ClickHouse 初体验

追求更好的体验，本文采用 docker 方式。

环境部署

详细可参考 server 官方 docker 镜像和 client 官方 docker 镜像

启动 Server

$ docker run -d --name some-clickhouse-server --ulimit nofile=262144:262144 yandex/clickhouse-server

启动 Client

$ docker run -it --rm --link some-clickhouse-server:clickhouse-server yandex/clickhouse-client --host clickhouse-server

附一：启动自定义 Server

如果需要自定义 Server 的启动参数，则：

$ docker run -d --name some-clickhouse-server --ulimit nofile=262144:262144 -v /path/to/your/config.xml:/etc/clickhouse-server/config.xml yandex/clickhouse-server

附二：其它安装包

参考官方文档

• Ubuntu: https://clickhouse.yandex/docs/en/getting_started/index.html
• From Source: https://clickhouse.yandex/docs/en/getting_started/index.html
• CentOS rpm: https://github.com/Altinity/clickhouse-rpm-install
• Gentoo : https://github.com/kmeaw/clickhouse-overlay

基本 SQL

select 1

:) select 1

SELECT 1

┌─1─┐
│ 1 │
└───┘

1 rows in set. Elapsed: 0.004 sec.

select now

:) select now()

SELECT now()

┌───────────────now()─┐
│ 2017-11-24 02:34:19 │
└─────────────────────┘

1 rows in set. Elapsed: 0.003 sec.

AMPLab 测试

如官方文档,

下载数据

1. 申请 S3 账号：会有两笔预授权的 1$ 账单，据说 3-5 天后会返还。

2. 下载数据

s3cmd sync s3://big-data-benchmark/pavlo/text-deflate/tiny/ /User/abeffect/tmp/tiny/

建表

CREATE TABLE rankings_tiny
(
    pageURL String,
    pageRank UInt32,
    avgDuration UInt32
) ENGINE = Log;

CREATE TABLE uservisits_tiny
(
    sourceIP String,
    destinationURL String,
    visitDate Date,
    adRevenue Float32,
    UserAgent String,
    cCode FixedString(3),
    lCode FixedString(6),
    searchWord String,
    duration UInt32
) ENGINE = MergeTree(visitDate, visitDate, 8192);

导入数据

查询
SELECT
    pageURL,
    pageRank
FROM rankings_tiny
WHERE pageRank > 300

┌─pageURL───────────────────────────────────────────────┬─pageRank─┐
│ nbizrgdziebsaecsecujfjcqtvnpcnxxwiopmddorcxnlijdizgoi │      665 │
│ nbizrgdziebsaecsecujfjcqtvnpcnxxwiopmddorcxnlijdizgoi │      665 │
└───────────────────────────────────────────────────────┴──────────┘
┌─pageURL──────────────────────────────────────────────────────────────────────────────────────┬─pageRank─┐
│ dfqlfhuuwxhhjvdtwljahxbwhqkutigdfcuiogfooprtmomeyysquqlzvzmrxhkttrbumglgwixsovxoqisibirdlgtc │      483 │
│ pucpwgjykbcelcevdmzuahojzjxgmpgojfehhabasvbzbzpczqcubfbfekv                                  │      397 │
│ ffygkvsklpmup                                                                                │      332 │
└──────────────────────────────────────────────────────────────────────────────────────────────┴──────────┘

5 rows in set. Elapsed: 0.007 sec. Processed 1.32 thousand rows, 90.28 KB (189.33 thousand rows/s., 12.95 MB/s.)

SELECT
    substring(sourceIP, 1, 8),
    sum(adRevenue)
FROM uservisits_tiny
GROUP BY substring(sourceIP, 1, 8)
LIMIT 5

┌─substring(sourceIP, 1, 8)─┬──────sum(adRevenue)─┐
│ 227.120.                  │  0.7206825017929077 │
│ 33.157.1                  │  0.9653052091598511 │
│ 134.195.                  │ 0.08809900283813477 │
│ 172.239.                  │  0.2393447756767273 │
│ 19.26.11                  │ 0.13361740112304688 │
└───────────────────────────┴─────────────────────┘

5 rows in set. Elapsed: 0.102 sec. Processed 10.00 thousand rows, 262.95 KB (98.18 thousand rows/s., 2.58 MB/s.)

SELECT
    sourceIP,
    sum(adRevenue) AS totalRevenue,
    avg(pageRank) AS pageRank
FROM rankings_tiny
ALL INNER JOIN
(
    SELECT
        sourceIP,
        destinationURL AS pageURL,
        adRevenue
    FROM uservisits_tiny
    WHERE (visitDate > '1980-01-01') AND (visitDate < '1980-04-01')
) USING (pageURL)
GROUP BY sourceIP
ORDER BY totalRevenue DESC
LIMIT 1

┌─sourceIP───────┬──────totalRevenue─┬─pageRank─┐
│ 242.170.245.71 │ 1.132317066192627 │       26 │
└────────────────┴───────────────────┴──────────┘

1 rows in set. Elapsed: 0.009 sec. Processed 1.38 thousand rows, 95.39 KB (150.26 thousand rows/s., 10.41 MB/s.)

进一步阅读

DB-Engines Ranking: 目前上升非常快
Berkeley BigData Benchmark: 相关 OLAP 产品的评测
clickhouse rpm install: 安装 rpm 格式的 client 和 server，文中测试部分的 client 即通过此方法安装
clickhouse jdbc: clickhouse 的 jdbc 驱动
tabix.ui: clickhouse gui 界面, 无需安装，直接进入
ClickHouse 之简单性能测试: 美国民用航班的数据，从 1987 年到 2017 年，有 1.7 亿条的测试 case
ClickHouse vs Amazon RedShift Benchmark
常见的 benchmark:


HiBench: Intel 开发，针对 Hadoop
Berkeley BigData Bench：AMPLab 开发，针对 Spark
Hadoop GridMix：Hadoop 自带
BigBench：Teradata、多伦多大学、InfoSizing、Oracle 开发
BigDataBenchmark：中科院研发
TPC-DS: 针对 SQL on Hadoop
其它 Malstone、Cloud Harmony、YCSB、SWIM、LinkBench、DFSIO、Hive performance Benchmark(Pavlo)等等