牛X | 一款比传统数据库快100-1000倍的数据库，认识一下

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mySoul

修改于 2020-09-21 10:09:58

4830

修改于 2020-09-21 10:09:58

文章被收录于专栏：mySoulmySoul

这是小小本周的第五篇

核酸检测

小小马上都要回学校考英语四级了，学校要求考英语四级的时候，需要做核算检测，这不，小小从小窝出发去做核算检测了。到北京佑安医院做核酸检测。

规划路线

小小规划路线中

启程出发

小小启程出发啦

路途

路途经过北京大观园，同时也经过一个不知道啥名称的河道。

到达筛查门诊

开发票

开发票，小小开发票，检测报告单，这次由于之前在京医通上预约过，所以直接就能开发票，检测！

到了晚上，检测结果出炉

到了晚上检测结果出炉，为阴性。小小本周六就能入校考试啦。

好啦，开始今天的文章

clickHouse 是什么？

ClickHouse 是一个列式数据库管理系统(OLAP)

学习之前需要一些基础概念

OLTP 传统的关系型数据库，操作为增删查改，强调事物一致性，例如银行系统，电商系统。

OLAP 仓库型数据库，主要任务读取数据，做复杂数据分析，侧重技术决策支持，提供直观简单的结果

在传统中，数据按照如下保存

在列式数据库中，按照如下保存

两者保存方式上的对比

用两张动图详细解释

ClickHouse实践

判断适合场景

网页端和客户端产品的数据分析

广告系统和实时竞价广告

电信行业

电商和金融行业

信息安全

实时监控和遥感测量

时间序列

商业智能

在线游戏

所有的互联网场景

不适合的场景

联机事物处理

键值对数据高效率访问请求

二进制数据或文件存储

简单使用

Ubuntu

sudo apt-get install apt-transport-https ca-certificates dirmngr
sudo apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv E0C56BD4

echo "deb https://repo.clickhouse.tech/deb/stable/ main/" | sudo tee 
    /etc/apt/sources.list.d/clickhouse.list
sudo apt-get update

sudo apt-get install -y clickhouse-server clickhouse-client

sudo service clickhouse-server start
clickhouse-client

Centos

添加存储库

sudo yum install yum-utils
sudo rpm --import https://repo.clickhouse.tech/CLICKHOUSE-KEY.GPG
sudo yum-config-manager --add-repo https://repo.clickhouse.tech/rpm/stable/x86_64

运行安装命令

sudo yum install clickhouse-server clickhouse-client

启动

在后台启动服务

sudo service clickhouse-server start

连接到ClickHouse

clickhouse-client --host=example.com

完整实例

milovidov@hostname:~/work/metrica/src/src/Client$ ./clickhouse-client
ClickHouse client version 0.0.18749.
Connecting to localhost:9000.
Connected to ClickHouse server version 0.0.18749.

:) SELECT 1

SELECT 1

┌─1─┐
│ 1 │
└───┘

1 rows in set. Elapsed: 0.003 sec.

:)

简单测试

这里导入10GB数据作为简单测试

下载数据

curl https://clickhouse-datasets.s3.yandex.net/hits/tsv/hits_v1.tsv.xz | unxz --threads=`nproc` > hits_v1.tsv
curl https://clickhouse-datasets.s3.yandex.net/visits/tsv/visits_v1.tsv.xz | unxz --threads=`nproc` > visits_v1.tsv

创建表

先创建数据库

clickhouse-client --query "CREATE DATABASE IF NOT EXISTS tutorial"

