ClickHouse 25.5 版本发布说明

大数据存储技术之ClickHouse入门学习(一) centos7以上的系统只有 systemctl 命令有效。 阅读详情

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本文字数:11882;估计阅读时间:30 分钟

作者:ClickHouse Team

本文在公众号【ClickHouseInc】首发

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又到了每月一次的版本更新时间!

发布概要

ClickHouse 25.5 带来了 15 项新功能 🌸 23 项性能优化 🦋 以及 64 个缺陷修复 🐝

本次发布的亮点包括:向量相似度索引进入 Beta 阶段、Iceberg 表支持 Hive metastore catalog、支持查看每个函数何时被添加到 ClickHouse、本地工具 clickhouse-local 引入隐式表支持等诸多功能更新。

新贡献者

我们热烈欢迎所有在 25.5 版本中首次做出贡献的开发者!ClickHouse 社区正在持续壮大,正是因为大家的努力,ClickHouse 才能不断发展壮大。

以下是本次的新贡献者名单:

Andrian Iliev, Colerar, Dasha Wessely, Denis, KovalevDima, Kyamran, Marta Paes, Mojtaba Ghahari, Sachin Singh, YjyJeff, andrei tinikov, caicre, codeworse, gvoelfin, morsapaes, samay-sharma, shanfengp, tdufour

Iceberg 表支持 Hive metastore catalog

贡献者:scanhex12

ClickHouse 正在不断拓展对 Lakehouse 架构的支持。此前的版本已支持 Unity 和 AWS Glue 数据目录,本次新增了对 Hive metastore catalog 的支持。

用户可以通过 DataLakeCatalog 表引擎创建一个表来连接 Hive catalog:

SET allow_experimental_database_hms_catalog=true;
CREATE DATABASE hive
ENGINE = DataLakeCatalog('thrift://hive:9083', '', '')
SETTINGS
  catalog_type = 'hive',
  warehouse = 'demo',
  storage_endpoint = 'http://minio:9000/warehouse';

随后,便可以像操作普通表一样查询该 catalog 中的表:

SELECT count()
FROM default.`iceberg.hits`;

clickhouse-local 中的隐式表

贡献者:Alexey Milovidov

在使用 clickhouse-local 工具处理标准输入文件时,现在可以省略 FROM 和 SELECT 子句。

举个例子,假设我们想要解析 GitHub 上 football.json 项目中的一个 JSON 文件,可以使用如下查询来探索文件中的属性结构:

curl -sS 'https://raw.githubusercontent.com/openfootball/football.json/refs/heads/master/2024-25/en.1.json' | 
./clickhouse -q "JSONAllPathsWithTypes(json)" --input-format JSONAsObject
{'matches':'Array(JSON(max_dynamic_types=16, max_dynamic_paths=256))','name':'String'}

从查询结果中,我们可以看到两个属性:name 和 matches。接下来,我们可以进一步探索 matches 属性的内容:

curl -sS https://raw.githubusercontent.com/openfootball/football.json/refs/heads/master/2024-25/en.1.json | 
./clickhouse -q "arrayJoin(json.matches::Array(JSON)) LIMIT 5" --input-format JSONAsObject
{"date":"2024-08-16","round":"Matchday 1","score":{"ft":["1","0"],"ht":["0","0"]},"team1":"Manchester United FC","team2":"Fulham FC","time":"20:00"}
{"date":"2024-08-17","round":"Matchday 1","score":{"ft":["0","2"],"ht":["0","0"]},"team1":"Ipswich Town FC","team2":"Liverpool FC","time":"12:30"}
{"date":"2024-08-17","round":"Matchday 1","score":{"ft":["2","0"],"ht":["1","0"]},"team1":"Arsenal FC","team2":"Wolverhampton Wanderers FC","time":"15:00"}
{"date":"2024-08-17","round":"Matchday 1","score":{"ft":["0","3"],"ht":["0","1"]},"team1":"Everton FC","team2":"Brighton & Hove Albion FC","time":"15:00"}
{"date":"2024-08-17","round":"Matchday 1","score":{"ft":["1","0"],"ht":["1","0"]},"team1":"Newcastle United FC","team2":"Southampton FC","time":"15:00"}

