Mr. Saravanan Prabhagaran

Taming Big Data in the Cloud: Partitioning and Bucketing Unveiled for Real-World Impact

Abstract:
In today’s Big Data and Cloud-driven world, organizations face significant challenges in managing and analyzing ever-expanding datasets. Traditional methods of storing and querying data often struggle to keep up with the scale, speed, and cost demands of Big Data ecosystems. Partitioning and Bucketing emerge as pivotal techniques to address these challenges, enabling organizations to optimize performance, reduce costs, and extract actionable insights from their data in cloud-based environments. However, their effective application requires a nuanced understanding—overusing or misapplying these techniques can lead to inefficiencies that negate their benefits.

While partitioning and bucketing are widely recognized for their advantages in direct lookup queries and optimizing joins through broadcast techniques, their implementation must consider the limitations of specific Big Data engines. Achieving optimal performance often hinges on balancing bucket counts during joins and employing workarounds where necessary. This session explores the practical dos and don’ts of partitioning and bucketing in Big Data and Cloud environments, focusing on scenarios where these techniques are critical and how to overcome constraints, ensuring organizations can maximize their potential without introducing new bottlenecks.