clickhouse / clickhouse-presentations

Presentations, meetups and talks about ClickHouse

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.

• v24.3 Community Call - Mar 26
• v24.4 Community Call - Apr 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 Dubai - May 28

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: v24.2 Release Call All the features of 24.2, 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]!

clickhouse-presentations's Issues

parseDateTime minutes:seconds.fraction

ClickHouse 23.8.2.7 LTS

SELECT parseDateTime('01:16.520000', '%i:%s.%f')

VALUE_IS_OUT_OF_RANGE_OF_DATA_TYPE (expected 76.52)

I am trying to parse the string into a fractional duration (in seconds), so not really a DateTime type, but I did not find a suitable parsing function

Index page with presentations names and links

Single page listing all presentations with clickable link to presentation itself and to YouTube recording (if avaliable)

《重大爆料》免费带人回血是真的吗《手机搜狐网》

（叶凡√企鹅√Ｑ✅：√8223590 √：✅推荐信誉平台√✅:ｚｈ1８．ｖｉｐ√金✅牌团队顶尖计划?万人推荐
千万人推荐！人可以平凡，但绝不能平庸。当你有想法时，与其听非专业人士随便说，影响了你对一个事物的认知和判断，莫不如找个你信得过的专业团队或者加我QQ
聊聊，专业的事交给专业的人去做，会让你省时、省力、省心且一本万利。来源：央视网、人民网、搜狐财经、新华网、凤凰资讯、网易新闻、知乎日报、热点资讯、搜狐新闻、新浪新闻

统筹：发财神、太陽神、醉逍遥

责任编辑：叶凡

监制：叶凡

want PDF edition

Could you provide a PDF edition for the following links ？
https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup49/roadmap/index.html
https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup50/new_features/index.html
the PDF edition is very convenient for the readonly user.

When is the model trained?

This presentation is confusing in that it does not explain how/when the model is trained. It goes right to the section "Working with the trained model". Did model training take place somewhere else?

:) SELECT avg(ACTION) FROM amazon_train

{{ what happens here? }}

Working with the trained model