ClickHouse Cloudにマルチステージ分散クエリ実行を導入

ClickHouse Cloud has introduced a multi-stage distributed execution model that allows a single query to scale across numerous nodes, effectively addressing bottlenecks in large JOIN operations and high cardinality aggregations by repartitioning intermediate data between stages. This advancement has demonstrated up to a 3.4x speedup in JOIN-heavy queries and nearly linear scaling in aggregation processes, achieving a 7.4x speedup with eight nodes compared to one. Despite previous capabilities for scaling queries across multiple nodes through physical sharding and distributed table engines, modern petabyte-scale workloads necessitated a solution beyond these methods, which were limited by their inability to freely repartition intermediate results between execution stages. The new model leverages shared storage and parallel replicas for query scaling within ClickHouse Cloud, and introduces an exchange operator to redistribute data between plan stages, enabling efficient large-scale JOINs without requiring a full right-hand hash table on each node. The multi-stage distributed execution model further improves memory efficiency and allows for consistent query performance by dynamically allocating stages across a cluster, utilizing shared storage for data access, and optimizing memory use through shuffling. Initial benchmarks using the TPC-H standard showed significant performance improvements, highlighting the model's potential for scaling analytical workloads and setting the stage for future optimizations with the development of a cost-based optimizer. Currently, this feature is in an experimental phase, available through ClickHouse Cloud’s private preview program.

No tracked trend matches for this post yet.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.