Databricks

Audience: Data Users

Content Summary: This page offers a tutorial on how to query data within the Databricks integration.

Prerequisites:

• Databricks integration configured with Immuta

• Databricks tables registered as Immuta data sources

Query Data with Python

1. Create a new workspace.

2. Query the Immuta-protected data, which takes the form of database.table_name:

   1. Database: The database that houses the backing tables of your Immuta data sources.

   2. Table Name: The name of the table backing your Immuta data sources.

3. Run your query, it should look something like:

   df = spark.sql('select * from database.table_name')
   df.show()

Query Data with SQL

1. Create a new workspace.

2. Query the Immuta-protected data, which takes the form of database.table_name:

   1. Database: The database that houses the backing tables of your Immuta data sources.

   2. Table Name: The name of the table backing your Immuta data sources.

3. Run your query. It should look something like this:

   select * from database.table_name;

Query Data with SparkR

Establish the User's Identity

1. Create a new workspace.

2. Run:

   library(SparkR)

Run a Query

1. In the same workspace, but a different cell, query the Immuta-protected data, which takes the form of database.table_name:

   1. Database: The database that houses the backing tables of your Immuta data sources.

   2. Table Name: The name of the table backing your Immuta data sources.

2. Run your query. It should look something like this:

   df <- SparkR::sql("select * from database.table_name")
   SparkR::head(df)

Query Data with Scala

1. Query the Immuta-protected data, which takes the form of database.table_name:

   1. Database: The database that houses the backing tables of your Immuta data sources.

   2. Table Name: The name of the table backing your Immuta data sources.

2. Run your query. It should look something like this:

   val sqlDF = spark.sql("select * from database.tablename")
   sqlDF.show()