# RPM安装方式
Elasticsearch的RPM软件包可以从[我们的网站下载](#install-rpm)或从[我们的APT仓库](#rpm-repo)安装。它可以用于任何基于RPM的系统上安装Elasticsearch,如OpenSuse、SLES、Centos、Red Hat与企业级Oracle。
> 注意
>
> RPM包不支持老的RPM平台,譬如SLES 11与CentOS 5,这些平台请采用[.zip或.tar.gz文件的安装方式](Installing_Elasticsearch/Install_Elasticsearch_with_.zip_or_.tar.gz.md)。
>
> 注意
>
> Elasticsearch需要Java 8或更高版本。可以使用[Oracle官方发布](http://www.oracle.com/technetwork/java/javase/downloads/index.html)或开源版本的[OpenJDK](http://openjdk.java.net/)。
Elasticsearch的最新稳定版本可以在[Elasticsearch下载](https://www.elastic.co/downloads/elasticsearch)页面获取。其它版本可以在上[之前的下载页面](https://www.elastic.co/downloads/past-releases)找到。
## 导入Elasticsearch PGP Key
Elasticsearch的所有包都采用如下指纹与签名Key进行签名(PGP key [D88E42B4](https://pgp.mit.edu/pks/lookup?op=vindex&search=0xD27D666CD88E42B4),可从[https://pgp.mit.edu](https://pgp.mit.edu/)):
```
4609 5ACC 8548 582C 1A26 99A9 D27D 666C D88E 42B4
```
下载并安装该公用签名密钥:
```
rpm --import https://artifacts.elastic.co/GPG-KEY-elasticsearch
```
## 从RPM仓库中安装
在基于RedHat的平台中请在`/etc/yum.repos.d/`文件夹下创建一个`elasticsearch.repo`文件,在基于OpenSuse的平台中请在`/etc/zypp/repos.d/`文件夹下创建一个`elasticsearch.repo`文件,内容如下:
```
[elasticsearch-6.x]
name=Elasticsearch repository for 6.x packages
baseurl=https://artifacts.elastic.co/packages/6.x/yum
gpgcheck=1
gpgkey=https://artifacts.elastic.co/GPG-KEY-elasticsearch
enabled=1
autorefresh=1
type=rpm-md
```
你的仓库就准备好了,你可以采用下面的命令来安装它:
```
sudo yum install elasticsearch #①
sudo dnf install elasticsearch #②
sudo zypper install elasticsearch #③
```
① 在CentOS与老的Red Hat发行版本中使用`yum`指令
② 在Fedora与新的Red Hat发行版本中使用`dnf`指令
③ 在OpenSuse的发行版本中使用`zypper`指令
## 手动下载并安装RPM软件包
Elasticsearch的6.0.0版本RPM安装包可以通过如下指令从网站下载与安装:
```
wget https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-6.0.0.rpm
wget https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-6.0.0.rpm.sha512
shasum -a 512 -c elasticsearch-6.0.0.rpm.sha512 ①
sudo rpm --install elasticsearch-6.0.0.rpm
```
① Compares the SHA of the downloaded RPM and the published checksum, which should output `elasticsearch-{version}.rpm: OK`.
> 注意
>
> On systemd-based distributions, the installation scripts will attempt to set kernel parameters (e.g., `vm.max_map_count`); you can skip this by masking the systemd-sysctl.service unit.
