On-Demand State Repartitioning for Spark Structured Streaming

This post introduces On-Demand State Repartitioning for Apache Spark Structured Streaming on Databricks. This capability allows for dynamic adjustment of state partitions in streaming queries, improving performance and resource utilization by enabling repartitioning without restarting the streaming job. This addresses challenges related to state management and scalability in long-running streaming applications.