<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Can't enable &amp;quot;variantType-preview&amp;quot; using DLTs in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/can-t-enable-quot-varianttype-preview-quot-using-dlts/m-p/135255#M50314</link>
    <description>&lt;P&gt;Using &lt;A href="https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-streaming-table" target="_self"&gt;create_streaming_table&lt;/A&gt; and passing table properties as follows, I get an error running the pipeline for the first time:&lt;/P&gt;&lt;P&gt;&amp;gt;&amp;nbsp;&lt;SPAN class=""&gt;Your table schema requires manually enablement of the following table feature(s): variantType-preview.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN class=""&gt;I'm using this code:&lt;/SPAN&gt;&lt;/P&gt;&lt;LI-CODE lang="python"&gt;create_streaming_table(
    name=name,
    schema=schema,
    table_properties={
        "delta.feature.variantType-preview": "supported",
        "delta.parquet.compression.codec": "ZSTD",
        "pipelines.reset.allowed": "false",
    }
)&lt;/LI-CODE&gt;&lt;P&gt;&lt;SPAN class=""&gt;That's a bit surprising because the table shows that this property was indeed set under the Unity Catalog table entry details. I believe this has been working in the past.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN class=""&gt;The workaround suggested (to manually enable it) does not work because the table was never refreshed:&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN class=""&gt;&amp;gt;&amp;nbsp;&lt;SPAN class=""&gt;Streaming table [REDACTED] needs to be refreshed to execute QUERY. If the table is created from DBSQL, please run REFRESH STREAMING TABLE. If the table is created by a pipeline in Delta Live Tables, please run a pipeline update. SQLSTATE: 55019&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;</description>
    <pubDate>Fri, 17 Oct 2025 16:07:06 GMT</pubDate>
    <dc:creator>Malthe</dc:creator>
    <dc:date>2025-10-17T16:07:06Z</dc:date>
    <item>
      <title>Can't enable "variantType-preview" using DLTs</title>
      <link>https://community.databricks.com/t5/data-engineering/can-t-enable-quot-varianttype-preview-quot-using-dlts/m-p/135255#M50314</link>
      <description>&lt;P&gt;Using &lt;A href="https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-streaming-table" target="_self"&gt;create_streaming_table&lt;/A&gt; and passing table properties as follows, I get an error running the pipeline for the first time:&lt;/P&gt;&lt;P&gt;&amp;gt;&amp;nbsp;&lt;SPAN class=""&gt;Your table schema requires manually enablement of the following table feature(s): variantType-preview.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN class=""&gt;I'm using this code:&lt;/SPAN&gt;&lt;/P&gt;&lt;LI-CODE lang="python"&gt;create_streaming_table(
    name=name,
    schema=schema,
    table_properties={
        "delta.feature.variantType-preview": "supported",
        "delta.parquet.compression.codec": "ZSTD",
        "pipelines.reset.allowed": "false",
    }
)&lt;/LI-CODE&gt;&lt;P&gt;&lt;SPAN class=""&gt;That's a bit surprising because the table shows that this property was indeed set under the Unity Catalog table entry details. I believe this has been working in the past.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN class=""&gt;The workaround suggested (to manually enable it) does not work because the table was never refreshed:&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN class=""&gt;&amp;gt;&amp;nbsp;&lt;SPAN class=""&gt;Streaming table [REDACTED] needs to be refreshed to execute QUERY. If the table is created from DBSQL, please run REFRESH STREAMING TABLE. If the table is created by a pipeline in Delta Live Tables, please run a pipeline update. SQLSTATE: 55019&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;</description>
