname or IP address of server on which database is available,
• Port - port under which database is available,
• User - username,
• Password - password,
• Metastore database - name of MySQL database hosting the metastore. You can expand list of databases by clicking ... button.
• Database - name of Hive database. You can expand list of databases by clicking ... button. You will get a table of Hive databases with Database Name, Description, Catalog Name and Catalog description columns:

Obtaining all details is described in section Get connection details.

Importing metadata

When connection was successful Dataedo will read objects and show a list of objects found. You can choose which objects to import. You can also use advanced filter to narrow down list of objects.

Confirm list of objects to import by clicking Next.

Next screen allow you to change default name of the documentation under which it will be visible in Dataedo repository.

Click Import to start the import. Once import is done, close import window with Finish button.

Outcome

Your database has been imported to new documentation in the repository.