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Fusion SQL Architecture

layout: default title: Fusion SQL Architecture toc: true skip: all ---

The following diagram depicts a common Fusion SQL service deployment scenario using the Kerberos network authentication protocol for single sign-on. Integration with Kerberos is optional. By default, the Fusion SQL service uses Fusion security for authentication and authorization.

Fusion SQL service architecture

The numbered steps in the diagram are:

  1. The JDBC/ODBC client application (for example, TIBCO Spotfire or Tableau) uses Kerberos to authenticate a Fusion data analyst.

  2. After authentication, the JDBC/ODBC client application sends the user’s SQL query to the Fusion SQL Thrift Server over HTTP.

  3. The SQL Thrift Server uses the keytab of the Kerberos service principal to validate the incoming user identity.

    The Fusion SQL Thrift Server is a Spark application with a specific number of CPU cores and memory allocated from the pool of Spark resources. You can scale out the number of Spark worker nodes to increase available memory and CPU resources to the Fusion SQL service.

  4. The Thrift Server sends the query to Spark to be parsed into a logical plan.

  5. During the query planning stage, Spark sends the logical plan to Fusion’s pushdown strategy component.

  6. During pushdown analysis, Fusion calls out to the registered AuthZ FilterProvider implementation to get a filter query to perform row-level filtering for the Kerberos-authenticated user.

    By default, there is no row-level security provider but users can install their own implementation using the Fusion SQL service API.

  7. Spark executes a distributed Solr query to return documents that satisfy the SQL query criteria and row-level security filter. To leverage the distributed nature of Spark and Solr, Fusion SQL sends a query to all replicas for each shard in a Solr collection. Consequently, you can scale out SQL query performance by adding more Spark and/or Solr resources to your cluster.