# /
# 集群cluster、节点node、分片shards
1、集群由节点组成。
2、集群的垂直划分，集群由一个或多个分片集合组成。
3、集群的水平扩展，即分片集合的水平扩展，分片集合由一个或多个节点组成。
#elasticsearch.yml
# ---------------------------------- Cluster -----------------------------------
# Use a descriptive name for your cluster:
#cluster.name: my-application
# ------------------------------------ Node ------------------------------------
# Use a descriptive name for the node:
#node.name: node-1
# Add custom attributes to the node:
#node.attr.rack: r1
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#GET _cluster/health
{
"cluster_name" : "elasticsearch",
"status" : "green",
"timed_out" : false,
"number_of_nodes" : 1,
"number_of_data_nodes" : 1,
"active_primary_shards" : 9,
"active_shards" : 9,
"relocating_shards" : 0,//迁移中的分片数
"initializing_shards" : 0,//初始化中的分片数
"unassigned_shards" : 0,//未分配的分片数
"delayed_unassigned_shards" : 0,
"number_of_pending_tasks" : 0,
"number_of_in_flight_fetch" : 0,
"task_max_waiting_in_queue_millis" : 0,
"active_shards_percent_as_number" : 100.0
}
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#GET kibana_sample_data_ecommerce/_search_shards
{
"nodes" : {
"Dw_g-_NuTAa4hh_BBwpZ1g" : {
"name" : "WIN-HBRBLPJVAQU",
"ephemeral_id" : "ReHwgfNiSCO7RCcPsGFSfg",
"transport_address" : "127.0.0.1:9300",
"attributes" : {
"ml.machine_memory" : "68625584128",
"xpack.installed" : "true",
"transform.node" : "true",
"ml.max_open_jobs" : "20"
}
}
},
"indices" : {
"kibana_sample_data_ecommerce" : { }
},
"shards" : [
[
{
"state" : "STARTED",
"primary" : true,
"node" : "Dw_g-_NuTAa4hh_BBwpZ1g",
"relocating_node" : null,
"shard" : 0,
"index" : "kibana_sample_data_ecommerce",
"allocation_id" : {
"id" : "boaDrqhkRJeYBVL2sAzKSg"
}
}
]
]
}
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# 索引、文档、Mapping、字段
#show create table kibana_sample_data_ecommerce;
SQL 错误: line 1:6: no viable alternative at input 'show create'
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-- kibana_sample_data_ecommerce definition
-- Drop table
-- DROP TABLE kibana_sample_data_ecommerce;
CREATE TABLE kibana_sample_data_ecommerce (
category TEXT,
"category.keyword" KEYWORD(32766),
currency KEYWORD(32766),
customer_birth_date DATETIME,
customer_first_name TEXT,
"customer_first_name.keyword" KEYWORD(32766),
customer_full_name TEXT,
"customer_full_name.keyword" KEYWORD(32766),
customer_gender KEYWORD(32766),
customer_id KEYWORD(32766),
customer_last_name TEXT,
"customer_last_name.keyword" KEYWORD(32766),
customer_phone KEYWORD(32766),
day_of_week KEYWORD(32766),
day_of_week_i INTEGER,
email KEYWORD(32766),
"event.dataset" KEYWORD(32766),
"geoip.city_name" KEYWORD(32766),
"geoip.continent_name" KEYWORD(32766),
"geoip.country_iso_code" KEYWORD(32766),
"geoip.location" GEO_POINT,
"geoip.region_name" KEYWORD(32766),
manufacturer TEXT,
"manufacturer.keyword" KEYWORD(32766),
order_date DATETIME,
order_id KEYWORD(32766),
"products._id" TEXT,
"products._id.keyword" KEYWORD(32766),
"products.base_price" HALF_FLOAT,
"products.base_unit_price" HALF_FLOAT,
"products.category" TEXT,
"products.category.keyword" KEYWORD(32766),
"products.created_on" DATETIME,
"products.discount_amount" HALF_FLOAT,
"products.discount_percentage" HALF_FLOAT,
"products.manufacturer" TEXT,
"products.manufacturer.keyword" KEYWORD(32766),
"products.min_price" HALF_FLOAT,
"products.price" HALF_FLOAT,
"products.product_id" LONG,
"products.product_name" TEXT,
"products.product_name.keyword" KEYWORD(32766),
"products.quantity" INTEGER,
"products.sku" KEYWORD(32766),
"products.tax_amount" HALF_FLOAT,
"products.taxful_price" HALF_FLOAT,
"products.taxless_price" HALF_FLOAT,
"products.unit_discount_amount" HALF_FLOAT,
sku KEYWORD(32766),
taxful_total_price HALF_FLOAT,
taxless_total_price HALF_FLOAT,
total_quantity INTEGER,