CREATE TABLE tutorial.hits_v1
(
    `WatchID` UInt64,
    `JavaEnable` UInt8,
    `Title` String,
    `GoodEvent` Int16,
    `EventTime` DateTime,
    `EventDate` Date,
    `CounterID` UInt32,
    `ClientIP` UInt32,
    `ClientIP6` FixedString(16),
    `RegionID` UInt32,
    `UserID` UInt64,
    `CounterClass` Int8,
    `OS` UInt8,
    `UserAgent` UInt8,
    `URL` String,
    `Referer` String,
    `URLDomain` String,
    `RefererDomain` String,
    `Refresh` UInt8,
    `IsRobot` UInt8,
    `RefererCategories` Array(UInt16),
    `URLCategories` Array(UInt16),
    `URLRegions` Array(UInt32),
    `RefererRegions` Array(UInt32),
    `ResolutionWidth` UInt16,
    `ResolutionHeight` UInt16,
    `ResolutionDepth` UInt8,
    `FlashMajor` UInt8,
    `FlashMinor` UInt8,
    `FlashMinor2` String,
    `NetMajor` UInt8,
    `NetMinor` UInt8,
    `UserAgentMajor` UInt16,
    `UserAgentMinor` FixedString(2),
    `CookieEnable` UInt8,
    `JavascriptEnable` UInt8,
    `IsMobile` UInt8,
    `MobilePhone` UInt8,
    `MobilePhoneModel` String,
    `Params` String,
    `IPNetworkID` UInt32,
    `TraficSourceID` Int8,
    `SearchEngineID` UInt16,
    `SearchPhrase` String,
    `AdvEngineID` UInt8,
    `IsArtifical` UInt8,
    `WindowClientWidth` UInt16,
    `WindowClientHeight` UInt16,
    `ClientTimeZone` Int16,
    `ClientEventTime` DateTime,
    `SilverlightVersion1` UInt8,
    `SilverlightVersion2` UInt8,
    `SilverlightVersion3` UInt32,
    `SilverlightVersion4` UInt16,
    `PageCharset` String,
    `CodeVersion` UInt32,
    `IsLink` UInt8,
    `IsDownload` UInt8,
    `IsNotBounce` UInt8,
    `FUniqID` UInt64,
    `HID` UInt32,
    `IsOldCounter` UInt8,
    `IsEvent` UInt8,
    `IsParameter` UInt8,
    `DontCountHits` UInt8,
    `WithHash` UInt8,
    `HitColor` FixedString(1),
    `UTCEventTime` DateTime,
    `Age` UInt8,
    `Sex` UInt8,
    `Income` UInt8,
    `Interests` UInt16,
    `Robotness` UInt8,
    `GeneralInterests` Array(UInt16),
    `RemoteIP` UInt32,
    `RemoteIP6` FixedString(16),
    `WindowName` Int32,
    `OpenerName` Int32,
    `HistoryLength` Int16,
    `BrowserLanguage` FixedString(2),
    `BrowserCountry` FixedString(2),
    `SocialNetwork` String,
    `SocialAction` String,
    `HTTPError` UInt16,
    `SendTiming` Int32,
    `DNSTiming` Int32,
    `ConnectTiming` Int32,
    `ResponseStartTiming` Int32,
    `ResponseEndTiming` Int32,
    `FetchTiming` Int32,
    `RedirectTiming` Int32,
    `DOMInteractiveTiming` Int32,
    `DOMContentLoadedTiming` Int32,
    `DOMCompleteTiming` Int32,
    `LoadEventStartTiming` Int32,
    `LoadEventEndTiming` Int32,
    `NSToDOMContentLoadedTiming` Int32,
    `FirstPaintTiming` Int32,
    `RedirectCount` Int8,
    `SocialSourceNetworkID` UInt8,
    `SocialSourcePage` String,
    `ParamPrice` Int64,
    `ParamOrderID` String,
    `ParamCurrency` FixedString(3),
    `ParamCurrencyID` UInt16,
    `GoalsReached` Array(UInt32),
    `OpenstatServiceName` String,
    `OpenstatCampaignID` String,
    `OpenstatAdID` String,
    `OpenstatSourceID` String,
    `UTMSource` String,
    `UTMMedium` String,
    `UTMCampaign` String,
    `UTMContent` String,
    `UTMTerm` String,
    `FromTag` String,
    `HasGCLID` UInt8,
    `RefererHash` UInt64,
    `URLHash` UInt64,
    `CLID` UInt32,
    `YCLID` UInt64,
    `ShareService` String,
    `ShareURL` String,
    `ShareTitle` String,
    `ParsedParams` Nested(
        Key1 String,
        Key2 String,
        Key3 String,
        Key4 String,
        Key5 String,
        ValueDouble Float64),
    `IslandID` FixedString(16),
    `RequestNum` UInt32,
    `RequestTry` UInt8
)
ENGINE = MergeTree()
PARTITION BY toYYYYMM(EventDate)
ORDER BY (CounterID, EventDate, intHash32(UserID))
SAMPLE BY intHash32(UserID)
SETTINGS index_granularity = 8192

