Help Center> Data Lake Insight> Developer Guide> Spark Jar Jobs> Using Spark Jobs to Access Data Sources of Datasource Connections> Overview
Updated on 2024-01-09 GMT+08:00
View PDF

Overview

DLI supports the native Spark DataSource capability and other extended capabilities. You can use SQL statements or Spark jobs to access other data storage services and import, query, analyze, and process data. Currently, DLI supports the following datasource access services: CloudTable, Cloud Search Service (CSS), Distributed Cache Service (DCS), Document Database Service (DDS), GaussDB(DWS), MapReduce Service (MRS), and Relational Database Service (RDS). To use the datasource capability of DLI, you need to create a datasource connection first.

For details about operations on the management console, see Data Lake Insight User Guide.

When you use Spark jobs to access other data sources, you can use Scala, PySpark, or Java to program functions for the jobs.