引入依赖
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-elasticsearch</artifactId>
</dependency>
配置客户端
@Configuration
public class RestClientConfig extends AbstractElasticsearchConfiguration {
@Override
@Bean
public RestHighLevelClient elasticsearchClient() {
final ClientConfiguration clientConfiguration = ClientConfiguration.builder()
.connectedTo("192.168.0.103:9200")
.build();
return RestClients.create(clientConfiguration).rest();
}
}
客户端对象
- ElasticsearchOperations
- RestHighLevelClient
推荐
ElasticsearchOperations
- 特点: 始终使用面向对象方式操作 ES
- 索引: 用来存放相似文档集合
- 映射: 用来决定放入文档的每个字段以什么样方式录入到 ES 中 字段类型 分词器..
- 文档: 可以被索引最小单元 json 数据格式
相关注解
@Document(indexName = "products", createIndex = true)
public class Product {
@Id
private Integer id;
@Field(type = FieldType.Keyword)
private String title;
@Field(type = FieldType.Float)
private Double price;
@Field(type = FieldType.Text)
private String description;
//get set ...
}
//1. @Document(indexName = "products", createIndex = true) 用在类上 作用:代表一个对象为一个文档
-- indexName属性: 创建索引的名称
-- createIndex属性: 是否创建索引
//2. @Id 用在属性上 作用:将对象id字段与ES中文档的_id对应
//3. @Field(type = FieldType.Keyword) 用在属性上 作用:用来描述属性在ES中存储类型以及分词情况
-- type: 用来指定字段类型
索引文档
@Test
public void testCreate() throws IOException {
Product product = new Product();
product.setId(1); //存在id指定id 不存在id自动生成id
product.setTitle("怡宝矿泉水");
product.setPrice(129.11);
product.setDescription("我们喜欢喝矿泉水....");
elasticsearchOperations.save(product);
}
删除文档
@Test
public void testDelete() {
Product product = new Product();
product.setId(1);
String delete = elasticsearchOperations.delete(product);
System.out.println(delete);
}
查询文档
@Test
public void testGet() {
Product product = elasticsearchOperations.get("1", Product.class);
System.out.println(product);
}
更新文档
@Test
public void testUpdate() {
Product product = new Product();
product.setId(1);
product.setTitle("怡宝矿泉水");
product.setPrice(129.11);
product.setDescription("我们喜欢喝矿泉水,你们喜欢吗....");
elasticsearchOperations.save(product);//不存在添加,存在更新
}
删除所有
@Test
public void testDeleteAll() {
elasticsearchOperations.delete(Query.findAll(), Product.class);
}
查询所有
@Test
public void testFindAll() {
SearchHits<Product> productSearchHits = elasticsearchOperations.search(Query.findAll(), Product.class);
productSearchHits.forEach(productSearchHit -> {
System.out.println("id: " + productSearchHit.getId());
System.out.println("score: " + productSearchHit.getScore());
Product product = productSearchHit.getContent();
System.out.println("product: " + product);
});
}
RestHighLevelClient
创建索引映射
@Test
public void testCreateIndex() throws IOException {
CreateIndexRequest createIndexRequest = new CreateIndexRequest("fruit");
createIndexRequest.mapping("{\n" +
" \"properties\": {\n" +
" \"title\":{\n" +
" \"type\": \"keyword\"\n" +
" },\n" +
" \"price\":{\n" +
" \"type\": \"double\"\n" +
" },\n" +
" \"created_at\":{\n" +
" \"type\": \"date\"\n" +
" },\n" +
" \"description\":{\n" +
" \"type\": \"text\"\n" +
" }\n" +
" }\n" +
" }\n" , XContentType.JSON);
CreateIndexResponse createIndexResponse = restHighLevelClient.indices().create(createIndexRequest, RequestOptions.DEFAULT);
System.out.println(createIndexResponse.isAcknowledged());
restHighLevelClient.close();
}
索引文档
@Test
public void testIndex() throws IOException {
IndexRequest indexRequest = new IndexRequest("fruit");
indexRequest.source("{\n" +
" \"id\" : 1,\n" +
" \"title\" : \"蓝月亮\",\n" +
" \"price\" : 123.23,\n" +
" \"description\" : \"这个洗衣液非常不错哦！\"\n" +
" }",XContentType.JSON);
IndexResponse index = restHighLevelClient.index(indexRequest, RequestOptions.DEFAULT);
System.out.println(index.status());
}
更新文档
@Test
public void testUpdate() throws IOException {
UpdateRequest updateRequest = new UpdateRequest("fruit","qJ0R9XwBD3J1IW494-Om");
updateRequest.doc("{\"title\":\"好月亮\"}",XContentType.JSON);
UpdateResponse update = restHighLevelClient.update(updateRequest, RequestOptions.DEFAULT);
System.out.println(update.status());
}
删除文档
@Test
public void testDelete() throws IOException {
DeleteRequest deleteRequest = new DeleteRequest("fruit","1");
DeleteResponse delete = restHighLevelClient.delete(deleteRequest, RequestOptions.DEFAULT);
System.out.println(delete.status());
}
基于 id 查询文档
@Test
public void testGet() throws IOException {
GetRequest getRequest = new GetRequest("fruit","1");
GetResponse getResponse = restHighLevelClient.get(getRequest, RequestOptions.DEFAULT);
System.out.println(getResponse.getSourceAsString());
}
查询所有
@Test
public void testSearch() throws IOException {
SearchRequest searchRequest = new SearchRequest("fruit");
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
