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    <title>topic Re: Incremental write in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/incremental-write/m-p/14567#M9039</link>
    <description>&lt;P&gt;Thanks werners&lt;/P&gt;</description>
    <pubDate>Mon, 27 Sep 2021 21:55:33 GMT</pubDate>
    <dc:creator>Nazar</dc:creator>
    <dc:date>2021-09-27T21:55:33Z</dc:date>
    <item>
      <title>Incremental write</title>
      <link>https://community.databricks.com/t5/data-engineering/incremental-write/m-p/14562#M9034</link>
      <description>&lt;P&gt;Hi All,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I have a daily spark job that reads and joins 3-4 source tables and writes the df in a parquet format. This data frame consists of 100+ columns. As this job run daily,  our deduplication logic identifies the latest record from each of source tables , joins them and eventually overwrites the existing parquet file.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;The question becomes - is there a  way to implement the incremental write only in cases of a new record or changes in the values in the existing record of the file.&lt;/P&gt;</description>
      <pubDate>Thu, 23 Sep 2021 22:06:15 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/incremental-write/m-p/14562#M9034</guid>
      <dc:creator>Nazar</dc:creator>
      <dc:date>2021-09-23T22:06:15Z</dc:date>
    </item>
    <item>
      <title>Re: Incremental write</title>
      <link>https://community.databricks.com/t5/data-engineering/incremental-write/m-p/14564#M9036</link>
      <description>&lt;P&gt;Thanks, Appreciate the quick response.&lt;/P&gt;</description>
      <pubDate>Fri, 24 Sep 2021 18:19:24 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/incremental-write/m-p/14564#M9036</guid>
      <dc:creator>Nazar</dc:creator>
      <dc:date>2021-09-24T18:19:24Z</dc:date>
    </item>
    <item>
      <title>Re: Incremental write</title>
      <link>https://community.databricks.com/t5/data-engineering/incremental-write/m-p/14566#M9038</link>
      <description>&lt;P&gt;the MERGE functionality of delta lake is what you are looking for.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;A href="https://docs.databricks.com/spark/latest/spark-sql/language-manual/delta-merge-into.html" target="test_blank"&gt;https://docs.databricks.com/spark/latest/spark-sql/language-manual/delta-merge-into.html&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;A href="https://docs.microsoft.com/en-us/azure/databricks/spark/latest/spark-sql/language-manual/delta-merge-into" target="test_blank"&gt;https://docs.microsoft.com/en-us/azure/databricks/spark/latest/spark-sql/language-manual/delta-merge-into&lt;/A&gt;&lt;/P&gt;</description>
      <pubDate>Mon, 27 Sep 2021 11:09:08 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/incremental-write/m-p/14566#M9038</guid>
      <dc:creator>-werners-</dc:creator>
      <dc:date>2021-09-27T11:09:08Z</dc:date>
    </item>
    <item>
      <title>Re: Incremental write</title>
      <link>https://community.databricks.com/t5/data-engineering/incremental-write/m-p/14567#M9039</link>
      <description>&lt;P&gt;Thanks werners&lt;/P&gt;</description>
      <pubDate>Mon, 27 Sep 2021 21:55:33 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/incremental-write/m-p/14567#M9039</guid>
      <dc:creator>Nazar</dc:creator>
      <dc:date>2021-09-27T21:55:33Z</dc:date>
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