      <pubDate>Fri, 17 Oct 2025 16:07:06 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/can-t-enable-quot-varianttype-preview-quot-using-dlts/m-p/135255#M50314</guid>
      <dc:creator>Malthe</dc:creator>
      <dc:date>2025-10-17T16:07:06Z</dc:date>
    </item>
    <item>
      <title>Re: Can't enable "variantType-preview" using DLTs</title>
      <link>https://community.databricks.com/t5/data-engineering/can-t-enable-quot-varianttype-preview-quot-using-dlts/m-p/135258#M50315</link>
      <description>&lt;P&gt;&lt;a href="https://community.databricks.com/t5/user/viewprofilepage/user-id/9268"&gt;@Malthe&lt;/a&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Root Cause:&lt;/P&gt;&lt;P&gt;The property delta.feature.variantType-preview = supported tells Delta Lake to use the new Variant type, which is still in preview or limited availability&lt;/P&gt;&lt;P&gt;Why It Worked Previously&lt;/P&gt;&lt;P&gt;Earlier Databricks versions implicitly activated such features at table creation.&lt;BR /&gt;Recent updates added stricter activation controls&lt;/P&gt;&lt;P&gt;Solution Thinking:&lt;/P&gt;&lt;P&gt;&lt;A href="https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-streaming-table" target="_blank" rel="noopener"&gt;https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-streaming-table&lt;/A&gt;&lt;/P&gt;&lt;P&gt;1. Clean Table Creation in Pipeline Code&lt;BR /&gt;If possible, delete the old table so your next pipeline run creates a new streaming table with all properties set and no legacy metadata issues. This works best when you control the pipeline end-to-end.&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="ManojkMohan_2-1760718221646.png" style="width: 400px;"&gt;&lt;img src="https://community.databricks.com/t5/image/serverpage/image-id/20819i25705C76B7071E50/image-size/medium?v=v2&amp;amp;px=400" role="button" title="ManojkMohan_2-1760718221646.png" alt="ManojkMohan_2-1760718221646.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;2. For Existing Tables (Manual Activation)&lt;BR /&gt;If your table already exists (created previously without the variantType flag fully activated), enable the feature manually using SQL&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="ManojkMohan_0-1760718002234.png" style="width: 400px;"&gt;&lt;img src="https://community.databricks.com/t5/image/serverpage/image-id/20817iD121FB4CF0088C02/image-size/medium?v=v2&amp;amp;px=400" role="button" title="ManojkMohan_0-1760718002234.png" alt="ManojkMohan_0-1760718002234.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;Immediately after Run&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="ManojkMohan_1-1760718030216.png" style="width: 400px;"&gt;&lt;img src="https://community.databricks.com/t5/image/serverpage/image-id/20818iE0DCA82BA13D29A3/image-size/medium?v=v2&amp;amp;px=400" role="button" title="ManojkMohan_1-1760718030216.png" alt="ManojkMohan_1-1760718030216.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;3. Final Step—Trigger Pipeline Update&lt;BR /&gt;If the table is under a Delta Live Tables pipeline, any schema or logic change will also trigger Databricks to re-activate its internal metadata:&lt;/P&gt;&lt;P&gt;Add or remove a comment in the create_streaming_table call, or&lt;/P&gt;&lt;P&gt;Edit and rerun your pipeline job.&lt;/P&gt;&lt;P&gt;This step triggers Databricks to finalize table activation and enable the new feature without manual SQL.​&lt;/P&gt;&lt;P&gt;&lt;A href="https://docs.databricks.com/aws/en/delta/variant" target="_blank" rel="noopener"&gt;https://docs.databricks.com/aws/en/delta/variant&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;BR /&gt;Be sure to use Databricks Runtime 15.3 or higher for full variant column support. If using DLT (Delta Live Tables), let the pipeline do the activation by deleting and recreating the table within the managed workflow.&lt;/P&gt;</description>