如果我们希望对 matches 数组执行更深入的查询操作,就需要将查询语句改写为包含 FROM 子句的形式,如下所示:

curl -sS https://raw.githubusercontent.com/openfootball/football.json/refs/heads/master/2024-25/en.1.json |
./clickhouse -q \
"m.date, m.team1, m.team2, m.score.ft::Array(String)[1] || '-' || m.score.ft::Array(String)[2] AS score
FROM table
ARRAY JOIN json.matches::Array(JSON) AS m
LIMIT 5" \
--input-format JSONAsObject \
--output-format Pretty \
--output_format_pretty_row_numbers=0

此外,我们还支持通过指定输出格式,在查询结果中包含列名:

┏━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━┓
┃ m.date     ┃ m.team1              ┃ m.team2                    ┃ score ┃
┡━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━┩
│ 2024-08-16 │ Manchester United FC │ Fulham FC                  │ 1-0   │
├────────────┼──────────────────────┼────────────────────────────┼───────┤
│ 2024-08-17 │ Ipswich Town FC      │ Liverpool FC               │ 0-2   │
├────────────┼──────────────────────┼────────────────────────────┼───────┤
│ 2024-08-17 │ Arsenal FC           │ Wolverhampton Wanderers FC │ 2-0   │
├────────────┼──────────────────────┼────────────────────────────┼───────┤
│ 2024-08-17 │ Everton FC           │ Brighton & Hove Albion FC  │ 0-3   │
├────────────┼──────────────────────┼────────────────────────────┼───────┤
│ 2024-08-17 │ Newcastle United FC  │ Southampton FC             │ 1-0   │
└────────────┴──────────────────────┴────────────────────────────┴───────┘

introduced_in 字段用于追踪函数的新增版本

贡献者:Robert Schulzesy

stem.functions 系统表新增了一个字段 introduced_in,用于记录每个函数首次被添加到 ClickHouse 的版本号。目前该字段已经覆盖了一部分新添加的函数,未来也会陆续补充旧函数的信息。

下面是 25.5 版本中新增的函数列表:

SELECT name, introduced_in, returned_value
FROM system.functions
WHERE introduced_in = '25.5'
FORMAT PrettySpace;
 name                   description

 icebergBucket          Implements logic of iceberg bucket transform: https://iceberg.apache.org/spec/#bucket-transform-details.
 icebergHash            Implements logic of iceberg hashing transform: https://iceberg.apache.org/spec/#appendix-b-32-bit-hash-requirements.
 mapContainsValue       Checks whether the map has the specified value.
 mapContainsValueLike   Checks whether map contains value LIKE specified pattern.
 mapContainsKey         Checks whether the map has the specified key.
 mapExtractValueLike    Returns a map with elements which value matches the specified pattern.
 stringBytesEntropy     Calculates Shannon's entropy of byte distribution in a string.
 stringBytesUniq        Counts the number of distinct bytes in a string.

Parquet 格式支持 Geo 类型

贡献者:scanhex12

ClickHouse 的 Parquet 读取器现已支持 Geo 类型。我们可以通过以下查询语句,对 Overture Maps 数据集中的几何字段进行解析:

SELECT id, geometry, bbox, 
       COLUMNS('^id|geometry|bbox') APPLY(toTypeName)
FROM s3('s3://overturemaps-us-west-2/release/2025-04-23.0/theme=places/type=place/*')
WHERE categories.primary = 'pizza_restaurant'
LIMIT 1
SETTINGS schema_inference_make_columns_nullable = 0;
Row 1:
──────
id:                   08f95008132998a6036bed7d0b7e7661
geometry:             (119.4407421,-5.15814)
bbox:                 (119.44073,119.44074,-5.15814,-5.158139)
toTypeName(id):       String
toTypeName(geometry): Tuple(Float64, Float64)
toTypeName(bbox):     Tuple(
    xmin Float32,
    xmax Float32,
    ymin Float32,
    ymax Float32)

现在,geometry 字段可以被正确识别并解析。而在旧版本中,该字段通常会以二进制的形式显示,如下所示:

Row 1:
──────
id:                   08ff2a1b744f064403498c7aa7fce7a1
geometry:             (-149.069345,-83.5991503)
bbox:                 (-149.06935,-149.06932,-83.59915,-83.599144)
toTypeName(id):       String
toTypeName(geometry): Point
toTypeName(bbox):     Tuple(
    xmin Float32,
    xmax Float32,
    ymin Float32,
    ymax Float32)

有了这个改进,ClickHouse 已可用于查询 GeoParquet 数据集。我们也一直在寻找有趣的地理数据集,欢迎大家推荐值得尝试的数据源!

