在docker里安装elasticsearch和Kibana
1 安装elasticsearch和Kibana
1.1.下载镜像
docker search elasticsearch docker pull elasticsearch:7.14.2
1.2.创建挂载的目录
mkdir -p /mydata/elasticsearch/config mkdir -p /mydata/elasticsearch/data chmod -R 777 echo "http.host: 0.0.0.0" >> /mydata/elasticsearch/config/elasticsearch.yml chmod -R 777
1.3.创建容器并启动
docker run --name elasticsearch -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" -e ES_JAVA_OPTS="-Xms64m -Xmx128m" -v /mydata/elasticsearch/config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml -v /mydata/elasticsearch/data:/usr/share/elasticsearch/data -v /mydata/elasticsearch/plugins:/usr/share/elasticsearch/plugins -d elasticsearch:7.14.2 其中elasticsearch.yml是挂载的配置文件，data是挂载的数据，plugins是es的插件，如ik，而数据挂载需要权限，需要设置data文件的权限为可读可写,需要下边的指令。 chmod -R 777 要修改的路径 -e "discovery.type=single-node" 设置为单节点 特别注意： -e ES_JAVA_OPTS="-Xms256m -Xmx256m" \ 测试环境下，设置ES的初始内存和最大内存，否则导致过大启动不了ES
1.4..Kibana启动
mkdir -p /data/elk7/kibana/config/ vi /data/elk7/kibana/config/kibana.yml # # ** THIS IS AN AUTO-GENERATED FILE ** # # Default Kibana configuration for docker target server.name: kibana server.host: "0" elasticsearch.hosts: [ "http://192.168.31.190:9200" ] xpack.monitoring.ui.container.elasticsearch.enabled: true
docker pull kibana:7.14.2
docker run -d \
--name=kibana \
--restart=always \
-p 5601:5601 \
-v /data/elk7/kibana/config/kibana.yml:/usr/share/kibana/config/kibana.yml \
kibana:7.14.2
查看日志
docker logs -f kibana
{"type":"log","@timestamp":"2020-08-27T03:00:28Z","tags":["listening","info"],"pid":6,"message":"Server running at http://0:5601"}
{"type":"log","@timestamp":"2020-08-27T03:00:28Z","tags":["info","http","server","Kibana"],"pid":6,"message":"http server running at http://0:5601"}
然后访问页面
http://自己的IP地址:5601
http://自己的IP地址:5601/app/kibana
docker pull kibana:7.14.2
docker run --name kibana -e ELASTICSEARCH_HOSTS=http://自己的IP地址:9200 -p 5601:5601 -d kibana:7.14.2
//docker run --name kibana -e ELASTICSEARCH_URL=http://自己的IP地址:9200 -p 5601:5601 -d kibana:7.14.2
进入容器修改相应内容
server.port: 5601
server.host: 0.0.0.0
elasticsearch.hosts: [ "http://自己的IP地址:9200" ]
i18n.locale: "Zh-CN"
然后访问页面
http://自己的IP地址:5601/app/kibana
2. kibana操作ElasticSearch
2.1._cat
GET /_cat/node 查看所有节点 GET /_cat/health 查看es健康状况 GET /_cat/master 查看主节点 GET /_cat/indices 查看所有索引
2.2 保存文档
保存一个数据，保存在那个索引的那个类型下，指定用唯一的标识，customer为索引,external为类型,1为标识。其中PUT和POST都可以，POST新增。如果不指定ID，会自动生成ID，指定ID就会修改这个数据，并新增版本号。PUT可以新增可以修改，PUT必须指定ID，一般都用来修改操作，不指定ID会报错。
PUT customer/external/1
{
"name":"张三"
}
返回结果
{
"_index" : "customer",
"_type" : "external",
"_id" : "1",
"_version" : 3,
"result" : "updated",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 1001,
"_primary_term" : 2
}
2.3 查询文档
GET customer/external/1
结果:
{
"_index" : "customer", //在那个索引
"_type" : "external", //在那个类型
"_id" : "1", //记录ID
"_version" : 1, //版本号
"_seq_no" : 0, //并发控制字段，每次更新就+1，可用于乐观锁
"_primary_term" : 1, //主分片重新分配，如重启，就会变化
"found" : true, //true就是找到数据了
"_source" : { //数据
"name" : "张三"
}
}
2.4 更新文档
POST操作带_update会对比原来的数据，如果是一样的那就不会更新了
POST customer/external/1/_update
{
"doc":{
"name":"你好"
}
}
POST操作不带_update会直接更新操作
POST customer/external/1
{
"name":"你好"
}
2.5 删除文档
DELETE customer/external/1
2.6 bulk批量API
需要加_bulk，然后请求体中的index是id，下边的是要保存的内容
POST customer/external/_bulk
{"index":{"_id":1}}
{"name":"榨干"}
{"index":{"_id":2}}
{"name":"你瞅啥"}
2.7 查询操作 .
先导入批量的数据，在进行查询操作。
1>.一种是通过REST request URI 发送搜索的参数，其中_search是固定写法，q=*是查询所有，sort=balance排序是按照balance排序的，asc是升序排序 GET customer/_search?q=*&sort=balance:asc 结果集，took是花费时间，timed_out没有超时，hits是命中的记录
2>.另一种是通过REST request body 来发送，query代表查询条件，match_all是查询所有，sort代表排序条件
GET customer/_search
{
"query": {
"match_all": {}
},
"sort": [
{
"balance": "asc"
}
]
}
3>.分页操作，from是从第几条数据开始，size是一页多少个，默认是十条数据
4>.按需返回参数为，_source
GET customer/_search
{
"query": {
"match_all": {}
},
"sort": [
{
"balance": "asc"
}
],
"from": 11,
"size": 2,
"_source": ["account_number","balance"]
}
5>.全文检索，使用match操作，查询的结果是按照评分从高到低排序的
GET customer/_search
{
"query": {
"match": {
"age": 20
}
}
}
6>.match_phrase的精确匹配，
GET customer/_search
{
"query": {
"match_phrase": {
"age": 20
}
}
}
7>.多字段匹配，multi_match
GET customer/_search
{
"query": {
"multi_match": {
"query": "mill",
"fields": ["address","email"]
}
}
}
8>.复合查询bool，其中must是必须满足，must_not是必须不满足，should是应该满足，不过不满足的也能查出来，就是得分低，range是区间查询
GET customer/_search
{
"query": {
"bool": {
"must": [
{"match": {
"gender": "F"
}},
{"match": {
"address": "Mill"
}}
],
"must_not": [
{"match": {
"age": "38"
}}
],
"should": [
{"match": {
"lastname": "Long"
}}
]
}
}
}
9>.filter过滤，区间查询操作，而且filter不会计算相关性得分
GET customer/_search
{
"query": {
"bool": {
"filter": [
{"range": {
"age": {
"gte": 10,
"lte": 30
}
}}
]
}
}
}
10>.team查询，一些精确字段的推荐使用team，而一些全文检索的推荐使用match
GET customer/_search
{
"query": {
"term": {
"age": "28"
}
}
}
11.keyword的作用：当有keyword的时候，就会精确查找，而没有keyword的时候，这个值会当成一个关键字
GET customer/_search
{
"query": {"match": {
"address.keyword": "789 Madison"
}}
}
GET customer/_search
{
"query": {"match_phrase": {
"address": "789 Madison"
}}
}
2.13 es分析功能（聚合函数）
搜索address中包含mill的所有人的年龄分布以及平均年龄，但不显示这些人的详情
其中，aggs代表使用聚合函数，terms为结果种类求和，avg为平均值，size为0则不显示详细信息
GET customer/_search
{
"query": {
"match": {
"address": "mill"
}
},
"aggs": {
"ageagg": {
"terms": {
"field": "age",
"size": 10
}
},
"ageavg":{
"avg": {
"field": "age"
}
}
},
"size": 0
}
聚合中还可以有子聚合
GET customer/_search
{
"query": {
"match_all": {}
},
"aggs": {
"ageagg": {
"terms": {
"field": "age",
"size": 10
},
"aggs": {
"ageAvg": {
"avg": {
"field": "balance"
}
}
}
}
},
"size": 0
}
3 rest-high-level-client整合ElasticSearch
3.1.导入依赖
<!-- 修改springboot默认整合的es的版本 -->
<properties>
<java.version>1.8</java.version>
<elasticsearch.version>7.6.2</elasticsearch.version>
</properties>
<!-- elasticsearch-rest-high-level-client -->
<dependency>
<groupId>org.elasticsearch.client</groupId>
<artifactId>elasticsearch-rest-high-level-client</artifactId>
<version>7.6.2</version>
</dependency>
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>fastjson</artifactId>
<version>1.2.68</version>
</dependency>
3.2.编写配置类
@Configuration
public class ElasticSearchClientConfig {
@Bean
public RestHighLevelClient restHighLevelClient(){
RestHighLevelClient client = new RestHighLevelClient(
RestClient.builder(
new HttpHost("自己的IP地址", 9200, "http")
)
);
return client;
}
}
3.3.进行es的索引操作
@Autowired
@Qualifier("restHighLevelClient")
private RestHighLevelClient client;
//index名字，静态一般都是放在另一个类中的
public static final String ES_INDEX="han_index";
//创建索引
@Test
public void createIndex() throws IOException {
//1. 创建索引
CreateIndexRequest index = new CreateIndexRequest(ES_INDEX);
//2. 客户端执行请求,请求后获得相应
CreateIndexResponse response = client.indices().create(index, RequestOptions.DEFAULT);
//3.打印结果
System.out.println(response.toString());
}
//测试索引是否存在
@Test
public void exitIndex() throws IOException{
//1.
