This article discusses solutions to system bottlenecks in supply chain planning business development, focusing on ClickHouse ReplacingMergeTree table creation, local join optimization, and real-time data synchronization between TiDB and ClickHouse to improve query performance and system stability.
The article describes a real‑world ClickHouse incident where excessive UPDATE‑style mutations caused a “too many mutations(1036)” error, explains the cluster’s configuration, and details a step‑by‑step recovery process that clears pending mutations and migrates tables to the ReplacingMergeTree engine to restore service.
This article details how JDQ+Flink+Elasticsearch was extended with ClickHouse for real‑time reporting, covering table‑engine selection, Flink sink implementation, query optimization techniques, high‑CPU shard analysis, and practical strategies to ensure high concurrency and stable performance in production.
This article explains how ClickHouse can act as a MySQL replica, covering full and incremental synchronization, supported MySQL versions, DDL compatibility, handling of DELETE/UPDATE events, the underlying binlog mechanism, and provides complete code examples to set up both MySQL master and ClickHouse slave.
