SpringBoot整合ElasticSearch（二）
文章目录
-
- es的批量操作
- es的重中之重——查询
- es与springboot集成
es的批量操作
- bulk批量操作
导入数据-分析与创建索引
PUT goods
{
"mappings": {
"properties": {
"title": {
"type": "text",
"analyzer": "ik_smart"
},
"price": {
"type": "double"
},
"createTime": {
"type": "date"
},
"categoryName": {
"type": "keyword"
},
"brandName": {
"type": "keyword"
},
"spec": {
"type": "object"
},
"saleNum": {
"type": "integer"
},
"stock": {
"type": "integer"
}
}
}
}
- 通过java代码实现导入数据
/**
* 从Mysql 批量导入 elasticSearch
*/
@Test
public void test3() throws IOException {
//1.查询所有数据，mysql
List<Goods> goodsList = goodsMapper.findAll();
//2.bulk导入
BulkRequest bulkRequest=new BulkRequest();
//2.1 循环goodsList，创建IndexRequest添加数据
for (Goods goods : goodsList) {
//2.2 设置spec规格信息 Map的数据 specStr:{}
String specStr = goods.getSpecStr();
//将json格式字符串转为Map集合
Map map = JSON.parseObject(specStr, Map.class);
//设置spec map
goods.setSpec(map);
//将goods对象转换为json字符串
String data = JSON.toJSONString(goods);
IndexRequest indexRequest=new IndexRequest("goods").source(data,XContentType.JSON);
bulkRequest.add(indexRequest);
}
BulkResponse response = client.bulk(bulkRequest, RequestOptions.DEFAULT);
System.out.println(response.status());
}
es的重中之重——查询
- matchAll
1.matchAll脚本
# 默认情况下，es一次展示10条数据,通过from和size来控制分页
# 查询结果详解
GET goods/_search
{
"query": {
"match_all": {}
},
"from": 0,
"size": 100
}
GET goods
- 代码实现
/**
* 查询所有
* 1. matchAll
* 2. 将查询结果封装为Goods对象，装载到List中
* 3. 分页。默认显示10条
*/
@Test
public void matchAll() throws IOException {
//2. 构建查询请求对象，指定查询的索引名称
SearchRequest searchRequest=new SearchRequest("goods");
//4. 创建查询条件构建器SearchSourceBuilder
SearchSourceBuilder sourceBuilder=new SearchSourceBuilder();
//6. 查询条件
QueryBuilder queryBuilder= QueryBuilders.matchAllQuery();
//5. 指定查询条件
sourceBuilder.query(queryBuilder);
//3. 添加查询条件构建器 SearchSourceBuilder
searchRequest.source(sourceBuilder);
// 8 . 添加分页信息 不设置 默认10条
// sourceBuilder.from(0);
// sourceBuilder.size(100);
//1. 查询,获取查询结果
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
//7. 获取命中对象 SearchHits
SearchHits hits = searchResponse.getHits();
//7.1 获取总记录数
Long total= hits.getTotalHits().value;
System.out.println("总数："+total);
//7.2 获取Hits数据 数组
SearchHit[] hits1 = hits.getHits();
//获取json字符串格式的数据
List<Goods> goodsList = new ArrayList<>();
for (SearchHit searchHit : hits1) {
String sourceAsString = searchHit.getSourceAsString();
//转为java对象
Goods goods = JSON.parseObject(sourceAsString, Goods.class);
goodsList.add(goods);
}
for (Goods goods : goodsList) {
System.out.println(goods);
}
}
- termQuery
term查询和字段类型有关系，term查询不会对查询条件进行分词的，所以对于text类型的字段，只有其中的词匹配到了都会查到。而keyword则时全部匹配到后才会查询到，也就是说完全匹配才行。 - matchQuery
它是会对查询条件进行分词的，然后对分词后的条件进行等值匹配的。并且默认是取并集的。 - 模糊查询
- wildcard查询：会对查询条件进行分词，并且还可以使用通配符？（任意单个字符）和*（0个或多个字符）
- 正则查询
\W：匹配包括下划线的任何单词字符，等价于 [A-Z a-z 0-9_] 开头的反斜杠是转义符
+号多次出现
(.)*为任意字符
正则查询取决于正则表达式的效率
