Jun 20, 2020 · Big Data

Apache Spark 3.0.0 Release: New Features, Improvements, and Timeline

Apache Spark 3.0.0, released after a 21‑month development cycle and several preview and release‑candidate votes, introduces major enhancements such as Dynamic Partition Pruning, Adaptive Query Execution, accelerator‑aware scheduling, DataSource V2, expanded pandas UDFs, new join hints, richer monitoring, SparkR vectorization, Kafka header support, and broader ecosystem integrations, while fixing over 3,400 issues.

Adaptive Query ExecutionApache SparkDataSource V2

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Apache Spark 3.0.0 Release: New Features, Improvements, and Timeline

dbaplus Community

Jun 20, 2020 · Big Data

What’s New in Apache Spark 3.0? Explore Dynamic Partition Pruning, AQE, and More

Apache Spark 3.0, released after a 21‑month development cycle, introduces dynamic partition pruning, adaptive query execution, accelerator‑aware scheduling, DataSource V2, enhanced pandas UDFs, new join hints, richer monitoring, ANSI‑SQL compatibility, SparkR vectorization, Kafka header support, and numerous platform upgrades, all backed by over 3,400 resolved issues.

Adaptive Query ExecutionApache SparkBig Data

0 likes · 17 min read

What’s New in Apache Spark 3.0? Explore Dynamic Partition Pruning, AQE, and More