用ClickHouse在GitHub上数星星

在最大的基友交友网站GitHub上，来自世界各地的开源开发者们进行着数百万个项目。这里每天都有大量的代码文档、修复和提交BUG之类的事件信息产生。

而GitHub Archive项目，正是搜集了这些GitHub timeline上记录的公共数据，并对其存档，使其易于访问，以进行进一步分析。

项目地址：

https://www.gharchive.org/

GitHub Archive数据包含了自2011年以来GitHub存储的所有事件。

记录的数据量有31亿条，总数据压缩后为73GB。

这样的数据集不放在ch里真是浪费了，下面就看看里面有啥好玩的东西，一起来数星星吧。

1 环境准备：

数据的获取方式有以下几种，没有试验环境的可以直接第三种。

方式1：下载文件载入数据集

# 1. 下载数据文件

wget https://datasets.clickhouse.tech/github_events_v2.native.xz

# 2. 建表：

CREATE TABLE test.github_events
(file_time DateTime,event_type Enum('CommitCommentEvent' = 1, 'CreateEvent' = 2, 'DeleteEvent' = 3, 'ForkEvent' = 4,'GollumEvent' = 5, 'IssueCommentEvent' = 6, 'IssuesEvent' = 7, 'MemberEvent' = 8,'PublicEvent' = 9, 'PullRequestEvent' = 10, 'PullRequestReviewCommentEvent' = 11,'PushEvent' = 12, 'ReleaseEvent' = 13, 'SponsorshipEvent' = 14, 'WatchEvent' = 15,'GistEvent' = 16, 'FollowEvent' = 17, 'DownloadEvent' = 18, 'PullRequestReviewEvent' = 19,'ForkApplyEvent' = 20, 'Event' = 21, 'TeamAddEvent' = 22),actor_login LowCardinality(String),repo_name LowCardinality(String),created_at DateTime,updated_at DateTime,action Enum('none' = 0, 'created' = 1, 'added' = 2, 'edited' = 3, 'deleted' = 4, 'opened' = 5, 'closed' = 6, 'reopened' = 7, 'assigned' = 8, 'unassigned' = 9,'labeled' = 10, 'unlabeled' = 11, 'review_requested' = 12, 'review_request_removed' = 13, 'synchronize' = 14, 'started' = 15, 'published' = 16, 'update' = 17, 'create' = 18, 'fork' = 19, 'merged' = 20),comment_id UInt64,body String,path String,position Int32,line Int32,ref LowCardinality(String),ref_type Enum('none' = 0, 'branch' = 1, 'tag' = 2, 'repository' = 3, 'unknown' = 4),creator_user_login LowCardinality(String),number UInt32,title String,labels Array(LowCardinality(String)),state Enum('none' = 0, 'open' = 1, 'closed' = 2),locked UInt8,assignee LowCardinality(String),assignees Array(LowCardinality(String)),comments UInt32,author_association Enum('NONE' = 0, 'CONTRIBUTOR' = 1, 'OWNER' = 2, 'COLLABORATOR' = 3, 'MEMBER' = 4, 'MANNEQUIN' = 5),closed_at DateTime,merged_at DateTime,merge_commit_sha String,requested_reviewers Array(LowCardinality(String)),requested_teams Array(LowCardinality(String)),head_ref LowCardinality(String),head_sha String,base_ref LowCardinality(String),base_sha String,merged UInt8,mergeable UInt8,rebaseable UInt8,mergeable_state Enum('unknown' = 0, 'dirty' = 1, 'clean' = 2, 'unstable' = 3, 'draft' = 4),merged_by LowCardinality(String),review_comments UInt32,maintainer_can_modify UInt8,commits UInt32,additions UInt32,deletions UInt32,changed_files UInt32,diff_hunk String,original_position UInt32,commit_id String,original_commit_id String,push_size UInt32,push_distinct_size UInt32,member_login LowCardinality(String),release_tag_name String,release_name String,review_state Enum('none' = 0, 'approved' = 1, 'changes_requested' = 2, 'commented' = 3, 'dismissed' = 4, 'pending' = 5)
)
ENGINE = MergeTree
ORDER BY (event_type, repo_name, created_at);

# 3. 导入数据

xz -d < github_events_v2.native.xz | clickhouse-client --query "INSERT INTO test.github_events FORMAT Native"

