📄️ Introduction to Query Tuning
Query tuning is essential for achieving high performance and reliability in StarRocks. This directory brings together practical guides, reference materials, and actionable recipes to help you analyze, diagnose, and optimize query performance at every stage—from writing SQL to interpreting execution details.
📄️ Query Plan
Optimizing query performance is a common challenge in analytics systems. Slow queries can impair user experience and overall cluster performance. In StarRocks, understanding and interpreting query plans and query profiles is the foundation for diagnosing and improving slow queries. These tools help you:
📄️ Query Profile Overview
Introduction
📄️ Query Tuning Recipes
A pragmatic playbook: symptom → root cause → proven fixes.
📄️ Schema Tuning Recipes
This document provides practical tips and best practices for optimizing query performance in StarRocks through effective schema design and foundational table choices. By understanding how different table types, keys, and distribution strategies impact query execution, you can significantly improve both speed and resource efficiency. Use these guidelines to make informed decisions when designing schemas, selecting table types, and tuning your StarRocks environment for high-performance analytics.
📄️ Explain Analyze
This document explains how to obtain and analyze text-based Query Profiles in StarRocks. It will help you understand query performance and find ways to optimize your SQL queries.
📄️ Query Hint
Query hints are directives or comments that explicitly suggest the query optimizer on how to execute a query. Currently, StarRocks supports three types of hints: system variable hint (SETVAR), user-defined variable hint (SETUSER_VARIABLE), and Join hint. Hints only take effect within a single query.
📄️ Query Profile Metrics
Authoritative reference for raw metrics emitted by StarRocks Query Profile, grouped by operator.