向量搜索进入 Beta 阶段

贡献者:Shankar Iyer

ClickHouse 中的向量相似度索引功能现已从实验阶段升级为 Beta 阶段,并新增了对混合搜索中前置过滤和后置过滤策略的支持。

我们以下面这段示例,展示如何基于 Cohere 的 Wikipedia 数据子集使用向量索引。首先,我们启用相似度索引功能:

SET allow_experimental_vector_similarity_index=1;

接着,我们创建一个包含 emb 向量字段的表,并基于该字段建立 HNSW 索引:

CREATE TABLE wikiEmbeddings (
  id Int32,
  title String,
  text String,
  url String,
  wiki_id Int32,
  views Float32,
  paragraph_id Int32,
  langs Int32,
  emb Array(Float32),
  INDEX emb_hnsw emb TYPE vector_similarity('hnsw', 'L2Distance', 768)
)
ORDER BY id;

然后从 Hugging Face 导入相应数据:

INSERT INTO wikiEmbeddings
select *
FROM url('https://huggingface.co/datasets/Cohere/wikipedia-22-12-en-embeddings/resolve/main/data/train-00000-of-00253-8d3dffb4e6ef0304.parquet')
SETTINGS max_http_get_redirects=10;

现在就可以开始查询了。以下查询将返回数据集中最相似的一条记录:

SELECT * EXCEPT emb
FROM wikiEmbeddings
WHERE id = 120356;
Row 1:
──────
id:           120356
title:        Germany national football team
text:         The Germany national football team () represents Germany in men's international football and played its first match in 1908. The team is governed by the German Football Association ("Deutscher Fußball-Bund"), founded in 1900. Between 1949 and 1990, separate German national teams were recognised by FIFA due to Allied occupation and division: the DFB's team representing the Federal Republic of Germany (commonly referred to as West Germany in English between 1949 and 1990), the Saarland team representing the Saar Protectorate (1950–1956) and the East Germany team representing the German Democratic Republic (1952–1990). The latter two were absorbed along with their records; the present team represents the reunified Federal Republic. The official name and code "Germany FR (FRG)" was shortened to "Germany (GER)" following reunification in 1990.
url:          https://en.wikipedia.org/wiki?curid=250204
wiki_id:      250204
views:        3271.844
paragraph_id: 0
langs:        98

结果显示,这条记录来自 Wikipedia 上关于德国国家足球队的页面。我们可以进一步查询与该记录最相似的其他条目:

WITH (SELECT emb FROM wikiEmbeddings WHERE id = 120356) AS lookup
SELECT id, title, text, url, L2Distance(emb, lookup) AS dist
FROM wikiEmbeddings
ORDER BY dist
LIMIT 3
FORMAT Vertical;
Row 1:
──────
id:    120356
title: Germany national football team
text:  The Germany national football team () represents Germany in men's international football and played its first match in 1908. The team is governed by the German Football Association ("Deutscher Fußball-Bund"), founded in 1900. Between 1949 and 1990, separate German national teams were recognised by FIFA due to Allied occupation and division: the DFB's team representing the Federal Republic of Germany (commonly referred to as West Germany in English between 1949 and 1990), the Saarland team representing the Saar Protectorate (1950–1956) and the East Germany team representing the German Democratic Republic (1952–1990). The latter two were absorbed along with their records; the present team represents the reunified Federal Republic. The official name and code "Germany FR (FRG)" was shortened to "Germany (GER)" following reunification in 1990.
url:   https://en.wikipedia.org/wiki?curid=250204
dist:  0

Row 2:
──────
id:    120367
title: Germany national football team
text:  The Federal Republic of Germany, which was referred to as West Germany, continued the DFB. With recognition by FIFA and UEFA, the DFB maintained and continued the record of the pre-war team. Switzerland was the first team that played West Germany in 1950, with the latter qualifying for the 1954 World Cup and the former hosting it.
url:   https://en.wikipedia.org/wiki?curid=250204
dist:  5.537961

Row 3:
──────
id:    120366
title: Germany national football team
text:  After World War II, Germany was banned from competition in most sports until 1950. The DFB was not a full member of FIFA, and none of the three new German states – West Germany, East Germany, and Saarland – entered the 1950 World Cup qualifiers.
url:   https://en.wikipedia.org/wiki?curid=250204
dist:  6.296622

