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    <title>topic Read and process large CSV files that updates regularly in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/read-and-process-large-csv-files-that-updates-regularly/m-p/75672#M35021</link>
    <description>&lt;P&gt;I've got a lot of large CSV files (&amp;gt; 1 GB) that updates regularly (stored in Data Lake Gen 2). The task is to concatenate these files into a single dataframe that is written to parquet format. However, since these files updates very often I get a read error. I've tested with both batch and streaming (autoloader). I think perhaps the only way to deal with this is to create a copy (snapshot) of the files, then process in batch. However that takes a very long time - ideally I would like to avoid that extra step if possible.&amp;nbsp;&lt;BR /&gt;&lt;BR /&gt;I've been stuck with this issue for two days now, so any help here is much appreciated.&lt;/P&gt;</description>
    <pubDate>Tue, 25 Jun 2024 08:09:16 GMT</pubDate>
    <dc:creator>Kjetil</dc:creator>
    <dc:date>2024-06-25T08:09:16Z</dc:date>
    <item>
      <title>Read and process large CSV files that updates regularly</title>
      <link>https://community.databricks.com/t5/data-engineering/read-and-process-large-csv-files-that-updates-regularly/m-p/75672#M35021</link>
      <description>&lt;P&gt;I've got a lot of large CSV files (&amp;gt; 1 GB) that updates regularly (stored in Data Lake Gen 2). The task is to concatenate these files into a single dataframe that is written to parquet format. However, since these files updates very often I get a read error. I've tested with both batch and streaming (autoloader). I think perhaps the only way to deal with this is to create a copy (snapshot) of the files, then process in batch. However that takes a very long time - ideally I would like to avoid that extra step if possible.&amp;nbsp;&lt;BR /&gt;&lt;BR /&gt;I've been stuck with this issue for two days now, so any help here is much appreciated.&lt;/P&gt;</description>
      <pubDate>Tue, 25 Jun 2024 08:09:16 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/read-and-process-large-csv-files-that-updates-regularly/m-p/75672#M35021</guid>
      <dc:creator>Kjetil</dc:creator>
      <dc:date>2024-06-25T08:09:16Z</dc:date>
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    <item>
      <title>Re: Read and process large CSV files that updates regularly</title>
      <link>https://community.databricks.com/t5/data-engineering/read-and-process-large-csv-files-that-updates-regularly/m-p/75696#M35031</link>
      <description>&lt;P&gt;&lt;a href="https://community.databricks.com/t5/user/viewprofilepage/user-id/105685"&gt;@Kjetil&lt;/a&gt;&amp;nbsp;Since they are getting updated often then IMO making a copy would make sense.&lt;BR /&gt;&lt;BR /&gt;What you could try is to create Microsoft.Storage.BlobCreated event to replicate the .CSV into the secondary bucket.&lt;/P&gt;&lt;P&gt;However, best practice would be to have some kind of incremental approach on the source side - creating a new file instead of appending to the existing one.&lt;/P&gt;</description>
      <pubDate>Tue, 25 Jun 2024 11:14:11 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/read-and-process-large-csv-files-that-updates-regularly/m-p/75696#M35031</guid>
      <dc:creator>daniel_sahal</dc:creator>
      <dc:date>2024-06-25T11:14:11Z</dc:date>
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