Java elasticSearch-api的具体操作步骤讲解
目录
1.环境准备
2.针对索引操作
3.针对doc操作(增删改)
4.针对doc操作(查)
5.java-api
6.spring-data-elasticsearch
使用步骤
1.环境准备
用的是windows版,自行下载
链接: 下载地址
2.针对索引操作
这里是kibana上操作的(也可以用postman操作)：
#创建索引,指定文档id
PUT /test1/type1/1
{
"name":"张三",
"age":30
}
#创建索引规则(类似数据库建表)
PUT /test2
{
"mappings": {
"properties": {
"name":{
"type":"text"
},
"age":{
"type": "integer"
},
"birthday":{
"type": "date"
}
}
}
}
#获取索引的信息,properties类型
GET test2
#创建索引,properties不指定类型会有默认类型
#也可以用作修改,但是必须写上全部字段,不然会丢失未写字段
PUT /test3/_doc/1
{
"name":"张三",
"age":30,
"birth":"1991-06-23"
}
GET test3
#查看es健康状态
GET _cat/health
#查看所有索引状态
GET _cat/indices?v
#修改
POST /test3/_doc/1/_update
{
"doc":{
"name":"李四"
}
}
3.针对doc操作(增删改)
代码如下(示例)：
#新增索引,并添加doc
POST /chen/user/1
{
"name":"张三",
"age":11,
"desc":"一顿操作猛如虎,一看工资2500",
"tags":["技术宅","温暖","直男"]
}
POST /chen/user/2
{
"name":"李四",
"age":12,
"desc":"憨批",
"tags":["渣男","旅游","交友"]
}
POST /chen/user/3
{
"name":"王五",
"age":13,
"desc":"瓜怂",
"tags":["靓女","旅游","美食"]
}
POST /chen/user/4
{
"name":"刘六",
"age":14,
"desc":"锅盔",
"tags":["衰仔","旅游","美食"]
}
#获取数据
GET chen/user/1
#更新数据
POST chen/user/1/_update
{
"doc":{
"name":"更新"
}
}
#删除
DELETE chen/user/1
#条件查询,匹配度越高,_score(分值)越高
GET chen/user/_search?q=name:李
GET chen/user/_search?q=name:李四
#等价于上面
GET chen/user/_search
{
"query": {
"match": {
"name": "李四"
}
}
}
4.针对doc操作(查)
查询1(示例)：
#_source结果过滤(指定需要字段结果集)
#sort排序
#from-size分页(类似limit )
#注意:这个查询是不可以些多个字段的(我试过了)
GET chen/user/_search
{
"query": {
"match": {
"name": "李四"
}
},
"_source": ["name","age"],
"sort": [
{
"age": {
"order": "asc"
}
}
],
"from":0,
"size":1
}
#多条件精确查询
#以下都是bool的二级属性
#must:必须
#should,满足任意条件
#must_not,表示不满足
GET chen/user/_search
{
"query": {
"bool": {
"must": [
{"match": {
"name": "李四"
}},
{"match": {
"age": 11
}}
]
}
}
}
#过滤.注意filter是bool(多条件)的二级属性
GET chen/user/_search
{
"query": {
"bool": {
"must": [
{"match": {
"name": "李四"
}}
],
"filter": {
"range": {
"age": {
"gte": 10,
"lte": 20
}
}
}
}
}
}
#分词器依然有效
#多个条件空格隔开就行,只要满足其中一个,就会被逮到
GET chen/user/_search
{
"query": {
"match": {
"tags": "男 技术"
}
}
}
#精确查询,结果只能为1,多条直接不显示
GET chen/user/_search
{
"query": {
"term": {
"name": "李四"
}
}
}
查询2(示例)：
#新建索引
PUT test4
{
"mappings": {
"properties": {
"name":{
"type": "text"
},
"desc":{
"type": "keyword"
}
}
}
}
#插入数据
PUT test4/_doc/1
{
"name":"张三name",
"desc":"张三desc"
}
PUT test4/_doc/2
{
"name":"张三name2",
"desc":"张三desc2"
}
#分词器查询(并不是查询索引里的数据,而是将text的内容用分词器拆分的结果)
GET _analyze
{
"analyzer": "keyword",
"text": ["张三name"]
}
GET _analyze
{
"analyzer": "standard",
"text": "张三name"
}
GET test4/_search
{
"query": {
"term": {
"name": "张"
}
}
}
#==keyword不会被分词器解析==
GET test4/_search
{
"query": {
"term": {
"desc": "张三desc"
}
}
}
查询3(示例)：
PUT test4/_doc/3
{
"t1":"22",
"t2":"2020-4-6"
}
PUT test4/_doc/4
{
"t1":"33",
"t2":"2020-4-7"
}
#精确查询多个值
GET test4/_search
{
"query": {
"bool": {
"should": [
{
"term": {
"t1": "22"
}
},
{
"term": {
"t1": "33"
}
}
]
}
}
}
#highlight:高亮
#pre_tags,post_tags:自定义高亮条件,前缀后缀
GET chen/user/_search
{
"query": {
"match": {
"name": "李四"
}
},
"highlight": {
"pre_tags": "<p class='key' style='color:red'",
"post_tags": "</p>",
"fields": {
"name":{}
}
}
}
5.java-api
索引操作：
public class ES_Index {
private static final String HOST_NAME = "localhost";
private static final Integer PORT = 9200;
private static RestHighLevelClient client;
//创建ES客户端
static {
RestClientBuilder restClientBuilder = RestClient.builder(new HttpHost(HOST_NAME, PORT));
