Senior engineer at a top internet giant, sharing Java, AI, tech knowledge, growth insights, and interview experiences.
The article walks through Elasticsearch’s document retrieval workflow, covering single‑document GET, multi‑document mget, the two‑stage query_then_fetch mechanism, shard routing, load balancing, query and fetch phases, collectors, rescore, and pagination optimizations.
This article walks through Elasticsearch’s document indexing pipeline—from single‑document and bulk request routing, through the write‑refresh‑flush‑merge cycle, to the roles of Lucene, the translog, primary and replica shards, and how reliability, consistency, atomicity, isolation, real‑time visibility and performance are achieved.
This article explains Elasticsearch’s overall structure, the underlying Lucene index layout, the indexing and search processing flow, and how built‑in analyzers work, illustrating each concept with diagrams, token examples, and query scenarios.
This article dissects RocketMQ's concurrency mechanisms, explaining why it uses ReentrantReadWriteLock with HashMaps, how Semaphore controls async send rates, the SemaphoreReleaseOnlyOnce wrapper, the CountDownLatch‑based sync‑to‑async pattern, and the CompletableFuture redesign that reduces blocking in message replication.
