This Week in Databend #131

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 GEO Data Types

This week, Databend has added preliminary support for geographic data types to better handle the storage and manipulation of geographic data. This implementation uses EWKB to serialize geographic data and EWKT to display it.

Previously, Databend already supported a large number of geographic data-related functions, and we will continue to advance our support for processing geographic data to provide a rich set of queries and operations for geographic locations.

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

Code Corner

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

Supporting Structured Tracing

Databend now supports structured logging that allows for grouping logs by request and arranging them by call stack.

Enable with the following configuration:

[log.structlog]
on = true
dir = "./.databend/structlog"

The structured log will look like this:

PR #14495 | feat: add structlog

Highlights

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

Added support for create or replace [ table | user | function | connection | stage ].
Added support for window functions in subqueries.
Added support for enabling parquet-rs as an alternative to parquet2 in FUSE engine.
Introduced aggregate hash tables into pipeline to further improve query performance.

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 Histogram Aggregate Function

Databend plans to support histogram statistics for columns in analyze table to provide distribution details of the data within a column.The first step is to support the histogram aggregate function:

histogram(number_of_bins)(values)

Issue #14588 | Feature: histogram aggregate function

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