第1部分 Elasticsearch基础
2024-09-02 17:27:29
一、安装
es端口：9200
kibana端口：5601
brew install elasticsearch
brew install elasticsearch
brew services start elasticsearch
brew services start kibana
二、elastic交互-基本
1、集群信息
访问数据模式REST
<HTTP Verb> /<Index>/<Type>/<ID>
查看集群健康检查
$ curl -X GET "localhost:9200/_cat/health?v"
epoch timestamp cluster status node.total node.data shards pri relo init unassign pending_tasks max_task_wait_time active_shards_percent
1551424260 07:11:00 elasticsearch_yjn green 1 1 0 0 0 0 0 0 - 100.0%
查看节点列表
$ curl -X GET "localhost:9200/_cat/nodes?v"
ip heap.percent ram.percent cpu load_1m load_5m load_15m node.role master name
127.0.0.1 24 99 23 2.89 mdi * d-0YrG2
查看所有指数
$ curl -X GET "localhost:9200/_cat/indices?v"
health status index uuid pri rep docs.count docs.deleted store.size pri.store.size
green open .kibana_1 oRuiVW1wSbWyFK4Wu0k6MA 1 0 1 0 3.6kb 3.6kb
2、索引
创建索引index
PUT /customer?pretty
GET /_cat/indices?v
health status index uuid pri rep docs.count docs.deleted store.size pri.store.size
green open .kibana_1 oRuiVW1wSbWyFK4Wu0k6MA 1 0 1 0 3.6kb 3.6kb
yellow open customer Fe4Y2hU2Rcek0kl7SYZoKQ 5 1 0 0 1.1kb 1.1kb
- 目前只有一个节点，默认为此索引值创建了一个副本，所以为黄色。
删除索引
DELETE /customer?pretty
3、文档
索引文档
PUT /customer/_doc/1?pretty
{
"name": "John Doe"
}
结果
{
"_index" : "customer",
"_type" : "_doc",
"_id" : "1",
"_version" : 1,
"result" : "created",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 0,
"_primary_term" : 1
}
查询
GET /customer/_doc/1?pretty
{
"_index" : "customer",
"_type" : "_doc",
"_id" : "1",
"_version" : 1,
"_seq_no" : 0,
"_primary_term" : 1,
"found" : true,
"_source" : {
"name" : "John Doe"
}
}
替换文档
POST /customer/_doc?pretty
{
"name": "Jane Doe"
}
- 不指定id会随机产生一个id，创建相同id的已经存在就会被替换。
更新文档
POST /customer/_doc/1/_update?pretty
{
"doc": { "name": "Jane Doe", "age": 20 }
}
- 结果：
GET /customer/_doc/1?pretty
{
"_index" : "customer",
"_type" : "_doc",
"_id" : "1",
"_version" : 3,
"_seq_no" : 2,
"_primary_term" : 1,
"found" : true,
"_source" : {
"name" : "Jane Doe",
"age" : 20
}
}
使用脚本更新文档：
POST /customer/_doc/1/_update?pretty
{
"script" : "ctx._source.age += 5"
}
- 结果：
GET /customer/_doc/1?pretty
{
"_index" : "customer",
"_type" : "_doc",
"_id" : "1",
"_version" : 4,
"_seq_no" : 3,
"_primary_term" : 1,
"found" : true,
"_source" : {
"name" : "Jane Doe",
"age" : 25
}
}
删除文档：
DELETE /customer/_doc/2?pretty
批量处理
POST /customer/_doc/_bulk?pretty
{"index":{"_id":"1"}}
{"name": "John Doe" }
{"index":{"_id":"2"}}
{"name": "Jane Doe" }
POST /customer/_doc/_bulk?pretty
{"update":{"_id":"1"}}
{"doc": { "name": "John Doe becomes Jane Doe" } }
{"delete":{"_id":"2"}}
GET /customer/_doc/_search
Bulk API不会因其中一个操作失败而失败，如果单个操作因任何原因失败，它将继续处理其后的其余操作。
批量API返回时，它将为每个操作提供一个状态（按照发送的顺序），以便您可以检查特定操作是否失败。状态："result" : "noop"（created，deleted，updated，not_found"）
4、数据集处理例子
添加数据集
curl -H "Content-Type: application/json" -XPOST "localhost:9200/bank/_doc/_bulk?pretty&refresh" --data-binary "@accounts.json"
curl "localhost:9200/_cat/indices?v"
查询
GET /bank/_search?q=*&sort=account_number:asc&pretty
- q=* 表示匹配索引中的所有文档
- sort=account_number:asc 结果按照account_number升序排序
- pretty 好看的格式
使用查询表达式：结果同上
GET /bank/_search
{
"query": { "match_all": {} },
"sort": [
{ "account_number": "asc" }
]
}
结果分析：
{
"took" : 8, #es执行搜索的时间ms
"timed_out" : false, #是否超时
"_shards" : {
"total" : 5, #搜索到了多少分片
"successful" : 5, #成功的分片数
"skipped" : 0,
"failed" : 0
},
"hits" : { #查询结果
"total" : 1000, #符合条件的文档总数
"max_score" : null,
"hits" : [ { #实际的搜索结果数组（默认前10个文档）
"_index" : "bank",
"_type" : "_doc",
"_id" : "0",
"sort": [0],
"_score" : null,
"_source" : {"account_number":0,"balance":16623,"firstname":"Bradshaw","lastname":"Mckenzie","age":29,"gender":"F","address":"244 Columbus Place","employer":"Euron","email":"bradshawmckenzie@euron.com","city":"Hobucken","state":"CO"}
}, {
"_index" : "bank",
"_type" : "_doc",
"_id" : "1",
"sort": [1],
"_score" : null,
"_source" : {"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"}
}, ...
]
}
}
5、查询
查询语言
GET /bank/_search
{
"query": { "match_all": {} },
"from": 10,
"size": 10
}
- from：从那个文档索引开始，不指定from默认为0
- size：从from开始返回的文档数
GET /bank/_search
{
"query": { "match_all": {} },
"sort": { "balance": { "order": "desc" } }
}
- 按照balance降序排序
更复杂的查询
GET /_all/tweet/_search?q=name:(mary john) +date:>2014-09-10 +(aggregations geo)
- _all在所有索引中
- 在tweet类型中
- name 字段中包含 mary 或者 john
- date 值大于 2014-09-10
- _all 字段包含 aggregations 或者 geo
6、聚合
GET /bank/_search
{
"size": 0,
"aggs": {
"group_by_state": {
"terms": {
"field": "state.keyword",
"order": {
"average_balance": "desc"
}
},
"aggs": {
"average_balance": {
"avg": {
"field": "balance"
}
}
}
}
}
}
三、分析器
测试分析器
可以使用 analyze API 来看文本是如何被分析的
GET /_analyze
{
"analyzer": "standard",
"text": "Text to analyze"
}
结果：
token 是实际存储到索引中的词条。 position 指明词条在原始文本中出现的位置。 start_offset 和 end_offset 指明字符在原始字符串中的位置。
映射
查看索引bank类型_doc的映射
GET /bank/_mapping/_doc
四、请求体查询 及 五、排序与相关性
详情查看：
(https://www.cnblogs.com/yangjianan/p/10525925.html)
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