一、快速入门
1. 查看集群的健康状况
http://localhost:9200/_cat
http://localhost:9200/_cat/health?v
说明：v是用来要求在结果中返回表头
状态值说明
Green - everything is good (cluster is fully functional)，即最佳状态
Yellow - all data is available but some replicas are not yet allocated (cluster is fully functional)，即数据和集群可用，但是集群的备份有的是坏的
Red - some data is not available for whatever reason (cluster is partially functional)，即数据和集群都不可用
查看集群的节点
http://localhost:9200/_cat/nodes?v
2. 查看所有索引
http://localhost:9200/_cat/indices?v
3. 创建一个索引
创建一个名为 customer 的索引。pretty要求返回一个漂亮的json 结果
PUT /customer?pretty
再查看一下所有索引
http://localhost:9200/_cat/indices?v
GET /_cat/indices?v
4. 索引一个文档到customer索引中
curl -X PUT "localhost:9200/customer/_doc/1?pretty" -H 'Content-Type: application/json' -d'
{
"name": "John Doe"
}
'5. 从customer索引中获取指定id的文档
curl -X GET "localhost:9200/customer/_doc/1?pretty"6. 查询所有文档
GET /customer/_search?q=*&sort=name:asc&prettyJSON格式方式
GET /customer/_search
{
"query": { "match_all": {} },
"sort": [
{"name": "asc" }
]
}
二、索引管理
1. 创建索引
创建一个名为twitter的索引，设置索引的分片数为3，备份数为2。注意：在ES中创建一个索引类似于在数据库中建立一个数据库(ES6.0之后类似于创建一个表)
PUT twitter
{
"settings" : {
"index" : {
"number_of_shards" : 3,
"number_of_replicas" : 2
}
}
}
说明：
默认的分片数是5到1024
默认的备份数是1
索引的名称必须是小写的，不可重名
创建结果：
创建的命令还可以简写为
PUT twitter
{
"settings" : {
"number_of_shards" : 3,
"number_of_replicas" : 2
}
}
2. 创建mapping映射
注意：在ES中创建一个mapping映射类似于在数据库中定义表结构，即表里面有哪些字段、字段是什么类型、字段的默认值等；也类似于solr里面的模式schema的定义
PUT twitter
{
"settings" : {
"index" : {
"number_of_shards" : 3,
"number_of_replicas" : 2
}
},
"mappings" : {
"type1" : {
"properties" : {
"field1" : { "type" : "text" }
}
}
}
}
3. 创建索引时加入别名定义
PUT twitter
{
"aliases" : {
"alias_1" : {},
"alias_2" : {
"filter" : {
"term" : {"user" : "kimchy" }
},
"routing" : "kimchy"
}
}
}
4. 创建索引时返回的结果说明
5. Get Index 查看索引的定义信息
GET /twitter，可以一次获取多个索引（以逗号间隔） 获取所有索引 _all 或 用通配符*
GET /twitter/_settings
GET /twitter/_mapping
6. 删除索引
DELETE /twitter
说明：
可以一次删除多个索引（以逗号间隔） 删除所有索引 _all 或 通配符 *
7. 判断索引是否存在
HEAD twitter
HTTP status code 表示结果 404 不存在 ， 200 存在
8. 修改索引的settings信息
索引的设置信息分为静态信息和动态信息两部分。静态信息不可更改，如索引的分片数。动态信息可以修改。
REST 访问端点：
/_settings 更新所有索引的。
{index}/_settings 更新一个或多个索引的settings。
详细的设置项请参考： https://www.elastic.co/guide/en/elasticsearch/reference/current/index-modules.html#index-modules-settings
9. 修改备份数
PUT /twitter/_settings
{
"index" : {
"number_of_replicas" : 2
}
}10. 设置回默认值，用null
PUT /twitter/_settings
{
"index" : {
"refresh_interval" : null
}
}11. 设置索引的读写
index.blocks.read_only：设为true,则索引以及索引的元数据只可读
index.blocks.read_only_allow_delete：设为true，只读时允许删除。
index.blocks.read：设为true，则不可读。
index.blocks.write：设为true，则不可写。
index.blocks.metadata：设为true，则索引元数据不可读写。12. 索引模板
在创建索引时，为每个索引写定义信息可能是一件繁琐的事情，ES提供了索引模板功能，让你可以定义一个索引模板，模板中定义好settings、mapping、以及一个模式定义来匹配创建的索引。
注意：模板只在索引创建时被参考，修改模板不会影响已创建的索引
12.1 新增/修改名为tempae_1的模板，匹配名称为te* 或 bar*的索引创建：
PUT _template/template_1
{
"index_patterns": ["te*", "bar*"],
"settings": {
"number_of_shards": 1
},
"mappings": {
"type1": {
"_source": {
"enabled": false
},
"properties": {
"host_name": {
"type": "keyword"
},
"created_at": {
"type": "date",
"format": "EEE MMM dd HH:mm:ss Z YYYY"
}
}
}
}
}
12.2 查看索引模板
GET /_template/template_1
GET /_template/temp*
GET /_template/template_1,template_2
GET /_template12.3 删除模板
DELETE /_template/template_113. Open/Close Index 打开/关闭索引
POST /my_index/_close
POST /my_index/_open说明：
关闭的索引不能进行读写操作，几乎不占集群开销。
关闭的索引可以打开，打开走的是正常的恢复流程。
14. Shrink Index 收缩索引
索引的分片数是不可更改的，如要减少分片数可以通过收缩方式收缩为一个新的索引。新索引的分片数必须是原分片数的因子值，如原分片数是8，则新索引的分片数可以为4、2、1 。
什么时候需要收缩索引呢?
最初创建索引的时候分片数设置得太大，后面发现用不了那么多分片，这个时候就需要收缩了
收缩的流程：
先把所有主分片都转移到一台主机上；
在这台主机上创建一个新索引，分片数较小，其他设置和原索引一致；
把原索引的所有分片，复制（或硬链接）到新索引的目录下；
对新索引进行打开操作恢复分片数据；
(可选)重新把新索引的分片均衡到其他节点上。
收缩前的准备工作：
将原索引设置为只读；
将原索引各分片的一个副本重分配到同一个节点上，并且要是健康绿色状态。
PUT /my_source_index/_settings
{
"settings": {
<!-- 指定进行收缩的节点的名称 -->
"index.routing.allocation.require._name": "shrink_node_name",
<!-- 阻止写，只读 -->
"index.blocks.write": true
}
}
进行收缩：
POST my_source_index/_shrink/my_target_index
{
"settings": {
"index.number_of_replicas": 1,
"index.number_of_shards": 1,
"index.codec": "best_compression"
}}
监控收缩过程：
GET _cat/recovery?v
GET _cluster/health15. Split Index 拆分索引
当索引的分片容量过大时，可以通过拆分操作将索引拆分为一个倍数分片数的新索引。能拆分为几倍由创建索引时指定的index.number_of_routing_shards 路由分片数决定。这个路由分片数决定了根据一致性hash路由文档到分片的散列空间。
如index.number_of_routing_shards = 30 ，指定的分片数是5，则可按如下倍数方式进行拆分：
5 → 10 → 30 (split by 2, then by 3)
5 → 15 → 30 (split by 3, then by 2)
5 → 30 (split by 6)
为什么需要拆分索引？
当最初设置的索引的分片数不够用时就需要拆分索引了，和压缩索引相反
注意：只有在创建时指定了index.number_of_routing_shards 的索引才可以进行拆分，ES7开始将不再有这个限制。
和solr的区别是，solr是对一个分片进行拆分，es中是整个索引进行拆分。
拆分步骤：
准备一个索引来做拆分：
PUT my_source_index
{
"settings": {
"index.number_of_shards" : 1,
<!-- 创建时需要指定路由分片数 -->
"index.number_of_routing_shards" : 2
}
}
先设置索引只读：
PUT /my_source_index/_settings
{
"settings": {
"index.blocks.write": true
}
}做拆分：
POST my_source_index/_split/my_target_index
{
"settings": {
<!--新索引的分片数需符合拆分规则-->
"index.number_of_shards": 2
}
}
监控拆分过程：
GET _cat/recovery?v
GET _cluster/health16. Rollover Index 别名滚动指向新创建的索引
对于有时效性的索引数据，如日志，过一定时间后，老的索引数据就没有用了。我们可以像数据库中根据时间创建表来存放不同时段的数据一样，在ES中也可用建多个索引的方式来分开存放不同时段的数据。比数据库中更方便的是ES中可以通过别名滚动指向最新的索引的方式，让你通过别名来操作时总是操作的最新的索引。
ES的rollover index API 让我们可以根据满足指定的条件（时间、文档数量、索引大小）创建新的索引，并把别名滚动指向新的索引。
注意：这时的别名只能是一个索引的别名。
Rollover Index 示例：
创建一个名字为logs-0000001 、别名为logs_write 的索引：
PUT /logs-000001
{
"aliases": {
"logs_write": {}
}
}添加1000个文档到索引logs-000001，然后设置别名滚动的条件
POST /logs_write/_rollover
{
"conditions": {
"max_age": "7d",
"max_docs": 1000,
"max_size": "5gb"
}
}
说明：
如果别名logs_write指向的索引是7天前（含）创建的或索引的文档数>=1000或索引的大小>= 5gb，则会创建一个新索引 logs-000002，并把别名logs_writer指向新创建的logs-000002索引
Rollover Index 新建索引的命名规则：
如果索引的名称是-数字结尾，如logs-000001，则新建索引的名称也会是这个模式，数值增1。
如果索引的名称不是-数值结尾，则在请求rollover api时需指定新索引的名称
POST /my_alias/_rollover/my_new_index_name
{
"conditions": {
"max_age": "7d",
"max_docs": 1000,
"max_size": "5gb"
}
}
在名称中使用Date math（时间表达式）
如果你希望生成的索引名称中带有日期，如logstash-2016.02.03-1 ，则可以在创建索引时采用时间表达式来命名：
# PUT /<logs-{now/d}-1> with URI encoding:
PUT /%3Clogs-%7Bnow%2Fd%7D-1%3E
{
"aliases": {
"logs_write": {}
}
}
PUT logs_write/_doc/1
{
"message": "a dummy log"
}
POST logs_write/_refresh
# Wait for a day to pass
POST /logs_write/_rollover
{
"conditions": {
"max_docs": "1"
}
}
Rollover时可对新的索引作定义：
PUT /logs-000001
{
"aliases": {
"logs_write": {}
}
}
POST /logs_write/_rollover
