https://www.elastic.co
https://www.elastic.co/guide/en/elasticsearch/client/java-rest/7.4/java-rest-high-create-index.html#java-rest-high-create-index-request
- 启动保错max virtual memory areas vm.max_map_count [65530] is too low, increase to at least [262144]，意思是elasticsearch的用户内存太小
vim /etc/sysctl.conf
添加配置：vm.max_map_count=262144
执行命令：/sbin/sysctl -p 立即生效
GET _search
{
"query": {
"match_all": {}
}
}
GET /_analyze
{
"analyzer": "ik_max_word",
"text": "乒乓球明年总冠军"
}
GET /_analyze
{
"analyzer": "ik_max_word",
"text": "深圳南山区"
}
GET /_analyze
{
"analyzer": "ik_smart",
"text": "乒乓球明年总冠军"
}
GET /_analyze
{
"analyzer": "standard",
"text": "乒乓球明年总冠军"
}
#索引操作
PUT person
GET person
GET /blog1
DELETE person
# 查询映射
GET person/_mapping
GET blog1/_mapping
# 添加映射
PUT person/_mapping
{
"properties":{
"name":{
"type":"keyword"
},
"age":{
"type":"integer"
}
}
}
# ------------------------------------------------
# 创建索引并添加映射
PUT person
{
"mappings": {
"properties": {
"name":{
"type": "keyword"
},
"age":{
"type":"integer"
}
}
}
}
# 索引库中添加字段
PUT person/_mapping
{
"properties":{
"address":{
"type":"text",
"analyzer": "ik_max_word"
}
}
}
# 索引库中添加字段
PUT person/_mapping
{
"properties":{
"address1":{
"type":"text"
}
}
}
# 添加文档，指定id
PUT person/_doc/1
{
"name":"张三",
"age":20,
"address":"深圳宝安区",
"address1":"深圳宝安区"
}
# 查询文档
GET person/_doc/1
# 添加文档,不指定id,会自动分配id
POST person/_doc/
{
"name":"李四",
"age":20,
"address":"深圳南山区",
"address1":"深圳宝安区"
}
# 查询文档
GET person/_doc/w-337XwB9vA-maKnuarV
# 查询所有文档
GET person/_search
# 删除文档
DELETE person/_doc/1
# 修改文档 根据id，id存在就是修改，id不存在就是添加
PUT person/_doc/2
{
"name":"硅谷",
"age":20,
"address":"深圳福田保税区",
"address1":"深圳宝安区"
}
#全文查询-match查询
# match 先会对查询的字符串进行分词，在查询，求交集
GET person/_search
{
"query": {
"match": {
"address": "深圳保税区"
}
}
}
# 查询所有数据
GET person/_search
GET person/_mapping
# 查询 带某词条的数据
#词条查询不会分析查询条件，只有当词条和查询字符串完全匹配时才匹配搜索，ik_max_word和standard有区别的，
#ik_max_word的倒排索引中有南山区，standard没有
GET person/_search
{
"query": {
"term": {
"address": {
"value": "南山区"
}
}
}
}
GET person/_search
{
"query": {
"term": {
"address1": {
"value": "南山区"
}
}
}
}
#关键字搜索数据
# 查询名字等于张三的用户
GET person/_search?q=name:张三
PUT shangguigu/_doc/1001
{
"id":"1001",
"name":"张三",
"age":20,
"sex":"男"
}
PUT shangguigu/_doc/1002
{
"id":"1002",
"name":"李四",
"age":25,
"sex":"女"
}
PUT shangguigu/_doc/1003
{
"id":"1003",
"name":"王五",
"age":30,
"sex":"女"
}
PUT shangguigu/_doc/1004
{
"id":"1004",
"name":"赵六",
"age":30,
"sex":"男"
}
GET shangguigu/_search
POST shangguigu/_doc/_search
{
"query":{
"match":{
"age":20
}
}
}
#查询年龄大于20岁的女性用户
GET shangguigu/_search
{
"query":{
"bool":{
"filter":{
"range":{
"age":{
"gt":20
}
}
},
"must":{
"match":{
"sex":"女"
}
}
}
}
}
GET shangguigu/_search
{
"query":{
"match":{
"name": "张三 李四"
}
}
}
#高亮
GET shangguigu/_search
{
"query":{
"match":{
"name": "张三 李四"
}
},
"highlight": {
"fields": {
"name": {}
}
}
}
#没有指定映射会自动生成映射
GET shangguigu/_mapping
GET shangguigu
#聚合
#在Elasticsearch中，支持聚合操作，类似SQL中的group
#by操作。
GET shangguigu/_search
{
"aggs": {
"all_interests": {
"terms": {
"field": "age"
}
}
}
}
#text字段分组须要name.keyword
GET shangguigu/_search
{
"aggs": {
"all_interests": {
"terms": {
"field": "name.keyword"
}
}
}
}
#指定响应字段
GET shangguigu/_doc/1001?_source=id,name
#等价于
GET /shangguigu/_search
{
"query": {
"match": {
"id": "1001"
}
},
"_source": ["id","name"]
}
#判断文档是否存在
HEAD shangguigu/_doc/1001
#批量操作 mget通配符请求; 下载多个文件;
POST shangguigu/_doc/_mget
{
"ids" : [ "1001", "1003" ]
}
#如果，某一条数据不存在，不影响整体响应，需要通过found的值进行判断是否查询到数据。
POST shangguigu/_doc/_mget
{
"ids" : [ "1001", "10086" ]
}
#_bulk操作 在Elasticsearch中，支持批量的插入、修改、删除操作，都是通过_bulk的api完成的。
#请求格式如下：（请求格式不同寻常）
#批量插入数据
POST _bulk
{"create":{"_index":"atguigu","_id":2001}}
{"id":2001,"name":"name1","age": 20,"sex": "男"}
{"create":{"_index":"atguigu","_id":2002}}
{"id":2002,"name":"name2","age": 20,"sex": "男"}
{"create":{"_index":"atguigu","_id":2003}}
{"id":2003,"name":"name3","age": 20,"sex": "男"}
#更新
POST _bulk
{"update":{"_index":"atguigu","_id":2001}}
{"doc":{"id":2001,"name":"name1","age":21,"sex":"男"}}
GET atguigu/_mapping
POST _bulk
{"delete":{"_index":"atguigu","_id":2001}}
{"delete":{"_index":"atguigu","_id":2002}}
{"delete":{"_index":"atguigu","_id":2003}}
#分页
GET /_search?size=5
GET /_search?size=5&from=5
GET /_search?size=5&from=10
GET /_search?size=5&from=20
#指定索引分页
GET shangguigu/_search?size=4&from=4
POST atguigu/_bulk
{"index":{"_index":"atguigu"}}
{"name":"张三","age": 20,"mail": "111@qq.com","hobby":"羽毛球、乒乓球、足球"}
{"index":{"_index":"atguigu"}}
{"name":"李四","age": 21,"mail": "222@qq.com","hobby":"羽毛球、乒乓球、足球、篮球"}
{"index":{"_index":"atguigu"}}
{"name":"王五","age": 22,"mail": "333@qq.com","hobby":"羽毛球、篮球、游泳、听音乐"}
{"index":{"_index":"atguigu"}}
{"name":"赵六","age": 23,"mail": "444@qq.com","hobby":"跑步、游泳"}
{"index":{"_index":"atguigu"}}
{"name":"孙七","age": 24,"mail": "555@qq.com","hobby":"听音乐、看电影"}
POST atguigu/_search
{
"query" : {
"match" : {
"hobby" : "音乐 羽毛球"
}
},
"from": 0,
"size": 5
}
#terms
POST atguigu/_search
{
"query" : {
"terms" : {
"age" : [20,21]
}
}
}
#range
POST atguigu/_search
{
"query": {
"range": {
"age": {
"gte": 20,
"lte": 22
}
}
},
"_source": ["id","name"]
}
POST atguigu/_search
{
"query": {
"range": {
"age": {
"gte": 20,
"lte": 22
}
}
}
}
# "exists": 必须包含
POST atguigu/_search
{
"query": {
"exists": {
"field": "mail"
}
}
}
# 新建student_index_v1索引，索引名称必须全部小写
PUT student_index_v1
{
"mappings": {
"properties": {
"birthday":{
"type": "date"
}
}
}
}
# 查询索引
GET student_index_v1
# 添加数据
PUT student_index_v1/_doc/1
{
"birthday":"2020-11-11"
}
# 查询数据
GET student_index_v1/_search
# 随着业务的变更，换种数据类型进行添加数据，程序会直接报错
PUT student_index_v1/_doc/1
{
"birthday":"2020年11月11号"
}
# 业务变更，需要改变birthday数据类型为text
# 1：创建新的索引 student_index_v2
# 2：将student_index_v1 数据拷贝到 student_index_v2
# 创建新的索引
PUT student_index_v2
{
"mappings": {
"properties": {
"birthday":{
"type": "text"
}
}
}
}
DELETE student_index_v2
# 2：将student_index_v1 数据拷贝到 student_index_v2
POST _reindex
{
"source": {
"index": "student_index_v1"
},
"dest": {
"index": "student_index_v2"
}
}
# 查询新索引库数据
GET student_index_v2/_search
# 在新的索引库里面添加数据
PUT student_index_v2/_doc/2
{
"birthday":"2020年11月13号"
}
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