CREATE TABLE tutorial.visits_v1
(
    `CounterID` UInt32,
    `StartDate` Date,
    `Sign` Int8,
    `IsNew` UInt8,
    `VisitID` UInt64,
    `UserID` UInt64,
    `StartTime` DateTime,
    `Duration` UInt32,
    `UTCStartTime` DateTime,
    `PageViews` Int32,
    `Hits` Int32,
    `IsBounce` UInt8,
    `Referer` String,
    `StartURL` String,
    `RefererDomain` String,
    `StartURLDomain` String,
    `EndURL` String,
    `LinkURL` String,
    `IsDownload` UInt8,
    `TraficSourceID` Int8,
    `SearchEngineID` UInt16,
    `SearchPhrase` String,
    `AdvEngineID` UInt8,
    `PlaceID` Int32,
    `RefererCategories` Array(UInt16),
    `URLCategories` Array(UInt16),
    `URLRegions` Array(UInt32),
    `RefererRegions` Array(UInt32),
    `IsYandex` UInt8,
    `GoalReachesDepth` Int32,
    `GoalReachesURL` Int32,
    `GoalReachesAny` Int32,
    `SocialSourceNetworkID` UInt8,
    `SocialSourcePage` String,
    `MobilePhoneModel` String,
    `ClientEventTime` DateTime,
    `RegionID` UInt32,
    `ClientIP` UInt32,
    `ClientIP6` FixedString(16),
    `RemoteIP` UInt32,
    `RemoteIP6` FixedString(16),
    `IPNetworkID` UInt32,
    `SilverlightVersion3` UInt32,
    `CodeVersion` UInt32,
    `ResolutionWidth` UInt16,
    `ResolutionHeight` UInt16,
    `UserAgentMajor` UInt16,
    `UserAgentMinor` UInt16,
    `WindowClientWidth` UInt16,
    `WindowClientHeight` UInt16,
    `SilverlightVersion2` UInt8,
    `SilverlightVersion4` UInt16,
    `FlashVersion3` UInt16,
    `FlashVersion4` UInt16,
    `ClientTimeZone` Int16,
    `OS` UInt8,
    `UserAgent` UInt8,
    `ResolutionDepth` UInt8,
    `FlashMajor` UInt8,
    `FlashMinor` UInt8,
    `NetMajor` UInt8,
    `NetMinor` UInt8,
    `MobilePhone` UInt8,
    `SilverlightVersion1` UInt8,
    `Age` UInt8,
    `Sex` UInt8,
    `Income` UInt8,
    `JavaEnable` UInt8,
    `CookieEnable` UInt8,
    `JavascriptEnable` UInt8,
    `IsMobile` UInt8,
    `BrowserLanguage` UInt16,
    `BrowserCountry` UInt16,
    `Interests` UInt16,
    `Robotness` UInt8,
    `GeneralInterests` Array(UInt16),
    `Params` Array(String),
    `Goals` Nested(
        ID UInt32,
        Serial UInt32,
        EventTime DateTime,
        Price Int64,
        OrderID String,
        CurrencyID UInt32),
    `WatchIDs` Array(UInt64),
    `ParamSumPrice` Int64,
    `ParamCurrency` FixedString(3),
    `ParamCurrencyID` UInt16,
    `ClickLogID` UInt64,
    `ClickEventID` Int32,
    `ClickGoodEvent` Int32,
    `ClickEventTime` DateTime,
    `ClickPriorityID` Int32,
    `ClickPhraseID` Int32,
    `ClickPageID` Int32,
    `ClickPlaceID` Int32,
    `ClickTypeID` Int32,
    `ClickResourceID` Int32,
    `ClickCost` UInt32,
    `ClickClientIP` UInt32,
    `ClickDomainID` UInt32,
    `ClickURL` String,
    `ClickAttempt` UInt8,
    `ClickOrderID` UInt32,
    `ClickBannerID` UInt32,
    `ClickMarketCategoryID` UInt32,
    `ClickMarketPP` UInt32,
    `ClickMarketCategoryName` String,
    `ClickMarketPPName` String,
    `ClickAWAPSCampaignName` String,
    `ClickPageName` String,
    `ClickTargetType` UInt16,
    `ClickTargetPhraseID` UInt64,
    `ClickContextType` UInt8,
    `ClickSelectType` Int8,
    `ClickOptions` String,
    `ClickGroupBannerID` Int32,
    `OpenstatServiceName` String,
    `OpenstatCampaignID` String,
    `OpenstatAdID` String,
    `OpenstatSourceID` String,
    `UTMSource` String,
    `UTMMedium` String,
    `UTMCampaign` String,
    `UTMContent` String,
    `UTMTerm` String,
    `FromTag` String,
    `HasGCLID` UInt8,
    `FirstVisit` DateTime,
    `PredLastVisit` Date,
    `LastVisit` Date,
    `TotalVisits` UInt32,
    `TraficSource` Nested(
        ID Int8,
        SearchEngineID UInt16,
        AdvEngineID UInt8,
        PlaceID UInt16,
        SocialSourceNetworkID UInt8,
        Domain String,
        SearchPhrase String,
        SocialSourcePage String),
    `Attendance` FixedString(16),
    `CLID` UInt32,
    `YCLID` UInt64,
    `NormalizedRefererHash` UInt64,
    `SearchPhraseHash` UInt64,
    `RefererDomainHash` UInt64,
    `NormalizedStartURLHash` UInt64,
    `StartURLDomainHash` UInt64,
    `NormalizedEndURLHash` UInt64,
    `TopLevelDomain` UInt64,
    `URLScheme` UInt64,
    `OpenstatServiceNameHash` UInt64,
    `OpenstatCampaignIDHash` UInt64,
    `OpenstatAdIDHash` UInt64,
    `OpenstatSourceIDHash` UInt64,
    `UTMSourceHash` UInt64,
    `UTMMediumHash` UInt64,
    `UTMCampaignHash` UInt64,
    `UTMContentHash` UInt64,
    `UTMTermHash` UInt64,
    `FromHash` UInt64,
    `WebVisorEnabled` UInt8,
    `WebVisorActivity` UInt32,
    `ParsedParams` Nested(
        Key1 String,
        Key2 String,
        Key3 String,
        Key4 String,
        Key5 String,
        ValueDouble Float64),
    `Market` Nested(
        Type UInt8,
        GoalID UInt32,
        OrderID String,
        OrderPrice Int64,
        PP UInt32,
        DirectPlaceID UInt32,
        DirectOrderID UInt32,
        DirectBannerID UInt32,
        GoodID String,
        GoodName String,
        GoodQuantity Int32,
        GoodPrice Int64),
    `IslandID` FixedString(16)
)
ENGINE = CollapsingMergeTree(Sign)
PARTITION BY toYYYYMM(StartDate)
ORDER BY (CounterID, StartDate, intHash32(UserID), VisitID)
SAMPLE BY intHash32(UserID)
SETTINGS index_granularity = 8192

