Optimization of ETL pipelines

About project:

Client overview

The client, a data-intensive organization with a complex ETL infrastructure, was experiencing frequent workflow disruptions due to deadlocks in their data pipelines. Operating in a Kubernetes environment, they needed a solution to prevent concurrent pipeline executions and ensure smooth, uninterrupted data processing.

Tech Stack:

ETL pipelines, Data Warehouse (DWH)

Tech stack after migration:

ETL pipelines, Data Warehouse (DWH), Exclusive Lock Mechanism, Signal Table

Time to deliver project:

4-6 Weeks

Problem

  • Running ETL pipelines sometimes led to deadlocks, disrupting the workflow.

Inspection

  • The ETL processes were running in Kubernetes, and occasionally, the same process would execute twice, causing deadlocks and halting the pipeline's progress.

Recommendation

  • For environments with complex ETL processes, it's recommended to use orchestrators like Airflow to manage and monitor ETL jobs effectively. This can prevent issues like deadlocks and ensure smoother pipeline execution.

Resolution

To resolve this, we created a signal table in the Data Warehouse (DWH), where each ETL pipeline was allocated a dedicated row. The ETL pipelines were rewritten to attempt an exclusive lock on their corresponding row at the start of the run. This approach ensured that only one instance of the pipeline could run at a time and allowed for better tracking of locks in the database.

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