      <pubDate>Fri, 17 Oct 2025 16:24:16 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/can-t-enable-quot-varianttype-preview-quot-using-dlts/m-p/135258#M50315</guid>
      <dc:creator>ManojkMohan</dc:creator>
      <dc:date>2025-10-17T16:24:16Z</dc:date>
    </item>
    <item>
      <title>Re: Can't enable "variantType-preview" using DLTs</title>
      <link>https://community.databricks.com/t5/data-engineering/can-t-enable-quot-varianttype-preview-quot-using-dlts/m-p/135261#M50316</link>
      <description>&lt;P&gt;Unfortunately this is on a brand new table.&lt;/P&gt;&lt;P&gt;I was able to track down the runtime that successfully created and refreshed the table:&lt;/P&gt;&lt;UL&gt;&lt;LI&gt;Worked:&lt;BR /&gt;dlt:16.4.10-delta-pipelines-dlt-release-dp-20251002-rc0-commit-6bcc9de-image-98a6a38&lt;/LI&gt;&lt;LI&gt;Did not work:&lt;BR /&gt;dlt:16.4.10-delta-pipelines-dlt-release-dp-20251009-rc0-commit-8c6b818-image-a20f551&lt;/LI&gt;&lt;/UL&gt;&lt;P&gt;Notice the October 2nd vs 9th release.&lt;/P&gt;&lt;P&gt;This could theoretically be an explanation, that we're seeing a regression here.&lt;/P&gt;&lt;P&gt;The problem persists whether I'm using the CURRENT or PREVIEW channel.&lt;/P&gt;</description>
      <pubDate>Fri, 17 Oct 2025 16:48:24 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/can-t-enable-quot-varianttype-preview-quot-using-dlts/m-p/135261#M50316</guid>
      <dc:creator>Malthe</dc:creator>
      <dc:date>2025-10-17T16:48:24Z</dc:date>
    </item>
    <item>
      <title>Re: Can't enable "variantType-preview" using DLTs</title>
      <link>https://community.databricks.com/t5/data-engineering/can-t-enable-quot-varianttype-preview-quot-using-dlts/m-p/135267#M50318</link>
      <description>&lt;P&gt;Here's a self-contained example in SQL that demonstrates the issue:&lt;/P&gt;&lt;LI-CODE lang="javascript"&gt;CREATE TEMPORARY VIEW dummy_kafka AS
SELECT
    'id' AS id,
	'topic' AS topic,
	current_timestamp() AS timestamp,
	1::INTEGER AS partition,
	1::long AS offset,
	parse_json('{}') AS body;

CREATE STREAMING TABLE raw_telemetry (
	id STRING PRIMARY KEY RELY,
	topic STRING NOT NULL,
	timestamp TIMESTAMP NOT NULL,
	partition INTEGER NOT NULL,
	offset LONG NOT NULL,
	body VARIANT NOT NULL
)
TBLPROPERTIES (
    'delta.feature.variantType-preview' = 'supported'
)
AS
SELECT * FROM dummy_kafka;&lt;/LI-CODE&gt;</description>
      <pubDate>Fri, 17 Oct 2025 17:49:31 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/can-t-enable-quot-varianttype-preview-quot-using-dlts/m-p/135267#M50318</guid>
      <dc:creator>Malthe</dc:creator>
      <dc:date>2025-10-17T17:49:31Z</dc:date>
    </item>
    <item>
      <title>Re: Can't enable "variantType-preview" using DLTs</title>
      <link>https://community.databricks.com/t5/data-engineering/can-t-enable-quot-varianttype-preview-quot-using-dlts/m-p/135274#M50319</link>
      <description>&lt;P&gt;There's a workaround available in most situations which is to first create the table without the VARIANT column, run the pipeline at least once, and then add the column in a subsequent refresh.&lt;/P&gt;</description>
      <pubDate>Fri, 17 Oct 2025 18:17:18 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/can-t-enable-quot-varianttype-preview-quot-using-dlts/m-p/135274#M50319</guid>
      <dc:creator>Malthe</dc:creator>
      <dc:date>2025-10-17T18:17:18Z</dc:date>
    </item>
  </channel>
</rss>

