The ch-bench from clickhouse

ch-bench's Introduction

ClickHouse® is an open-source column-oriented database management system that allows generating analytical data reports in real-time.

How To Install (Linux, macOS, FreeBSD)

curl https://clickhouse.com/ | sh

Useful Links

Official website has a quick high-level overview of ClickHouse on the main page.
ClickHouse Cloud ClickHouse as a service, built by the creators and maintainers.
Tutorial shows how to set up and query a small ClickHouse cluster.
Documentation provides more in-depth information.
YouTube channel has a lot of content about ClickHouse in video format.
Slack and Telegram allow chatting with ClickHouse users in real-time.
Blog contains various ClickHouse-related articles, as well as announcements and reports about events.
Code Browser (github.dev) with syntax highlighting, powered by github.dev.
Contacts can help to get your questions answered if there are any.

Monthly Release & Community Call

Every month we get together with the community (users, contributors, customers, those interested in learning more about ClickHouse) to discuss what is coming in the latest release. If you are interested in sharing what you've built on ClickHouse, let us know.

v24.5 Community Call - May 30

Upcoming Events

Keep an eye out for upcoming meetups and events around the world. Somewhere else you want us to be? Please feel free to reach out to tyler <at> clickhouse <dot> com. You can also peruse ClickHouse Events for a list of all upcoming trainings, meetups, speaking engagements, etc.

ClickHouse Meetup in Bengaluru - May 4
ClickHouse Happy Hour @ Tom's Watch Bar - Los Angeles - May 22
ClickHouse & Confluent Meetup in Dubai - May 28
ClickHouse Meetup in Stockholm - Jun 3
ClickHouse Meetup @ Cloudflare - San Francisco - Jun 4
ClickHouse (クリックハウス) Meetup Tokyo - Jun 5
ClickHouse Meetup in Amsterdam - Jun 27
ClickHouse Meetup in Paris - Jul 9
ClickHouse Meetup @ Ramp - New York City - Jul 9

Recent Recordings

Recent Meetup Videos: Meetup Playlist Whenever possible recordings of the ClickHouse Community Meetups are edited and presented as individual talks. Current featuring "Modern SQL in 2023", "Fast, Concurrent, and Consistent Asynchronous INSERTS in ClickHouse", and "Full-Text Indices: Design and Experiments"
Recording available: v24.4 Release Call All the features of 24.4, one convenient video! Watch it now!

Interested in joining ClickHouse and making it your full-time job?

We are a globally diverse and distributed team, united behind a common goal of creating industry-leading, real-time analytics. Here, you will have an opportunity to solve some of the most cutting-edge technical challenges and have direct ownership of your work and vision. If you are a contributor by nature, a thinker and a doer - we’ll definitely click!

Check out our current openings here: https://clickhouse.com/company/careers

Can't find what you are looking for, but want to let us know you are interested in joining ClickHouse? Email [email protected]!

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ch-bench's Issues

use numbers_mt instead numbers

mt - multi thread

select * from system.numbers limit 1000000000 format Null;
0 rows in set. Elapsed: 0.475 sec. Processed 1.00 billion rows, 8.00 GB (2.10 billion rows/s., 16.83 GB/s.)

select * from system.numbers_mt limit 1000000000 format Null;
0 rows in set. Elapsed: 0.305 sec. Processed 1.00 billion rows, 8.00 GB (3.28 billion rows/s., 26.21 GB/s.)

Deserialization should be considered in benchmark

Hi @ernado, it seems not all benchmarks considered de-serialization(not only reading blocks but also converting bytes into uint64). Taking ch-bench-official as an example, rows.Scan should be called before count++ according to the example below:

https://github.com/ClickHouse/clickhouse-go/blob/a22f61818dd9c2d23e457c792b8dca44ab875060/benchmark/v2/read/main.go#L43-L53

Consider about adding benchmarks to measure inserting performance

In readme: The main goal is to measure minimal client overhead (CPU, RAM) to **read data**, i.e. data blocks deserialization and transfer.

Maybe adding benchmarks to measure inserting performance will help people who are in heavy insert use cases to choose clickhouse client.

Benchmarks should be more accurate, more attention to details please

Thanks for benchmarking.

I've noticed that not all libraries are in the same condition. For instance, loyd/clickhouse.rs uses LZ4 by default, that's a reasonable default, but the best library uses no compression by default AFAIK. Disabling it increases performance x2 on my machine.

I would like to see more attention to such details for all other libraries, not only for your favorite one.

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