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    <title>topic what mode is the deploy-mode when calling spark in databricks/ in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/what-mode-is-the-deploy-mode-when-calling-spark-in-databricks/m-p/5292#M1745</link>
    <description>&lt;P&gt;&lt;A href="https://spark.apache.org/docs/latest/submitting-applications.html" target="test_blank"&gt;https://spark.apache.org/docs/latest/submitting-applications.html&lt;/A&gt;&lt;/P&gt;&lt;P&gt;mainly want to know if extra class path could be used or not when i submit a job &lt;/P&gt;</description>
    <pubDate>Tue, 25 Apr 2023 14:34:12 GMT</pubDate>
    <dc:creator>source2sea</dc:creator>
    <dc:date>2023-04-25T14:34:12Z</dc:date>
    <item>
      <title>what mode is the deploy-mode when calling spark in databricks/</title>
      <link>https://community.databricks.com/t5/data-engineering/what-mode-is-the-deploy-mode-when-calling-spark-in-databricks/m-p/5292#M1745</link>
      <description>&lt;P&gt;&lt;A href="https://spark.apache.org/docs/latest/submitting-applications.html" target="test_blank"&gt;https://spark.apache.org/docs/latest/submitting-applications.html&lt;/A&gt;&lt;/P&gt;&lt;P&gt;mainly want to know if extra class path could be used or not when i submit a job &lt;/P&gt;</description>
      <pubDate>Tue, 25 Apr 2023 14:34:12 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/what-mode-is-the-deploy-mode-when-calling-spark-in-databricks/m-p/5292#M1745</guid>
      <dc:creator>source2sea</dc:creator>
      <dc:date>2023-04-25T14:34:12Z</dc:date>
    </item>
    <item>
      <title>Re: what mode is the deploy-mode when calling spark in databricks/</title>
      <link>https://community.databricks.com/t5/data-engineering/what-mode-is-the-deploy-mode-when-calling-spark-in-databricks/m-p/5293#M1746</link>
      <description>&lt;P&gt;@min shi​&amp;nbsp;:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;In Databricks, when you run a job, you are submitting a Spark application to run in the cluster. The deploy-mode that is used by default depends on the type of job you are running:&lt;/P&gt;&lt;P&gt;For interactive clusters, the deploy-mode is client. This means that the driver program runs on the client machine that submitted the job.&lt;/P&gt;&lt;P&gt;For job clusters, the deploy-mode is cluster. This means that the driver program runs on one of the worker nodes in the cluster.&lt;/P&gt;&lt;P&gt;Note that in Databricks, you do not need to explicitly specify the deploy-mode when submitting a job. Instead, you can simply use the spark-submit command provided by Databricks:&lt;/P&gt;&lt;PRE&gt;&lt;CODE&gt;databricks jobs submit --jar &amp;lt;path to jar file&amp;gt; --class &amp;lt;main class&amp;gt; --args &amp;lt;args&amp;gt;&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;When you run this command, Databricks automatically handles the details of submitting the Spark application to the cluster and starting the driver program.&lt;/P&gt;&lt;P&gt;Regarding your question about using extra classpath when submitting a job, you can specify extra classpath using the --jars and --py-files options provided by Databricks spark-submit. Here's an example:&lt;/P&gt;&lt;PRE&gt;&lt;CODE&gt;databricks jobs submit --jar &amp;lt;path to jar file&amp;gt; --class &amp;lt;main class&amp;gt; --args &amp;lt;args&amp;gt; --jars &amp;lt;comma-separated list of jars&amp;gt; --py-files &amp;lt;comma-separated list of Python files&amp;gt;&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;The --jars option is used to specify a comma-separated list of jars to be added to the classpath of the driver and executor JVMs. Similarly, the --py-files option is used to specify a comma-separated list of Python files to be added to the Python path of the driver and executor processes.&lt;/P&gt;</description>
      <pubDate>Thu, 27 Apr 2023 05:05:18 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/what-mode-is-the-deploy-mode-when-calling-spark-in-databricks/m-p/5293#M1746</guid>
      <dc:creator>Anonymous</dc:creator>
      <dc:date>2023-04-27T05:05:18Z</dc:date>
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