How to Optimize Delta Lake Performance for Large-Scale Data Ingestion?
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07-12-2024 08:30 AM
Hi everyone,
I'm currently working on a project that involves large-scale data ingestion into Delta Lake on Databricks. While the ingestion process is functioning, I've noticed performance bottlenecks, especially with increasing data volumes. Could you share some best practices and optimization techniques to enhance Delta Lake's performance in such scenarios? Specifically, I am interested in:
- Partitioning strategies for Delta Lake tables
- Efficient handling of small files and metadata management
- Tuning Spark configurations for large-scale ingestion
- Any other tips or resources that might be helpful
Thank you in advance for your insights and suggestions!"
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07-14-2024 08:44 PM
Hi @Syleena23 ,
I believe this Comprehensive Guide to Optimize Databricks, Spark and Delta Lake Workloads provides a lot of answers to these questions and can be a great performance tuning and optimization guide in general. Please take a look.
Thank you.
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07-19-2024 05:30 AM
Hi @Syleena23 ,
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