View Running Queries
This article describes how to view running queries in StarRocks and analyze their resource consumption.
Gather statistics for CBO
This topic describes the basic concept of CelerData CBO and how to collect statistics for the CBO. CelerData introduces histograms to gather accurate data distribution statistics.
Use Bitmap for exact Count Distinct
This topic describes how to use bitmaps to compute the number of distinct values in CelerData.
Bitmap indexing
This topic describes how to create and manage a bitmap index, along with usage cases.
Query Feedback
This topic introduces the Query Feedback feature, its application scenarios, and how to optimize query plans based on feedback from execution statistics using Query Plan Advisor.
Synchronous materialized view
This topic describes how to create, use, and manage a synchronous materialized view (Rollup).
Use HLL for approximate count distinct
Background
Bloom filter indexing
This topic describes how to create and modify bloom filter indexes, along with how they works.
Asynchronous materialized views
This topic describes how to understand, create, use, and manage an asynchronous materialized view.
Asynchronous materialized views
6 items
Automatic Materialized View Recommendation
This topic describes how to leverage the Automatic Materialized View Recommendation feature to generate schemas for materialized views that can be used to accelerate the queries in your business scenarios.
Colocate Join
For shuffle join and broadcast join, if the join condition is met, the data rows of the two joining tables are merged into a single node to complete the join. Neither of these two join methods can avoid latency or overhead caused by data network transmission between nodes.
Caching
2 items
Use Lateral Join for column-to-row conversion
Column-to-row conversion is a common operation in ETL processing. Lateral is a special Join keyword that can associate a row with an internal subquery or table function. By using Lateral in conjunction with unnest(), you can expand one row into multiple rows. For more information, see unnest.
Computing distinct value count
2 items
Sorted streaming aggregate
Common aggregation methods in database systems include hash aggregate and sort aggregate.
Accelerate COUNT(DISTINCT) and Joins with AUTO INCREMENT and Global Dictionary
This topic describes how to accelerate COUNT(DISTINCT) calculation and Joins using AUTO INCREMENT columns and Global Dictionary.
Flat JSON
This article introduces the basic concept of Flat JSON and how to use this feature.
Accelerate Cardinality-Preserving Joins
This topic describes how to accelerate cardinality-preserving joins with table pruning. This feature is supported from v3.1 onwards.
JIT Compilation for Expressions
This topic describes how to enable and configure JIT compilation for expressions in StarRocks.
Skew Join V2
Skew Join V2 is an advanced optimization feature in StarRocks that addresses data skew issues in JOIN operations by broadcasting skew values. This feature significantly improves query performance when dealing with heavily skewed data distributions.