导入数据

clickhouse-client --query "INSERT INTO tutorial.hits_v1 FORMAT TSV" --max_insert_block_size=100000 < hits_v1.tsv
clickhouse-client --query "INSERT INTO tutorial.visits_v1 FORMAT TSV" --max_insert_block_size=100000 < visits_v1.tsv

简单测试

clickhouse-client --query "SELECT COUNT(*) FROM tutorial.hits_v1"
clickhouse-client --query "SELECT COUNT(*) FROM tutorial.visits_v1"

查询实例

SELECT
    StartURL AS URL,
    AVG(Duration) AS AvgDuration
FROM tutorial.visits_v1
WHERE StartDate BETWEEN '2014-03-23' AND '2014-03-30'
GROUP BY URL
ORDER BY AvgDuration DESC
LIMIT 10

SELECT
    sum(Sign) AS visits,
    sumIf(Sign, has(Goals.ID, 1105530)) AS goal_visits,
    (100. * goal_visits) / visits AS goal_percent
FROM tutorial.visits_v1
WHERE (CounterID = 912887) AND (toYYYYMM(StartDate) = 201403) AND (domain(StartURL) = 'yandex.ru')

这样就完成了一个简单的部署与测试。

MySql 数据导入ClickHouse中

Altinity提供了一个工具clickhouse-mysql-data-reader来实现数据导入。该工具可以实现MySQL的存量数据导出，和增量数据的导出。

按照官网推荐，使用pypy工具能够显著提升clickhouse-mysql-data-reader导入数据的性能。

工具准备

步骤1：下载pypy, pypy3.6-7.2.0 , 解压为pypy目录下。
步骤2：安装clickhouse-mysql

安装pip: 执行

pypy/bin/pypy3 -m ensurepip

安装mysql-replication,clickhouse-driver, 执行

pypy/bin/pip3 install mysql-replication

和

pypy/bin/pip3 install  clickhouse-driver

安装clickhouse-mysql并初始化，执行

pypy/bin/pip3 install clickhouse-mysql,

和

pypy/bin/clickhouse-mysql --install

安装clickhouse-client，执行

yum install -y clickhouse-client

安装mysql-community-devel, 执行

yum install -y mysql-community-devel

这样即可完成。

原创声明：本文系作者授权腾讯云开发者社区发表，未经许可，不得转载。

如有侵权，请联系 cloudcommunity@tencent.com 删除。

jquery

原创声明：本文系作者授权腾讯云开发者社区发表，未经许可，不得转载。

如有侵权，请联系 cloudcommunity@tencent.com 删除。

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