不过,这些结果都来自同一篇 Wikipedia 文章的不同段落,因此参考意义有限。为了让结果更加丰富多样,我们可以添加 WHERE 子句,排除与查询记录具有相同 wiki_id 的条目:

WITH (SELECT emb FROM wikiEmbeddings WHERE id = 120356) AS lookup,
     (SELECT wiki_id FROM wikiEmbeddings WHERE id = 120356) AS lookup_wiki_id
SELECT id, title, text, url, L2Distance(emb, lookup) AS dist
FROM wikiEmbeddings
WHERE wiki_id <> lookup_wiki_id
ORDER BY dist
LIMIT 3
FORMAT Vertical;
Row 1:
──────
id:    6420
title: Germany
text:  Football is the most popular sport in Germany. With more than 7 million official members, the German Football Association ("Deutscher Fußball-Bund") is the largest single-sport organisation worldwide, and the German top league, the Bundesliga, attracts the second-highest average attendance of all professional sports leagues in the world. The German men's national football team won the FIFA World Cup in 1954, 1974, 1990, and 2014, the UEFA European Championship in 1972, 1980 and 1996, and the FIFA Confederations Cup in 2017.
url:   https://en.wikipedia.org/wiki?curid=11867
dist:  6.9714794

Row 2:
──────
id:    6336
title: Germany
text:  Formal unification of Germany into the modern nation-state was commenced on 18 August 1866 with the North German Confederation Treaty establishing the Prussia-led North German Confederation later transformed in 1871 into the German Empire. After World War I and the German Revolution of 1918–1919, the Empire was in turn transformed into the semi-presidential Weimar Republic. The Nazi seizure of power in 1933 led to the establishment of a totalitarian dictatorship, World War II, and the Holocaust. After the end of World War II in Europe and a period of Allied occupation, Germany as a whole was organized into two separate polities with limited sovereignity: the Federal Republic of Germany, generally known as West Germany, and the German Democratic Republic, East Germany, while Berlin continued its Four Power status. The Federal Republic of Germany was a founding member of the European Economic Community and the European Union, while the German Democratic Republic was a communist Eastern Bloc state and member of the Warsaw Pact. After the fall of communism, German reunification saw the former East German states join the Federal Republic of Germany on 3 October 1990—becoming a federal parliamentary republic.
url:   https://en.wikipedia.org/wiki?curid=11867
dist:  6.98255

Row 3:
──────
id:    7767
title: FIFA World Cup
text:  After FIFA was founded in 1904, it tried to arrange an international football tournament between nations outside the Olympic framework in Switzerland in 1906. These were very early days for international football, and the official history of FIFA describes the competition as having been a failure.
url:   https://en.wikipedia.org/wiki?curid=11370
dist:  7.5603456
dist:  7.736428

正如前文所述,WHERE 子句中的过滤条件可以采用后置或前置方式执行。

后置过滤指的是先使用向量索引检索候选数据,再对其执行过滤条件;而前置过滤则是先筛选符合条件的记录,再进行向量相似度匹配。

你可以通过设置系统参数 vector_search_filter_strategy 来控制过滤方式。该参数默认值为 auto,表示由查询引擎根据启发式规则自动决定最优策略。你也可以将其显式设置为 postfilter 或 prefilter,以指定过滤顺序。

ClickHouse 25.4 Docker单机部署实战:从零搭建到备份恢复 容器化部署正在成为数据库交付的主流方式,它通过镜像封装环境依赖,让一次构建随处运行成为可能。在众多OLAP引擎中,ClickHouse凭借列式存储和极速查询性能广受青睐,而采用Docker进行单机部署,既能快速获得可用实例,又能大幅降低升级和迁移成本。本文从部署选型切入,对比Docker、二进制包与包管理器三种方式的优劣,详细解析clickhouse/clickhouse-server镜像的版本选择、compose文件核心参数、config.d与users.d配置优先级等关键细节,并给出完整的初始化、启动、 阅读详情

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ClickHouseDB的博客 1841

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华为OD机试 新系统 题库疯狂收录中,刷题。

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android 下蓝牙通讯demo,实现了发现蓝牙,使能蓝牙,通过蓝牙发送消息。

ClickHouse 25.4 版本发布说明

ClickHouse 25.4 带来了 25 项新功能 🌸 23 项性能优化 🦋 以及 58 个缺陷修复 🐝

ClickHouseDB的博客 1467

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WINCC7.3硬件够破解文件,有需要的下载!WINCC7.3硬件够破解文件,有需要的下载!