# 4. 可以看到导入速度还是很快的

方式2：URL地址方式导入数据集

如果觉得下载导入的方式比较慢，可以创建一个外部表，直接从URL地址中读取数据，省去了单独下载和解压缩步骤。

注意：要求ClickHouse版本20.12以上，并且操作系统支持xz解压。

# 1. 建立url外部表

CREATE TABLE github_events_url
(file_time DateTime,event_type Enum('CommitCommentEvent' = 1, 'CreateEvent' = 2, 'DeleteEvent' = 3, 'ForkEvent' = 4,'GollumEvent' = 5, 'IssueCommentEvent' = 6, 'IssuesEvent' = 7, 'MemberEvent' = 8,'PublicEvent' = 9, 'PullRequestEvent' = 10, 'PullRequestReviewCommentEvent' = 11,'PushEvent' = 12, 'ReleaseEvent' = 13, 'SponsorshipEvent' = 14, 'WatchEvent' = 15,'GistEvent' = 16, 'FollowEvent' = 17, 'DownloadEvent' = 18, 'PullRequestReviewEvent' = 19,'ForkApplyEvent' = 20, 'Event' = 21, 'TeamAddEvent' = 22),actor_login LowCardinality(String),repo_name LowCardinality(String),created_at DateTime,updated_at DateTime,action Enum('none' = 0, 'created' = 1, 'added' = 2, 'edited' = 3, 'deleted' = 4, 'opened' = 5, 'closed' = 6, 'reopened' = 7, 'assigned' = 8, 'unassigned' = 9,'labeled' = 10, 'unlabeled' = 11, 'review_requested' = 12, 'review_request_removed' = 13, 'synchronize' = 14, 'started' = 15, 'published' = 16, 'update' = 17, 'create' = 18, 'fork' = 19, 'merged' = 20),comment_id UInt64,body String,path String,position Int32,line Int32,ref LowCardinality(String),ref_type Enum('none' = 0, 'branch' = 1, 'tag' = 2, 'repository' = 3, 'unknown' = 4),creator_user_login LowCardinality(String),number UInt32,title String,labels Array(LowCardinality(String)),state Enum('none' = 0, 'open' = 1, 'closed' = 2),locked UInt8,assignee LowCardinality(String),assignees Array(LowCardinality(String)),comments UInt32,author_association Enum('NONE' = 0, 'CONTRIBUTOR' = 1, 'OWNER' = 2, 'COLLABORATOR' = 3, 'MEMBER' = 4, 'MANNEQUIN' = 5),closed_at DateTime,merged_at DateTime,merge_commit_sha String,requested_reviewers Array(LowCardinality(String)),requested_teams Array(LowCardinality(String)),head_ref LowCardinality(String),head_sha String,base_ref LowCardinality(String),base_sha String,merged UInt8,mergeable UInt8,rebaseable UInt8,mergeable_state Enum('unknown' = 0, 'dirty' = 1, 'clean' = 2, 'unstable' = 3, 'draft' = 4),merged_by LowCardinality(String),review_comments UInt32,maintainer_can_modify UInt8,commits UInt32,additions UInt32,deletions UInt32,changed_files UInt32,diff_hunk String,original_position UInt32,commit_id String,original_commit_id String,push_size UInt32,push_distinct_size UInt32,member_login LowCardinality(String),release_tag_name String,release_name String,review_state Enum('none' = 0, 'approved' = 1, 'changes_requested' = 2, 'commented' = 3, 'dismissed' = 4, 'pending' = 5)
) ENGINE = URL('https://datasets.clickhouse.tech/github_events_v2.native.xz', Native);

# 2. 创建目标表并插入数据：

CREATE TABLE github_events
ENGINE = MergeTree
ORDER BY (event_type, repo_name, created_at)
AS SELECT * FROM github_events_url;

这时候，有两个年轻人，三十多岁，一个直接导入，一个用RUL导入。

他们说，我佐田啊，搞到现在数据都没载入完，很慢啊！

公老师你能不能教教我浑元功法，哎…帮助加快下速度？

我说：可以

方式3：拿来现成的直接用

感谢慷慨大方的Yandex 和 Altinity大老爷，提供了的完整的demo环境，可以拿来直接跑SQL。

# Yandex.Cloud 提供的连接方式

--客户端连接:

clickhouse-client -m --secure --host gh-api.clickhouse.tech --user explorer

HTTPS interface:

https://gh-api.clickhouse.tech/ (port 443)

# Altinity.Cloud 提供的连接方式

--客户端连接:

clickhouse-client -m -h github.demo.trial.altinity.cloud --port 9440 -s --user=demo --password=demo

--使用DBeaver通过 HTTPS 或 JDBC方式连接:

https://demo:demo@github.demo.trial.altinity.cloud:8443jdbc:clickhouse://github.demo.trial.altinity.cloud:8443

有人又说了，那我这里刚通网，连个能装客户端的电脑都没有。

没关系，还能通过Web UI手机直连:

https://gh-api.clickhouse.tech/play?user=play

手机微信里点开效果是这样的：

2 查询：

# GitHub上所有的项目库数量

SELECT uniq(repo_name)
FROM github_eventsQuery id: 1ce49a10-5847-4913-97cc-14057961ac16┌─uniq(repo_name)─┐
│       165892137 │
└─────────────────┘1 rows in set. Elapsed: 6.098 sec. Processed 3.17 billion rows, 25.39 GB (519.31 million rows/s., 4.16 GB/s.)