- 前缀查询
# 前缀查询 对keyword类型支持比较好
GET goods/_search
{
"query": {
"prefix": {
"brandName": {
"value": "三"
}
}
}
}
- java代码实现
//模糊查询
WildcardQueryBuilder query = QueryBuilders.wildcardQuery("title", "华*");//华后多个字符
//正则查询
RegexpQueryBuilder query = QueryBuilders.regexpQuery("title", "\\w+(.)*");
//前缀查询
PrefixQueryBuilder query = QueryBuilders.prefixQuery("brandName", "三");
- 范围与排序操作
1 . 脚本
# 范围查询
GET goods/_search
{
"query": {
"range": {
"price": {
"gte": 2000,
"lte": 3000
}
}
},
"sort": [
{
"price": {
"order": "desc"
}
}
]
}
- java代码实现
//范围查询 以price 价格为条件
RangeQueryBuilder query = QueryBuilders.rangeQuery("price");
//指定下限
query.gte(2000);
//指定上限
query.lte(3000);
sourceBuilder.query(query);
//排序 价格 降序排列
sourceBuilder.sort("price",SortOrder.DESC);
- 多条件查询（queryString）
- queryString多条件查询，会对查询条件进行分词，然后将分词后的查询条件和词条进行等值匹配，默认取的是并集，同时也可以指定多个查询字段
- 脚本实现
// query_string：识别query中的连接符（or 、and）
GET goods/_search
{
"query": {
"query_string": {
"fields": ["title","categoryName","brandName"],
"query": "华为 AND 手机"
}
}
}
// simple_query_string：不识别query中的连接符（or 、and），查询时会将 “华为”、"and"、“手机”分别进行查询
GET goods/_search
{
"query": {
"simple_query_string": {
"fields": ["title","categoryName","brandName"],
"query": "华为 AND 手机"
}
}
}
// query_string：有default_operator连接符的脚本
GET goods/_search
{
"query": {
"query_string": {
"fields": ["title","brandName","categoryName"],
"query": "华为手机 "
, "default_operator": "AND"
}
}
}
- java代码实现
QueryStringQueryBuilder query = QueryBuilders.queryStringQuery("华为手机").field("title").field("categoryName")
.field("brandName").defaultOperator(Operator.AND);
注意点： default_operator的or and 是对结果进行 并集（or）、交集（and）
- 布尔查询
- boolQuery：对多个查询条件连接。
连接方式：- must（and）条件必须成立
- must_not(条件必须不成立)
- should（or）条件可以成立
- filter：条件必须成立，性能比must高。不会计算得分（得分越高，匹配度就越高）
# boolquery
#must和filter配合使用时，max_score（得分）是显示的
#must 默认数组形式
GET goods/_search
{
"query": {
"bool": {
"must": [
{
"term": {
"brandName": {
"value": "华为"
}
}
}
],
"filter":[
{
"term": {
"title": "手机"
}
},
{
"range":{
"price": {
"gte": 2000,
"lte": 3000
}
}
}
]
}
}
}
#filter 单独使用 filter可以是单个条件，也可多个条件（数组形式）
GET goods/_search
{
"query": {
"bool": {
"filter": [
{
"term": {
"brandName": {
"value": "华为"
}
}
}
]
}
}
}
- java代码实现
//1.构建boolQuery
BoolQueryBuilder boolQuery = QueryBuilders.boolQuery();
//2.构建各个查询条件
//2.1 查询品牌名称为:华为
TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("brandName", "华为");
boolQuery.must(termQueryBuilder);
//2.2. 查询标题包含：手机
MatchQueryBuilder matchQuery = QueryBuilders.matchQuery("title", "手机");
boolQuery.filter(matchQuery);
//2.3 查询价格在：2000-3000
RangeQueryBuilder rangeQuery = QueryBuilders.rangeQuery("price");
rangeQuery.gte(2000);
rangeQuery.lte(3000);
boolQuery.filter(rangeQuery);
sourceBuilder.query(boolQuery);
- 聚合查询
- 指标聚合：相当于mysql的聚合函数一样的，比如max，sum等
- 桶聚合：相当于mysql的group by 操作，需要注意的是不要对text类型的数据进行分组，会失败的。
# 聚合查询
# 指标聚合 聚合函数
GET goods/_search