client = new RestHighLevelClient(restClientBuilder);
}
//关闭ES客户端
public void close() {
if (null != client) {
try {
client.close();
} catch (IOException e) {
e.printStackTrace();
}
}
}
//创建索引
public void addIndex() throws IOException {
//创建索引
CreateIndexRequest request = new CreateIndexRequest("chen");
CreateIndexResponse response = client.indices().create(request, RequestOptions.DEFAULT);
//响应状态
System.out.println("索引创建操作: " + response.isAcknowledged());
}
//查询索引
public void selectIndex() throws IOException {
GetIndexRequest request = new GetIndexRequest("chen");
GetIndexResponse response = client.indices().get(request, RequestOptions.DEFAULT);
System.out.println("索引查询操作: " +response.getAliases());
System.out.println("索引查询操作: " +response.getMappings());
System.out.println("索引查询操作: " +response.getSettings());
}
//删除索引
public void deleteIndex() throws IOException {
DeleteIndexRequest request = new DeleteIndexRequest("chen");
AcknowledgedResponse response = client.indices().delete(request, RequestOptions.DEFAULT);
System.out.println("索引删除操作: "+response.isAcknowledged());
}
public static void main(String[] args) throws IOException {
ES_Index index=new ES_Index();
//index.addIndex();
//index.selectIndex();
index.deleteIndex();
index.close();
}
}
文档操作：
public class ES_Doc {
private static final String HOST_NAME = "localhost";
private static final Integer PORT = 9200;
private static RestHighLevelClient client;
//创建ES客户端
static {
RestClientBuilder restClientBuilder = RestClient.builder(new HttpHost(HOST_NAME, PORT));
client = new RestHighLevelClient(restClientBuilder);
}
//关闭ES客户端
public void close() {
if (null != client) {
try {
client.close();
} catch (IOException e) {
e.printStackTrace();
}
}
}
//插入数据
public void addDoc() throws IOException {
IndexRequest request = new IndexRequest();
User user = new User("张三", "男", 18);
//向es插入数据,必须将数据转换为json格式
String userJson = new ObjectMapper().writeValueAsString(user);
request.index("user").id("1001").source(userJson, XContentType.JSON);
IndexResponse response = client.index(request, RequestOptions.DEFAULT);
System.out.println("文档创建操作: " + response.getResult());
}
//修改数据(局部修改)
public void updateDoc() throws IOException {
UpdateRequest request = new UpdateRequest();
request.index("user").id("1001").doc(XContentType.JSON, "sex", "女");
UpdateResponse response = client.update(request, RequestOptions.DEFAULT);
System.out.println("文档修改操作: " + response.getResult());
}
//获取数据
public void getDoc() throws IOException {
GetRequest request = new GetRequest();
request.index("user").id("1001");
GetResponse response = client.get(request, RequestOptions.DEFAULT);
User user = new ObjectMapper().readValue(response.getSourceAsString(), User.class);
System.out.println("文档获取操作: " + user);
}
//删除数据
public void deleteDoc() throws IOException {
DeleteRequest request = new DeleteRequest();
request.index("user").id("1001");
DeleteResponse response = client.delete(request, RequestOptions.DEFAULT);
System.out.println("文档删除操作: " + response.getResult());
}
//批量插入数据
public void addBatch() throws IOException {
BulkRequest request = new BulkRequest();
request.add(new IndexRequest().index("user").id("1001").source(XContentType.JSON, "name", "张三", "sex", "男", "age", 10));
request.add(new IndexRequest().index("user").id("1002").source(XContentType.JSON, "name", "李四", "sex", "男", "age", 20));
