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    <title>topic Re: lnkd.in in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/lnkd-in/m-p/4105#M915</link>
    <description>&lt;P&gt;Thanks for sharing&lt;/P&gt;</description>
    <pubDate>Mon, 22 May 2023 08:51:07 GMT</pubDate>
    <dc:creator>Ajay-Pandey</dc:creator>
    <dc:date>2023-05-22T08:51:07Z</dc:date>
    <item>
      <title>lnkd.in</title>
      <link>https://community.databricks.com/t5/data-engineering/lnkd-in/m-p/4104#M914</link>
      <description>&lt;P&gt;Databricks Auto Loader is an interesting feature that can be used to load data incrementally.&lt;/P&gt;&lt;P&gt;✳ It can process new data files as they arrive in the cloud object stores&lt;/P&gt;&lt;P&gt;✳ It can be used to ingest JSON, CSV, PARQUET, AVRO, ORC, TEXT and even Binary file formats&lt;/P&gt;&lt;P&gt;✳ Auto Loader can support a scale of even million files per hour. It maintains the state information at a checkpoint location in a key-value store called RocksDB. As the state is now maintained in the checkpoint, it can resume from where it was left off even in times of failure and can guarantee exactly-once semantics.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Please find my write-up on Databricks AutoLoader on Medium here. Happy for any feedbacks &lt;span class="lia-unicode-emoji" title=":slightly_smiling_face:"&gt;🙂&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;span class="lia-unicode-emoji" title=":dim_button:"&gt;🔅&lt;/span&gt; Databricks Autoloader Series- Accelerating Incremental Data Ingestion:&amp;nbsp;&lt;A href="https://lnkd.in/ew3vaPmp" alt="https://lnkd.in/ew3vaPmp" target="_blank"&gt;https://lnkd.in/ew3vaPmp&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;span class="lia-unicode-emoji" title=":dim_button:"&gt;🔅&lt;/span&gt; Databricks Auto Loader Series— The basics:&amp;nbsp;&lt;A href="https://lnkd.in/e2zanWfc" alt="https://lnkd.in/e2zanWfc" target="_blank"&gt;https://lnkd.in/e2zanWfc&lt;/A&gt;&lt;/P&gt;</description>
      <pubDate>Mon, 22 May 2023 07:10:59 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/lnkd-in/m-p/4104#M914</guid>
      <dc:creator>pvignesh92</dc:creator>
      <dc:date>2023-05-22T07:10:59Z</dc:date>
    </item>
    <item>
      <title>Re: lnkd.in</title>
      <link>https://community.databricks.com/t5/data-engineering/lnkd-in/m-p/4105#M915</link>
      <description>&lt;P&gt;Thanks for sharing&lt;/P&gt;</description>
      <pubDate>Mon, 22 May 2023 08:51:07 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/lnkd-in/m-p/4105#M915</guid>
      <dc:creator>Ajay-Pandey</dc:creator>
      <dc:date>2023-05-22T08:51:07Z</dc:date>
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