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    <title>topic Re: Lakeflow connect in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/lakeflow-connect/m-p/170573#M56320</link>
    <description>&lt;P&gt;Thanks for the answer..it's now clear..I also followed the doc and understood!&lt;/P&gt;</description>
    <pubDate>Mon, 05 Oct 2026 03:17:01 GMT</pubDate>
    <dc:creator>ram_11</dc:creator>
    <dc:date>2026-10-05T03:17:01Z</dc:date>
    <item>
      <title>Lakeflow connect</title>
      <link>https://community.databricks.com/t5/data-engineering/lakeflow-connect/m-p/170473#M56307</link>
      <description>&lt;LI-SPOILER&gt;&amp;nbsp;&lt;/LI-SPOILER&gt;&lt;P&gt;What is extractor_sql-server-conn_cdc_sink in the Ingestion gateway pipeline in lakeflow connect and is it crreated by deafualta and how does it work?&lt;/P&gt;</description>
      <pubDate>Sat, 03 Oct 2026 06:51:17 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/lakeflow-connect/m-p/170473#M56307</guid>
      <dc:creator>ram_11</dc:creator>
      <dc:date>2026-10-03T06:51:17Z</dc:date>
    </item>
    <item>
      <title>Re: Lakeflow connect</title>
      <link>https://community.databricks.com/t5/data-engineering/lakeflow-connect/m-p/170476#M56308</link>
      <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="https://community.databricks.com/t5/user/viewprofilepage/user-id/263097"&gt;@ram_11&lt;/a&gt;&amp;nbsp;!&lt;/P&gt;
&lt;P&gt;The&lt;STRONG&gt; extractor_sql-server-conn_cdc_sink&lt;/STRONG&gt;&lt;SPAN&gt;&lt;STRONG&gt;&amp;nbsp;&lt;/STRONG&gt;is the shared CDC sink that the SQL Server CDC extractor job inside the IG pipeline writes to&lt;/SPAN&gt;.&lt;BR /&gt;&lt;BR /&gt;&lt;STRONG&gt;Example screenshot below:&lt;/STRONG&gt;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="K_Anudeep_1-1791011265117.png" style="width: 400px;"&gt;&lt;img src="https://community.databricks.com/t5/image/serverpage/image-id/31676iD8599FCE19FCBA99/image-size/medium?v=v2&amp;amp;px=400" role="button" title="K_Anudeep_1-1791011265117.png" alt="K_Anudeep_1-1791011265117.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P class="ui-markdown__paragraph ui-z80ra4 ui-uu7i3w ui-1nhcn8o ui-j7cesy ui-13faqbe ui-14l7nz5 ui-zboxd6 ui-19d5a1n ui-bpgzfc"&gt;What actually happens:&lt;/P&gt;
&lt;OL class="ui-markdown__list ui-78zum5 ui-dt5ytf ui-1ae8yn7 ui-13vk20g ui-1e8yfua ui-j7cesy ui-1bae07f"&gt;
&lt;LI class="ui-markdown__list-item ui--default-marker ui-exx8yu ui-1xpa7k ui-18d9i69 ui-1uhho1l ui-13faqbe ui-ez2fb" data-md-list-item=""&gt;The IG extractor (the job/process) reads change rows from each table’s capture instance / CT table.&lt;/LI&gt;
&lt;LI class="ui-markdown__list-item ui--default-marker ui-exx8yu ui-1xpa7k ui-18d9i69 ui-1uhho1l ui-13faqbe ui-ez2fb" data-md-list-item=""&gt;When the IG pipelines run, we see that the per-table&amp;nbsp;&lt;SPAN class="font-semibold" data-streamdown="strong"&gt;CDC flows&lt;/SPAN&gt;&amp;nbsp;are defined&amp;nbsp;&lt;/LI&gt;
&lt;LI class="ui-markdown__list-item ui--default-marker ui-exx8yu ui-1xpa7k ui-18d9i69 ui-1uhho1l ui-13faqbe ui-ez2fb" data-md-list-item=""&gt;All of those flows append JSON into&amp;nbsp;&lt;SPAN class="font-semibold" data-streamdown="strong"&gt;one&lt;/SPAN&gt;&amp;nbsp;shared sink:&amp;nbsp;&lt;CODE class="ui-markdown__inline-code ui-rtu7ee ui-1i9v5mb ui-1hhlpkd ui-6lrnw6 ui-115g5cq ui-odjx36 ui-1wd3ewq ui-hayvgc ui-eb7xqv ui-15bjb6t ui-1lldw8n ui-1mzt3pk"&gt;extractor_&amp;lt;connection-name&amp;gt;_cdc_sink&lt;/CODE&gt;.&lt;/LI&gt;
&lt;LI class="ui-markdown__list-item ui--default-marker ui-exx8yu ui-1xpa7k ui-18d9i69 ui-1uhho1l ui-13faqbe ui-ez2fb" data-md-list-item=""&gt;This sink is a UC volume&amp;nbsp;&lt;CODE class="ui-markdown__inline-code ui-rtu7ee ui-1i9v5mb ui-1hhlpkd ui-6lrnw6 ui-115g5cq ui-odjx36 ui-1wd3ewq ui-hayvgc ui-eb7xqv ui-15bjb6t ui-1lldw8n ui-1mzt3pk"&gt;cdc/&lt;/CODE&gt;&amp;nbsp;directory inside your staging location where your ingesting pipeline reads from later.&lt;/LI&gt;
&lt;/OL&gt;
&lt;P&gt;Also, when you start your IG pipleine for the first time, you should see&amp;nbsp;&lt;STRONG&gt;extractor_sql-server-conn_snaphsot_sink &lt;/STRONG&gt;as well, which is a sink defined, one for each table&amp;nbsp;where the snapshot extractor writes the initial/full-load Parquet files.&lt;/P&gt;
&lt;P&gt;I hope this answers your question.&lt;/P&gt;</description>
      <pubDate>Sat, 03 Oct 2026 07:07:56 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/lakeflow-connect/m-p/170476#M56308</guid>
      <dc:creator>K_Anudeep</dc:creator>
      <dc:date>2026-10-03T07:07:56Z</dc:date>
    </item>
    <item>
      <title>Re: Lakeflow connect</title>
      <link>https://community.databricks.com/t5/data-engineering/lakeflow-connect/m-p/170573#M56320</link>
      <description>&lt;P&gt;Thanks for the answer..it's now clear..I also followed the doc and understood!&lt;/P&gt;</description>
      <pubDate>Mon, 05 Oct 2026 03:17:01 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/lakeflow-connect/m-p/170573#M56320</guid>
      <dc:creator>ram_11</dc:creator>
      <dc:date>2026-10-05T03:17:01Z</dc:date>
    </item>
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