Hadoop Hive migration to Databricks

[ShankarM]

Hi,

Can you let me know what are the challenges and how to mitigate while migrating Hive objects to Databricks. I could not get any information on this. 

Can you please provide.

[Kaniz_Fatma · Accepted solution]

Hi @ShankarM, Here are the main considerations and mitigation strategies:

1. Hive Workload Adaptation:

   • Challenge: Adapting existing Hadoop workloads to Databricks’ advanced analytics framework.
   • Mitigation: Rework and fine-tune your Hadoop workloads to leverage Databricks’ speedy, in-memory processing. 

2. Architecture Differences:

   • Challenge: Hadoop and Databricks have distinct architectures.
   • Mitigation: Understand the differences. Hadoop operates across multiple hardware systems, while Databricks offers a unified analytics platform built on Apache Spark. 

3. Hive Metastore and UDFs:

   • Challenge: Hive SerDe and UDFs need adjustments.
   • Mitigation:
     • Update Hive SerDe to use Databricks-native file codecs (change DDL from STORED AS to USING).
     • Install Hive UDFs as libraries or refactor them to native Spark.
     • Adjust directory structure for tables (Databricks uses partitions differently).

4. SQL Workloads:

   • Challenge: Migrating SQL workloads from other systems.
   • Mitigation:
     • Refactor SQL pipelines as needed (Databricks uses Delta Lake by default).
     • Configure access to external data sources.

If you encounter specific issues during the migration, feel free to ask for further assistance! 😊