# GitHub上所有项目星星的数量

SELECT count()
FROM github_events
WHERE event_type = 'WatchEvent'Query id: 0e025870-afcd-4376-ba05-7cfb418a2e04┌───count()─┐
│ 234497476 │
└───────────┘

# 星星分布情况，超过10万星的有21个项目。

SELECTexp10(floor(log10(c))) AS stars,uniq(k)
FROM
(SELECTrepo_name AS k,count() AS cFROM github_eventsWHERE event_type = 'WatchEvent'GROUP BY k
)
GROUP BY stars
ORDER BY stars ASCQuery id: b5defdb0-2ce6-46cb-911a-70b4ba3de038┌──stars─┬──uniq(k)─┐
│      1 │ 15129932 │
│     10 │  1207927 │
│    100 │   214942 │
│   1000 │    29202 │
│  10000 │     1864 │
│ 100000 │       21 │
└────────┴──────────┘6 rows in set. Elapsed: 3.895 sec. Processed 234.53 million rows, 1.84 GB (60.21 million rows/s., 472.73 MB/s.)

# 每年增长的星星数量

SELECTtoYear(created_at) AS year,count() AS stars,bar(stars, 0, 50000000, 10) AS bar
FROM github_events
WHERE event_type = 'WatchEvent'
GROUP BY year
ORDER BY year ASCQuery id: 79d1086b-dba9-4a23-a066-9ac945e3fb3a┌─year─┬────stars─┬─bar────────┐
│ 2011 │  1831742 │ ▎          │
│ 2012 │  4048676 │ ▋          │
│ 2013 │  7432800 │ █▍         │
│ 2014 │ 11952935 │ ██▍        │
│ 2015 │ 18994833 │ ███▋       │
│ 2016 │ 26166310 │ █████▏     │
│ 2017 │ 32640040 │ ██████▌    │
│ 2018 │ 37068153 │ ███████▍   │
│ 2019 │ 46118187 │ █████████▏ │
│ 2020 │ 48266671 │ █████████▋ │
└──────┴──────────┴────────────┘10 rows in set. Elapsed: 1.135 sec. Processed 234.56 million rows, 1.17 GB (206.75 million rows/s., 1.03 GB/s.)

# ClickHouse项目的星星数

SELECT count()
FROM github_events
WHERE (event_type = 'WatchEvent') AND (repo_name IN ('ClickHouse/ClickHouse', 'yandex/ClickHouse'))
GROUP BY actionQuery id: f1aeab13-9359-4661-83ca-e0e73c3ead19┌─count()─┐
│   14613 │
└─────────┘

这个数字和当前GitHub页面中的数量还是很接近的。

# 星星数量排名前10的项目库

SELECTrepo_name,count() AS stars
FROM github_events
WHERE event_type = 'WatchEvent'
GROUP BY repo_name
ORDER BY stars DESC
LIMIT 10Query id: 1b693fe3-69ce-4a12-bb9d-7a1bb42c85b1┌─repo_name───────────────────────┬──stars─┐
│ 996icu/996.ICU                  │ 355326 │
│ FreeCodeCamp/FreeCodeCamp       │ 225490 │
│ vuejs/vue                       │ 200737 │
│ facebook/react                  │ 189715 │
│ tensorflow/tensorflow           │ 174528 │
│ sindresorhus/awesome            │ 162187 │
│ kamranahmedse/developer-roadmap │ 150154 │
│ getify/You-Dont-Know-JS         │ 145096 │
│ freeCodeCamp/freeCodeCamp       │ 140868 │
│ twbs/bootstrap                  │ 126939 │
└─────────────────────────────────┴────────┘10 rows in set. Elapsed: 2.052 sec. Processed 234.53 million rows, 1.84 GB (114.32 million rows/s., 897.53 MB/s.)

排名靠前的很多都是学习教育类的项目，编程学习类项目FreeCodeCamp由于大小写问题被分成了2项，它实际上是星数最多的。

排名第一，完全不讲武德的996.ICU。

it's not for software, but more like a project to improve awareness about work schedules in different Chinese companies. But wait... it's not the top repo.