## `SysV init` vs `systemd`
Elasticsearch不是在安装后自动启动。如何启动和停止Elasticsearch取决于你的系统是否使用的`SysV init`或`system`(较新发行版中使用)。你可以说这是一个用来运行以下命令:
```
ps -p 1
```
## 通过`SysV init`启动Elasticsearch
使用`chkconfig`命令来配置Elasticsearch在系统启动时自动启动:
```
sudo chkconfig --add elasticsearch
```
Elasticsearch可以通过`service`命令来启动与停止:
```
sudo -i service elasticsearch start
sudo -i service elasticsearch stop
```
任何原因的Elasticsearch启动失败,都会将原因打印到控制套。日志文件可以在`/var/log/elasticsearch/`中找到。
## 通过`systemd`启动Elasticsearch
要配置Elasticsearch在系统启动时自动启动,运行以下命令:
```
sudo /bin/systemctl daemon-reload
sudo /bin/systemctl enable elasticsearch.service
```
Elasticsearch可以通过service命令来启动与停止:
```
sudo systemctl start elasticsearch.service
sudo systemctl stop elasticsearch.service
```
无论Elasticsearch是否成功没有启动, 这些命令不提供反馈。相反,该信息将被写入位于`/var/log/elasticsearch/`的日志文件中。
默认情况下,Elasticsearch服务的信息不记录在信息`systemd` 的`journal`日志中。若要启用`journalctl`日志记录,在`elasticsearch.service`文件的`ExecStart`命令行中必须删除`--quiet`选项。
当`systemd`启用了日志记录,日志信息的使用可用`journalctl`命令:
`tail`查看`journal`:
```
sudo journalctl -f
```
要列出`journal`中elasticsearch服务的日志条目:
```
sudo journalctl --unit elasticsearch
```
要列出指定时间之后的列出`journal`中elasticsearch服务的日志条目:
```
sudo journalctl --unit elasticsearch --since "2016-10-30 18:17:16"
```
更多的`journalctl`操作手册,请参考:<https://www.freedesktop.org/software/systemd/man/journalctl.html>。
## 检查Elasticsearch运行
您可以在已运行的Elasticsearch节点上,发送一个HTTP请求测试`localhost`的`9200`端口:
```
GET /
```
返回的消息应该是这样的:
```
{
"name" : "Cp8oag6",
"cluster_name" : "elasticsearch",
"cluster_uuid" : "AT69_T_DTp-1qgIJlatQqA",
"version" : {
"number" : "6.0.0",
"build_hash" : "f27399d",
"build_date" : "2016-03-30T09:51:41.449Z",
"build_snapshot" : false,
"lucene_version" : "7.0.1",
"minimum_wire_compatibility_version" : "1.2.3",
"minimum_index_compatibility_version" : "1.2.3"
},
"tagline" : "You Know, for Search"
}
```
## 配置Elasticsearch
Elasticsearch defaults to using `/etc/elasticsearch` for runtime configuration. The ownership of this directory and all files in this directory are set to`root:elasticsearch` on package installation and the directory has the `setgid` flag set so that any files and subdirectories created under `/etc/elasticsearch` are created with this ownership as well (e.g., if a keystore is created using the[keystore tool](https://www.elastic.co/guide/en/elasticsearch/reference/6.0/secure-settings.html "Secure Settings")). It is expected that this be maintained so that the Elasticsearch process can read the files under this directory via the group permissions.
Elasticsearch loads its configuration from the`/etc/elasticsearch/elasticsearch.yml` file by default. The format of this config file is explained in [*Configuring Elasticsearch*](https://www.elastic.co/guide/en/elasticsearch/reference/6.0/settings.html "Configuring Elasticsearch").
RPM软件包也有一个系统配置文件(`/etc/sysconfig/elasticsearch`),它允许你设置以下参数:
* JAVA\_HOME自定义java路径。
* MAX\_OPEN\_FILES最大的打开文件数,默认最大数量`65536`。
* MAX\_LOCKED\_MEMORY最大锁定内存大小。你使用`bootstrap.memory_lock`的`elasticsearch.yml`选项将被设置为`unlimited`。
* MAX\_MAP\_COUNT进程的内存映射区域最大数量。如果你使用`mmapfs`的索引存储类型,确保此项设置为高值。欲了解更多信息,请查看[Linux内核文件](https://github.com/torvalds/linux/blob/master/Documentation/sysctl/vm.txt)查看相关的`max_map_count`。这是在启动elasticsearch之前通过`sysctl`设置的,默认为262144。
* ES_PATH_CONF配置文件目录(其中必须包括`elasticsearch.yml`和`log4j2.properties`文件),默认为`/etc/elasticsearch`。
* ES\_JAVA\_OPTS任何额外的JVM系统属性,你可能要应用。
* RESTART\_ON\_UPGRADE配置在安装包升级后重启,默认为`false`。这意味着你将在安装包后需要手动重新启动您的elasticsearch实例。这样做的原因是为了保证,在群集升级时不会连续的重新分配分片导致高网络流量、并降低群集的响应时间。
> 注意
>
> 使用systemd部署需要配置`systemd`的系统资源限制,而不是通过`/etc/sysconfig/elasticsearch`文件。更多信息请参见:[系统设置](../Important_System_Configuration/Configuring_system_settings.md#systemd)。
## RPM目录结构
RPM包中配置文件、日志和数据目录在RPM-based系统中对应的位置:
* home Elasticsearch主目录或 $ES\_HOME/usr/share/elasticsearch
* bin 二进制脚本,包括启动节点的`elasticsearch`、安装插件的`elasticsearch-plugin`/usr/share/elasticsearch/bin
* conf 配置文件,包括`lasticsearch.yml`/etc/elasticsearch path.conf
* conf 环境变量,包括heap大小、文件操作符/etc/sysconfig/elasticsearch
* data 节点上分配的各索引/分片的数据文件的目录,可以配置多个位置。/var/lib/elasticsearch path.data
* logs 日志文件的位置。/var/log/elasticsearchpath.logs
* plugins 插件的位置。每一个插件将被包含在一个子目录。/usr/share/elasticsearch/plugins
* repo 共享文件系统存储库位置。可以容纳多个位置。文件系统存储库可以放在这里指定的任意目录中的任何子目录。未配置path.repo
## 下一步
现在,您搭建了一个测试环境Elasticsearch。开始更深入的研究或投入生产使用Elasticsearch之前,你需要做一些额外的配置:
- 了解如何[配置Elasticsearch](../Configuring_Elasticsearch.md)。
- 配置[重要的Elasticsearch设置](../Important_Elasticsearch_configuration.md)。
- 配置[重要的系统设置](../Important_System_Configuration.md)。
> my note
>
> `/etc/sysconfig/elasticsearch` 文件的配置
> journalctl 查看日志
> 注意elasticsearch的目录权限
- 入门
- 基本概念
- 安装
- 探索你的集群
- 集群健康
- 列出所有索引库
- 创建一个索引库
- 索引文档创建与查询
- 删除一个索引库
- 修改你的数据
- 更新文档
- 删除文档
- 批量处理
- 探索你的数据
- 搜索API
- 查询语言介绍
- 执行搜索
- 执行过滤
- 执行聚合
- 总结
- Elasticsearch设置
- 安装Elasticsearch
- .zip或.tar.gz文件的安装方式
- Install Elasticsearch with .zip on Windows
- Debian软件包安装方式
- RPM安装方式
- Install Elasticsearch with Windows MSI Installer
- Docker安装方式
- 配置Elasticsearch
- 安全配置
- 日志配置
- 重要的Elasticsearch配置
- 重要的系统配置
- 系统设置
- 在jvm.options中设置JVM堆大小
- 禁用swapping
- 文件描述符
- 虚拟内存
- 线程数
- DNS cache settings
- 启动前检查
- 堆大小检查
- 文件描述符检查
- 内存锁定检查
- 最大线程数检查
- 最大虚拟内存检查
- Max file size check
- 最大map数检查
- JVM Client模式检查
- 串行收集使用检查
- 系统调用过滤检查
- OnError与OnOutOfMemoryError检查
- Early-access check
- G1GC检查
- Elasticsearch停机
- Elasticsearch升级
- 滚动升级
- 全集群重启升级
- 索引重建升级
- Set up X-Pack
- Installing X-Pack
- X-Pack Settings
- Watcher Settings
- Configuring Security
- Breaking changes in 6.0
- X-Pack Breaking Changes
- 重大变化
- 6.0的重大变化
- 聚合变化
- Cat API变化
- 客户端变化
- 集群变化
- 文档API变化
- 索引变化
- 预处理变化
- 映射变化
- Packaging变化
- Percolator变化
- 插件变化
- 索引重建变化
- 信息统计变化
- DSL查询变化
- 设置变化
- 脚本变化
- API约定
- 多索引语法
- 索引库名称的日期运算
- 常用选项
- URL-based访问控制
- 文档APIs
- 读写文档
- 索引接口
- Get接口
- Delete API
- Delete By Query API
- Update API
- Update By Query API
- Multi Get API
- Bulk API
- Reindex API
- Term Vectors
- Multi termvectors API
- ?refresh
- 搜索APIs
- Search
- URI Search
- Request Body Search
- Query
- From / Size
- Sort
- Source filtering
- Fields
- Script Fields
- Doc value Fields
- Post filter
- Highlighting
- Rescoring
- Search Type
- Scroll
- Preference
- Explain
- Version
- Index Boost
- min_score
- Named Queries
- Inner hits
- Field Collapsing
- Search After
- Search Template
- Multi Search Template
- Search Shards API
- Suggesters
- Term suggester
- Phrase Suggester
- Completion Suggester
- Context Suggester
- Returning the type of the suggester
- Multi Search API
- Count API
- Validate API
- Explain API
- Profile API
- Profiling Queries
- Profiling Aggregations
- Profiling Considerations
- Field Capabilities API
- Aggregations
- Metrics Aggregations
- 平均值聚合
- 值计数聚合(Value Count Aggregation)
- Cardinality Aggregation
- Extended Stats Aggregation
- 地理边界聚合
- 地理重心聚合
- Max Aggregation
- Min Aggregation
- Percentiles Aggregation
- Percentile Ranks Aggregation
- Scripted Metric Aggregation
- Stats Aggregation
- Sum Aggregation
- Top hits Aggregation
- Value Count Aggregation
- Bucket Aggregations
- 邻接矩阵聚合
- Children Aggregation
- Date Histogram Aggregation
- Date Range Aggregation
- Significant Terms Aggregation
- Filter Aggregation(过滤器聚合)
- Filters Aggregation
- Geo Distance Aggregation(地理距离聚合) 转至元数据结尾
- GeoHash grid Aggregation(GeoHash网格聚合)
- Global Aggregation(全局聚合) 转至元数据结尾
- Histogram Aggregation
- IP Range Aggregation(IP范围聚合)
- Missing Aggregation
- Nested Aggregation(嵌套聚合)
- Range Aggregation(范围聚合)
- Reverse nested Aggregation
- Sampler Aggregation
- Significant Terms Aggregation
- Significant Text Aggregation
- Terms Aggregation
- Pipeline Aggregations
- Avg Bucket Aggregation
- Derivative Aggregation(导数聚合)
- Max Bucket Aggregation
- Min Bucket Aggregation
- Sum Bucket Aggregation
- Stats Bucket Aggregation
- Extended Stats Bucket Aggregation(扩展信息桶聚合)
- Percentiles Bucket Aggregation(百分数桶聚合)
- Moving Average Aggregation
- Cumulative Sum Aggregation(累积汇总聚合)
- Bucket Script Aggregation(桶脚本聚合)
- Bucket Selector Aggregation(桶选择器聚合)
- Serial Differencing Aggregation(串行差异聚合)
- Matrix Aggregations
- Matrix Stats
- Caching heavy aggregations
- Returning only aggregation results
- Aggregation Metadata
- Returning the type of the aggregation
- Indices APIs
- Create Index /创建索引
- Delete Index /删除索引
- Get Index /获取索引
- Indices Exists /索引存在
- Open / Close Index API /启动关闭索引
- Shrink Index /缩小索引
- Rollover Index/滚动索引
- Put Mapping /提交映射
- Get Mapping /获取映射
- Get Field Mapping /获取字段映射
- Types Exists
- Index Aliases
- Update Indices Settings
- Get Settings
- Analyze
- Explain Analyze
- Index Templates
- 索引统计信息
- 索引段
- 索引恢复
- 索引分片存储
- 清理缓存
- 刷新
- 同步刷新
- 重新加载
- 强制合并
- Cat APIs
- cat aliases
- cat allocation
- cat count
- cat fielddata
- cat health
- cat indices
- cat master
- cat nodeattrs
- cat nodes
- cat pending tasks
- cat plugins
- cat recovery
- cat repositories
- cat segments
- cat shards
- cat thread pool
- cat snapshots
- cat templates
- Cluster APIs
- 集群健康
- 集群状态
- 集群统计
- 挂起的集群任务
- 集群重新路由
- Cluster Update Settings
- Nodes Stats
- Nodes Info
- Nodes Feature Usage
- Remote Cluster Info
- Task Management API
- Nodes hot_threads
- Cluster Allocation Explain API
- Query DSL
- 查询context与过滤context
- Match All Query
- 全文搜索
- 匹配查询
- 短语匹配查询
- 短语前缀匹配查询
- 多字段查询
- 常用术语查询
- 查询语句查询
- 简单查询语句
- Term level queries
- Term Query
- Terms Query
- Range Query
- Exists Query
- Prefix Query
- Wildcard Query
- Regexp Query
- Fuzzy Query
- Type Query
- Ids Query
- 复合查询
- Constant Score 查询
- Bool 查询
- Dis Max 查询
- Function Score 查询
- Boosting 查询
- Joining queries
- Has Child Query
- Has Parent Query
- Nested Query(嵌套查询)
- Parent Id Query
- Geo queries
- GeoShape Query(地理形状查询)
- Geo Bounding Box Query(地理边框查询)
- Geo Distance Query(地理距离查询)
- Geo Polygon Query(地理多边形查询)
- Specialized queries
- More Like This Query
- Script Query
- Percolate Query
- Span queries
- Span Term 查询
- Span Multi Term 查询
- Span First 查询
- Span Near 查询
- Span Or 查询
- Span Not 查询
- Span Containing 查询
- Span Within 查询
- Span Field Masking 查询 转至元数据结尾
- Minimum Should Match
- Multi Term Query Rewrite
- Mapping
- Removal of mapping types
- Field datatypes
- Array
- Binary
- Range
- Boolean
- Date
- Geo-point datatype
- Geo-Shape datatype
- IP datatype
- Keyword datatype