GetIndexRequest request = new GetIndexRequest(ES_INDEX);
boolean exists = client.indices().exists(request, RequestOptions.DEFAULT);
System.out.println("是否存在"+exists);
}
//删除索引
@Test
public void deleteIndex() throws IOException{
DeleteIndexRequest request = new DeleteIndexRequest(ES_INDEX);
AcknowledgedResponse response = client.indices().delete(request, RequestOptions.DEFAULT);
System.out.println("是否删除"+response);
}
3.4.es的文档操作
@Autowired
@Qualifier("restHighLevelClient")
private RestHighLevelClient client;
public static final String ES_INDEX="han_index";
//创建文档
@Test
public void createDocument() throws IOException {
//创建对象
UserInfo userInfo = new UserInfo("张三",12);
//创建请求
IndexRequest request = new IndexRequest(ES_INDEX);
//规则
request.id("1").timeout(TimeValue.timeValueSeconds(1));
//将数据放到请求中
request.source(JSON.toJSONString(userInfo), XContentType.JSON);
//客户端发送请求，获取相应的结果
IndexResponse response = client.index(request, RequestOptions.DEFAULT);
//打印一下
System.out.println(response.toString());
System.out.println(response.status());
}
//判断是否存在
@Test
public void exitDocument() throws IOException {
GetRequest request = new GetRequest(ES_INDEX, "1");
//不获取返回的_source 的上下文
request.fetchSourceContext(new FetchSourceContext(false));
request.storedFields("_none");
boolean exists = client.exists(request, RequestOptions.DEFAULT);
System.out.println(exists);
}
//获取文档信息
@Test
public void getDocument() throws IOException {
GetRequest request = new GetRequest(ES_INDEX, "1");
GetResponse response = client.get(request, RequestOptions.DEFAULT);
System.out.println("获取到的结果"+response.getSourceAsString());
}
//更新文档
@Test
public void updateDocument() throws IOException {
//创建对象
UserInfo userInfo = new UserInfo("李四",12);
UpdateRequest request = new UpdateRequest(ES_INDEX, "1");
request.timeout("1s");
request.doc(JSON.toJSONString(userInfo),XContentType.JSON);
UpdateResponse response = client.update(request, RequestOptions.DEFAULT);
System.out.println(response.status());
}
//删除文档
@Test
public void deleteDocument() throws IOException{
DeleteRequest request = new DeleteRequest(ES_INDEX, "1");
request.timeout("1s");
DeleteResponse response = client.delete(request, RequestOptions.DEFAULT);
System.out.println(response.status());
}
//批量添加
@Test
public void bulkDocument() throws IOException{
BulkRequest request = new BulkRequest();
request.timeout("10s");
ArrayList<UserInfo> userInfos = new ArrayList<>();
userInfos.add(new UserInfo("李四",1));
userInfos.add(new UserInfo("李四",2));
userInfos.add(new UserInfo("李四",3));
userInfos.add(new UserInfo("李四",4));
userInfos.add(new UserInfo("李四",5));
userInfos.add(new UserInfo("李四",6));
userInfos.add(new UserInfo("李四",7));
//进行批处理请求
for (int i = 0; i <userInfos.size() ; i++) {
request.add(
new IndexRequest(ES_INDEX)
.id(""+(i+1))
.source(JSON.toJSONString(userInfos.get(i)),XContentType.JSON));
}
BulkResponse response = client.bulk(request, RequestOptions.DEFAULT);
System.out.println(response.hasFailures());
}
//查询
@Test
public void SearchDocument() throws IOException{
SearchRequest request = new SearchRequest(ES_INDEX);
//构建搜索条件
SearchSourceBuilder builder = new SearchSourceBuilder();
//查询条件使用QueryBuilders工具来实现
//QueryBuilders.termQuery 精准查询
//QueryBuilders.matchAllQuery() 匹配全部
MatchQueryBuilder matchQuery = QueryBuilders.matchQuery("name", "李四");
builder.query(matchQuery);
builder.timeout(new TimeValue(60, TimeUnit.SECONDS));
request.source(builder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
System.out.println("查询出的结果"+JSON.toJSONString(response.getHits()));
}
posted on 2021-11-21 21:20 clearriver 阅读(132) 评论(0) 编辑 收藏 举报
