Apache Spark

This page contains information about connecting Looker to Apache Spark 3.

Looker connects to Apache Spark 3+ through a JDBC connection to the Spark Thrift Server.

Encrypting network traffic

It is a best practice to encrypt network traffic between the Looker application and your database. Consider one of the options described on the Enabling secure database access documentation page.

Creating the Looker connection to your database

In the Admin section of Looker, select Connections, and then click Add Connection.

Fill out the connection details. The majority of the settings are common to most database dialects. See the Connecting Looker to your database documentation page for information. Some of the settings are described next:

  • Name: The name of the connection. This is how the connection will be referred to in the LookML model.
  • Dialect: Select Apache Spark 3+.
  • Host: The Thrift server host.
  • Port The Thrift server port (10000 by default).
  • Database: The default schema/database that will be modeled. When no database is specified for a table, this will be assumed.
  • Username: The user that Looker will authenticate as.
  • Password: The optional password for Looker user.
  • Enable PDTs: Use this toggle to enable persistent derived tables. When PDTs are enabled, the Connection window reveals additional PDT settings and the PDT Overrides section.
  • Temp Database: A temporary schema/database for storing PDTs. It must be created beforehand, with a statement such as CREATE SCHEMA looker_scratch;.
  • Additional JDBC parameters: Add any additional Hive JDBC parameters here, such as:
    • ;spark.sql.inMemoryColumnarStorage.compressed=true
    • ;auth=noSasl
  • SSL: Leave this unchecked.
  • Database Time Zone: The time zone of data stored in Spark. Usually it can be left blank or set to UTC.
  • Query Time Zone: The time zone to display data queried in Looker.

To verify that the connection is successful, click Test. See the Testing database connectivity documentation page for troubleshooting information.

To save these settings, click Connect.

Feature support

For Looker to support some features, your database dialect must also support them.

Apache Spark 3+

Apache Spark 3+ supports the following features as of Looker 24.18:

Feature Supported?
Support Level
Supported
Looker (Google Cloud core)
Yes
Symmetric Aggregates
Yes
Derived Tables
Yes
Persistent SQL Derived Tables
Yes
Persistent Native Derived Tables
Yes
Stable Views
Yes
Query Killing
Yes
SQL-based Pivots
Yes
Timezones
Yes
SSL
Yes
Subtotals
Yes
JDBC Additional Params
Yes
Case Sensitive
Yes
Location Type
Yes
List Type
Yes
Percentile
Yes
Distinct Percentile
No
SQL Runner Show Processes
No
SQL Runner Describe Table
Yes
SQL Runner Show Indexes
No
SQL Runner Select 10
Yes
SQL Runner Count
Yes
SQL Explain
Yes
Oauth Credentials
No
Context Comments
Yes
Connection Pooling
No
HLL Sketches
No
Aggregate Awareness
Yes
Incremental PDTs
No
Milliseconds
Yes
Microseconds
Yes
Materialized Views
No
Approximate Count Distinct
No

Next steps

After you have created the connection, set authentication options.