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Guide for Query Optimization

TL;DR

Query optimization in ClickHouse starts with understanding how queries are executed, identifying bottlenecks, and applying systematic optimization techniques. The most impactful optimizations come from proper schema design (sorting keys, data types), reducing data scanned (partition pruning, data skipping indices), and choosing the right query structure (PREWHERE, avoiding unnecessary JOINs).

This guide provides a framework for query optimization in ClickHouse.

Understanding Query Execution

ClickHouse executes queries in several stages:

  1. Query parsing and planning: ClickHouse parses the SQL and creates an execution plan
  2. Data pruning: Uses partition keys and data skipping indices to reduce data scanned
  3. Data reading: Reads only the necessary columns and rows
  4. Processing: Applies filters, aggregations, and transformations
PreviousHow to write efficient queries
NextSorting Key and Index Granularity

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Guide for Query Optimization | ClickHouse for Developers