2 April 2024

Navigating Financial Transactions Reporting: Guide to Build Spark Scala Pipelines in AWS

Building efficient pipelines on AWS for managing daily financial transactions using Spark Scala.

Building Spark Scala Pipelines in AWS for Advanced & Strategic Financial Reporting

In the realm of financial data management, creating efficient pipelines in AWS is pivotal. This blog delves into a comprehensive financial domain project, showcasing the development of pipelines using Spark Scala for handling daily financial transactions.

Introduction To Building To Spark Scala Pipelines

The project revolves around the incremental loading of daily financial transactions into S3 buckets as Parquet files, facilitating seamless reporting in Amazon QuickSight. The data originates from various sources, including EDX parcels and snapshots from a legacy Oracle database, requiring meticulous handling for downstream processing.

Efficient pipelines in AWS are pivotal for managing daily financial transactions using Spark Scala.

Spark Scala Pipeline Development:

The journey begins with ingesting data and transforming it into raw source tables in an S3 bucket, organized by categories such as Customer Master Data, GL Ledgers, AP Purchases, and more. Glue Tables are then created through crawlers, converting these base tables into a readable format for reports and other job processes.

Transactional Reporting:

The creation of transactional report-specific final reporting tables, incorporating business logic for AP reports, AR reports, Purchases reports, and others. The entire process involves meticulous pipeline engineering activities, including cluster configuration, IAM roles setup, bootstrap processes, and data security measures with KMS key pair and secrets manager.

Optimization and Challenges:

The optimization of PySpark code for handling high-volume data is detailed, covering partitioning techniques, memory overhead considerations, and other Spark configurations for optimal performance. The blog concludes by addressing the challenges of scheduling jobs, conflict resolution in read and write tasks, and ensuring data integrity in a daily/hourly refreshing high-volume report environment.

DataTerrain Inc's cutting-edge expertise in Deploying Spark Scala Pipelines on AWS for precision reporting. Harnesses the strategic data solutions and master financial insights for enterprises with forefront analytics.