Elasticsearch
一、集群状态查看
1：查看集群健康状态
GET /_cat/health?v
2：查看节点状态；
GET /_cat/nodes?v
3：查看所有索引信息
GET /_cat/indices?v
4：查看主节点
GET /_cat/master?v
二、索引操作
1：创建索引并查看；
PUT /customer
GET /_cat/indices?v
2：删除索引并查看
DELETE /customer
GET /_cat/indices?v
三、文档操作
1：在索引中添加文档；
PUT /customer/doc/1
{
"name": "John Doe"
}
2：查看索引中的文档；
GET /customer/doc/1
3：修改索引中的文档：
POST /customer/doc/1/_update
{
"doc": { "name": "Jane Doe" }
}
4：删除索引中的文档；
DELETE /customer/doc/1
5：对索引中的文档执行批量操作；
POST /customer/doc/_bulk
{"index":{"_id":"1"}}
{"name": "John Doe" }
{"index":{"_id":"2"}}
{"name": "Jane Doe" }
四、文档的类型操作
1：创建文档的类型
PUT /new_bank/
{
"mappings" : {
"properties" : {
"account_number" : {
"type" : "long"
},
"address" : {
"type" : "text"
},
"age" : {
"type" : "integer"
},
"balance" : {
"type" : "long"
},
"city" : {
"type" : "keyword"
},
"email" : {
"type" : "keyword"
},
"employer" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"firstname" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"gender" : {
"type" : "keyword"
},
"lastname" : {
"type" : "keyword"
},
"state" : {
"type" : "keyword"
}
}
}
}
2：查看文档的类型
GET /new_bank/_mapping
五、简单收索
1：最简单的搜索，使用match_all来表示，例如搜索全部
GET /bank/_search
{
"query": { "match_all": {} }
}
2：分页搜索，from表示偏移量，从0开始，size表示每页显示的数量
GET /bank/_search
{
"query": { "match_all": {} },
"from": 0,
"size": 10
}
3：搜索排序，使用sort表示，例如按balance字段降序排列
GET /bank/_search
{
"query": { "match_all": {} },
"sort": { "balance": { "order": "desc" } }
}
4：搜索并返回指定字段内容，使用_source表示，例如只返回account_number和balance两个字段内容
GET /bank/_search
{
"query": { "match_all": {} },
"_source": ["account_number", "balance"]
}
六、条件搜索
1：条件搜索，使用match表示匹配条件，例如搜索出account_number为20的文档
GET /bank/_search
{
"query": {
"match": {
"account_number": 20
}
}
}
2：文本类型字段的条件搜索，对于数值类型match操作使用的是精确匹配，对于文本类型使用的是模糊匹配
GET /bank/_search
{
"query": {
"match": {
"address": "mill"
}
},
"_source": [
"address",
"account_number"
]
}
3：短语匹配搜索，使用match_phrase表示，例如搜索address字段中同时包含mill和lane的文档
GET /bank/_search
{
"query": {
"match_phrase": {
"address": "mill lane"
}
}
}
七、组合搜索
1：组合搜索，使用bool来进行组合，must表示同时满足，例如搜索address字段中同时包含mill和lane的文档
GET /bank/_search
{
"query": {
"bool": {
"must": [
{ "match": { "address": "mill" } },
{ "match": { "address": "lane" } }
]
}
}
}
2：组合搜索，should表示满足其中任意一个，搜索address字段中包含mill或者lane的文档
GET /bank/_search
{
"query": {
"bool": {
"should": [
{ "match": { "address": "mill" } },
{ "match": { "address": "lane" } }
]
}
}
}
3：组合搜索，must_not表示同时不满足，例如搜索address字段中不包含mill且不包含lane的文档
GET /bank/_search
{
"query": {
"bool": {
"must_not": [
{ "match": { "address": "mill" } },
{ "match": { "address": "lane" } }
]
}
}
}
4: 组合搜索，组合must和must_not，例如搜索age字段等于40且state字段不包含ID的文档
GET /bank/_search
{
"query": {
"bool": {
"must": [
{ "match": { "age": "40" } }
],
"must_not": [
{ "match": { "state": "ID" } }
]
}
}
}
八、过滤搜索
1：搜索过滤，使用filter来表示，例如过滤出balance字段在20000~30000的文档
GET /bank/_search
{
"query": {
"bool": {
"must": { "match_all": {} },
"filter": {
"range": {
"balance": {
"gte": 20000,
"lte": 30000
}
}
}
}
}
}
九、搜索聚合
1：对搜索结果进行聚合，使用aggs来表示，类似于MySql中的group by，例如对state字段进行聚合，统计出相同state的文档数量，terms相当count(1)
GET /bank/_search
{
"size": 0,
"aggs": {
"group_by_state": {
"terms": {
"field": "state.keyword"
}
}
}
}
2：嵌套聚合，按照年龄聚会，并且请求这些年龄段的这些人的平均薪资
GET /bank/_search
{
"query": {
"match_all": {}
},
"aggs": {
"avgAge": {
"terms": {
"field": "age",
"size": 100
},
"aggs": {
"avgBalance": {
"avg": {
"field": "balance"
}
}
}
}
},
"size": 0
}
3: 嵌套聚合：查出所有年龄分布，并且这些年龄段中M的平均薪资和F的平均薪资以及这个年龄段的总体平均薪资
GET /bank/_search
{
"query": {
"match_all": {}
},
"aggs": {
"age_agg": {
"terms": {
"field": "age",
"size": 100
},
"aggs": {
"gender_agg": {
"terms": {
"field": "gender.keyword",
"size": 100
},
"aggs": {
"balance_avg": {
"avg": {
"field": "balance"
}
}
}
},
"balance_avg":{
"avg": {
"field": "balance"
}
}
}
}
},
"size": 0
}
4：对聚合搜索的结果进行排序，例如按balance的平均值降序排列
GET /bank/_search
{
"size": 0,
"aggs": {
"group_by_state": {
"terms": {
"field": "state.keyword",
"order": {
"average_balance": "desc"
}
},
"aggs": {
"average_balance": {
"avg": {
"field": "balance"
}
}
}
}
}
}
5：按字段值的范围进行分段聚合，例如分段范围为age字段的[20,30] [30,40] [40,50]，之后按gender统计文档个数和balance的平均值
GET /bank/_search
{
"size": 0,
"aggs": {
"group_by_age": {
"range": {
"field": "age",
"ranges": [
{
"from": 20,
"to": 30
},
{
"from": 30,
"to": 40
},
{
"from": 40,
"to": 50
}
]
},
"aggs": {
"group_by_gender": {
"terms": {
"field": "gender.keyword"
},
"aggs": {
"average_balance": {
"avg": {
"field": "balance"
}
}
}
}
}
}
}
十、数据迁移
1：source指原索引，dest指新索引
POST _reindex
{
"source": {
"index": "bank",
"type": "account"
},
"dest": {
"index": "new_bank"
}
}
}
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