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Work with Alfresco Data in Apache Spark Using SQL

Access and process Alfresco Data in Apache Spark using the CData JDBC Driver.

Apache Spark is a fast and general engine for large-scale data processing. When paired with the CData JDBC Driver for Alfresco, Spark can work with live Alfresco data. This article describes how to connect to and query Alfresco data from a Spark shell.

The CData JDBC Driver offers unmatched performance for interacting with live Alfresco data due to optimized data processing built into the driver. When you issue complex SQL queries to Alfresco, the driver pushes supported SQL operations, like filters and aggregations, directly to Alfresco and utilizes the embedded SQL engine to process unsupported operations (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can work with and analyze Alfresco data using native data types.

Install the CData JDBC Driver for Alfresco

Download the CData JDBC Driver for Alfresco installer, unzip the package, and run the JAR file to install the driver.

Start a Spark Shell and Connect to Alfresco Data

  1. Open a terminal and start the Spark shell with the CData JDBC Driver for Alfresco JAR file as the jars parameter: $ spark-shell --jars /CData/CData JDBC Driver for Alfresco/lib/cdata.jdbc.alfresco.jar
  2. With the shell running, you can connect to Alfresco with a JDBC URL and use the SQL Context load() function to read a table.

    To connect to Alfresco, the following connection properties must be supplied: User, Password, and InstanceUrl. User and Password correspond to the login credentials that you use to access Alfresco in a web browser. InstanceUrl corresponds to the Alfresco instance you will be querying. For instance, if you expect your queries to hit https://search-demo.dev.alfresco.me/alfresco/api/-default-/public/search/versions/1/sql, you should supply search-demo.dev.alfresco.me for InstanceUrl.

    Built-in Connection String Designer

    For assistance in constructing the JDBC URL, use the connection string designer built into the Alfresco JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

    java -jar cdata.jdbc.alfresco.jar

    Fill in the connection properties and copy the connection string to the clipboard.

    scala> val alfresco_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:alfresco:User=MyUsername; Password=MyPassword; Format=Solr; InstanceUrl=api-explorer.alfresco.com;").option("dbtable","Alfresco").option("driver","cdata.jdbc.alfresco.AlfrescoDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the Alfresco data as a temporary table:

    scala> alfresco_df.registerTable("alfresco")
  5. Perform custom SQL queries against the Data using commands like the one below:

    scala> alfresco_df.sqlContext.sql("SELECT DBID, Column1 FROM Alfresco WHERE Column2 = MyFilter").collect.foreach(println)

    You will see the results displayed in the console, similar to the following:

Using the CData JDBC Driver for Alfresco in Apache Spark, you are able to perform fast and complex analytics on Alfresco data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 170+ CData JDBC Drivers and get started today.