{
"query": {
"match": {
"title": "手机"
}
},
"aggs": {
"max_price": {
"max": {
"field": "price"
}
}
}
}
# 桶聚合 分组
GET goods/_search
{
"query": {
"match": {
"title": "手机"
}
},
"aggs": {
"goods_brands": {
"terms": {
"field": "brandName",
"size": 100
}
}
}
}
- java代码实现
/**
* 聚合查询：桶聚合，分组查询
* 1. 查询title包含手机的数据
* 2. 查询品牌列表
*/
@Test
public void testAggQuery() throws IOException {
SearchRequest searchRequest=new SearchRequest("goods");
SearchSourceBuilder sourceBuilder=new SearchSourceBuilder();
//1. 查询title包含手机的数据
MatchQueryBuilder queryBuilder = QueryBuilders.matchQuery("title", "手机");
sourceBuilder.query(queryBuilder);
//2. 查询品牌列表 只展示前100条
AggregationBuilder aggregation=AggregationBuilders.terms("goods_brands").field("brandName").size(100);
sourceBuilder.aggregation(aggregation);
searchRequest.source(sourceBuilder);
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
//7. 获取命中对象 SearchHits
SearchHits hits = searchResponse.getHits();
//7.1 获取总记录数
Long total= hits.getTotalHits().value;
System.out.println("总数："+total);
// aggregations 对象
Aggregations aggregations = searchResponse.getAggregations();
//将aggregations 转化为map
Map<String, Aggregation> aggregationMap = aggregations.asMap();
//通过key获取goods_brands 对象 使用Aggregation的子类接收 buckets属性在Terms接口中体现
// Aggregation goods_brands1 = aggregationMap.get("goods_brands");
Terms goods_brands =(Terms) aggregationMap.get("goods_brands");
//获取buckets 数组集合
List<? extends Terms.Bucket> buckets = goods_brands.getBuckets();
Map<String,Object>map=new HashMap<>();
//遍历buckets key 属性名，doc_count 统计聚合数
for (Terms.Bucket bucket : buckets) {
System.out.println(bucket.getKey());
map.put(bucket.getKeyAsString(),bucket.getDocCount());
}
System.out.println(map);
}
- 高亮查询
- 它有一个三要素：高亮字段、前缀、后缀。默认前后缀为
GET goods/_search
{
"query": {
"match": {
"title": "电视"
}
},
"highlight": {
"fields": {
"title": {
"pre_tags": "",
"post_tags": ""
}
}
}
}
- java 代码操作
/**
*
* 高亮查询：
* 1. 设置高亮
* * 高亮字段
* * 前缀
* * 后缀
* 2. 将高亮了的字段数据，替换原有数据
*/
@Test
public void testHighLightQuery() throws IOException {
SearchRequest searchRequest = new SearchRequest("goods");
SearchSourceBuilder sourceBulider = new SearchSourceBuilder();
// 1. 查询title包含手机的数据
MatchQueryBuilder query = QueryBuilders.matchQuery("title", "手机");
sourceBulider.query(query);
//设置高亮
HighlightBuilder highlighter = new HighlightBuilder();
//设置三要素
highlighter.field("title");
//设置前后缀标签
highlighter.preTags("");
highlighter.postTags("");
//加载已经设置好的高亮配置
sourceBulider.highlighter(highlighter);
searchRequest.source(sourceBulider);
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
SearchHits searchHits = searchResponse.getHits();
//获取记录数
long value = searchHits.getTotalHits().value;
System.out.println("总记录数："+value);
List<Goods> goodsList = new ArrayList<>();
SearchHit[] hits = searchHits.getHits();
for (SearchHit hit : hits) {