total_unique_products INTEGER,
"type" KEYWORD(32766),
"user" KEYWORD(32766)
);
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#describe kibana_sample_data_ecommerce;
#show columns from kibana_sample_data_ecommerce;
column |type |mapping |
-----------------------------+---------+----------+
category |VARCHAR |text |
category.keyword |VARCHAR |keyword |
currency |VARCHAR |keyword |
customer_birth_date |TIMESTAMP|datetime |
customer_first_name |VARCHAR |text |
customer_first_name.keyword |VARCHAR |keyword |
customer_full_name |VARCHAR |text |
customer_full_name.keyword |VARCHAR |keyword |
customer_gender |VARCHAR |keyword |
customer_id |VARCHAR |keyword |
customer_last_name |VARCHAR |text |
customer_last_name.keyword |VARCHAR |keyword |
customer_phone |VARCHAR |keyword |
day_of_week |VARCHAR |keyword |
day_of_week_i |INTEGER |integer |
email |VARCHAR |keyword |
event |STRUCT |object |
event.dataset |VARCHAR |keyword |
geoip |STRUCT |object |
geoip.city_name |VARCHAR |keyword |
geoip.continent_name |VARCHAR |keyword |
geoip.country_iso_code |VARCHAR |keyword |
geoip.location |GEOMETRY |geo_point |
geoip.region_name |VARCHAR |keyword |
manufacturer |VARCHAR |text |
manufacturer.keyword |VARCHAR |keyword |
order_date |TIMESTAMP|datetime |
order_id |VARCHAR |keyword |
products |STRUCT |object |
products._id |VARCHAR |text |
products._id.keyword |VARCHAR |keyword |
products.base_price |FLOAT |half_float|
products.base_unit_price |FLOAT |half_float|
products.category |VARCHAR |text |
products.category.keyword |VARCHAR |keyword |
products.created_on |TIMESTAMP|datetime |
products.discount_amount |FLOAT |half_float|
products.discount_percentage |FLOAT |half_float|
products.manufacturer |VARCHAR |text |
products.manufacturer.keyword|VARCHAR |keyword |
products.min_price |FLOAT |half_float|
products.price |FLOAT |half_float|
products.product_id |BIGINT |long |
products.product_name |VARCHAR |text |
products.product_name.keyword|VARCHAR |keyword |
products.quantity |INTEGER |integer |
products.sku |VARCHAR |keyword |
products.tax_amount |FLOAT |half_float|
products.taxful_price |FLOAT |half_float|
products.taxless_price |FLOAT |half_float|
products.unit_discount_amount|FLOAT |half_float|
sku |VARCHAR |keyword |
taxful_total_price |FLOAT |half_float|
taxless_total_price |FLOAT |half_float|
total_quantity |INTEGER |integer |
total_unique_products |INTEGER |integer |
type |VARCHAR |keyword |
user |VARCHAR |keyword |
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#GET kibana_sample_data_ecommerce/_mapping
{
"kibana_sample_data_ecommerce" : {
"mappings" : {
"properties" : {
"category" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword"
}
}
},
"currency" : {
"type" : "keyword"
},
"customer_birth_date" : {
"type" : "date"
},
"customer_first_name" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"customer_full_name" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"customer_gender" : {
"type" : "keyword"
},
"customer_id" : {
"type" : "keyword"
},
"customer_last_name" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"customer_phone" : {
"type" : "keyword"
},
"day_of_week" : {
"type" : "keyword"
},
"day_of_week_i" : {
"type" : "integer"
},
"email" : {
"type" : "keyword"
},
"event" : {
"properties" : {
"dataset" : {
"type" : "keyword"
}
}
},
"geoip" : {
"properties" : {
"city_name" : {
"type" : "keyword"
},
"continent_name" : {
"type" : "keyword"
},
"country_iso_code" : {
"type" : "keyword"
},
"location" : {
"type" : "geo_point"
},
"region_name" : {
"type" : "keyword"
}
}
},
"manufacturer" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword"
}
}
},
"order_date" : {
"type" : "date"
},
"order_id" : {
"type" : "keyword"
},
"products" : {
"properties" : {
