Modern Open Table Format integration with ODP
Apache Hive was the pioneering data lake table format popularized for warehousing within the big data ecosystem, but it had significant limitations due to its design and architecture. Recent advancements in new table formats have empowered data engineers and architects with superior capabilities in compliance and maintenance standards.
These features include enhanced ACID transactions, time traveling, historical snapshot creation, branching and tagging, and Change Data Capture (CDC) procedures that simplify upserts and deletions. With HDFS or object storage, these table formats support full CRUD operations, boasting improved performance and scalability through updated data organization strategies.
The following pages offer a preliminary guide on using these open table formats with ODP Spark integration, featuring Spark Scala/SQL. This guide provides a concise overview of the format, its capabilities, and usage, including code snippets for inserting, updating, deleting, and leveraging other available features.