Query Acceleration

📄️ 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.

📄️ 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

5 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.