# 历年的TOP5项目

SELECTyear,lower(repo_name) AS repo,count()
FROM github_events
WHERE (event_type = 'WatchEvent') AND (year >= 2015)
GROUP BYrepo,toYear(created_at) AS year
ORDER BYyear ASC,count() DESC
LIMIT 5 BY yearQuery id: d4c78b77-0827-4588-89ef-a18bdd3f236e┌─year─┬─repo──────────────────────┬─count()─┐
│ 2015 │ freecodecamp/freecodecamp │   53806 │
│ 2015 │ facebook/react-native     │   25888 │
│ 2015 │ apple/swift               │   25834 │
│ 2015 │ sindresorhus/awesome      │   24420 │
│ 2015 │ facebook/react            │   22977 │
└──────┴───────────────────────────┴─────────┘
┌─year─┬─repo────────────────────────────────┬─count()─┐
│ 2016 │ freecodecamp/freecodecamp           │  182203 │
│ 2016 │ jwasham/google-interview-university │   31522 │
│ 2016 │ vhf/free-programming-books          │   28870 │
│ 2016 │ vuejs/vue                           │   28831 │
│ 2016 │ tensorflow/tensorflow               │   28282 │
└──────┴─────────────────────────────────────┴─────────┘
┌─year─┬─repo────────────────────────────────┬─count()─┐
│ 2017 │ freecodecamp/freecodecamp           │   96359 │
│ 2017 │ tensorflow/tensorflow               │   49278 │
│ 2017 │ vuejs/vue                           │   48185 │
│ 2017 │ facebook/react                      │   34524 │
│ 2017 │ mr-mig/every-programmer-should-know │   30991 │
└──────┴─────────────────────────────────────┴─────────┘
┌─year─┬─repo────────────────────────────┬─count()─┐
│ 2018 │ vuejs/vue                       │   51515 │
│ 2018 │ trekhleb/javascript-algorithms  │   39249 │
│ 2018 │ facebook/react                  │   38817 │
│ 2018 │ flutter/flutter                 │   38357 │
│ 2018 │ danistefanovic/build-your-own-x │   37815 │
└──────┴─────────────────────────────────┴─────────┘
┌─year─┬─repo──────────────────────┬─count()─┐
│ 2019 │ 996icu/996.icu            │  344825 │
│ 2019 │ jackfrued/python-100-days │   76845 │
│ 2019 │ m4cs/babysploit           │   71013 │
│ 2019 │ microsoft/terminal        │   56844 │
│ 2019 │ snailclimb/javaguide      │   53444 │
└──────┴───────────────────────────┴─────────┘
┌─year─┬─repo────────────────────────────────┬─count()─┐
│ 2020 │ labuladong/fucking-algorithm        │   80938 │
│ 2020 │ jwasham/coding-interview-university │   60509 │
│ 2020 │ kamranahmedse/developer-roadmap     │   53550 │
│ 2020 │ donnemartin/system-design-primer    │   39731 │
│ 2020 │ public-apis/public-apis             │   39552 │
└──────┴─────────────────────────────────────┴─────────┘30 rows in set. Elapsed: 18.161 sec. Processed 233.93 million rows, 2.75 GB (12.88 million rows/s., 151.52 MB/s.)

每年的历代王者：

freecodecamp (2015-2017 )
vue (2018 )
996.icu (2019)
国产算法刷题 fucking-algorithm (2020)

# 各大公司组织的星星数量（阿里还是挺NB）

SELECTlower(substring(repo_name, 1, position(repo_name, '/'))) AS org,count() AS stars
FROM github_events
WHERE event_type = 'WatchEvent'
GROUP BY org
ORDER BY stars DESC
LIMIT 10Query id: 2db5a630-1b1f-4755-af5d-b58d29ab0596┌─org───────────┬───stars─┐
│ google/       │ 1425341 │
│ microsoft/    │ 1382470 │
│ facebook/     │ 1128478 │
│ alibaba/      │  586424 │
│ sindresorhus/ │  572216 │
│ apache/       │  558924 │
│ vuejs/        │  497920 │
│ tensorflow/   │  428196 │
│ freecodecamp/ │  408759 │
│ fossasia/     │  403761 │
└───────────────┴─────────┘10 rows in set. Elapsed: 2.041 sec. Processed 234.56 million rows, 1.84 GB (114.91 million rows/s., 903.00 MB/s.)

类似的分析还有很多，感兴趣的可以参照原文地址挨个试试

https://gh.clickhouse.tech/explorer/#counting-stars

# 历史文章

GitHub都在用的高可用工具Orch：

Orchestrator：01 基础篇

Orchestrator：02 高可用方案VIP篇

Orchestrator：03 高可用方案ProxySQL篇

Orchestrator：04 高可用方式部署

Percona 全力打造的监控平台 PMM：

监控利器 PMM2.0X GA 版本发布！

PMM监控的告警配置

PMM的Ansible部署与重点指标

在PMM中添加Redis和ES

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