{
"conditions" : {
"max_age": "7d",
"max_docs": 1000,
"max_size": "5gb"
},
"settings": {
"index.number_of_shards": 2
}
}
Dry run 实际操作前先测试是否达到条件：
POST /logs_write/_rollover?dry_run
{
"conditions" : {
"max_age": "7d",
"max_docs": 1000,
"max_size": "5gb"
}
}
说明：
测试不会创建索引，只是检测条件是否满足
注意：rollover是你请求它才会进行操作，并不是自动在后台进行的。你可以周期性地去请求它。
17. 索引监控
17.1 查看索引状态信息
官网链接：
https://www.elastic.co/guide/en/elasticsearch/reference/current/indices-stats.html
查看所有的索引状态：
GET /_stats
查看指定索引的状态信息：
GET /index1,index2/_stats
17.2 查看索引段信息
官网链接：
https://www.elastic.co/guide/en/elasticsearch/reference/current/indices-segments.html
GET /test/_segments
GET /index1,index2/_segments
GET /_segments17.3 查看索引恢复信息
官网链接：
https://www.elastic.co/guide/en/elasticsearch/reference/current/indices-recovery.html
GET index1,index2/_recovery?human
GET /_recovery?human
17.4 查看索引分片的存储信息
官网链接：
https://www.elastic.co/guide/en/elasticsearch/reference/current/indices-shards-stores.html
# return information of only index test
GET /test/_shard_stores
# return information of only test1 and test2 indices
GET /test1,test2/_shard_stores
# return information of all indices
GET /_shard_stores
GET /_shard_stores?status=green
18. 索引状态管理
18.1 Clear Cache 清理缓存
POST /twitter/_cache/clear
默认会清理所有缓存，可指定清理query, fielddata or request 缓存
POST /kimchy,elasticsearch/_cache/clear
POST /_cache/clear18.2 Refresh，重新打开读取索引
POST /kimchy,elasticsearch/_refresh
POST /_refresh18.3 Flush，将缓存在内存中的索引数据刷新到持久存储中
POST twitter/_flush
18.4 Force merge 强制段合并
POST /kimchy/_forcemerge?only_expunge_deletes=false&max_num_segments=100&flush=true可选参数说明：
max_num_segments 合并为几个段，默认1
only_expunge_deletes 是否只合并含有删除文档的段，默认false
flush 合并后是否刷新，默认true
POST /kimchy,elasticsearch/_forcemerge
POST /_forcemerge三、映射详解
1. Mapping 映射是什么
映射定义索引中有什么字段、字段的类型等结构信息。相当于数据库中表结构定义，或 solr中的schema。因为lucene索引文档时需要知道该如何来索引存储文档的字段。
ES中支持手动定义映射，动态映射两种方式。
1.1. 为索引创建mapping
PUT test
{
<!--映射定义 -->
"mappings" : {
<!--名为type1的映射类别 mapping type-->
"type1" : {
<!-- 字段定义 -->
"properties" : {
<!-- 名为field1的字段，它的field datatype 为 text -->
"field1" : { "type" : "text" }
}
}
}
}
说明：映射定义后续可以修改
2. 映射类别 Mapping type 废除说明
ES最先的设计是用索引类比关系型数据库的数据库，用mapping type 来类比表，一个索引中可以包含多个映射类别。这个类比存在一个严重的问题，就是当多个mapping type中存在同名字段时（特别是同名字段还是不同类型的），在一个索引中不好处理，因为搜索引擎中只有 索引-文档的结构，不同映射类别的数据都是一个一个的文档（只是包含的字段不一样而已）
从6.0.0开始限定仅包含一个映射类别定义（ "index.mapping.single_type": true ），兼容5.x中的多映射类别。从7.0开始将移除映射类别。
为了与未来的规划匹配，请现在将这个唯一的映射类别名定义为“_doc”,因为索引的请求地址将规范为：PUT {index}/_doc/{id} and POST {index}/_doc
Mapping 映射示例：
PUT twitter
{
"mappings": {
"_doc": {
"properties": {
"type": { "type": "keyword" },
"name": { "type": "text" },
"user_name": { "type": "keyword" },
"email": { "type": "keyword" },
"content": { "type": "text" },
"tweeted_at": { "type": "date" }
}
}
}
}
多映射类别数据转储到独立的索引中：
ES 提供了reindex API 来做这个事
3. 字段类型 datatypes
字段类型定义了该如何索引存储字段值。ES中提供了丰富的字段类型定义，请查看官网链接详细了解每种类型的特点：
https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-types.html
3.1 Core Datatypes 核心类型
string
text and keyword
Numeric datatypes
long, integer, short, byte, double, float, half_float, scaled_float
Date datatype
date
Boolean datatype
boolean
Binary datatype
binary
Range datatypes 范围
integer_range, float_range, long_range, double_range, date_range
3.2 Complex datatypes 复合类型
Array datatype
数组就是多值，不需要专门的类型
Object datatype
object ：表示值为一个JSON 对象
Nested datatype
nested：for arrays of JSON objects（表示值为JSON对象数组 ）3.3 Geo datatypes 地理数据类型
Geo-point datatype
geo_point： for lat/lon points （经纬坐标点）
Geo-Shape datatype
geo_shape： for complex shapes like polygons （形状表示）3.4 Specialised datatypes 特别的类型
IP datatype
ip： for IPv4 and IPv6 addresses
Completion datatype
completion： to provide auto-complete suggestions
Token count datatype
token_count： to count the number of tokens in a string
mapper-murmur3
murmur3： to compute hashes of values at index-time and store them in the index
Percolator type
Accepts queries from the query-dsl
join datatype
Defines parent/child relation for documents within the same index
4. 字段定义属性介绍
字段的type (Datatype)定义了如何索引存储字段值，还有一些属性可以让我们根据需要来覆盖默认的值或进行特别定义。请参考官网介绍详细了解： https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-params.html
analyzer 指定分词器
normalizer 指定标准化器
boost 指定权重值
coerce 强制类型转换
copy_to 值复制给另一字段
doc_values 是否存储docValues
dynamic
enabled 字段是否可用
fielddata
eager_global_ordinals
format 指定时间值的格式
ignore_above
ignore_malformed
index_options
index
fields
norms
null_value
position_increment_gap
properties
search_analyzer
similarity
store
term_vector
字段定义属性—示例
PUT my_index
{
"mappings": {
"_doc": {
"properties": {
"date": {
"type": "date",
<!--格式化日期 -->
"format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis"
}
}
}
}
}
5. Multi Field 多重字段
当我们需要对一个字段进行多种不同方式的索引时，可以使用fields多重字段定义。如一个字符串字段即需要进行text分词索引，也需要进行keyword 关键字索引来支持排序、聚合；或需要用不同的分词器进行分词索引。
示例：
定义多重字段：
说明：raw是一个多重版本名（自定义）
PUT my_index
{
"mappings": {
"_doc": {
"properties": {
"city": {
"type": "text",
"fields": {
"raw": {
"type": "keyword"
}
}
}
}
}
}
}
往多重字段里面添加文档
PUT my_index/_doc/1
{
"city": "New York"
}
PUT my_index/_doc/2
{
"city": "York"
}
获取多重字段的值：
GET my_index/_search
{
"query": {
"match": {
"city": "york"
}
},
"sort": {
"city.raw": "asc"
},
"aggs": {
"Cities": {
"terms": {
"field": "city.raw"
}
}
}
}
6. 元字段
官网链接：
https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-fields.html
元字段是ES中定义的文档字段，有以下几类：
7. 动态映射
动态映射：ES中提供的重要特性，让我们可以快速使用ES，而不需要先创建索引、定义映射。 如我们直接向ES提交文档进行索引：
PUT data/_doc/1
{ "count": 5 }
ES将自动为我们创建data索引、_doc 映射、类型为 long 的字段 count
索引文档时，当有新字段时， ES将根据我们字段的json的数据类型为我们自动加人字段定义到mapping中。
7.1 字段动态映射规则
7.2 Date detection 时间侦测
所谓时间侦测是指我们往ES里面插入数据的时候会去自动检测我们的数据是不是日期格式的，是的话就会给我们自动转为设置的格式
date_detection 默认是开启的，默认的格式dynamic_date_formats为：
[ "strict_date_optional_time","yyyy/MM/dd HH:mm:ss Z||yyyy/MM/dd Z"]
PUT my_index/_doc/1
{
"create_date": "2015/09/02"
}
GET my_index/_mapping自定义时间格式：
PUT my_index
{
"mappings": {
"_doc": {
"dynamic_date_formats": ["MM/dd/yyyy"]
}
}
}
禁用时间侦测：
PUT my_index
{
"mappings": {
"_doc": {
"date_detection": false
}
}
}
7.3 Numeric detection 数值侦测
开启数值侦测（默认是禁用的）
PUT my_index
{
"mappings": {
"_doc": {
"numeric_detection": true
}
}
}
PUT my_index/_doc/1
{
"my_float": "1.0",
"my_integer": "1"
}
四、索引别名
1. 别名的用途
如果希望一次查询可查询多个索引。
如果希望通过索引的视图来操作索引，就像数据库库中的视图一样。
索引的别名机制，就是让我们可以以视图的方式来操作集群中的索引，这个视图可是多个索引，也可是一个索引或索引的一部分。
2. 新建索引时定义别名
PUT /logs_20162801
{
"mappings" : {
"type" : {
"properties" : {
"year" : {"type" : "integer"}
}
}
},
<!-- 定义了两个别名 -->
"aliases" : {
"current_day" : {},
"2016" : {
"filter" : {
"term" : {"year" : 2016 }
}
}
}
}
3. 创建别名 /_aliases
为索引test1创建别名alias1
POST /_aliases
{
"actions" : [
{ "add" : { "index" : "test1", "alias" : "alias1" } }
]
}4. 删除别名
POST /_aliases
{
"actions" : [
{ "remove" : { "index" : "test1", "alias" : "alias1" } }
]
}还可以这样写
DELETE /{index}/_alias/{name}5. 批量操作别名
删除索引test1的别名alias1，同时为索引test2添加别名alias1
POST /_aliases
{
"actions" : [
{ "remove" : { "index" : "test1", "alias" : "alias1" } },
{ "add" : { "index" : "test2", "alias" : "alias1" } }
]
}
6. 为多个索引定义一样的别名
方式1：
POST /_aliases
{
"actions" : [
{ "add" : { "index" : "test1", "alias" : "alias1" } },
{ "add" : { "index" : "test2", "alias" : "alias1" } }
]
}
方式2：
POST /_aliases
{
"actions" : [
{ "add" : { "indices" : ["test1", "test2"], "alias" : "alias1" } }
]
}注意：只可通过多索引别名进行搜索，不可进行文档索引和根据id获取文档。
方式3：通过统配符*模式来指定要别名的索引
POST /_aliases
{
"actions" : [
{ "add" : { "index" : "test*", "alias" : "all_test_indices" } }
]
}注意：在这种情况下，别名是一个点时间别名，它将对所有匹配的当前索引进行别名，当添加/删除与此模式匹配的新索引时，它不会自动更新。
7. 带过滤器的别名
索引中需要有字段
PUT /test1
{
"mappings": {
"type1": {
"properties": {
"user" : {
"type": "keyword"
}
}
}
}
}
过滤器通过Query DSL来定义，将作用于通过该别名来进行的所有Search, Count, Delete By Query and More Like This 操作。
POST /_aliases
{
"actions" : [
{
"add" : {
"index" : "test1",
"alias" : "alias2",
"filter" : { "term" : { "user" : "kimchy" } }
}
}
]
}
8. 带routing的别名
可在别名定义中指定路由值，可和filter一起使用，用来限定操作的分片，避免不需要的其他分片操作。
POST /_aliases
{
"actions" : [
{
"add" : {
"index" : "test",
"alias" : "alias1",
"routing" : "1"
}
}
]
}
为搜索、索引指定不同的路由值
POST /_aliases
{
"actions" : [
{
"add" : {
"index" : "test",
"alias" : "alias2",
"search_routing" : "1,2",
"index_routing" : "2"
}
}
]
}
9. 以PUT方式来定义一个别名
PUT /{index}/_alias/{name}
PUT /logs_201305/_alias/2013带filter 和 routing
PUT /users
{
"mappings" : {
"user" : {
"properties" : {
"user_id" : {"type" : "integer"}
}
}
}
}
PUT /users/_alias/user_12
{
"routing" : "12",
"filter" : {
"term" : {
"user_id" : 12
}
}
}
10. 查看别名定义信息
GET /{index}/_alias/{alias}
GET /logs_20162801/_alias/*
GET /_alias/2016
GET /_alias/20*elasticsearch系列三：索引详解（分词器、文档管理、路由详解（集群））
一、分词器
1. 认识分词器
1.1 Analyzer 分析器
在ES中一个Analyzer 由下面三种组件组合而成：
character filter ：字符过滤器，对文本进行字符过滤处理，如处理文本中的html标签字符。处理完后再交给tokenizer进行分词。一个analyzer中可包含0个或多个字符过滤器，多个按配置顺序依次进行处理。
tokenizer：分词器，对文本进行分词。一个analyzer必需且只可包含一个tokenizer。
token filter：词项过滤器，对tokenizer分出的词进行过滤处理。如转小写、停用词处理、同义词处理。一个analyzer可包含0个或多个词项过滤器，按配置顺序进行过滤。
1.2 如何测试分词器
POST _analyze
{
"analyzer": "whitespace",
"text": "The quick brown fox."
}
POST _analyze
{
"tokenizer": "standard",
"filter": [ "lowercase", "asciifolding" ],
"text": "Is this déja vu?"
}
position：第几个词
offset：词的偏移位置
2. 内建的character filter
HTML Strip Character Filter
html_strip ：过滤html标签，解码HTML entities like &.
Mapping Character Filter
mapping ：用指定的字符串替换文本中的某字符串。
Pattern Replace Character Filter
pattern_replace ：进行正则表达式替换。
2.1 HTML Strip Character Filter
POST _analyze
{
"tokenizer": "keyword",
"char_filter": [ "html_strip" ],
"text": "<p>I'm so <b>happy</b>!</p>"
} 
在索引中配置：
PUT my_index
{
"settings": {
"analysis": {
"analyzer": {
"my_analyzer": {
"tokenizer": "keyword",
"char_filter": ["my_char_filter"]
}
},
"char_filter": {
"my_char_filter": {
"type": "html_strip",
"escaped_tags": ["b"]
}
}
}
}
}
escaped_tags 用来指定例外的标签。 如果没有例外标签需配置，则不需要在此进行客户化定义，在上面的my_analyzer中直接使用 html_strip
测试：
POST my_index/_analyze
{
"analyzer": "my_analyzer",
"text": "<p>I'm so <b>happy</b>!</p>"
}2.2 Mapping character filter
官网链接：https://www.elastic.co/guide/en/elasticsearch/reference/current/analysis-mapping-charfilter.html
PUT my_index
{
"settings": {
"analysis": {
"analyzer": {
"my_analyzer": {
"tokenizer": "keyword",
"char_filter": [
"my_char_filter"
]
}
},
"char_filter": {
"my_char_filter": {
"type": "mapping",
"mappings": [
"٠ => 0",
"١ => 1",
"٢ => 2",
"٣ => 3",
"٤ => 4",
"٥ => 5",
"٦ => 6",
"٧ => 7",
"٨ => 8",
"٩ => 9"
]
}
}
}
}
}
测试
POST my_index/_analyze
{
"analyzer": "my_analyzer",
"text": "My license plate is ٢٥٠١٥"
} 
2.3 Pattern Replace Character Filter
官网链接：https://www.elastic.co/guide/en/elasticsearch/reference/current/analysis-pattern-replace-charfilter.html
PUT my_index
{
"settings": {
"analysis": {
"analyzer": {
"my_analyzer": {
"tokenizer": "standard",
"char_filter": [
"my_char_filter"
]
}
},
"char_filter": {
"my_char_filter": {
"type": "pattern_replace",
"pattern": "(\d+)-(?=\d)",
"replacement": "$1_"
}
}
}
}
}
测试
POST my_index/_analyze
{
"analyzer": "my_analyzer",
"text": "My credit card is 123-456-789"
} 
3. 内建的Tokenizer
官网链接：https://www.elastic.co/guide/en/elasticsearch/reference/current/analysis-tokenizers.html
Standard Tokenizer
Letter Tokenizer
Lowercase Tokenizer
Whitespace Tokenizer
UAX URL Email Tokenizer
Classic Tokenizer
Thai Tokenizer
NGram Tokenizer
Edge NGram Tokenizer
Keyword Tokenizer
Pattern Tokenizer
Simple Pattern Tokenizer
Simple Pattern Split Tokenizer
Path Hierarchy Tokenizer前面集成的中文分词器Ikanalyzer中提供的tokenizer：ik_smart 、 ik_max_word
测试tokenizer
POST _analyze
{
"tokenizer": "standard",
"text": "张三说的确实在理"
}
POST _analyze
{
"tokenizer": "ik_smart",
"text": "张三说的确实在理"
}
4. 内建的Token Filter
ES中内建了很多Token filter ，详细了解：https://www.elastic.co/guide/en/elasticsearch/reference/current/analysis-tokenizers.html
Lowercase Token Filter ：lowercase 转小写
Stop Token Filter ：stop 停用词过滤器
Synonym Token Filter： synonym 同义词过滤器说明：中文分词器Ikanalyzer中自带有停用词过滤功能。
4.1 Synonym Token Filter 同义词过滤器
PUT /test_index
{
"settings": {
"index" : {
"analysis" : {
"analyzer" : {
"my_ik_synonym" : {
"tokenizer" : "ik_smart",
"filter" : ["synonym"]
}
},
"filter" : {
"synonym" : {
"type" : "synonym",
<!-- synonyms_path：指定同义词文件（相对config的位置）-->
"synonyms_path" : "analysis/synonym.txt"
}
}
}
}
}
}
同义词定义格式
ES同义词格式支持 solr、 WordNet 两种格式。
在analysis/synonym.txt中用solr格式定义如下同义词
张三,李四
电饭煲,电饭锅 => 电饭煲
电脑 => 计算机,computer注意：
文件一定要UTF-8编码
一行一类同义词，=> 表示标准化为
测试：通过例子的结果了解同义词的处理行为
POST test_index/_analyze
{
"analyzer": "my_ik_synonym",
"text": "张三说的确实在理"
}
POST test_index/_analyze
{
"analyzer": "my_ik_synonym",
"text": "我想买个电饭锅和一个电脑"
}
5. 内建的Analyzer
官网链接：
https://www.elastic.co/guide/en/elasticsearch/reference/current/analysis-analyzers.html
Standard Analyzer
Simple Analyzer
Whitespace Analyzer
Stop Analyzer
Keyword Analyzer
Pattern Analyzer
Language Analyzers
Fingerprint Analyzer集成的中文分词器Ikanalyzer中提供的Analyzer：ik_smart 、 ik_max_word
内建的和集成的analyzer可以直接使用。如果它们不能满足我们的需要，则我们可自己组合字符过滤器、分词器、词项过滤器来定义自定义的analyzer
5.1 自定义 Analyzer
配置参数：
PUT my_index8
{
"settings": {
"analysis": {
"analyzer": {
"my_ik_analyzer": {
"type": "custom",
"tokenizer": "ik_smart",
"char_filter": [
"html_strip"
],
"filter": [
"synonym"
]
}
},
"filter": {
"synonym": {
"type": "synonym",
"synonyms_path": "analysis/synonym.txt"
}
} } }}
5.2 为字段指定分词器
PUT my_index8/_mapping/_doc
{
"properties": {
"title": {
"type": "text",
"analyzer": "my_ik_analyzer"
}
}
}
如果该字段的查询需要使用不同的analyzer
PUT my_index8/_mapping/_doc
{
"properties": {
"title": {
"type": "text",
"analyzer": "my_ik_analyzer",
"search_analyzer": "other_analyzer"
}
}
}
测试结果
PUT my_index8/_doc/1
{
"title": "张三说的确实在理"
}
GET /my_index8/_search
{
"query": {
"term": {
"title": "张三"
}
}
}
5.3 为索引定义个default分词器
PUT /my_index10
{
"settings": {
"analysis": {
"analyzer": {
"default": {
"tokenizer": "ik_smart",
"filter": [
"synonym"
]
}
},
"filter": {
"synonym": {
"type": "synonym",
"synonyms_path": "analysis/synonym.txt"
}
}
}
},
"mappings": {
"_doc": {
"properties": {
"title": {
"type": "text"
}
}
}
}
}
测试结果：
PUT my_index10/_doc/1
{
"title": "张三说的确实在理"
}
GET /my_index10/_search
{
"query": {
"term": {
"title": "张三"
}
}
}
6. Analyzer的使用顺序
我们可以为每个查询、每个字段、每个索引指定分词器。
在索引阶段ES将按如下顺序来选用分词：
首先选用字段mapping定义中指定的analyzer
字段定义中没有指定analyzer，则选用 index settings中定义的名字为default 的analyzer。
如index setting中没有定义default分词器，则使用 standard analyzer.
查询阶段ES将按如下顺序来选用分词：
The analyzer defined in a full-text query.
The search_analyzer defined in the field mapping.
The analyzer defined in the field mapping.
An analyzer named default_search in the index settings.
An analyzer named default in the index settings.
The standard analyzer.
二、文档管理
1. 新建文档
指定文档id，新增/修改
PUT twitter/_doc/1
{
"id": 1,
"user" : "kimchy",
"post_date" : "2009-11-15T14:12:12",
"message" : "trying out Elasticsearch"
}
新增，自动生成文档id
POST twitter/_doc/
{
"id": 1,
"user" : "kimchy",
"post_date" : "2009-11-15T14:12:12",
"message" : "trying out Elasticsearch"
}
返回结果说明：
2. 获取单个文档
HEAD twitter/_doc/11
GET twitter/_doc/1
不获取文档的source：
GET twitter/_doc/1?_source=false获取文档的source：
GET twitter/_doc/1/_source
{
"_index": "twitter",
"_type": "_doc",
"_id": "1",
"_version": 2,
"found": true,
"_source": {
"id": 1,
"user": "kimchy",
"post_date": "2009-11-15T14:12:12",
"message": "trying out Elasticsearch"
}}
获取存储字段
PUT twitter11
{
"mappings": {
"_doc": {
"properties": {
"counter": {
"type": "integer",
"store": false
},
"tags": {
"type": "keyword",
"store": true
} } } }}
PUT twitter11/_doc/1
{
"counter" : 1,
"tags" : ["red"]
}
GET twitter11/_doc/1?stored_fields=tags,counter
3. 获取多个文档 _mget
方式1：
GET /_mget
{
"docs" : [
{
"_index" : "twitter",
"_type" : "_doc",
"_id" : "1"
},
{
"_index" : "twitter",
"_type" : "_doc",
"_id" : "2"
"stored_fields" : ["field3", "field4"]
}
]
}
方式2：
GET /twitter/_mget
{
"docs" : [
{
"_type" : "_doc",
"_id" : "1"
},
{
"_type" : "_doc",
"_id" : "2"
}
]
}
方式3：
GET /twitter/_doc/_mget
{
"docs" : [
{
"_id" : "1"
},
{
"_id" : "2"
}
]
}
方式4：
GET /twitter/_doc/_mget
{
"ids" : ["1", "2"]
}4. 删除文档
指定文档id进行删除
DELETE twitter/_doc/1
用版本来控制删除
DELETE twitter/_doc/1?version=1
返回结果：
{
"_shards" : {
"total" : 2,
"failed" : 0,
"successful" : 2
},
"_index" : "twitter",
"_type" : "_doc",
"_id" : "1",
"_version" : 2,
"_primary_term": 1,
"_seq_no": 5,
"result": "deleted"
}
查询删除
POST twitter/_delete_by_query
{
"query": {
"match": {
"message": "some message"
}
}
}
当有文档有版本冲突时，不放弃删除操作（记录冲突的文档，继续删除其他复合查询的文档）
POST twitter/_doc/_delete_by_query?conflicts=proceed
{
"query": {
"match_all": {}
}
}通过task api 来查看 查询删除任务
GET _tasks?detailed=true&actions=*/delete/byquery查询具体任务的状态
GET /_tasks/taskId:1取消任务
POST _tasks/task_id:1/_cancel5. 更新文档
指定文档id进行修改
PUT twitter/_doc/1
{
"id": 1,
"user" : "kimchy",
"post_date" : "2009-11-15T14:12:12",
"message" : "trying out Elasticsearch"
}
乐观锁并发更新控制
PUT twitter/_doc/1?version=1
{
"id": 1,
"user" : "kimchy",
"post_date" : "2009-11-15T14:12:12",
"message" : "trying out Elasticsearch"
}
返回结果
{
"_index": "twitter",
"_type": "_doc",
"_id": "1",
"_version": 3,
"result": "updated",
"_shards": {
"total": 3,
"successful": 1,
"failed": 0
},
"_seq_no": 2,
"_primary_term": 3
}
6.Scripted update 通过脚本来更新文档
6.1 准备一个文档
PUT uptest/_doc/1
{
"counter" : 1,
"tags" : ["red"]
}6.2、对文档1的counter + 4
POST uptest/_doc/1/_update
{
"script" : {
"source": "ctx._source.counter += params.count",
"lang": "painless",
"params" : {
"count" : 4
}
}
}
6.3、往数组中加入元素
POST uptest/_doc/1/_update
{
"script" : {
"source": "ctx._source.tags.add(params.tag)",
"lang": "painless",
"params" : {
"tag" : "blue"
}
}
}
脚本说明：painless是es内置的一种脚本语言，ctx执行上下文对象（通过它还可访问_index, _type, _id, _version, _routing and _now (the current timestamp) ），params是参数集合
说明：脚本更新要求索引的_source 字段是启用的。更新执行流程：
a、获取到原文档
b、通过_source字段的原始数据，执行脚本修改。
c、删除原索引文档
d、索引修改后的文档
它只是降低了一些网络往返，并减少了get和索引之间版本冲突的可能性。
6.4、添加一个字段
POST uptest/_doc/1/_update
{
"script" : "ctx._source.new_field = 'value_of_new_field'"
}6.5、移除一个字段
POST uptest/_doc/1/_update
{
"script" : "ctx._source.remove('new_field')"
}6.6、判断删除或不做什么
POST uptest/_doc/1/_update
{
"script" : {
"source": "if (ctx._source.tags.contains(params.tag)) { ctx.op = 'delete' } else { ctx.op = 'none' }",
"lang": "painless",
"params" : {
"tag" : "green"
}
}
}
6.7、合并传人的文档字段进行更新
POST uptest/_doc/1/_update
{
"doc" : {
"name" : "new_name"
}
}6.8、再次执行7，更新内容相同，不需做什么
{
"_index": "uptest",
"_type": "_doc",
"_id": "1",
"_version": 4,
"result": "noop",
"_shards": {
"total": 0,
"successful": 0,
"failed": 0
}
}
6.9、设置不做noop检测
POST uptest/_doc/1/_update
{
"doc" : {
"name" : "new_name"
},
"detect_noop": false
}
什么是noop检测？
即已经执行过的脚本不再执行
6.10、upsert 操作：如果要更新的文档存在，则执行脚本进行更新，如不存在，则把 upsert中的内容作为一个新文档写入。
POST uptest/_doc/1/_update
{
"script" : {
"source": "ctx._source.counter += params.count",
"lang": "painless",
"params" : {
"count" : 4
}
},
"upsert" : {
"counter" : 1
}
}
7. 通过条件查询来更新文档
满足查询条件的才更新
POST twitter/_update_by_query
{
"script": {
"source": "ctx._source.likes++",
"lang": "painless"
},
"query": {
"term": {
"user": "kimchy"
}
}
}
8. 批量操作
批量操作API /_bulk 让我们可以在一次调用中执行多个索引、删除操作。这可以大大提高索引数据的速度。批量操作内容体需按如下以新行分割的json结构格式给出：
语法：
action_and_meta_data
optional_source
action_and_meta_data
optional_source
....
