A deep dive into designing high-throughput ETL pipelines in Java using Project Reactor. Covers reactive, non-blocking pipeline construction with Flux/Mono, backpressure management, error isolation at the record level, retry with exponential backoff, dead letter queues, idempotency via MongoDB upserts, batching vs streaming trade-offs, parallel transformations, Kafka integration for event-driven ingestion, and observability with Micrometer. Includes a complete pipeline code example combining all patterns.
Table of contents
Rethinking ETL for modern systemsArchitectural building blocksEmbracing concurrency with reactive pipelinesBackpressure: the hidden heroDesigning for failure: error handling strategiesRetry and recovery patternsIdempotency: the cornerstone of safe retriesBatching vs streamingParallelizing transformationsIntegrating with messaging systemsObservability and monitoringPutting it all togetherTrade-offs and practical considerationsConclusionSort: