How to work with Odoo Data in Apache Spark using SQL



Access and process Odoo 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 Odoo, Spark can work with live Odoo data. This article describes how to connect to and query Odoo data from a Spark shell.

The CData JDBC Driver offers unmatched performance for interacting with live Odoo data due to optimized data processing built into the driver. When you issue complex SQL queries to Odoo, the driver pushes supported SQL operations, like filters and aggregations, directly to Odoo 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 Odoo data using native data types.

About Odoo Data Integration

Accessing and integrating live data from Odoo has never been easier with CData. Customers rely on CData connectivity to:

  • Access live data from both Odoo API 8.0+ and Odoo.sh Cloud ERP.
  • Extend the native Odoo features with intelligent handling of many-to-one, one-to-many, and many-to-many data properties. CData's connectivity solutions also intelligently handle complex data properties within Odoo. In addition to columns with simple values like text and dates, there are also columns that contain multiple values on each row. The driver decodes these kinds of values differently, depending upon the type of column the value comes from:
    • Many-to-one columns are references to a single row within another model. Within CData solutions, many-to-one columns are represented as integers, whose value is the ID to which they refer in the other model.
    • Many-to-many columns are references to many rows within another model. Within CData solutions, many-to-many columns are represented as text containing a comma-separated list of integers. Each value in that list is the ID of a row that is being referenced.
    • One-to-many columns are references to many rows within another model - they are similar to many-to-many columns (comma-separated lists of integers), except that each row in the referenced model must belong to only one in the main model.
  • Use SQL stored procedures to call server-side RFCs within Odoo.

Users frequently integrate Odoo with analytics tools such as Power BI and Qlik Sense, and leverage our tools to replicate Odoo data to databases or data warehouses.


Getting Started


Install the CData JDBC Driver for Odoo

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

Start a Spark Shell and Connect to Odoo Data

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

    To connect, set the Url to a valid Odoo site, User and Password to the connection details of the user you are connecting with, and Database to the Odoo database.

    Built-in Connection String Designer

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

    java -jar cdata.jdbc.odoo.jar

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

    Configure the connection to Odoo, using the connection string generated above.

    scala> val odoo_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:odoo:User=MyUser;Password=MyPassword;URL=http://MyOdooSite/;Database=MyDatabase;").option("dbtable","res_users").option("driver","cdata.jdbc.odoo.OdooDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the Odoo data as a temporary table:

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

    scala> odoo_df.sqlContext.sql("SELECT name, email FROM res_users WHERE id = 1").collect.foreach(println)

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

Using the CData JDBC Driver for Odoo in Apache Spark, you are able to perform fast and complex analytics on Odoo data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 200+ CData JDBC Drivers and get started today.

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