action_and_meta_data
optional_source
说明：
action_and_meta_data: action可以是 index, create, delete and update ，meta_data 指: _index ,_type,_id 请求端点可以是: /_bulk, /{index}/_bulk, {index}/{type}/_bulk
示例：
POST _bulk
{ "index" : { "_index" : "test", "_type" : "_doc", "_id" : "1" } }
{ "field1" : "value1" }
{ "delete" : { "_index" : "test", "_type" : "_doc", "_id" : "2" } }
{ "create" : { "_index" : "test", "_type" : "_doc", "_id" : "3" } }
{ "field1" : "value3" }
{ "update" : {"_id" : "1", "_type" : "_doc", "_index" : "test"} }
{ "doc" : {"field2" : "value2"} }
8.1 curl + json 文件 批量索引多个文档
注意：accounts.json要放在执行curl命令的同等级目录下，后续学习的测试数据基本都使用这份银行的数据了
curl -H "Content-Type: application/json" -XPOST "localhost:9200/bank/_doc/_bulk?pretty&refresh" --data-binary "@accounts.json"
accounts.json：
复制代码
{"index":{"_id":"1"}}
{"account_number":1,"balance":39225,"firstname":"Amber","lastname":"Duke","age":32,"gender":"M","address":"880 Holmes Lane","employer":"Pyrami","email":"amberduke@pyrami.com","city":"Brogan","state":"IL"}
{"index":{"_id":"6"}}
{"account_number":6,"balance":5686,"firstname":"Hattie","lastname":"Bond","age":36,"gender":"M","address":"671 Bristol Street","employer":"Netagy","email":"hattiebond@netagy.com","city":"Dante","state":"TN"}
{"index":{"_id":"13"}}
{"account_number":13,"balance":32838,"firstname":"Nanette","lastname":"Bates","age":28,"gender":"F","address":"789 Madison Street","employer":"Quility","email":"nanettebates@quility.com","city":"Nogal","state":"VA"}
{"index":{"_id":"18"}}
{"account_number":18,"balance":4180,"firstname":"Dale","lastname":"Adams","age":33,"gender":"M","address":"467 Hutchinson Court","employer":"Boink","email":"daleadams@boink.com","city":"Orick","state":"MD"}
{"index":{"_id":"20"}}
{"account_number":20,"balance":16418,"firstname":"Elinor","lastname":"Ratliff","age":36,"gender":"M","address":"282 Kings Place","employer":"Scentric","email":"elinorratliff@scentric.com","city":"Ribera","state":"WA"}
{"index":{"_id":"25"}}
{"account_number":25,"balance":40540,"firstname":"Virginia","lastname":"Ayala","age":39,"gender":"F","address":"171 Putnam Avenue","employer":"Filodyne","email":"virginiaayala@filodyne.com","city":"Nicholson","state":"PA"}
{"index":{"_id":"32"}}
{"account_number":32,"balance":48086,"firstname":"Dillard","lastname":"Mcpherson","age":34,"gender":"F","address":"702 Quentin Street","employer":"Quailcom","email":"dillardmcpherson@quailcom.com","city":"Veguita","state":"IN"}
{"index":{"_id":"37"}}
{"account_number":37,"balance":18612,"firstname":"Mcgee","lastname":"Mooney","age":39,"gender":"M","address":"826 Fillmore Place","employer":"Reversus","email":"mcgeemooney@reversus.com","city":"Tooleville","state":"OK"}
{"index":{"_id":"44"}}
{"account_number":44,"balance":34487,"firstname":"Aurelia","lastname":"Harding","age":37,"gender":"M","address":"502 Baycliff Terrace","employer":"Orbalix","email":"aureliaharding@orbalix.com","city":"Yardville","state":"DE"}
{"index":{"_id":"49"}}
{"account_number":49,"balance":29104,"firstname":"Fulton","lastname":"Holt","age":23,"gender":"F","address":"451 Humboldt Street","employer":"Anocha","email":"fultonholt@anocha.com","city":"Sunriver","state":"RI"}
{"index":{"_id":"51"}}
{"account_number":51,"balance":14097,"firstname":"Burton","lastname":"Meyers","age":31,"gender":"F","address":"334 River Street","employer":"Bezal","email":"burtonmeyers@bezal.com","city":"Jacksonburg","state":"MO"}
{"index":{"_id":"56"}}
{"account_number":56,"balance":14992,"firstname":"Josie","lastname":"Nelson","age":32,"gender":"M","address":"857 Tabor Court","employer":"Emtrac","email":"josienelson@emtrac.com","city":"Sunnyside","state":"UT"}
{"index":{"_id":"63"}}
{"account_number":63,"balance":6077,"firstname":"Hughes","lastname":"Owens","age":30,"gender":"F","address":"510 Sedgwick Street","employer":"Valpreal","email":"hughesowens@valpreal.com","city":"Guilford","state":"KS"}
{"index":{"_id":"68"}}
{"account_number":68,"balance":44214,"firstname":"Hall","lastname":"Key","age":25,"gender":"F","address":"927 Bay Parkway","employer":"Eventex","email":"hallkey@eventex.com","city":"Shawmut","state":"CA"}
{"index":{"_id":"70"}}
{"account_number":70,"balance":38172,"firstname":"Deidre","lastname":"Thompson","age":33,"gender":"F","address":"685 School Lane","employer":"Netplode","email":"deidrethompson@netplode.com","city":"Chestnut","state":"GA"}
{"index":{"_id":"75"}}
{"account_number":75,"balance":40500,"firstname":"Sandoval","lastname":"Kramer","age":22,"gender":"F","address":"166 Irvington Place","employer":"Overfork","email":"sandovalkramer@overfork.com","city":"Limestone","state":"NH"}
{"index":{"_id":"82"}}
{"account_number":82,"balance":41412,"firstname":"Concetta","lastname":"Barnes","age":39,"gender":"F","address":"195 Bayview Place","employer":"Fitcore","email":"concettabarnes@fitcore.com","city":"Summerfield","state":"NC"}
{"index":{"_id":"87"}}
{"account_number":87,"balance":1133,"firstname":"Hewitt","lastname":"Kidd","age":22,"gender":"M","address":"446 Halleck Street","employer":"Isologics","email":"hewittkidd@isologics.com","city":"Coalmont","state":"ME"}
{"index":{"_id":"94"}}
{"account_number":94,"balance":41060,"firstname":"Brittany","lastname":"Cabrera","age":30,"gender":"F","address":"183 Kathleen Court","employer":"Mixers","email":"brittanycabrera@mixers.com","city":"Cornucopia","state":"AZ"}
{"index":{"_id":"99"}}
{"account_number":99,"balance":47159,"firstname":"Ratliff","lastname":"Heath","age":39,"gender":"F","address":"806 Rockwell Place","employer":"Zappix","email":"ratliffheath@zappix.com","city":"Shaft","state":"ND"}
{"index":{"_id":"102"}}
{"account_number":102,"balance":29712,"firstname":"Dena","lastname":"Olson","age":27,"gender":"F","address":"759 Newkirk Avenue","employer":"Hinway","email":"denaolson@hinway.com","city":"Choctaw","state":"NJ"}
{"index":{"_id":"107"}}
{"account_number":107,"balance":48844,"firstname":"Randi","lastname":"Rich","age":28,"gender":"M","address":"694 Jefferson Street","employer":"Netplax","email":"randirich@netplax.com","city":"Bellfountain","state":"SC"}
{"index":{"_id":"114"}}
{"account_number":114,"balance":43045,"firstname":"Josephine","lastname":"Joseph","age":31,"gender":"F","address":"451 Oriental Court","employer":"Turnabout","email":"josephinejoseph@turnabout.com","city":"Sedley","state":"AL"}
{"index":{"_id":"119"}}
{"account_number":119,"balance":49222,"firstname":"Laverne","lastname":"Johnson","age":28,"gender":"F","address":"302 Howard Place","employer":"Senmei","email":"lavernejohnson@senmei.com","city":"Herlong","state":"DC"}
{"index":{"_id":"121"}}
{"account_number":121,"balance":19594,"firstname":"Acevedo","lastname":"Dorsey","age":32,"gender":"M","address":"479 Nova Court","employer":"Netropic","email":"acevedodorsey@netropic.com","city":"Islandia","state":"CT"}
{"index":{"_id":"126"}}
{"account_number":126,"balance":3607,"firstname":"Effie","lastname":"Gates","age":39,"gender":"F","address":"620 National Drive","employer":"Digitalus","email":"effiegates@digitalus.com","city":"Blodgett","state":"MD"}
{"index":{"_id":"133"}}
{"account_number":133,"balance":26135,"firstname":"Deena","lastname":"Richmond","age":36,"gender":"F","address":"646 Underhill Avenue","employer":"Sunclipse","email":"deenarichmond@sunclipse.com","city":"Austinburg","state":"SC"}
