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    <title>topic How to unload a Jar for UDF without restart spark context? in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/how-to-unload-a-jar-for-udf-without-restart-spark-context/m-p/40189#M27146</link>
    <description>&lt;P&gt;In the scala notebook of databricks, I created a temporary function with a certain Jar and class name.&amp;nbsp;&lt;/P&gt;&lt;P&gt;Then I want to update the Jar. But without restart the context, I can not reload the new Jar, the temporary function always reuses the old classes.&lt;/P&gt;&lt;P&gt;I noticed that for normal function it support refresh, but temporary function doesn't.&lt;/P&gt;&lt;P&gt;Does anyone know the way to resolve this issue?&lt;/P&gt;</description>
    <pubDate>Thu, 17 Aug 2023 09:38:38 GMT</pubDate>
    <dc:creator>vonjack</dc:creator>
    <dc:date>2023-08-17T09:38:38Z</dc:date>
    <item>
      <title>How to unload a Jar for UDF without restart spark context?</title>
      <link>https://community.databricks.com/t5/data-engineering/how-to-unload-a-jar-for-udf-without-restart-spark-context/m-p/40189#M27146</link>
      <description>&lt;P&gt;In the scala notebook of databricks, I created a temporary function with a certain Jar and class name.&amp;nbsp;&lt;/P&gt;&lt;P&gt;Then I want to update the Jar. But without restart the context, I can not reload the new Jar, the temporary function always reuses the old classes.&lt;/P&gt;&lt;P&gt;I noticed that for normal function it support refresh, but temporary function doesn't.&lt;/P&gt;&lt;P&gt;Does anyone know the way to resolve this issue?&lt;/P&gt;</description>
      <pubDate>Thu, 17 Aug 2023 09:38:38 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/how-to-unload-a-jar-for-udf-without-restart-spark-context/m-p/40189#M27146</guid>
      <dc:creator>vonjack</dc:creator>
      <dc:date>2023-08-17T09:38:38Z</dc:date>
    </item>
    <item>
      <title>Re: How to unload a Jar for UDF without restart spark context?</title>
      <link>https://community.databricks.com/t5/data-engineering/how-to-unload-a-jar-for-udf-without-restart-spark-context/m-p/40203#M27150</link>
      <description>&lt;P&gt;Hi, I tried updated Jar, drop and re-create the temporary function, the UDF still use the old Jar.&lt;/P&gt;&lt;P&gt;I don't want to restart context and cleanup workspace, are there any other better solutions?&lt;/P&gt;</description>
      <pubDate>Thu, 17 Aug 2023 10:28:20 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/how-to-unload-a-jar-for-udf-without-restart-spark-context/m-p/40203#M27150</guid>
      <dc:creator>vonjack</dc:creator>
      <dc:date>2023-08-17T10:28:20Z</dc:date>
    </item>
    <item>
      <title>Re: How to unload a Jar for UDF without restart spark context?</title>
      <link>https://community.databricks.com/t5/data-engineering/how-to-unload-a-jar-for-udf-without-restart-spark-context/m-p/40347#M27184</link>
      <description>&lt;P&gt;So if I don't want to restart the cluster, do you think the versionized jar name and class name would be a better solution?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;At first, I used this command to create the original UDF:&lt;/P&gt;&lt;P&gt;create or replace temporary function test_udf as 'com.example.TestUDF_v1' using jar '/tmp/test_udf_v1.jar';&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Then I want to update the UDF, I'll try that:&amp;nbsp;&lt;/P&gt;&lt;P&gt;create or replace temporary function test_udf as 'com.example.TestUDF_v2' using jar '/tmp/test_udf_v2.jar';&lt;/P&gt;&lt;P&gt;But that may be into another problem, if different jars have the same class name like 'com.example.SameClass', which version of class will spark cluster use eventually without restart?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Fri, 18 Aug 2023 00:39:56 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/how-to-unload-a-jar-for-udf-without-restart-spark-context/m-p/40347#M27184</guid>
      <dc:creator>vonjack</dc:creator>
      <dc:date>2023-08-18T00:39:56Z</dc:date>
    </item>
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