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    <title>topic Re: How not to reprocess old files without delta ? in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/how-not-to-reprocess-old-files-without-delta/m-p/12335#M7150</link>
    <description>&lt;P&gt;you can land your raw data in a folder with a date/timestamp.&lt;/P&gt;&lt;P&gt;f.e. /raw/sales/2021/10/27/dataset.csv&lt;/P&gt;&lt;P&gt;In your spark program you can program to read only from the path with a certain date (today, yesterday etc).&lt;/P&gt;&lt;P&gt;If you get full extracts every day, this works fine.  The downside is that your raw storage has a lot of redundant data (because of the full extracts every day) but with data lakes being so cheap that is not a big issue.&lt;/P&gt;&lt;P&gt;The biggest plus for delta imo is the merge functionality which enables you to go for an incremental scenario.&lt;/P&gt;</description>
    <pubDate>Wed, 27 Oct 2021 06:17:54 GMT</pubDate>
    <dc:creator>-werners-</dc:creator>
    <dc:date>2021-10-27T06:17:54Z</dc:date>
    <item>
      <title>How not to reprocess old files without delta ?</title>
      <link>https://community.databricks.com/t5/data-engineering/how-not-to-reprocess-old-files-without-delta/m-p/12333#M7148</link>
      <description>&lt;P&gt;Hi guys,&lt;/P&gt;&lt;P&gt;​&lt;/P&gt;&lt;P&gt;Look that case: Company ACME (hypothetical company)&lt;/P&gt;&lt;P&gt;​&lt;/P&gt;&lt;P&gt;This company does not use delta, but uses open source Spark to process raw data for .parquet, we have a 'sales' process which consists of receiving every hour a new dataset (.csv) within the '/raw/sales' and write to '/insight/sales' (df.write.parquet ... ), after a few hours how do you go about not reprocessing the older datasets?&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;​&lt;/P&gt;</description>
      <pubDate>Tue, 26 Oct 2021 18:42:15 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/how-not-to-reprocess-old-files-without-delta/m-p/12333#M7148</guid>
      <dc:creator>William_Scardua</dc:creator>
      <dc:date>2021-10-26T18:42:15Z</dc:date>
    </item>
    <item>
      <title>Re: How not to reprocess old files without delta ?</title>
      <link>https://community.databricks.com/t5/data-engineering/how-not-to-reprocess-old-files-without-delta/m-p/12335#M7150</link>
      <description>&lt;P&gt;you can land your raw data in a folder with a date/timestamp.&lt;/P&gt;&lt;P&gt;f.e. /raw/sales/2021/10/27/dataset.csv&lt;/P&gt;&lt;P&gt;In your spark program you can program to read only from the path with a certain date (today, yesterday etc).&lt;/P&gt;&lt;P&gt;If you get full extracts every day, this works fine.  The downside is that your raw storage has a lot of redundant data (because of the full extracts every day) but with data lakes being so cheap that is not a big issue.&lt;/P&gt;&lt;P&gt;The biggest plus for delta imo is the merge functionality which enables you to go for an incremental scenario.&lt;/P&gt;</description>
      <pubDate>Wed, 27 Oct 2021 06:17:54 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/how-not-to-reprocess-old-files-without-delta/m-p/12335#M7150</guid>
      <dc:creator>-werners-</dc:creator>
      <dc:date>2021-10-27T06:17:54Z</dc:date>
    </item>
    <item>
      <title>Re: How not to reprocess old files without delta ?</title>
      <link>https://community.databricks.com/t5/data-engineering/how-not-to-reprocess-old-files-without-delta/m-p/12336#M7151</link>
      <description>&lt;P&gt;In such a case the best option is to use spark autoload to detect new csvs (or new records) in /raw/sales and than use append to add transformed records to insights.&lt;/P&gt;</description>
      <pubDate>Wed, 27 Oct 2021 08:42:39 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/how-not-to-reprocess-old-files-without-delta/m-p/12336#M7151</guid>
      <dc:creator>Hubert-Dudek</dc:creator>
      <dc:date>2021-10-27T08:42:39Z</dc:date>
    </item>
    <item>
      <title>Re: How not to reprocess old files without delta ?</title>
      <link>https://community.databricks.com/t5/data-engineering/how-not-to-reprocess-old-files-without-delta/m-p/12337#M7152</link>
      <description>&lt;P&gt;Hi @William Scardua​&amp;nbsp;,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Like @Hubert Dudek​&amp;nbsp;mentioned, maybe the best option is to use auto loader. You can find docs and examples on how to use it &lt;A href="https://docs.databricks.com/spark/latest/structured-streaming/auto-loader.html" alt="https://docs.databricks.com/spark/latest/structured-streaming/auto-loader.html" target="_blank"&gt;here&lt;/A&gt;&lt;/P&gt;</description>
      <pubDate>Fri, 29 Oct 2021 23:49:04 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/how-not-to-reprocess-old-files-without-delta/m-p/12337#M7152</guid>
      <dc:creator>jose_gonzalez</dc:creator>
      <dc:date>2021-10-29T23:49:04Z</dc:date>
    </item>
    <item>
      <title>Re: How not to reprocess old files without delta ?</title>
      <link>https://community.databricks.com/t5/data-engineering/how-not-to-reprocess-old-files-without-delta/m-p/12338#M7153</link>
      <description>&lt;P&gt;Hi @Jose Gonzalez​&amp;nbsp;, ​&lt;/P&gt;&lt;P&gt;I agree the best option is to use auto load, but some cases you don`t have the databricks plataform and don`t use delta, i this cases you need build a way to process the new raw files&lt;/P&gt;</description>
      <pubDate>Mon, 01 Nov 2021 18:44:24 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/how-not-to-reprocess-old-files-without-delta/m-p/12338#M7153</guid>
      <dc:creator>William_Scardua</dc:creator>
      <dc:date>2021-11-01T18:44:24Z</dc:date>
    </item>
    <item>
      <title>Re: How not to reprocess old files without delta ?</title>
      <link>https://community.databricks.com/t5/data-engineering/how-not-to-reprocess-old-files-without-delta/m-p/12339#M7154</link>
      <description>&lt;P&gt;In that case I suggest my suggestion &lt;span class="lia-unicode-emoji" title=":slightly_smiling_face:"&gt;🙂&lt;/span&gt;  We work like that for quite a few data streams.&lt;/P&gt;</description>
      <pubDate>Tue, 02 Nov 2021 08:35:23 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/how-not-to-reprocess-old-files-without-delta/m-p/12339#M7154</guid>
      <dc:creator>-werners-</dc:creator>
      <dc:date>2021-11-02T08:35:23Z</dc:date>
    </item>
    <item>
      <title>Re: How not to reprocess old files without delta ?</title>
      <link>https://community.databricks.com/t5/data-engineering/how-not-to-reprocess-old-files-without-delta/m-p/12340#M7155</link>
      <description>&lt;P&gt;Databricks autloader works excellent also with other types of files like csv etc. If you don't want to use as stream you can trigger it once.&lt;/P&gt;</description>
      <pubDate>Tue, 02 Nov 2021 12:01:37 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/how-not-to-reprocess-old-files-without-delta/m-p/12340#M7155</guid>
      <dc:creator>Hubert-Dudek</dc:creator>
      <dc:date>2021-11-02T12:01:37Z</dc:date>
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