String sourceAsString = hit.getSourceAsString();
//转为java
Goods goods = JSON.parseObject(sourceAsString, Goods.class);
// 获取高亮结果，替换goods中的title
Map<String, HighlightField> highlightFields = hit.getHighlightFields();
HighlightField HighlightField = highlightFields.get("title");
Text[] fragments = HighlightField.fragments();
//highlight title替换 替换goods中的title
goods.setTitle(fragments[0].toString());
goodsList.add(goods);
}
for (Goods goods : goodsList) {
System.out.println(goods);
}
}
es与springboot集成
所需jar包
<dependency>
<groupId>org.springframework.bootgroupId>
<artifactId>spring-boot-starter-data-elasticsearchartifactId>
dependency>
es配置
#es集群配置
spring.data.elasticsearch.cluster-name=es-tanhua-cluster
spring.data.elasticsearch.cluster-nodes=192.168.31.81:9300,192.168.31.81:9301,192.168.31.81:9302
es代码编写
@Autowired
private ElasticsearchTemplate elasticsearchTemplate;
/**
* 初始化索引库
*
*/
@PostConstruct
public void initIndex(){
//判断索引库是否存在，如果不存在，需要创建
if(!this.elasticsearchTemplate.indexExists("tanhua")){
this.elasticsearchTemplate.createIndex(UserLocation.class);
}
//判断表是否存在，如果不存在，需要创建
if(!this.elasticsearchTemplate.typeExists("tanhua", "user_location")){
this.elasticsearchTemplate.putMapping(UserLocation.class);
}
}
@Override
public Boolean updateUserLocation(Long userId, Double longitude, Double latitude, String address) {
//查询个人的地理位置数据，如果不存在，需要新增，如果是存在数据，更新数据
try {
GetQuery getQuery = new GetQuery();
getQuery.setId(String.valueOf(userId));
UserLocation userLocation = this.elasticsearchTemplate.queryForObject(getQuery, UserLocation.class);
if(ObjectUtil.isEmpty(userLocation)){
//新增数据
userLocation = new UserLocation();
userLocation.setUserId(userId);
userLocation.setAddress(address);
userLocation.setCreated(System.currentTimeMillis());
userLocation.setUpdated(userLocation.getCreated());
userLocation.setLastUpdated(userLocation.getCreated());
userLocation.setLocation(new GeoPoint(latitude, longitude));
IndexQuery indexQuery = new IndexQueryBuilder().withObject(userLocation).build();
//保存数据到ES中
this.elasticsearchTemplate.index(indexQuery);
}else {
//更新数据
//更新的字段
Map<String,Object> map = new HashMap<>();
map.put("location", new GeoPoint(latitude, longitude));
map.put("updated", System.currentTimeMillis());
map.put("lastUpdated", userLocation.getUpdated());
map.put("address", address);
UpdateRequest updateRequest = new UpdateRequest();
updateRequest.doc(map);
UpdateQuery updateQuery = new UpdateQueryBuilder()
.withId(String.valueOf(userId))
.withClass(UserLocation.class)
.withUpdateRequest(updateRequest).build();
//更新数据
this.elasticsearchTemplate.update(updateQuery);
}
return true;
} catch (Exception e) {
log.error("更新地理位置失败~ userId = " + userId + ", longitude = " + longitude + ", latitude = " + latitude + ", address = " + address, e);
}
return false;
}
基本使用就这些了
SpringBoot整合ElasticSearch（一）