request.add(new IndexRequest().index("user").id("1003").source(XContentType.JSON, "name", "王五", "sex", "女", "age", 30));
request.add(new IndexRequest().index("user").id("1004").source(XContentType.JSON, "name", "赵六", "sex", "男", "age", 40));
request.add(new IndexRequest().index("user").id("1005").source(XContentType.JSON, "name", "孙七", "sex", "女", "age", 50));
BulkResponse response = client.bulk(request, RequestOptions.DEFAULT);
System.out.println("文档批量新增操作: " + response.getTook());
System.out.println("文档批量新增操作: " + !response.hasFailures());//是否失败
}
//批量删除数据
public void deleteBatch() throws IOException {
BulkRequest request = new BulkRequest();
request.add(new DeleteRequest().index("user").id("1001"));
request.add(new DeleteRequest().index("user").id("1002"));
request.add(new DeleteRequest().index("user").id("1003"));
request.add(new DeleteRequest().index("user").id("1004"));
request.add(new DeleteRequest().index("user").id("1005"));
BulkResponse response = client.bulk(request, RequestOptions.DEFAULT);
System.out.println("文档批量删除操作: " + response.getTook());
System.out.println("文档批量删除操作: " + !response.hasFailures());//是否失败
}
//查询(重点)
public void searchDoc() throws IOException {
SearchRequest request = new SearchRequest();
request.indices("user");
//1.查询索引中的全部数据
//request.source(new SearchSourceBuilder().query(QueryBuilders.matchAllQuery()));
//2.查询年龄为30的数据
//request.source(new SearchSourceBuilder().query(QueryBuilders.termQuery("age", 30)));
//3.分页查询,当前第0页,每页两条
//request.source(new SearchSourceBuilder().query(QueryBuilders.matchAllQuery()).from(0).size(2));
//4.排序,倒序
//request.source(new SearchSourceBuilder().query(QueryBuilders.matchAllQuery()).sort("age", SortOrder.DESC));
//5.过滤字段(排除和包含,也可以是数组)
//request.source(new SearchSourceBuilder().fetchSource("name", null));
//6.组合查询
//BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
//6.1 must相当于and
//boolQueryBuilder.must(QueryBuilders.matchQuery("age", 30));
//boolQueryBuilder.must(QueryBuilders.matchQuery("sex", "女"));
//6.2 should相当于or
//boolQueryBuilder.should(QueryBuilders.matchQuery("age", 30));
//boolQueryBuilder.should(QueryBuilders.matchQuery("sex", "女"));
//request.source(new SearchSourceBuilder().query(boolQueryBuilder));
//7.范围查询
//request.source(new SearchSourceBuilder().query(QueryBuilders.rangeQuery("age").gte(30).lte(40)));
//8.模糊查询Fuzziness.ONE即只差1个字符
//request.source(new SearchSourceBuilder().query(QueryBuilders.fuzzyQuery("name", "王五").fuzziness(Fuzziness.ONE)));
//9.高亮显示
//SearchSourceBuilder builder = new SearchSourceBuilder().query(QueryBuilders.matchPhraseQuery("name", "张三"));
//builder.highlighter(new HighlightBuilder().preTags("<font color='red'>").postTags("</font>").field("name"));
//request.source(builder);
//10.聚合查询
//SearchSourceBuilder builder = new SearchSourceBuilder();
//MaxAggregationBuilder aggregationBuilder = AggregationBuilders.max("maxAge").field("age");
//builder.aggregation(aggregationBuilder);
//request.source(builder);
//11.分组查询
SearchSourceBuilder builder = new SearchSourceBuilder();
TermsAggregationBuilder aggregationBuilder = AggregationBuilders.terms("ageGroup").field("age");
builder.aggregation(aggregationBuilder);
request.source(builder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
SearchHits hits = response.getHits();
System.out.println("--条数: " + hits.getTotalHits());
System.out.println("--用时: " + response.getTook());
hits.forEach((item)->{
