forked from docs/doc-exports
Hasko, Vladimir
cfc48b3aed
Reviewed-by: Pruthi, Vineet <vineet.pruthi@t-systems.com> Co-authored-by: Hasko, Vladimir <vladimir.hasko@t-systems.com> Co-committed-by: Hasko, Vladimir <vladimir.hasko@t-systems.com>
14 lines
1.1 KiB
HTML
14 lines
1.1 KiB
HTML
<a name="dli_09_0020"></a><a name="dli_09_0020"></a>
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<h1 class="topictitle1">Overview</h1>
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<div id="body8662426"><p id="dli_09_0020__p1697165194619">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.</p>
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<p id="dli_09_0020__en-us_topic_0149356083_en-us_topic_0142920068_p17615162014209">When you use Spark jobs to access other data sources, you can use Scala, PySpark, or Java to program functions for the jobs.</p>
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</div>
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<div>
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<div class="familylinks">
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<div class="parentlink"><strong>Parent topic:</strong> <a href="dli_09_0019.html">Using Spark Jobs to Access Data Sources of Datasource Connections</a></div>
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</div>
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</div>
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