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    <title>topic Is it possible to clone/read an existing external Iceberg table in Databricks? in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/is-it-possible-to-clone-read-an-existing-external-iceberg-table/m-p/51877#M29316</link>
    <description>&lt;P&gt;Hello,&amp;nbsp;&lt;/P&gt;&lt;P&gt;I've been experimenting with trying to read and/or clone an existing Iceberg table into Databricks/Delta.&amp;nbsp;&lt;/P&gt;&lt;P&gt;I have an Azure Blob Storage container (configured to use absf for access) that contains an existing Iceberg table structure (data in parquet + the associated metadata) that was created in a local instance of Spark.&lt;/P&gt;&lt;P&gt;I am following:&amp;nbsp;&lt;A href="https://docs.databricks.com/en/delta/clone-parquet.html" target="_blank" rel="noopener"&gt;https://docs.databricks.com/en/delta/clone-parquet.html&amp;nbsp;- It's not entirely clear to me what "/path/to/data" is supposed to represent.&amp;nbsp;&lt;/A&gt;&lt;/P&gt;&lt;P&gt;My query looks like:&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;LI-CODE lang="java"&gt;CREATE TABLE icebergtable CLONE iceberg.`abfs://[redacted].dfs.core.windows.net/warehouse/nyc/taxis/`;&lt;/LI-CODE&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;DIV&gt;I've tried various permutations&amp;nbsp; of the above data path. The directory structure looks like warehouse-&amp;gt;nyc-&amp;gt;taxis-&amp;gt;data,metadata&lt;DIV&gt;&amp;nbsp;&lt;DIV&gt;No matter what I do, I end up with&amp;nbsp;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;LI-CODE lang="java"&gt;NoSuchTableException: Table does not exist at location: ...&lt;/LI-CODE&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;What exactly am I supposed to put in the path? Or is there another syntax issue here?&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Tue, 14 Nov 2023 22:47:50 GMT</pubDate>
    <dc:creator>MarcintheCloud</dc:creator>
    <dc:date>2023-11-14T22:47:50Z</dc:date>
    <item>
      <title>Is it possible to clone/read an existing external Iceberg table in Databricks?</title>
      <link>https://community.databricks.com/t5/data-engineering/is-it-possible-to-clone-read-an-existing-external-iceberg-table/m-p/51877#M29316</link>
      <description>&lt;P&gt;Hello,&amp;nbsp;&lt;/P&gt;&lt;P&gt;I've been experimenting with trying to read and/or clone an existing Iceberg table into Databricks/Delta.&amp;nbsp;&lt;/P&gt;&lt;P&gt;I have an Azure Blob Storage container (configured to use absf for access) that contains an existing Iceberg table structure (data in parquet + the associated metadata) that was created in a local instance of Spark.&lt;/P&gt;&lt;P&gt;I am following:&amp;nbsp;&lt;A href="https://docs.databricks.com/en/delta/clone-parquet.html" target="_blank" rel="noopener"&gt;https://docs.databricks.com/en/delta/clone-parquet.html&amp;nbsp;- It's not entirely clear to me what "/path/to/data" is supposed to represent.&amp;nbsp;&lt;/A&gt;&lt;/P&gt;&lt;P&gt;My query looks like:&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;LI-CODE lang="java"&gt;CREATE TABLE icebergtable CLONE iceberg.`abfs://[redacted].dfs.core.windows.net/warehouse/nyc/taxis/`;&lt;/LI-CODE&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;DIV&gt;I've tried various permutations&amp;nbsp; of the above data path. The directory structure looks like warehouse-&amp;gt;nyc-&amp;gt;taxis-&amp;gt;data,metadata&lt;DIV&gt;&amp;nbsp;&lt;DIV&gt;No matter what I do, I end up with&amp;nbsp;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;LI-CODE lang="java"&gt;NoSuchTableException: Table does not exist at location: ...&lt;/LI-CODE&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;What exactly am I supposed to put in the path? Or is there another syntax issue here?&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 14 Nov 2023 22:47:50 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/is-it-possible-to-clone-read-an-existing-external-iceberg-table/m-p/51877#M29316</guid>
      <dc:creator>MarcintheCloud</dc:creator>
      <dc:date>2023-11-14T22:47:50Z</dc:date>
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