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What is the importance of the checkpoint location in Databricks?

Spark/Big Datahard0.4 min readPremium
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**Purpose**: Checkpoint stores (1) processed offsets (Kafka, files) and (2) state (aggregations, joins) for Structured Streaming. Enables exactly-once and failure recovery. **Why Critical**: No checkpoint = no recovery. Restart = reprocess from start or lose state. Exactly-once impossible. **Requirements**: Durable storage (DBFS, S3). Unique per query. Never delete. **Scalability Trade-offs**: Checkpoint can grow; monitor....
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