"_id" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"base_price" : {
"type" : "half_float"
},
"base_unit_price" : {
"type" : "half_float"
},
"category" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword"
}
}
},
"created_on" : {
"type" : "date"
},
"discount_amount" : {
"type" : "half_float"
},
"discount_percentage" : {
"type" : "half_float"
},
"manufacturer" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword"
}
}
},
"min_price" : {
"type" : "half_float"
},
"price" : {
"type" : "half_float"
},
"product_id" : {
"type" : "long"
},
"product_name" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword"
}
},
"analyzer" : "english"
},
"quantity" : {
"type" : "integer"
},
"sku" : {
"type" : "keyword"
},
"tax_amount" : {
"type" : "half_float"
},
"taxful_price" : {
"type" : "half_float"
},
"taxless_price" : {
"type" : "half_float"
},
"unit_discount_amount" : {
"type" : "half_float"
}
}
},
"sku" : {
"type" : "keyword"
},
"taxful_total_price" : {
"type" : "half_float"
},
"taxless_total_price" : {
"type" : "half_float"
},
"total_quantity" : {
"type" : "integer"
},
"total_unique_products" : {
"type" : "integer"
},
"type" : {
"type" : "keyword"
},
"user" : {
"type" : "keyword"
}
}
}
}
}
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#注意：index不仅仅包含mapping
#GET kibana_sample_data_ecommerce
{
"kibana_sample_data_ecommerce" : {
"aliases" : { },
"mappings" : {
"properties" : {
"category" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword"
}
}
},
"currency" : {
"type" : "keyword"
},
"customer_birth_date" : {
"type" : "date"
},
"customer_first_name" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"customer_full_name" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"customer_gender" : {
"type" : "keyword"
},
"customer_id" : {
"type" : "keyword"
},
"customer_last_name" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"customer_phone" : {
"type" : "keyword"
},
"day_of_week" : {
"type" : "keyword"
},
"day_of_week_i" : {
"type" : "integer"
},
"email" : {
"type" : "keyword"
},
"event" : {
"properties" : {
"dataset" : {
"type" : "keyword"
}
}
},
"geoip" : {
"properties" : {
"city_name" : {
"type" : "keyword"
},
"continent_name" : {
"type" : "keyword"
},
"country_iso_code" : {
"type" : "keyword"
},
"location" : {
"type" : "geo_point"
},
"region_name" : {
"type" : "keyword"
}
}
},
"manufacturer" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword"
}
}
},
"order_date" : {
"type" : "date"
},
"order_id" : {
"type" : "keyword"
},
"products" : {
"properties" : {
"_id" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"base_price" : {
"type" : "half_float"
},
"base_unit_price" : {
"type" : "half_float"
},
"category" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword"
}
}
},
"created_on" : {
"type" : "date"
},
"discount_amount" : {
"type" : "half_float"
},
"discount_percentage" : {
"type" : "half_float"
},
"manufacturer" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword"
}
}
},
"min_price" : {
"type" : "half_float"
},
"price" : {
"type" : "half_float"
},
"product_id" : {
"type" : "long"
},
"product_name" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword"
}
},
"analyzer" : "english"
},
"quantity" : {
"type" : "integer"
},
"sku" : {
"type" : "keyword"
},
"tax_amount" : {
"type" : "half_float"
},
"taxful_price" : {
"type" : "half_float"
},
"taxless_price" : {
"type" : "half_float"
},
"unit_discount_amount" : {
"type" : "half_float"
}
}
},
"sku" : {
"type" : "keyword"
},
"taxful_total_price" : {
"type" : "half_float"
},
"taxless_total_price" : {
"type" : "half_float"
},
"total_quantity" : {
"type" : "integer"
},
"total_unique_products" : {
"type" : "integer"
},
"type" : {
"type" : "keyword"
},
"user" : {
"type" : "keyword"
}
}
},
"settings" : {
"index" : {
"routing" : {
