Basic Concepts
There are a few concepts that are core to Elasticsearch.
Understanding these concepts from the outset will tremendously help ease the learning process.
Elasticsearch 的核心概念，从一开始就理解这些概念将极大地帮助简化学习过程。

Near Realtime (NRT)
近实时
Elasticsearch is a near-realtime search platform.
What this means is there is a slight latency (normally one second)
from the time you index a document until the time it becomes searchable.
Elasticsearch 是一个近实时的搜索平台，这意味着从搜索文档到可搜索文档的时间有一点延迟（通常是1s）。

Getting Started
入门

Elasticsearch is a highly scalable open-source full-text search and analytics engine.
It allows you to store, search, and analyze big volumes of data quickly and in near real time.
It is generally used as the underlying engine/technology
that powers applications that have complex search features and requirements.
Elasticsearch 是一个高度可扩展的开源全文搜索和分析引擎。它允许你快速且近实时地存储、搜索、分析大量数据。
它通常用于底层引擎/技术，为具有复杂搜索功能和要求的应用程序提供支持。

Here are a few sample use-cases that Elasticsearch could be used for:
Elasticsearch 使用案例

下载kibana
wget https://artifacts.elastic.co/downloads/kibana/kibana-6.5.4-linux-x86_64.tar.gz

解压
tar -zxvf kibana-6.5.4-linux-x86_64.tar.gz -C /usr/local/software/

修改配置
vim config/kibana.yml

下载

https://github.com/medcl/elasticsearch-analysis-ik

从elasticsearch 的release中选择对应的ik版本，进行下载
wget https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v6.5.4/elasticsearch-analysis-ik-6.5.4.zip

在elasticsearch 安装目录下创建目录
mkdir -p /usr/local/software/elasticsearch-6.5.4/plugins/ik

将elasticsearch-analysis-ik-6.5.4.zip 解压到ik 目录下
unzip -d /usr/local/software/elasticsearch-6.5.4/plugins/ik elasticsearch-analysis-ik-6.5.4.zip

数据分片

- 垂直分片：按照业务拆分，专库专用。
- 水平分片：通过某个字段（或某几个字段），根据某种规则将数据分散至多个库或表中，每个分片仅包含数据的一部分。

逻辑表
真实表
数据节点
绑定表：指分片规则一致的主表和子表，绑定表之间的分区键要完全相同。
广播表：字典表
逻辑索引

https://mirrors.tuna.tsinghua.edu.cn/apache/hbase/

vim conf/hbase-site.xml

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<configuration>
    <property>
        <name>hbase.rootdir</name>
        <value>file:///opt/data/hbase</value>
    </property>
</configuration>

启动
bin/start-hbase.sh

分库分表

水平分表
id 分段
取模

按照日期
单表数据量大，
tb_order_2018
tb_order_2019

认识mycat
数据库中间件

mycat 安装

tar -zxvf haproxy-1.8.20.tar.gz
cd haproxy-1.8.20
make TARGET=linux2628 ARCH=x86_64 PREFIX=/usr/local/haproxy
make install PREFIX=/usr/local/haproxy

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参数说明
TARGET=linux26 #内核版本，使用uname -r查看内核，如：2.6.18-371.el5，此时该参数就为linux26；kernel 大于2.6.28的
用：TARGET=linux2628
ARCH=x86_64 #系统位数
PREFIX=/usr/local/haprpxy  #/usr/local/haprpxy为haprpxy安装路径

Distributed systems for fun and profit
Introduction
介绍
I wanted a text that would bring together the ideas behind many of the more recent distributed systems

• systems such as Amazon’s Dynamo, Google’s BigTable and MapReduce, Apache’s Hadoop and so on.
  我想要一篇汇集许多最近的分布式系统（如 Amazon 的 Dynamo, Google 的 BigTable 和 MapReduce, Apache 的 Hadoop等系统）背后思想的文章。

In this text I’ve tried to provide a more accessible introduction to distributed systems.
在本文中，我尝试提供一个更易于理解的分布式系统介绍。