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    <title>topic Re: Lakebridge code conversion in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/lakebridge-code-conversion/m-p/123083#M46941</link>
    <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="https://community.databricks.com/t5/user/viewprofilepage/user-id/172350"&gt;@Sreejuv&lt;/a&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;You're encountering a very common challenge. Oracle and Synapse to Databricks SQL procedure conversion is notoriously difficult, and many organizations struggle with this.&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;Common Issues with Automated Conversion&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;Why procedures often fail to convert:&lt;/STRONG&gt;&lt;BR /&gt;- Syntax differences (Oracle PL/SQL vs T-SQL vs Databricks SQL)&lt;BR /&gt;- Procedural logic doesn't translate well to Databricks' SQL dialect&lt;BR /&gt;- Built-in functions have different names/behaviors&lt;BR /&gt;- Control flow structures (loops, cursors, exception handling)&lt;BR /&gt;- Data types and precision differences&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;Successful Conversion Strategies&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;1. Manual Conversion Approach&lt;/STRONG&gt;&lt;BR /&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp;- Most successful migrations involve manual conversion.&lt;BR /&gt;&lt;STRONG&gt;2. Hybrid Approach - Python/Scala + SQL&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;3. Delta Live Tables for ETL Procedures&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;Successful Migration Patterns&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;1. Categorize Your Procedures&lt;/STRONG&gt;&lt;BR /&gt;- ETL procedures → Convert to Delta Live Tables or Databricks workflows&lt;BR /&gt;- Business logic procedures → Convert to Python/Scala functions&lt;BR /&gt;- Data validation procedures → Convert to data quality checks&lt;BR /&gt;- Reporting procedures → Convert to parameterized queries or dashboards&lt;BR /&gt;&lt;BR /&gt;&lt;STRONG&gt;2. Common Conversion Mappings&lt;/STRONG&gt;&lt;BR /&gt;- Oracle/Synapse → Databricks:&lt;BR /&gt;-- Cursors → DataFrame operations&lt;BR /&gt;-- SYSDATE/GETDATE() → current_timestamp()&lt;BR /&gt;-- NVL/ISNULL → coalesce()&lt;BR /&gt;-- ROWNUM → row_number()&lt;BR /&gt;-- Exception handling → try/catch in Python&lt;BR /&gt;-- Loops → DataFrame transformations or Python loops&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;3. Tools That Actually Work&lt;/STRONG&gt;&lt;BR /&gt;- Manual conversion (most reliable)&lt;BR /&gt;AWS Schema Conversion Tool (limited success)&lt;BR /&gt;Custom Python scripts for pattern matching&lt;BR /&gt;Databricks Assistant for individual query conversion&lt;/P&gt;&lt;P&gt;&lt;BR /&gt;&lt;STRONG&gt;Recommended Approach&lt;/STRONG&gt;&lt;BR /&gt;- Start with simple procedures to understand patterns&lt;BR /&gt;- Create a conversion template for common patterns&lt;BR /&gt;- Use Databricks notebooks for complex logic&lt;BR /&gt;- Implement as workflows rather than stored procedures&lt;BR /&gt;- Test thoroughly with representative data&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Fri, 27 Jun 2025 15:34:11 GMT</pubDate>
    <dc:creator>lingareddy_Alva</dc:creator>
    <dc:date>2025-06-27T15:34:11Z</dc:date>
    <item>
      <title>Lakebridge code conversion</title>
      <link>https://community.databricks.com/t5/data-engineering/lakebridge-code-conversion/m-p/123047#M46933</link>
      <description>&lt;P&gt;m currently working on a proof of concept to convert Oracle &amp;amp; Synapse procedures into Databricks SQL &amp;nbsp;and none of these are getting converted.&amp;nbsp;&lt;BR /&gt;followed the steps mentioned in documentation . Wanted to check any one able to sucvessfuly convert and execute in target platform&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Fri, 27 Jun 2025 10:16:18 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/lakebridge-code-conversion/m-p/123047#M46933</guid>
      <dc:creator>Sreejuv</dc:creator>
      <dc:date>2025-06-27T10:16:18Z</dc:date>
    </item>
    <item>
      <title>Re: Lakebridge code conversion</title>
      <link>https://community.databricks.com/t5/data-engineering/lakebridge-code-conversion/m-p/123083#M46941</link>
      <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="https://community.databricks.com/t5/user/viewprofilepage/user-id/172350"&gt;@Sreejuv&lt;/a&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;You're encountering a very common challenge. Oracle and Synapse to Databricks SQL procedure conversion is notoriously difficult, and many organizations struggle with this.&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;Common Issues with Automated Conversion&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;Why procedures often fail to convert:&lt;/STRONG&gt;&lt;BR /&gt;- Syntax differences (Oracle PL/SQL vs T-SQL vs Databricks SQL)&lt;BR /&gt;- Procedural logic doesn't translate well to Databricks' SQL dialect&lt;BR /&gt;- Built-in functions have different names/behaviors&lt;BR /&gt;- Control flow structures (loops, cursors, exception handling)&lt;BR /&gt;- Data types and precision differences&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;Successful Conversion Strategies&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;1. Manual Conversion Approach&lt;/STRONG&gt;&lt;BR /&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp;- Most successful migrations involve manual conversion.&lt;BR /&gt;&lt;STRONG&gt;2. Hybrid Approach - Python/Scala + SQL&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;3. Delta Live Tables for ETL Procedures&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;Successful Migration Patterns&lt;/STRONG&gt;&lt;BR /&gt;&lt;STRONG&gt;1. Categorize Your Procedures&lt;/STRONG&gt;&lt;BR /&gt;- ETL procedures → Convert to Delta Live Tables or Databricks workflows&lt;BR /&gt;- Business logic procedures → Convert to Python/Scala functions&lt;BR /&gt;- Data validation procedures → Convert to data quality checks&lt;BR /&gt;- Reporting procedures → Convert to parameterized queries or dashboards&lt;BR /&gt;&lt;BR /&gt;&lt;STRONG&gt;2. Common Conversion Mappings&lt;/STRONG&gt;&lt;BR /&gt;- Oracle/Synapse → Databricks:&lt;BR /&gt;-- Cursors → DataFrame operations&lt;BR /&gt;-- SYSDATE/GETDATE() → current_timestamp()&lt;BR /&gt;-- NVL/ISNULL → coalesce()&lt;BR /&gt;-- ROWNUM → row_number()&lt;BR /&gt;-- Exception handling → try/catch in Python&lt;BR /&gt;-- Loops → DataFrame transformations or Python loops&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;3. Tools That Actually Work&lt;/STRONG&gt;&lt;BR /&gt;- Manual conversion (most reliable)&lt;BR /&gt;AWS Schema Conversion Tool (limited success)&lt;BR /&gt;Custom Python scripts for pattern matching&lt;BR /&gt;Databricks Assistant for individual query conversion&lt;/P&gt;&lt;P&gt;&lt;BR /&gt;&lt;STRONG&gt;Recommended Approach&lt;/STRONG&gt;&lt;BR /&gt;- Start with simple procedures to understand patterns&lt;BR /&gt;- Create a conversion template for common patterns&lt;BR /&gt;- Use Databricks notebooks for complex logic&lt;BR /&gt;- Implement as workflows rather than stored procedures&lt;BR /&gt;- Test thoroughly with representative data&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Fri, 27 Jun 2025 15:34:11 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/lakebridge-code-conversion/m-p/123083#M46941</guid>
      <dc:creator>lingareddy_Alva</dc:creator>
      <dc:date>2025-06-27T15:34:11Z</dc:date>
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