This Week in Databend #132

Databend is a modern cloud data warehouse, serving your massive-scale analytics needs at low cost and complexity. Open source alternative to Snowflake. Also available in the cloud: https://app.databend.com .

What's New

Stay informed about the latest features of Databend.

Supporting

CREATE [ OR REPLACE ]

Databend now offers comprehensive support for the syntactic sugar

CREATE [ OR REPLACE ]

DROP IF EXISTS ...

CREATE ...

Objects that currently support this syntactic sugar include: DATABASE, TABLE, VIEW, AGGREGATING INDEX, STREAM, CONNECTION, FUNCTION, FILE FORMAT, and MASKING POLICY.

If you would like to learn more, please contact the Databend team or refer to the resources listed below:

• Issue #14299 | tracking: CREATE OR REPLACE

Code Corner

Discover some fascinating code snippets or projects that showcase our work or learning journey.

Query Analysis with Databend Cloud

Databend Cloud offers a visualization tool to simplify the analysis and understanding of complex queries.

This tool can track the performance of each step, from the duration of TableScan to the details of HashJoin, and monitor data spillage. It helps you easily analyze query costs and time for targeted optimization.

The Databend team also makes full use of this tool to assess the impact of code changes on query execution. For example, PR #14561 | feat: use materialized cte for standard stream .

Highlights

We have also made these improvements to Databend that we hope you will find helpful:

• Support for the JSON operator

  #-
  
  .
• Use of Materialized CTE in the standard stream to avoid redundant scans.
• Read the Docs | Data Management to learn how to use Databend to manage, recover, and protect your data.

What's Up Next

We're always open to cutting-edge technologies and innovative ideas. You're more than welcome to join the community and bring them to Databend.

Supporting Multi-table Insert

Databend is planning to introduce multi-table insert functionality that will allow the use of a single statement to insert into multiple tables either conditionally or unconditionally.

Multi-table insert statements can reduce the number of table scans and SQL statements needed for multiple conditional inserts. This feature is mainly applicable to the ETL process in data warehouses, supporting parallelization and/or the transformation of non-relational data into a relational format.

-- Unconditional multi-table insert
INSERT [OVERWRITE] ALL
  intoClause [...]
<subquery>

-- Conditional multi-table insert
INSERT [OVERWRITE] {FIRST | ALL}
  {WHEN <condition> THEN intoClause [...]}
  [...]
  [ELSE intoClause]
<subquery>

Issue #14565 | Feature: Multi-table Inserts support

Please let us know if you're interested in contributing to this feature, or pick up a good first issue at https://link.databend.com/i-m-feeling-lucky to get started.

Changelog

You can check the changelog of Databend Nightly for details about our latest developments.

Full Changelog: https://github.com/datafuselabs/databend/compare/v1.2.331-nightly...v1.2.341-nightly