ClickHouse® is a free analytics DBMS for big data

ClickHouse — open source distributed column-oriented DBMS

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

Useful Links

  • Official website has quick high-level overview of ClickHouse on main page.
  • Tutorial shows how to set up and query 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 to chat with ClickHouse users in real-time.
  • Blog contains various ClickHouse-related articles, as well as announcements and reports about events.
  • Code Browser with syntax highlight and navigation.
  • Contacts can help to get your questions answered if there are any.
Comments
  • Let's Encrypt Integration

    Let's Encrypt Integration

    Use case

    Specify the domain name and open the HTTP port in the server config to automatically request an SSL certificate. Maintain certificate renewal automatically.

    See https://caddyserver.com/ for example.

  • tests/stress: fix TSan detection (enables thread fuzzer for non-TSan builds)

    tests/stress: fix TSan detection (enables thread fuzzer for non-TSan builds)

    Right now check does not work:

    ++ clickhouse local -q 'select value like '\''% -fsanitize=thread %'\'' from system.build_options where name='\''CXX_FLAGS'\'''
    /run.sh: line 10: clickhouse: command not found
    + is_tsan_build=
    + '[' '' -eq 0 ']'
    /run.sh: line 11: [: : integer expression expected
    

    Follow-up for: #38106 (cc @tavplubix @alesapin)

    Changelog category (leave one):

    • Not for changelog (changelog entry is not required)
  • ClickHouse Upsampling Time Series

    ClickHouse Upsampling Time Series

    I want to upsample time series in ClickHouse. I have a 1 hour frequency data that I want to upsample into 1 minute data by linear interpolation or other simple filling methods.

    The documentation shows that the FILL operator allows to do that, however, it allows to fill null values whenever found. What I am doing is first create new Datetime values with 1 minute frequency, then perform the fill operator.

    Any ideas on how to increase the time granularity in ClickHouse?

  • (Window View is an experimental feature) Fix LOGICAL_ERROR for WINDOW VIEW with incorrect structure

    (Window View is an experimental feature) Fix LOGICAL_ERROR for WINDOW VIEW with incorrect structure

    Changelog category (leave one):

    • Bug Fix (user-visible misbehavior in official stable or prestable release)

    Changelog entry (a user-readable short description of the changes that goes to CHANGELOG.md):

    (Window View is a experimental feature) Fix LOGICAL_ERROR for WINDOW VIEW with incorrect structure

    Caching header of the source table in the WINDOW VIEW should not be done, since there is no ability to get notification when it had been changed (ALTER or CREATE/DROP).

    And this fires on CI, when the following tests had been executed in order in stress tests:

    • 01050_window_view_parser_tumble (leaves wm for mt)

    • 01748_partition_id_pruning (cache input_header)

    • 01188_attach_table_from_path (insert into mt with wm attached and incorrect structure)

    Follow-up for: #37965 (@Vxider) Fixes: #37815

  • Enable `enable_positional_arguments`

    Enable `enable_positional_arguments`

    Changelog category (leave one):

    • Backward Incompatible Change

    Changelog entry (a user-readable short description of the changes that goes to CHANGELOG.md):

    Enable setting enable_positional_arguments by default.

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