{"index":{"_id":"138"}}
{"account_number":138,"balance":9006,"firstname":"Daniel","lastname":"Arnold","age":39,"gender":"F","address":"422 Malbone Street","employer":"Ecstasia","email":"danielarnold@ecstasia.com","city":"Gardiner","state":"MO"}
{"index":{"_id":"140"}}
{"account_number":140,"balance":26696,"firstname":"Cotton","lastname":"Christensen","age":32,"gender":"M","address":"878 Schermerhorn Street","employer":"Prowaste","email":"cottonchristensen@prowaste.com","city":"Mayfair","state":"LA"}
{"index":{"_id":"145"}}
{"account_number":145,"balance":47406,"firstname":"Rowena","lastname":"Wilkinson","age":32,"gender":"M","address":"891 Elton Street","employer":"Asimiline","email":"rowenawilkinson@asimiline.com","city":"Ripley","state":"NH"}
{"index":{"_id":"152"}}
{"account_number":152,"balance":8088,"firstname":"Wolfe","lastname":"Rocha","age":21,"gender":"M","address":"457 Guernsey Street","employer":"Hivedom","email":"wolferocha@hivedom.com","city":"Adelino","state":"MS"}
{"index":{"_id":"157"}}
{"account_number":157,"balance":39868,"firstname":"Claudia","lastname":"Terry","age":20,"gender":"F","address":"132 Gunnison Court","employer":"Lumbrex","email":"claudiaterry@lumbrex.com","city":"Castleton","state":"MD"}
{"index":{"_id":"164"}}
{"account_number":164,"balance":9101,"firstname":"Cummings","lastname":"Little","age":26,"gender":"F","address":"308 Schaefer Street","employer":"Comtrak","email":"cummingslittle@comtrak.com","city":"Chaparrito","state":"WI"}
{"index":{"_id":"169"}}
{"account_number":169,"balance":45953,"firstname":"Hollie","lastname":"Osborn","age":34,"gender":"M","address":"671 Seaview Court","employer":"Musaphics","email":"hollieosborn@musaphics.com","city":"Hanover","state":"GA"}
{"index":{"_id":"171"}}
{"account_number":171,"balance":7091,"firstname":"Nelda","lastname":"Hopper","age":39,"gender":"M","address":"742 Prospect Place","employer":"Equicom","email":"neldahopper@equicom.com","city":"Finderne","state":"SC"}
{"index":{"_id":"176"}}
{"account_number":176,"balance":18607,"firstname":"Kemp","lastname":"Walters","age":28,"gender":"F","address":"906 Howard Avenue","employer":"Eyewax","email":"kempwalters@eyewax.com","city":"Why","state":"KY"}
{"index":{"_id":"183"}}
{"account_number":183,"balance":14223,"firstname":"Hudson","lastname":"English","age":26,"gender":"F","address":"823 Herkimer Place","employer":"Xinware","email":"hudsonenglish@xinware.com","city":"Robbins","state":"ND"}
{"index":{"_id":"188"}}
{"account_number":188,"balance":41504,"firstname":"Tia","lastname":"Miranda","age":24,"gender":"F","address":"583 Ainslie Street","employer":"Jasper","email":"tiamiranda@jasper.com","city":"Summerset","state":"UT"}
{"index":{"_id":"190"}}
{"account_number":190,"balance":3150,"firstname":"Blake","lastname":"Davidson","age":30,"gender":"F","address":"636 Diamond Street","employer":"Quantasis","email":"blakedavidson@quantasis.com","city":"Crumpler","state":"KY"}
{"index":{"_id":"195"}}
{"account_number":195,"balance":5025,"firstname":"Kaye","lastname":"Gibson","age":31,"gender":"M","address":"955 Hopkins Street","employer":"Zork","email":"kayegibson@zork.com","city":"Ola","state":"WY"}
{"index":{"_id":"203"}}
{"account_number":203,"balance":21890,"firstname":"Eve","lastname":"Wyatt","age":33,"gender":"M","address":"435 Furman Street","employer":"Assitia","email":"evewyatt@assitia.com","city":"Jamestown","state":"MN"}
{"index":{"_id":"208"}}
{"account_number":208,"balance":40760,"firstname":"Garcia","lastname":"Hess","age":26,"gender":"F","address":"810 Nostrand Avenue","employer":"Quiltigen","email":"garciahess@quiltigen.com","city":"Brooktrails","state":"GA"}
{"index":{"_id":"210"}}
{"account_number":210,"balance":33946,"firstname":"Cherry","lastname":"Carey","age":24,"gender":"M","address":"539 Tiffany Place","employer":"Martgo","email":"cherrycarey@martgo.com","city":"Fairacres","state":"AK"}
{"index":{"_id":"215"}}
{"account_number":215,"balance":37427,"firstname":"Copeland","lastname":"Solomon","age":20,"gender":"M","address":"741 McDonald Avenue","employer":"Recognia","email":"copelandsolomon@recognia.com","city":"Edmund","state":"ME"}
{"index":{"_id":"222"}}
{"account_number":222,"balance":14764,"firstname":"Rachelle","lastname":"Rice","age":36,"gender":"M","address":"333 Narrows Avenue","employer":"Enaut","email":"rachellerice@enaut.com","city":"Wright","state":"AZ"}
{"index":{"_id":"227"}}
{"account_number":227,"balance":19780,"firstname":"Coleman","lastname":"Berg","age":22,"gender":"M","address":"776 Little Street","employer":"Exoteric","email":"colemanberg@exoteric.com","city":"Eagleville","state":"WV"}
{"index":{"_id":"234"}}
{"account_number":234,"balance":44207,"firstname":"Betty","lastname":"Hall","age":37,"gender":"F","address":"709 Garfield Place","employer":"Miraclis","email":"bettyhall@miraclis.com","city":"Bendon","state":"NY"}
{"index":{"_id":"239"}}
{"account_number":239,"balance":25719,"firstname":"Chang","lastname":"Boyer","age":36,"gender":"M","address":"895 Brigham Street","employer":"Qaboos","email":"changboyer@qaboos.com","city":"Belgreen","state":"NH"}
{"index":{"_id":"241"}}
{"account_number":241,"balance":25379,"firstname":"Schroeder","lastname":"Harrington","age":26,"gender":"M","address":"610 Tapscott Avenue","employer":"Otherway","email":"schroederharrington@otherway.com","city":"Ebro","state":"TX"}
{"index":{"_id":"246"}}
{"account_number":246,"balance":28405,"firstname":"Katheryn","lastname":"Foster","age":21,"gender":"F","address":"259 Kane Street","employer":"Quantalia","email":"katherynfoster@quantalia.com","city":"Bath","state":"TX"}
{"index":{"_id":"253"}}
{"account_number":253,"balance":20240,"firstname":"Melissa","lastname":"Gould","age":31,"gender":"M","address":"440 Fuller Place","employer":"Buzzopia","email":"melissagould@buzzopia.com","city":"Lumberton","state":"MD"}
{"index":{"_id":"258"}}
{"account_number":258,"balance":5712,"firstname":"Lindsey","lastname":"Hawkins","age":37,"gender":"M","address":"706 Frost Street","employer":"Enormo","email":"lindseyhawkins@enormo.com","city":"Gardners","state":"AK"}
{"index":{"_id":"260"}}
{"account_number":260,"balance":2726,"firstname":"Kari","lastname":"Skinner","age":30,"gender":"F","address":"735 Losee Terrace","employer":"Singavera","email":"kariskinner@singavera.com","city":"Rushford","state":"WV"}
{"index":{"_id":"265"}}
{"account_number":265,"balance":46910,"firstname":"Marion","lastname":"Schneider","age":26,"gender":"F","address":"574 Everett Avenue","employer":"Evidends","email":"marionschneider@evidends.com","city":"Maplewood","state":"WY"}
{"index":{"_id":"272"}}
{"account_number":272,"balance":19253,"firstname":"Lilly","lastname":"Morgan","age":25,"gender":"F","address":"689 Fleet Street","employer":"Biolive","email":"lillymorgan@biolive.com","city":"Sunbury","state":"OH"}
{"index":{"_id":"277"}}
{"account_number":277,"balance":29564,"firstname":"Romero","lastname":"Lott","age":31,"gender":"M","address":"456 Danforth Street","employer":"Plasto","email":"romerolott@plasto.com","city":"Vincent","state":"VT"}
{"index":{"_id":"284"}}