- Nested datatype
- Numeric datatypes
- Object datatype
- Text
- Token数
- 渗滤型
- join datatype
- Meta-Fields
- _all field
- _field_names field
- _id field
- _index field
- _meta field
- _routing field
- _source field
- _type field
- _uid field
- Mapping parameters
- analyzer(分析器)
- normalizer(归一化)
- boost(提升)
- Coerce(强制类型转换)
- copy_to(合并参数)
- doc_values(文档值)
- dynamic(动态设置)
- enabled(开启字段)
- eager_global_ordinals
- fielddata(字段数据)
- format (日期格式)
- ignore_above(忽略超越限制的字段)
- ignore_malformed(忽略格式不对的数据)
- index (索引)
- index_options(索引设置)
- fields(字段)
- Norms (标准信息)
- null_value(空值)
- position_increment_gap(短语位置间隙)
- properties (属性)
- search_analyzer (搜索分析器)
- similarity (匹配方法)
- store(存储)
- Term_vectors(词根信息)
- Dynamic Mapping
- Dynamic field mapping(动态字段映射)
- Dynamic templates(动态模板)
- default mapping(mapping中的_default_)
- Analysis
- Anatomy of an analyzer(分析器的分析)
- Testing analyzers(测试分析器)
- Analyzers(分析器)
- Configuring built-in analyzers(配置内置分析器)
- Standard Analyzer(标准分析器)
- Simple Analyzer(简单分析器)
- 空白分析器
- Stop Analyzer
- Keyword Analyzer
- 模式分析器
- 语言分析器
- 指纹分析器
- 自定义分析器
- Normalizers
- Tokenizers(分词器)
- Standard Tokenizer(标准分词器)
- Letter Tokenizer
- Lowercase Tokenizer (小写分词器)
- Whitespace Analyzer
- UAX URL Email Tokenizer
- Classic Tokenizer
- Thai Tokenizer(泰语分词器)
- NGram Tokenizer
- Edge NGram Tokenizer
- Keyword Analyzer
- Pattern Tokenizer
- Simple Pattern Tokenizer
- Simple Pattern Split Tokenizer
- Path Hierarchy Tokenizer(路径层次分词器)
- Token Filters(词元过滤器)
- Standard Token Filter
- ASCII Folding Token Filter
- Flatten Graph Token Filter
- Length Token Filter
- Lowercase Token Filter
- Uppercase Token Filter
- NGram Token Filter
- Edge NGram Token Filter
- Porter Stem Token Filter
- Shingle Token Filter
- Stop Token Filter
- Word Delimiter Token Filter
- Word Delimiter Graph Token Filter
- Stemmer Token Filter
- Stemmer Override Token Filter
- Keyword Marker Token Filter
- Keyword Repeat Token Filter
- KStem Token Filter
- Snowball Token Filter
- Phonetic Token Filter
- Synonym Token Filter
- Synonym Graph Token Filter
- Compound Word Token Filters
- Reverse Token Filter
- Elision Token Filter
- Truncate Token Filter
- Unique Token Filter
- Pattern Capture Token Filter
- Pattern Replace Token Filter
- Trim Token Filter
- Limit Token Count Token Filter
- Hunspell Token Filter
- Common Grams Token Filter
- Normalization Token Filter
- CJK Width Token Filter
- CJK Bigram Token Filter
- Delimited Payload Token Filter
- Keep Words Token Filter
- Keep Types Token Filter
- Classic Token Filter
- Apostrophe Token Filter
- Decimal Digit Token Filter
- Fingerprint Token Filter
- Minhash Token Filter
- Character Filters(字符过滤器)
- HTML Strip Character Filter
- Mapping Character Filter
- Pattern Replace Character Filter
- 模块
- Cluster
- 集群级路由和碎片分配
- 基于磁盘的分片分配
- 分片分配awareness
- 分片分配过滤
- Miscellaneous cluster settings
- Scripting
- Painless Scripting Language
- Lucene Expressions Language
- Advanced scripts using script engines
- Snapshot And Restore
- Thread Pool
- Index Modules(索引模块)
- 预处理节点
- Pipeline Definition
- Ingest APIs
- Put Pipeline API
- Get Pipeline API
- Delete Pipeline API
- Simulate Pipeline API
- Accessing Data in Pipelines
- Handling Failures in Pipelines
- Processors
- Monitoring Elasticsearch
- X-Pack APIs
- X-Pack Commands
- How To
- Testing(测试)
- Glossary of terms
- Release Notes
- X-Pack Release Notes