Optimizing JobTarget’s Data Lake: Migrating to Hudi, a Serverless Architecture, and Templated Glue Jobs
Blog post from Onehouse
JobTarget has significantly enhanced its data management capabilities by migrating to an Apache Hudi-based data lake architecture, coupled with an AWS Glue-based framework called LakeBoost, amid rapid data growth. By adopting this architecture, they have achieved automated data ingestion, efficient deduplication, and substantial improvements in storage and compute resource utilization, leading to faster querying and reduced costs. Apache Hudi provides ACID transactions and supports both streaming and batch processing, making it ideal for managing the challenges posed by JobTarget's expanding data needs. Soumil Shah, Data Engineering Lead at JobTarget, highlighted these benefits in his presentation at the Open Source Data Summit 2023, explaining how the AWS Glue framework allows for programmatic data ingestion without the need for infrastructure code. The system efficiently processes transactional data through a series of templated AWS Glue jobs, which automate data cleaning, transformation, and storage in a scalable manner. This approach has streamlined data operations, reduced manual effort, and provided a unified interface for data consumers, enabling them to query large datasets quickly using their preferred tools.
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