{"account_number":284,"balance":22806,"firstname":"Randolph","lastname":"Banks","age":29,"gender":"M","address":"875 Hamilton Avenue","employer":"Caxt","email":"randolphbanks@caxt.com","city":"Crawfordsville","state":"WA"}
{"index":{"_id":"289"}}
{"account_number":289,"balance":7798,"firstname":"Blair","lastname":"Church","age":29,"gender":"M","address":"370 Sutton Street","employer":"Cubix","email":"blairchurch@cubix.com","city":"Nile","state":"NH"}
{"index":{"_id":"291"}}
{"account_number":291,"balance":19955,"firstname":"Lynn","lastname":"Pollard","age":40,"gender":"F","address":"685 Pierrepont Street","employer":"Slambda","email":"lynnpollard@slambda.com","city":"Mappsville","state":"ID"}
{"index":{"_id":"296"}}
{"account_number":296,"balance":24606,"firstname":"Rosa","lastname":"Oliver","age":34,"gender":"M","address":"168 Woodbine Street","employer":"Idetica","email":"rosaoliver@idetica.com","city":"Robinson","state":"WY"}
{"index":{"_id":"304"}}
{"account_number":304,"balance":28647,"firstname":"Palmer","lastname":"Clark","age":35,"gender":"M","address":"866 Boulevard Court","employer":"Maximind","email":"palmerclark@maximind.com","city":"Avalon","state":"NH"}
{"index":{"_id":"309"}}
{"account_number":309,"balance":3830,"firstname":"Rosemarie","lastname":"Nieves","age":30,"gender":"M","address":"206 Alice Court","employer":"Zounds","email":"rosemarienieves@zounds.com","city":"Ferney","state":"AR"}
{"index":{"_id":"311"}}
{"account_number":311,"balance":13388,"firstname":"Vinson","lastname":"Ballard","age":23,"gender":"F","address":"960 Glendale Court","employer":"Gynk","email":"vinsonballard@gynk.com","city":"Fairforest","state":"WY"}
{"index":{"_id":"316"}}
{"account_number":316,"balance":8214,"firstname":"Anita","lastname":"Ewing","age":32,"gender":"M","address":"396 Lombardy Street","employer":"Panzent","email":"anitaewing@panzent.com","city":"Neahkahnie","state":"WY"}
{"index":{"_id":"323"}}
{"account_number":323,"balance":42230,"firstname":"Chelsea","lastname":"Gamble","age":34,"gender":"F","address":"356 Dare Court","employer":"Isosphere","email":"chelseagamble@isosphere.com","city":"Dundee","state":"MD"}
{"index":{"_id":"328"}}
{"account_number":328,"balance":12523,"firstname":"Good","lastname":"Campbell","age":27,"gender":"F","address":"438 Hicks Street","employer":"Gracker","email":"goodcampbell@gracker.com","city":"Marion","state":"CA"}
{"index":{"_id":"330"}}
{"account_number":330,"balance":41620,"firstname":"Yvette","lastname":"Browning","age":34,"gender":"F","address":"431 Beekman Place","employer":"Marketoid","email":"yvettebrowning@marketoid.com","city":"Talpa","state":"CO"}
{"index":{"_id":"335"}}
{"account_number":335,"balance":35433,"firstname":"Vera","lastname":"Hansen","age":24,"gender":"M","address":"252 Bushwick Avenue","employer":"Zanilla","email":"verahansen@zanilla.com","city":"Manila","state":"TN"}
{"index":{"_id":"342"}}
{"account_number":342,"balance":33670,"firstname":"Vivian","lastname":"Wells","age":36,"gender":"M","address":"570 Cobek Court","employer":"Nutralab","email":"vivianwells@nutralab.com","city":"Fontanelle","state":"OK"}
{"index":{"_id":"347"}}
{"account_number":347,"balance":36038,"firstname":"Gould","lastname":"Carson","age":24,"gender":"F","address":"784 Pulaski Street","employer":"Mobildata","email":"gouldcarson@mobildata.com","city":"Goochland","state":"MI"}
{"index":{"_id":"354"}}
{"account_number":354,"balance":21294,"firstname":"Kidd","lastname":"Mclean","age":22,"gender":"M","address":"691 Saratoga Avenue","employer":"Ronbert","email":"kiddmclean@ronbert.com","city":"Tioga","state":"ME"}
{"index":{"_id":"359"}}
{"account_number":359,"balance":29927,"firstname":"Vanessa","lastname":"Harvey","age":28,"gender":"F","address":"679 Rutledge Street","employer":"Zentime","email":"vanessaharvey@zentime.com","city":"Williston","state":"IL"}
{"index":{"_id":"361"}}
{"account_number":361,"balance":23659,"firstname":"Noreen","lastname":"Shelton","age":36,"gender":"M","address":"702 Tillary Street","employer":"Medmex","email":"noreenshelton@medmex.com","city":"Derwood","state":"NH"}
{"index":{"_id":"366"}}
{"account_number":366,"balance":42368,"firstname":"Lydia","lastname":"Cooke","age":31,"gender":"M","address":"470 Coleman Street","employer":"Comstar","email":"lydiacooke@comstar.com","city":"Datil","state":"TN"}
{"index":{"_id":"373"}}
{"account_number":373,"balance":9671,"firstname":"Simpson","lastname":"Carpenter","age":21,"gender":"M","address":"837 Horace Court","employer":"Snips","email":"simpsoncarpenter@snips.com","city":"Tolu","state":"MA"}
{"index":{"_id":"378"}}
{"account_number":378,"balance":27100,"firstname":"Watson","lastname":"Simpson","age":36,"gender":"F","address":"644 Thomas Street","employer":"Wrapture","email":"watsonsimpson@wrapture.com","city":"Keller","state":"TX"}
{"index":{"_id":"380"}}
{"account_number":380,"balance":35628,"firstname":"Fernandez","lastname":"Reid","age":33,"gender":"F","address":"154 Melba Court","employer":"Cosmosis","email":"fernandezreid@cosmosis.com","city":"Boyd","state":"NE"}
{"index":{"_id":"385"}}
{"account_number":385,"balance":11022,"firstname":"Rosalinda","lastname":"Valencia","age":22,"gender":"M","address":"933 Lloyd Street","employer":"Zoarere","email":"rosalindavalencia@zoarere.com","city":"Waverly","state":"GA"}
{"index":{"_id":"392"}}
{"account_number":392,"balance":31613,"firstname":"Dotson","lastname":"Dean","age":35,"gender":"M","address":"136 Ford Street","employer":"Petigems","email":"dotsondean@petigems.com","city":"Chical","state":"SD"}
{"index":{"_id":"397"}}
{"account_number":397,"balance":37418,"firstname":"Leonard","lastname":"Gray","age":36,"gender":"F","address":"840 Morgan Avenue","employer":"Recritube","email":"leonardgray@recritube.com","city":"Edenburg","state":"AL"}
{"index":{"_id":"400"}}
{"account_number":400,"balance":20685,"firstname":"Kane","lastname":"King","age":21,"gender":"F","address":"405 Cornelia Street","employer":"Tri@Tribalog","email":"kaneking@tri@tribalog.com","city":"Gulf","state":"VT"}
{"index":{"_id":"405"}}
{"account_number":405,"balance":5679,"firstname":"Strickland","lastname":"Fuller","age":26,"gender":"M","address":"990 Concord Street","employer":"Digique","email":"stricklandfuller@digique.com","city":"Southmont","state":"NV"}
{"index":{"_id":"412"}}
{"account_number":412,"balance":27436,"firstname":"Ilene","lastname":"Abbott","age":26,"gender":"M","address":"846 Vine Street","employer":"Typhonica","email":"ileneabbott@typhonica.com","city":"Cedarville","state":"VT"}
{"index":{"_id":"417"}}
{"account_number":417,"balance":1788,"firstname":"Wheeler","lastname":"Ayers","age":35,"gender":"F","address":"677 Hope Street","employer":"Fortean","email":"wheelerayers@fortean.com","city":"Ironton","state":"PA"}
{"index":{"_id":"424"}}
{"account_number":424,"balance":36818,"firstname":"Tracie","lastname":"Gregory","age":34,"gender":"M","address":"112 Hunterfly Place","employer":"Comstruct","email":"traciegregory@comstruct.com","city":"Onton","state":"TN"}
{"index":{"_id":"429"}}
{"account_number":429,"balance":46970,"firstname":"Cantu","lastname":"Lindsey","age":31,"gender":"M","address":"404 Willoughby Avenue","employer":"Inquala","email":"cantulindsey@inquala.com","city":"Cowiche","state":"IA"}