"allocation" : {
"include" : {
"_tier_preference" : "data_content"
}
}
},
"number_of_shards" : "1",
"auto_expand_replicas" : "0-1",
"blocks" : {
"read_only_allow_delete" : "true"
},
"provided_name" : "kibana_sample_data_ecommerce",
"creation_date" : "1699864076981",
"number_of_replicas" : "0",
"uuid" : "gdH9u2JjS0-PswW9cK-Vig",
"version" : {
"created" : "7100099"
}
}
}
}
}
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# 数据建模
Elasticsearch是文档数据库。（不是关系型数据库）
数据建模是指将现实世界中的概念和关系转化为数据库中的表、列和约束的过程。（对应Elasticsearch的索引、字段）
数据建模可以帮助我们更好地组织和管理数据。
在关系型数据库中，我们使用实体关系模型（ERM）进行数据建模。
通过ERM描述现实世界中的实体和实体之间的关系。实体表示现实世界中的一个对象，属性表示实体的特征，关系表示实体之间的联系，约束表示数据的限制条件。
数据建模的基本过程：
1、概念模型，比如一个订单包含多个商品。
2、逻辑模型，比如ER图。
3、数据模型，比如数据库表中的记录。
4、优化迭代。
# 字段数据类型（Field data types）
Field data types 字段数据类型
每个字段都有一个字段数据类型或字段类型。此类型指示字段包含的数据类型，如字符串或布尔值，以及其预期用途。例如，可以将字符串索引到文本字段和关键字字段。但是，将分析文本字段值以进行全文搜索，而保留关键字字符串以进行筛选和排序。
Common types 常见类型
binary
boolean
Keywords //关键字
Numbers
Dates
alias
Objects and relational types 对象和关系类型
object
flattened
nested
join
Structured data types 结构化数据类型
Range
ip
version
murmur3
Aggregate data types 聚合数据类型
aggregate_metric_double
histogram
Text search types 文本搜索类型
text //文本
annotated-text
completion
search_as_you_type
token_count
Document ranking types 文档排名类型
dense_vector
sparse_vector
rank_feature
rank_features
Spatial data types 空间数据类型
geo_point
geo_shape
point
shape
Other types 其他类型
percolator
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# Keyword field type（不分词）
如果出现以下情况，请考虑将数字标识符映射为关键字：
您不打算使用范围查询来搜索标识符数据。
快速检索很重要。对关键字字段的术语查询搜索通常比对数字字段的术语搜索快。
# Text field type（分词）
用于索引全文值的字段，例如电子邮件正文或产品描述。对这些字段进行分析，也就是说，在索引之前，它们通过分析器将字符串转换为单个术语的列表。分析过程允许Elasticsearch在每个全文字段中搜索单个单词。文本字段不用于排序，也很少用于聚合（尽管重要的文本聚合是一个显著的例外）。
如果您需要对电子邮件地址、主机名、状态代码或标记等结构化内容进行索引，则可能应该使用关键字字段。
# 对象和关系类型（Objects and relational types）
# 嵌套字段类型（Nested field type）
# 使用Object field type存放对象数组，会出现错误的查询结果。
#Elasticsearch没有内部对象的概念。Object field type存放对象数组的结构为：
{
"group" : "fans",
"user.first" : [ "alice", "john" ],
"user.last" : [ "smith", "white" ]
}
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#存放两个对象
PUT my-index-000001/_doc/1
{
"group" : "fans",
"user" : [
{
"first" : "John",
"last" : "Smith"
},
{
"first" : "Alice",
"last" : "White"
}
]
}
#查询一个不存在的对象
GET my-index-000001/_search
{
"query": {
"bool": {
"must": [
{ "match": { "user.first": "Alice" }},
{ "match": { "user.last": "Smith" }}
]
}
}
}
#却返回一个命中
{
"took" : 12,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 0.5753642,
"hits" : [
{
"_index" : "my-index-000001",
"_type" : "_doc",
"_id" : "1",
"_score" : 0.5753642,
"_source" : {
"group" : "fans",
"user" : [
{
"first" : "John",
"last" : "Smith"
},
{
"first" : "Alice",
"last" : "White"
}
]
}
}
]
}
}
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# 使用Nested field type存放对象数组。
PUT my-index-000001
{
"mappings": {
"properties": {
"user": {
"type": "nested"
}
}
}
}
#存放两个对象
PUT my-index-000001/_doc/1
{
"group" : "fans",
"user" : [
{
"first" : "John",
"last" : "Smith"
},
{
"first" : "Alice",
"last" : "White"
}
]
}
#查询一个不存在的对象
GET my-index-000001/_search
{
"query": {
"nested": {
"path": "user",
"query": {
"bool": {
"must": [
{ "match": { "user.first": "Alice" }},
{ "match": { "user.last": "Smith" }}
]
}
}
}
}
}
#返回0个命中
{
"took" : 7,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 0,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
}
}
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#查询一个存在的对象
GET my-index-000001/_search
{
"query": {
"nested": {
"path": "user",
"query": {
"bool": {
"must": [
{ "match": { "user.first": "Alice" }},
{ "match": { "user.last": "White" }}
]
}
},
"inner_hits": {
"highlight": {
"fields": {
"user.first": {}
}
}
}
}
}
}
#返回存在对象
{
"took" : 3,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.3862942,
