ES不香吗,为啥还要ClickHouse?
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2021-12-23 14:21
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作者:Gang Tao 编辑:陶家龙
来源:zhuanlan.zhihu.com/p/353296392
Elasticsearch是一个实时的分布式搜索分析引擎,它的底层是构建在 Lucene 之上的。简单来说是通过扩展 Lucene 的搜索能力,使其具有分布式的功能。
架构和设计的对比
Client Node,负责 API 和数据的访问的节点,不存储/处理数据。
Data Node,负责数据的存储和索引。
Master Node,管理节点,负责 Cluster 中的节点的协调,不存储数据。
查询对比实战
https://github.com/gangtao/esvsch
version: '3.7'
services:
elasticsearch:
image: docker.elastic.co/elasticsearch/elasticsearch:7.4.0
container_name: elasticsearch
environment:
- xpack.security.enabled=false
- discovery.type=single-node
ulimits:
memlock:
soft: -1
hard: -1
nofile:
soft: 65536
hard: 65536
cap_add:
- IPC_LOCK
volumes:
- elasticsearch-data:/usr/share/elasticsearch/data
ports:
- 9200:9200
- 9300:9300
deploy:
resources:
limits:
cpus: '4'
memory: 4096M
reservations:
memory: 4096M
kibana:
container_name: kibana
image: docker.elastic.co/kibana/kibana:7.4.0
environment:
- ELASTICSEARCH_HOSTS=http://elasticsearch:9200
ports:
- 5601:5601
depends_on:
- elasticsearch
volumes:
elasticsearch-data:
driver: local
version: "3.7"
services:
clickhouse:
container_name: clickhouse
image: yandex/clickhouse-server
volumes:
- ./data/config:/var/lib/clickhouse
ports:
- "8123:8123"
- "9000:9000"
- "9009:9009"
- "9004:9004"
ulimits:
nproc: 65535
nofile:
soft: 262144
hard: 262144
healthcheck:
test: ["CMD", "wget", "--spider", "-q", "localhost:8123/ping"]
interval: 30s
timeout: 5s
retries: 3
deploy:
resources:
limits:
cpus: '4'
memory: 4096M
reservations:
memory: 4096M
tabixui:
container_name: tabixui
image: spoonest/clickhouse-tabix-web-client
environment:
- CH_NAME=dev
- CH_HOST=127.0.0.1:8123
- CH_LOGIN=default
ports:
- "18080:80"
depends_on:
- clickhouse
deploy:
resources:
limits:
cpus: '0.1'
memory: 128M
reservations:
memory: 128M
CREATE TABLE default.syslog(
application String,
hostname String,
message String,
mid String,
pid String,
priority Int16,
raw String,
timestamp DateTime('UTC'),
version Int16
) ENGINE = MergeTree()
PARTITION BY toYYYYMMDD(timestamp)
ORDER BY timestamp
TTL timestamp + toIntervalMonth(1);
[sources.in]
type = "generator"
format = "syslog"
interval = 0.01
count = 100000
[transforms.clone_message]
type = "add_fields"
inputs = ["in"]
fields.raw = "{{ message }}"
[transforms.parser]
# General
type = "regex_parser"
inputs = ["clone_message"]
field = "message" # optional, default
patterns = ['^<(?P\d*)>(?P \d) (?P \d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}\.\d{3}Z) (?P \w+\.\w+) (?P \w+) (?P \d+) (?P ID\d+) - (?P .*)$']
[transforms.coercer]
type = "coercer"
inputs = ["parser"]
types.timestamp = "timestamp"
types.version = "int"
types.priority = "int"
[sinks.out_console]
# General
type = "console"
inputs = ["coercer"]
target = "stdout"
# Encoding
encoding.codec = "json"
[sinks.out_clickhouse]
host = "http://host.docker.internal:8123"
inputs = ["coercer"]
table = "syslog"
type = "clickhouse"
encoding.only_fields = ["application", "hostname", "message", "mid", "pid", "priority", "raw", "timestamp", "version"]
encoding.timestamp_format = "unix"
[sinks.out_es]
# General
type = "elasticsearch"
inputs = ["coercer"]
compression = "none"
endpoint = "http://host.docker.internal:9200"
index = "syslog-%F"
# Encoding
# Healthcheck
healthcheck.enabled = true
source.in:生成 syslog 的模拟数据,生成 10w 条,生成间隔和 0.01 秒。
transforms.clone_message:把原始消息复制一份,这样抽取的信息同时可以保留原始消息。
transforms.parser:使用正则表达式,按照 syslog 的定义,抽取出 application,hostname,message,mid,pid,priority,timestamp,version 这几个字段。
transforms.coercer:数据类型转化。
sinks.out_console:把生成的数据打印到控制台,供开发调试。
sinks.out_clickhouse:把生成的数据发送到Clickhouse。
sinks.out_es:把生成的数据发送到 ES。
运行 Docker 命令,执行该流水线:
docker run \
-v $(mkfile_path)/vector.toml:/etc/vector/vector.toml:ro \
-p 18383:8383 \
timberio/vector:nightly-alpine
# ES
{
"query":{
"match_all":{}
}
}
# Clickhouse
"SELECT * FROM syslog"
# ES
{
"query":{
"match":{
"hostname":"for.org"
}
}
}
# Clickhouse
"SELECT * FROM syslog WHERE hostname='for.org'"
# ES
{
"query":{
"multi_match":{
"query":"up.com ahmadajmi",
"fields":[
"hostname",
"application"
]
}
}
}
# Clickhouse、
"SELECT * FROM syslog WHERE hostname='for.org' OR application='ahmadajmi'"
# ES
{
"query":{
"term":{
"message":"pretty"
}
}
}
# Clickhouse
"SELECT * FROM syslog WHERE lowerUTF8(raw) LIKE '%pretty%'"
# ES
{
"query":{
"range":{
"version":{
"gte":2
}
}
}
}
# Clickhouse
"SELECT * FROM syslog WHERE version >= 2"
# ES
{
"query":{
"exists":{
"field":"application"
}
}
}
# Clickhouse
"SELECT * FROM syslog WHERE application is not NULL"
# ES
{
"query":{
"regexp":{
"hostname":{
"value":"up.*",
"flags":"ALL",
"max_determinized_states":10000,
"rewrite":"constant_score"
}
}
}
}
# Clickhouse
"SELECT * FROM syslog WHERE match(hostname, 'up.*')"
# ES
{
"aggs":{
"version_count":{
"value_count":{
"field":"version"
}
}
}
}
# Clickhouse
"SELECT count(version) FROM syslog"
# ES
{
"aggs":{
"my-agg-name":{
"cardinality":{
"field":"priority"
}
}
}
}
# Clickhouse
"SELECT count(distinct(priority)) FROM syslog "
总结