{"index":{"_id":"431"}}
{"account_number":431,"balance":13136,"firstname":"Laurie","lastname":"Shaw","age":26,"gender":"F","address":"263 Aviation Road","employer":"Zillanet","email":"laurieshaw@zillanet.com","city":"Harmon","state":"WV"}
{"index":{"_id":"436"}}
{"account_number":436,"balance":27585,"firstname":"Alexander","lastname":"Sargent","age":23,"gender":"M","address":"363 Albemarle Road","employer":"Fangold","email":"alexandersargent@fangold.com","city":"Calpine","state":"OR"}
{"index":{"_id":"443"}}
{"account_number":443,"balance":7588,"firstname":"Huff","lastname":"Thomas","age":23,"gender":"M","address":"538 Erskine Loop","employer":"Accufarm","email":"huffthomas@accufarm.com","city":"Corinne","state":"AL"}
{"index":{"_id":"448"}}
{"account_number":448,"balance":22776,"firstname":"Adriana","lastname":"Mcfadden","age":35,"gender":"F","address":"984 Woodside Avenue","employer":"Telequiet","email":"adrianamcfadden@telequiet.com","city":"Darrtown","state":"WI"}
{"index":{"_id":"450"}}
{"account_number":450,"balance":2643,"firstname":"Bradford","lastname":"Nielsen","age":25,"gender":"M","address":"487 Keen Court","employer":"Exovent","email":"bradfordnielsen@exovent.com","city":"Hamilton","state":"DE"}
{"index":{"_id":"455"}}
{"account_number":455,"balance":39556,"firstname":"Lynn","lastname":"Tran","age":36,"gender":"M","address":"741 Richmond Street","employer":"Optyk","email":"lynntran@optyk.com","city":"Clinton","state":"WV"}
{"index":{"_id":"462"}}
{"account_number":462,"balance":10871,"firstname":"Calderon","lastname":"Day","age":27,"gender":"M","address":"810 Milford Street","employer":"Cofine","email":"calderonday@cofine.com","city":"Kula","state":"OK"}
{"index":{"_id":"467"}}
{"account_number":467,"balance":6312,"firstname":"Angelica","lastname":"May","age":32,"gender":"F","address":"384 Karweg Place","employer":"Keeg","email":"angelicamay@keeg.com","city":"Tetherow","state":"IA"}
{"index":{"_id":"474"}}
{"account_number":474,"balance":35896,"firstname":"Obrien","lastname":"Walton","age":40,"gender":"F","address":"192 Ide Court","employer":"Suremax","email":"obrienwalton@suremax.com","city":"Crucible","state":"UT"}
{"index":{"_id":"479"}}
{"account_number":479,"balance":31865,"firstname":"Cameron","lastname":"Ross","age":40,"gender":"M","address":"904 Bouck Court","employer":"Telpod","email":"cameronross@telpod.com","city":"Nord","state":"MO"}
{"index":{"_id":"481"}}
{"account_number":481,"balance":20024,"firstname":"Lina","lastname":"Stanley","age":33,"gender":"M","address":"361 Hanover Place","employer":"Strozen","email":"linastanley@strozen.com","city":"Wyoming","state":"NC"}
{"index":{"_id":"486"}}
{"account_number":486,"balance":35902,"firstname":"Dixie","lastname":"Fuentes","age":22,"gender":"F","address":"991 Applegate Court","employer":"Portico","email":"dixiefuentes@portico.com","city":"Salix","state":"VA"}
{"index":{"_id":"493"}}
{"account_number":493,"balance":5871,"firstname":"Campbell","lastname":"Best","age":24,"gender":"M","address":"297 Friel Place","employer":"Fanfare","email":"campbellbest@fanfare.com","city":"Kidder","state":"GA"}
{"index":{"_id":"498"}}
{"account_number":498,"balance":10516,"firstname":"Stella","lastname":"Hinton","age":39,"gender":"F","address":"649 Columbia Place","employer":"Flyboyz","email":"stellahinton@flyboyz.com","city":"Crenshaw","state":"SC"}9. reindex 重索引
Reindex API /_reindex 让我们可以将一个索引中的数据重索引到另一个索引中（拷贝），要求源索引的_source 是开启的。目标索引的setting 、mapping 信息与源索引无关。
什么时候需要重索引？
即当需要做数据的拷贝的时候
POST _reindex
{
"source": {
"index": "twitter"
},
"dest": {
"index": "new_twitter"
}
}
重索引要考虑的一个问题：目标索引中存在源索引中的数据，这些数据的version如何处理。
1、如果没有指定version_type 或指定为 internal，则会是采用目标索引中的版本，重索引过程中，执行的就是新增、更新操作。
POST _reindex
{
"source": {
"index": "twitter"
},
"dest": {
"index": "new_twitter",
"version_type": "internal"
}
}
2、如果想使用源索引中的版本来进行版本控制更新，则设置 version_type 为extenal。重索引操作将写入不存在的，更新旧版本的数据。
POST _reindex
{
"source": {
"index": "twitter"
},
"dest": {
"index": "new_twitter",
"version_type": "external"
}
}
如果你只想从源索引中复制目标索引中不存在的文档数据，可以指定 op_type 为 create 。此时存在的文档将触发 版本冲突（会导致放弃操作），可设置“conflicts”: “proceed“，跳过继续
POST _reindex
{
"conflicts": "proceed",
"source": {
"index": "twitter"
},
"dest": {
"index": "new_twitter",
"op_type": "create"
}
}
你也可以只索引源索引的一部分数据，通过 type 或 查询来指定你需要的数据
POST _reindex
{
"source": {
"index": "twitter",
"type": "_doc",
"query": {
"term": {
"user": "kimchy"
}
}
},
"dest": {
"index": "new_twitter"
}
}
可以从多个源获取数据
POST _reindex
{
"source": {
"index": ["twitter", "blog"],
"type": ["_doc", "post"]
},
"dest": {
"index": "all_together"
}
}
可以限定文档数量
POST _reindex
{
"size": 10000,
"source": {
"index": "twitter",
"sort": { "date": "desc" }
},
"dest": {
"index": "new_twitter"
}
}
可以选择复制源文档的哪些字段
POST _reindex
{
"source": {
"index": "twitter",
"_source": ["user", "_doc"]
},
"dest": {
"index": "new_twitter"
}
}
可以用script来改变文档
POST _reindex
{
"source": {
"index": "twitter"
},
"dest": {
"index": "new_twitter",
"version_type": "external"
},
"script": {
"source": "if (ctx._source.foo == 'bar') {ctx._version++; ctx._source.remove('foo')}",
"lang": "painless"
}
}
可以指定路由值把文档放到哪个分片上
POST _reindex
{
"source": {
"index": "source",
"query": {
"match": {
"company": "cat"
}
}
},
"dest": {
"index": "dest",
"routing": "=cat"
}
}
从远程源复制
POST _reindex
{
"source": {
"remote": {
"host": "http://otherhost:9200",
"username": "user",
"password": "pass"
},
"index": "source",
"query": {
"match": {
"test": "data"
}
}
},
"dest": {
"index": "dest"
}
}
通过_task 来查询执行状态
GET _tasks?detailed=true&actions=*reindex10. refresh
对于索引、更新、删除操作如果想操作完后立马重刷新可见，可带上refresh参数
PUT /test/_doc/1?refresh
{"test": "test"}
PUT /test/_doc/2?refresh=true
{"test": "test"}refresh 可选值说明
未给值或=true，则立马会重刷新读索引。
=false ，相当于没带refresh 参数，遵循内部的定时刷新。
=wait_for ，登记等待刷新，当登记的请求数达到index.max_refresh_listeners 参数设定的值时(defaults to 1000)，将触发重刷新。
三、路由详解
1. 集群组成
第一个节点启动
说明：首先启动的一定是主节点，主节点存储的是集群的元数据信息
Node2启动
说明：
Node2节点启动之前会配置集群的名称Cluster-name：ess，然后配置可以作为主节点的ip地址信息discovery.zen.ping.unicast.hosts: [“10.0.1.11",“10.0.1.12"]，配置自己的ip地址networ.host: 10.0.1.12；
Node2启动的过程中会去找到主节点Node1告诉Node1我要加入到集群里面了，主节点Node1接收到请求以后看Node2是否满足加入集群的条件，如果满足就把node2的ip地址加入的元信息里面，然后广播给集群中的其他节点有
新节点加入，并把最新的元信息发送给其他的节点去更新
Node3..NodeN加入
说明：集群中的所有节点的元信息都是和主节点一致的，因为一旦有新的节点加入进来，主节点会通知其他的节点同步元信息
2. 在集群中创建索引的流程
3. 有索引的集群
4. 集群有节点出现故障，如主节点挂了，会重新选择主节点
5. 在集群中索引文档
索引文档的步骤：
1、node2计算文档的路由值得到文档存放的分片（假定路由选定的是分片0）。
2、将文档转发给分片0(P0)的主分片节点 node1。
3、node1索引文档，同步给副本（R0）节点node3索引文档。
4、node1向node2反馈结果
5、node2作出响应
6. 文档是如何路由的
文档该存到哪个分片上？
决定文档存放到哪个分片上就是文档路由。ES中通过下面的计算得到每个文档的存放分片：
shard = hash(routing) % number_of_primary_shards参数说明：
routing 是用来进行hash计算的路由值，默认是使用文档id值。我们可以在索引文档时通过routing参数指定别的路由值
number_of_primary_shards：创建索引时指定的主分片数
POST twitter/_doc?routing=kimchy
{
"user" : "kimchy",
"post_date" : "2009-11-15T14:12:12",
"message" : "trying out Elasticsearch"
}在索引、删除、更新、查询中都可以使用routing参数（可多值）指定操作的分片。
创建索引时强制要求给定路由值：
PUT my_index2
{
"mappings": {
"_doc": {
"_routing": {
"required": true
}
}
}
}
7. 在集群中进行搜索
搜索的步骤：如要搜索 索引 s0
1、node2解析查询。
2、node2将查询发给索引s0的分片/副本（R1,R2,R0）节点
3、各节点执行查询，将结果发给Node2
4、Node2合并结果，作出响应。
8. Master节点的工作是什么？
1. 存储集群的元信息，如集群名称、集群中的节点
2. 转发创建索引和索引文档的请求
3. 和其他的节点进行通信，告诉其他节点有新的节点加入等
转自：推荐博客地址