"hits" : [
{
"_index" : "my-index-000001",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.3862942,
"_source" : {
"group" : "fans",
"user" : [
{
"first" : "John",
"last" : "Smith"
},
{
"first" : "Alice",
"last" : "White"
}
]
},
"inner_hits" : {
"user" : {
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.3862942,
"hits" : [
{
"_index" : "my-index-000001",
"_type" : "_doc",
"_id" : "1",
"_nested" : {
"field" : "user",
"offset" : 1
},
"_score" : 1.3862942,
"_source" : {
"last" : "White",
"first" : "Alice"
},
"highlight" : {
"user.first" : [
"<em>Alice</em>"
]
}
}
]
}
}
}
}
]
}
}
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# 联接字段类型（Join field type）
# 通过join type定义父子文档关系
#定义父子文档关联关系
PUT my-index-000001
{
"mappings": {
"properties": {
"my_id": {
"type": "keyword"
},
"my_join_field": { //字段的名称
"type": "join",
"relations": {
"question": "answer" //定义一个单一关系，其中question是answer的父级。
}
}
}
}
}
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#添加两个父文档
PUT my-index-000001/_doc/1?refresh
{
"my_id": "1",
"text": "This is a question",
"my_join_field": {
"name": "question"
}
}
PUT my-index-000001/_doc/2?refresh
{
"my_id": "2",
"text": "This is another question",
"my_join_field": {
"name": "question"
}
}
#添加两个子文档
PUT my-index-000001/_doc/3?routing=1&refresh
{
"my_id": "3",
"text": "This is an answer",
"my_join_field": {
"name": "answer",
"parent": "1" //此子文档的父id
}
}
PUT my-index-000001/_doc/4?routing=1&refresh
{
"my_id": "4",
"text": "This is another answer",
"my_join_field": {
"name": "answer",
"parent": "1"
}
}
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#查询全index数据
GET my-index-000001/_search
{
"query": {
"match_all": {}
},
"sort": ["my_id"]
}
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# 通过parent_id查询关联的answer子文档
#通过parent_id查询关联的answer子文档
GET my-index-000001/_search
{
"query": {
"parent_id": {
"type": "answer",
"id": "1"
}
}
}
#返回关联的子文档
{
"took" : 2,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 0.35667494,
"hits" : [
{
"_index" : "my-index-000001",
"_type" : "_doc",
"_id" : "3",
"_score" : 0.35667494,
"_routing" : "1",
"_source" : {
"my_id" : "3",
"text" : "This is an answer",
"my_join_field" : {
"name" : "answer",
"parent" : "1"
}
}
},
{
"_index" : "my-index-000001",
"_type" : "_doc",
"_id" : "4",
"_score" : 0.35667494,
"_routing" : "1",
"_source" : {
"my_id" : "4",
"text" : "This is another answer",
"my_join_field" : {
"name" : "answer",
"parent" : "1"
}
}
}
]
}
}
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# 通过has_parent查询关联的answer子文档
#通过has_parent查询关联的answer子文档
GET /my-index-000001/_search
{
"query": {
"has_parent": {
"parent_type": "question", //parent
"query": {
"match_all": {}
}
}
}
}
#返回关联的子文档
{
"took" : 15,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "my-index-000001",
"_type" : "_doc",
"_id" : "3",
"_score" : 1.0,
"_routing" : "1",
"_source" : {
"my_id" : "3",
"text" : "This is an answer",
"my_join_field" : {
"name" : "answer",
"parent" : "1"
}
}
},
{
"_index" : "my-index-000001",
"_type" : "_doc",
"_id" : "4",
"_score" : 1.0,
"_routing" : "1",
"_source" : {
"my_id" : "4",
"text" : "This is another answer",
"my_join_field" : {
"name" : "answer",
"parent" : "1"
}
}
}
]
}
}
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# 通过has_child查询关联的父文档
#通过has_child查询关联的父文档
GET /my-index-000001/_search
{
"query": {
"has_child": {
"type": "answer", //child
"query": {
"match_all": {}
}
}
}
}
#返回关联的父文档
{
"took" : 2,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "my-index-000001",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"my_id" : "1",
"text" : "This is a question",
"my_join_field" : {
"name" : "question"
}
}
}
]
}
}
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← es1.1环境安装 es1.3一些API →