System.out.println("--数据: " + item.getSourceAsString());
});
}
public static void main(String[] args) throws IOException {
ES_Doc doc = new ES_Doc();
//doc.addDoc();
//doc.updateDoc();
//doc.getDoc();
//doc.deleteDoc();
//doc.addBatch();
//doc.deleteBatch();
doc.searchDoc();
doc.close();
}
}
6.spring-data-elasticsearch
实体类: 关键在于@Document和@Field注解
shards 代表分片
replicas 代表副本
@Data
@NoArgsConstructor
@AllArgsConstructor
@Document(indexName = "product", shards = 3, replicas = 1)
public class Product {
@Id
private Long id;//商品唯一标识
@Field(type = FieldType.Text)
private String title;//商品名称
@Field(type = FieldType.Keyword)
private String category;//分类名称
@Field(type = FieldType.Double)
private Double price;//商品价格
@Field(type = FieldType.Keyword,index = false)
private String images;//图片地址
}
dao层: 这样就已经可以了,类似mybatis-plus的BaseMapper,封装好了一些操作
@Repository
public interface ProductDao extends ElasticsearchRepository<Product,Long> {
}
yaml :不用怎么配置,默认就去找localhost:9200
测试 :不知道为啥dao的很多方法都过时了,看源码注释让回去用elasticsearchRestTemplate,感觉更繁琐
@SpringBootTest
class ElasticsearchApplicationTests {
@Autowired
ElasticsearchRestTemplate elasticsearchRestTemplate;
@Autowired
ProductDao productDao;
@Test
void createIndex() {
//创建索引，系统初始化会自动创建索引
System.out.println("创建索引");
}
@Test
void deleteIndex() {
//创建索引，系统初始化会自动创建索引
boolean flg = elasticsearchRestTemplate.deleteIndex(Product.class);
System.out.println("删除索引 = " + flg);
}
//新增数据
@Test
void addDoc() {
Product product = new Product();
product.setId(1001L);
product.setTitle("华为手机");
product.setCategory("手机");
product.setPrice(2999.0);
product.setImages("www.huawei.com");
productDao.save(product);
}
//修改
@Test
void updateDoc() {
Product product = new Product();
product.setId(1001L);
product.setTitle("小米手机");
product.setCategory("手机");
product.setPrice(4999.0);
product.setImages("www.xiaomi.com");
productDao.save(product);
}
//根据 id 查询
@Test
void findById() {
Product product = productDao.findById(1001L).get();
System.out.println(product);
}
//查询所有
@Test
void findAll() {
Iterable<Product> products = productDao.findAll();
for (Product product : products) {
System.out.println(product);
}
}
//删除
@Test
public void delete() {
productDao.deleteById(1001L);
}
//批量新增
@Test
public void saveAll() {
List<Product> productList = new ArrayList<>();
for (int i = 0; i < 10; i++) {
Product product = new Product();
product.setId((long) i);
product.setTitle("[" + i + "]小米手机");
product.setCategory("手机");
product.setPrice(1999.0 + i);
product.setImages("
productList.add(product);
}
productDao.saveAll(productList);
}
//分页查询
@Test
void findByPageable() {
Sort orders = Sort.by(Sort.Direction.DESC, "id");
Pageable pageable = PageRequest.of(0, 5, orders);
Page<Product> products = productDao.findAll(pageable);
products.forEach(System.out::println);
}
/**
* term 查询
* search(termQueryBuilder) 调用搜索方法，参数查询构建器对象
*/
@Test
void termQuery() {
TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("category", "手机");
Iterable<Product> products = productDao.search(termQueryBuilder);
products.forEach(System.out::println);
}
/**
* term 查询加分页
*/
@Test
void termQueryByPage() {
PageRequest pageRequest = PageRequest.of(0, 5);
TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("category", "手机");
Iterable<Product> products = productDao.search(termQueryBuilder, pageRequest);
products.forEach(System.out::println);
}
}
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