https://community.databricks.com/t5/data-engineering/while-accessing-the-data-on-recipient-side-using-delta-sharing/m-p/15197#M9554 <P>When I tried to access specific version data and set the arguments value to the specific number, I get all version data.</P><P></P><P>data1 = delta_sharing.load_table_changes_as_spark(table_url, starting_version=1, ending_version=1)</P><P></P><P>data2 = delta_sharing.load_table_changes_as_spark(table_url, starting_version=2, ending_version=2)</P><P></P><P>Here data1 and data2 gives the same data. When I check the same version data using load_table_changes_as_pandas(), it gives specific version data.</P><P></P><P>data1 = delta_sharing.load_table_changes_as_pandas(table_url, starting_version=1, ending_version=1)</P><P></P><P>data2 = delta_sharing.load_table_changes_as_pandas(table_url, starting_version=2, ending_version=2)</P><P></P><P>In the pandas scenario, data1 is having version 1 data and data2 is having version 2 data. Both of these, data1 and data2, are having different data which was as expected.</P><P></P><P>What we have to do to get the specific version data in spark dataframe using load_table_changes_as_spark function?</P> Thu, 22 Dec 2022 05:04:43 GMT Mahesh_789 2022-12-22T05:04:43Z https://community.databricks.com/t5/data-engineering/while-accessing-the-data-on-recipient-side-using-delta-sharing/m-p/15197#M9554 <P>When I tried to access specific version data and set the arguments value to the specific number, I get all version data.</P><P></P><P>data1 = delta_sharing.load_table_changes_as_spark(table_url, starting_version=1, ending_version=1)</P><P></P><P>data2 = delta_sharing.load_table_changes_as_spark(table_url, starting_version=2, ending_version=2)</P><P></P><P>Here data1 and data2 gives the same data. When I check the same version data using load_table_changes_as_pandas(), it gives specific version data.</P><P></P><P>data1 = delta_sharing.load_table_changes_as_pandas(table_url, starting_version=1, ending_version=1)</P><P></P><P>data2 = delta_sharing.load_table_changes_as_pandas(table_url, starting_version=2, ending_version=2)</P><P></P><P>In the pandas scenario, data1 is having version 1 data and data2 is having version 2 data. Both of these, data1 and data2, are having different data which was as expected.</P><P></P><P>What we have to do to get the specific version data in spark dataframe using load_table_changes_as_spark function?</P> Thu, 22 Dec 2022 05:04:43 GMT https://community.databricks.com/t5/data-engineering/while-accessing-the-data-on-recipient-side-using-delta-sharing/m-p/15197#M9554 Mahesh_789 2022-12-22T05:04:43Z