sourceBuilder.query(QueryBuilders.matchAllQuery());
searchRequest.source(sourceBuilder);
SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
//System.out.println(searchResponse.getHits().getTotalHits().value);
SearchHit[] hits = searchResponse.getHits().getHits();
for (SearchHit hit : hits) {
System.out.println(hit.getSourceAsString());
}
}
综合查询
@Test
public void testSearch() throws IOException {
SearchRequest searchRequest = new SearchRequest("fruit");
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
sourceBuilder
.from(0)
.size(2)
.sort("price", SortOrder.DESC)
.fetchSource(new String[]{"title"},new String[]{})
.highlighter(new HighlightBuilder().field("description").requireFieldMatch(false).preTags("<span style='color:red;'>").postTags("</span>"))
.query(QueryBuilders.termQuery("description","错"));
searchRequest.source(sourceBuilder);
SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
System.out.println("总条数: "+searchResponse.getHits().getTotalHits().value);
SearchHit[] hits = searchResponse.getHits().getHits();
for (SearchHit hit : hits) {
System.out.println(hit.getSourceAsString());
Map<String, HighlightField> highlightFields = hit.getHighlightFields();
highlightFields.forEach((k,v)-> System.out.println("key: "+k + " value: "+v.fragments()[0]));
}
}
聚合查询
聚合：英文为Aggregation，是es除搜索功能外提供的针对es数据做统计分析的功能。聚合有助于根据搜索查询提供聚合数据。聚合查询是数据库中重要的功能特性，ES作为搜索引擎兼数据库，同样提供了强大的聚合分析能力。它基于查询条件来对数据进行分桶、计算的方法。有点类似于 SQL 中的 group by 再加一些函数方法的操作。
注意事项：text类型是不支持聚合的。
测试数据
# 创建索引 index 和映射 mapping
PUT /fruit
{
"mappings": {
"properties": {
"title":{
"type": "keyword"
},
"price":{
"type":"double"
},
"description":{
"type": "text",
"analyzer": "ik_max_word"
}
}
}
}
# 放入测试数据
PUT /fruit/_bulk
{"index":{}}
{"title" : "面包","price" : 19.9,"description" : "小面包非常好吃"}
{"index":{}}
{"title" : "旺仔牛奶","price" : 29.9,"description" : "非常好喝"}
{"index":{}}
{"title" : "日本豆","price" : 19.9,"description" : "日本豆非常好吃"}
{"index":{}}
{"title" : "小馒头","price" : 19.9,"description" : "小馒头非常好吃"}
{"index":{}}
{"title" : "大辣片","price" : 39.9,"description" : "大辣片非常好吃"}
{"index":{}}
{"title" : "透心凉","price" : 9.9,"description" : "透心凉非常好喝"}
{"index":{}}
{"title" : "小浣熊","price" : 19.9,"description" : "童年的味道"}
{"index":{}}
{"title" : "海苔","price" : 19.9,"description" : "海的味道"}
使用
根据某个字段分组
# 根据某个字段进行分组 统计数量
GET /fruit/_search
{
"query": {
"term": {
"description": {
"value": "好吃"
}
}
},
"aggs": {
"price_group": {
"terms": {
"field": "price"
}
}
}
}
求最大值
# 求最大值
GET /fruit/_search
{
"aggs": {
"price_max": {
"max": {
"field": "price"
}
}
}
}
求最小值
# 求最小值
GET /fruit/_search
{
"aggs": {
"price_min": {
"min": {
"field": "price"
}
}
}
}
求平均值
# 求平均值
GET /fruit/_search
{
"aggs": {
"price_agv": {
"avg": {
"field": "price"
}
}
}
}
求和
# 求和
GET /fruit/_search
{
"aggs": {
"price_sum": {
"sum": {
"field": "price"
}
}
}
}
整合应用
// 求不同价格的数量
@Test
public void testAggsPrice() throws IOException {
SearchRequest searchRequest = new SearchRequest("fruit");
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
sourceBuilder.aggregation(AggregationBuilders.terms("group_price").field("price"));
searchRequest.source(sourceBuilder);
SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
Aggregations aggregations = searchResponse.getAggregations();
ParsedDoubleTerms terms = aggregations.get("group_price");
List<extends Terms.Bucket> buckets = terms.getBuckets();
for (Terms.Bucket bucket : buckets) {
System.out.println(bucket.getKey() + ", "+ bucket.getDocCount());
}
}
// 求不同名称的数量
@Test
public void testAggsTitle() throws IOException {
SearchRequest searchRequest = new SearchRequest("fruit");
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
sourceBuilder.aggregation(AggregationBuilders.terms("group_title").field("title"));
searchRequest.source(sourceBuilder);
SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
Aggregations aggregations = searchResponse.getAggregations();
ParsedStringTerms terms = aggregations.get("group_title");
List<extends Terms.Bucket> buckets = terms.getBuckets();
for (Terms.Bucket bucket : buckets) {
System.out.println(bucket.getKey() + ", "+ bucket.getDocCount());
}
}
// 求和
@Test
public void testAggsSum() throws IOException {
SearchRequest searchRequest = new SearchRequest("fruit");
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
sourceBuilder.aggregation(AggregationBuilders.sum("sum_price").field("price"));
searchRequest.source(sourceBuilder);
SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
ParsedSum parsedSum = searchResponse.getAggregations().get("sum_price");
System.out.println(parsedSum.getValue());
}
本文由mdnice多平台发布