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8 Ways to Optimize AWS Glue Jobs in a Nutshell

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  Improving the performance of AWS Glue jobs involves several strategies that target different aspects of the ETL (Extract, Transform, Load) process. Here are some key practices. 1. Optimize Job Scripts Partitioning : Ensure your data is properly partitioned. Partitioning divides your data into manageable chunks, allowing parallel processing and reducing the amount of data scanned. Filtering : Apply pushdown predicates to filter data early in the ETL process, reducing the amount of data processed downstream. Compression : Use compressed file formats (e.g., Parquet, ORC) for your data sources and sinks. These formats not only reduce storage costs but also improve I/O performance. Optimize Transformations : Minimize the number of transformations and actions in your script. Combine transformations where possible and use DataFrame APIs which are optimized for performance. 2. Use Appropriate Data Formats Parquet and ORC : These columnar formats are efficient for storage and querying, signif
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Storage Node Vs Compute Node

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Here are the differences between compute node vs storage node Nodes are two types. Those are compute and storage. The compute node process business logic whereas the storage node stores the data.

Compute node Vs. Storage node



compute node vs storage node


Compute Node

  • A computer (machine) where you can execute actual business logic.
  • The two parameters it might have are RAM and CPU.


Compute node


Storage Node

  • Stores the processing-data where your file system resides
  • Compute and storage nodes you can find at one location.
  • It designates block storage.

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