ClickHouse 25.12 版本发布说明

ClickHouse 25.12 版本带来了 26 项新特性 🎄、31 项性能优化 ⛸,以及 129 个 bug 修复 ☃

ClickHouseDB的博客 940

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汉书HE8,好用的汇编代码编写工具

汉书HE8,好用的汇编代码编写工具早期编写汇编代码所用功能强大

ClickHouse 24.10 版本发布说明

本文字数:13817;估计阅读时间:35 分钟作者:ClickHouse Team本文在公众号【ClickHouseInc】首发又到了新版本发布的时间!本次ClickHouse 24.10 版本包含了🎁、🛷、🐛在本次发布中,clickhouse-local 更加实用,新增了复制和计算器模式。可刷新物化视图已达到生产就绪标准,远程文件支持缓存,表克隆操作也得到了简化。正如往常,我们热烈欢迎所有 24.9 版本中的新贡献者!

ClickHouseDB的博客 1746

ClickHouse 26.2 版本发布说明

ClickHouse 26.2 来了!在本文中,文本索引和 QBit 数据类型达到生产就绪状态。

ClickHouseDB的博客 635

ClickHouse 23.9 版本发布说明

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ClickHouseDB的博客 607

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gitblog_00260的博客 406

ClickHouse v25.9.5.21-stable 发布说明深度解析:7 个 Bug 修复的源码级解读

本文以 [v25.9.5.21-stable 变更日志](https://link.gitcode.com/i/2a88fbe0aef680e8bb81e7f8cfd5714d) 为骨架,逐条解读该稳定版中 7 个用户可见的 Bug 修复与 2 个内部改动。你可以从中掌握:Variant 子列读取、HTTP 分块流异常、Replicated 数据库恢复、`loop` 表函数访问控制、UTF-8 字

gitblog_00030的博客 9

ClickHouse v25.5.7.52-stable 发布说明:性能优化、Keeper 后台迁移与关键 Bug 修复全景解析

本文基于 ClickHouse 官方稳定版本发布日志,深入解析 v25.5.7.52-stable(commit `6e66ab95d8a`)相对上一稳定版 v25.5.6.14-stable 的全部变更内容。该版本属于 v25.5 LTS 系列的安全维护与 bugfix 迭代,聚焦 QueryTree 哈希性能加速、Keeper 变更日志异步迁移、分布式 DDL 复制延迟控制、S3/Azure

gitblog_00036的博客 10

ClickHouse 补丁发布体检:诊断 AutoReleases 流水线为何静默停发,并手动补齐缺失的补丁版本

ClickHouse 会对其支持版本(最近 3 个大版本 + 最新 LTS)按约两周一次的节奏自动发布 stable **补丁版本**,驱动者是每日调度的 `AutoReleases` 工作流。但这条流水线会"静默卡死":某个未合并的 version-bump PR 或一个失联的自托管 runner 就能让所有分支停发,而不会有任何显式报错。本文以仓库中的技能文档 [.claude/skills/

gitblog_00013的博客 260

ClickHouse v25.8.6.11-lts 发布解析:路径包含判断、Mutation Patch 与 EmbeddedRocksDB 等五处修复的源码级解读

本篇基于官方 changelog [v25.8.6.11-lts](https://link.gitcode.com/i/9f23722109a870b4e984ad19201ed22e) 展开,逐条解析该 LTS 版本相对 v25.8.5.17-lts 引入的 4 个 Bug Fix 与 1 个内部调整,并结合当前仓库中的源码实现([src/Common/filesystemHelpers.cp

gitblog_00097的博客 508

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v25.5.8.13-stable(commit `b594fb9739e`,基于 v25.5.7.52-stable)是 ClickHouse 25.5 系列的一个官方稳定补丁版本,聚焦于修复 25.5 主版本引入的**性能回退**与**稳定性缺陷**。本篇以该版本的官方变更日志([docs/changelogs/v25.5.8.13-stable.md](https://link.gitcod

gitblog_00254的博客 48
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