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    <title>topic The Nightmare of Initial Load (And How to Tame It) in MVP Articles</title>
    <link>https://community.databricks.com/t5/mvp-articles/the-nightmare-of-initial-load-and-how-to-tame-it/m-p/147474#M65</link>
    <description>&lt;P&gt;Initial loads can be a total nightmare. Imagine that every day you ingest 1 TB of data, but for the initial load, you need to ingest the last 5 years in a single pass. Roughly, that’s 1 TB × 365 days × 5 years = 1825 TB of data. The new row_filter setting in Lakeflow Connect helps to handle it. #databricks&lt;/P&gt;
&lt;P&gt;&lt;A href="https://databrickster.medium.com/the-nightmare-of-initial-load-and-how-to-tame-it-9c81c2a4fbf7" target="_blank"&gt;https://databrickster.medium.com/the-nightmare-of-initial-load-and-how-to-tame-it-9c81c2a4fbf7&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&lt;A href="https://www.sunnydata.ai/blog/initial-data-load-best-practices-databricks" target="_blank"&gt;https://www.sunnydata.ai/blog/initial-data-load-best-practices-databricks&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="ship.png" style="width: 999px;"&gt;&lt;img src="https://community.databricks.com/t5/image/serverpage/image-id/23794iBC2C9356BB4568D8/image-size/large?v=v2&amp;amp;px=999" role="button" title="ship.png" alt="ship.png" /&gt;&lt;/span&gt;&lt;/P&gt;</description>
    <pubDate>Sat, 07 Feb 2026 19:25:58 GMT</pubDate>
    <dc:creator>Hubert-Dudek</dc:creator>
    <dc:date>2026-02-07T19:25:58Z</dc:date>
    <item>
      <title>The Nightmare of Initial Load (And How to Tame It)</title>
      <link>https://community.databricks.com/t5/mvp-articles/the-nightmare-of-initial-load-and-how-to-tame-it/m-p/147474#M65</link>
      <description>&lt;P&gt;Initial loads can be a total nightmare. Imagine that every day you ingest 1 TB of data, but for the initial load, you need to ingest the last 5 years in a single pass. Roughly, that’s 1 TB × 365 days × 5 years = 1825 TB of data. The new row_filter setting in Lakeflow Connect helps to handle it. #databricks&lt;/P&gt;
&lt;P&gt;&lt;A href="https://databrickster.medium.com/the-nightmare-of-initial-load-and-how-to-tame-it-9c81c2a4fbf7" target="_blank"&gt;https://databrickster.medium.com/the-nightmare-of-initial-load-and-how-to-tame-it-9c81c2a4fbf7&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&lt;A href="https://www.sunnydata.ai/blog/initial-data-load-best-practices-databricks" target="_blank"&gt;https://www.sunnydata.ai/blog/initial-data-load-best-practices-databricks&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="ship.png" style="width: 999px;"&gt;&lt;img src="https://community.databricks.com/t5/image/serverpage/image-id/23794iBC2C9356BB4568D8/image-size/large?v=v2&amp;amp;px=999" role="button" title="ship.png" alt="ship.png" /&gt;&lt;/span&gt;&lt;/P&gt;</description>
      <pubDate>Sat, 07 Feb 2026 19:25:58 GMT</pubDate>
      <guid>https://community.databricks.com/t5/mvp-articles/the-nightmare-of-initial-load-and-how-to-tame-it/m-p/147474#M65</guid>
      <dc:creator>Hubert-Dudek</dc:creator>
      <dc:date>2026-02-07T19:25:58Z</dc:date>
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