Ravindra Pesala is a seasoned big-data technology leader and open-source advocate, currently SVP, Big Data Platform Lead at DBS Bank, where he oversees ingestion, compute, data access and metadata across a unified analytics platform. As an Apache Spark contributor and PMC of CarbonData, he has shipped production-ready SQL enhancements and back-end fixes—such as CACHE TABLE AS SELECT, Parquet edge cases, and advanced case/not-like support—demonstrating a knack for turning research into scalable features. With 17+ years of core Java, Hadoop, Spark, HBase, Hive and in-memory analytics, he has steered large-scale BI and analytics programs across Huawei and DBS, delivering robust data platforms. His Huawei tenure includes leading the design of next-gen SQL-on-Hadoop engines and a custom columnar storage, underscoring performance-driven architecture and active open-source collaboration, complemented by multiple analytics patents (three as primary/inventor). Based in Singapore, he leads cross-functional teams across ingestion, compute, data access, and governance to drive end-to-end platform excellence. In addition to his leadership, he remains a prolific contributor to Spark SQL and CarbonData, shaping the broader big-data ecosystem.
11 years of coding experience
15 years of employment as a software developer
Bachelor of Technology (B.Tech.), Bachelor of Technology (B.Tech.) at Acharya Nagarjuna University
Contributions:2 reviews, 662 commits, 344 PRs in 3 years 6 months
Contributions summary:Ravindra appears to be a back-end developer focusing on bug fixes and implementing functionality to handle interactions between CarbonData and HDFS locks, as well as schema-related operations when deleting tables. The user's commits involve modifications to core Java and Scala files, indicating contributions to the underlying code of the CarbonData project. The code modifications include deletion of files, directory creation, and fixing the various file formats while applying filters.
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer
Contributions:2 PRs, 11 comments in 1 month
Contributions summary:Ravindra primarily contributed to enhancing the Apache Spark SQL engine, implementing features and fixing bugs related to SQL parsing, caching, and data processing. Their work included adding support for "CACHE TABLE AS SELECT" functionality, fixing issues related to empty Parquet files and backticks in aliases, and supporting "case when" and "not like" syntax. They also implemented bitwise operators and multi-column count distinct.
analyticspythondata-processingsqlapache
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