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    <title>topic Re: Reading a materialised view locally or using databricks api in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/reading-a-materialised-view-locally-or-using-databricks-api/m-p/79342#M35739</link>
    <description>&lt;P&gt;I used this approach&amp;nbsp;&lt;BR /&gt;- Querying the materialised view using databricks serverless SQL endpoint by connecting it with SQL connect.&amp;nbsp;&lt;BR /&gt;Its working right now. If I face any issues, I will write it into a normal table and delta share it.&lt;/P&gt;&lt;P&gt;Thanks for your reply&amp;nbsp;&lt;a href="https://community.databricks.com/t5/user/viewprofilepage/user-id/9"&gt;@Retired_mod&lt;/a&gt;&amp;nbsp;as always very helpful.&lt;/P&gt;</description>
    <pubDate>Fri, 19 Jul 2024 07:18:14 GMT</pubDate>
    <dc:creator>ashraf1395</dc:creator>
    <dc:date>2024-07-19T07:18:14Z</dc:date>
    <item>
      <title>Reading a materialised view locally or using databricks api</title>
      <link>https://community.databricks.com/t5/data-engineering/reading-a-materialised-view-locally-or-using-databricks-api/m-p/78930#M35641</link>
      <description>&lt;P&gt;Hi there,&amp;nbsp;&lt;BR /&gt;&lt;BR /&gt;This was my previous approach&amp;nbsp;&lt;BR /&gt;- I had a databricks notebook with a streaming table bronze level reading data from volumes which created a 2 downstream tables.&lt;/P&gt;&lt;P&gt;- 1st A a materialised view gold level, another a table for storing ingestion_metadata like most_recent_timestamp of events.&lt;/P&gt;&lt;P&gt;- ingestion metadata table was shared using open delta sharing&lt;/P&gt;&lt;P&gt;Then I would run an ingestion script from aws ecs / locally - I read the ingestion_metadata with delta sharing and then find the most_recent_timestamp log and fetch further data ahead from that timestamp and then other stuffs.This is was working good only issue - I needed to run the databricks notebook manually.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;So I shifted to dlt pipeline.&lt;/P&gt;&lt;P&gt;Things are same but I cannot create a normal table either it will be a streaming table / materialised view / view&amp;nbsp;&lt;/P&gt;&lt;P&gt;and mv and views cannot be delta shared.So then I tried to access that ingestion_metadata materialised table created in dlt pipeline using databricks API but I cannot read the actual data inside it.&lt;/P&gt;&lt;P&gt;How to do this or any other way I should solve this case&lt;/P&gt;</description>
      <pubDate>Tue, 16 Jul 2024 08:19:29 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/reading-a-materialised-view-locally-or-using-databricks-api/m-p/78930#M35641</guid>
      <dc:creator>ashraf1395</dc:creator>
      <dc:date>2024-07-16T08:19:29Z</dc:date>
    </item>
    <item>
      <title>Re: Reading a materialised view locally or using databricks api</title>
      <link>https://community.databricks.com/t5/data-engineering/reading-a-materialised-view-locally-or-using-databricks-api/m-p/79342#M35739</link>
      <description>&lt;P&gt;I used this approach&amp;nbsp;&lt;BR /&gt;- Querying the materialised view using databricks serverless SQL endpoint by connecting it with SQL connect.&amp;nbsp;&lt;BR /&gt;Its working right now. If I face any issues, I will write it into a normal table and delta share it.&lt;/P&gt;&lt;P&gt;Thanks for your reply&amp;nbsp;&lt;a href="https://community.databricks.com/t5/user/viewprofilepage/user-id/9"&gt;@Retired_mod&lt;/a&gt;&amp;nbsp;as always very helpful.&lt;/P&gt;</description>
      <pubDate>Fri, 19 Jul 2024 07:18:14 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/reading-a-materialised-view-locally-or-using-databricks-api/m-p/79342#M35739</guid>
      <dc:creator>ashraf1395</dc:creator>
      <dc:date>2024-07-19T07:18:14Z</dc:date>
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