Springboot2.x整合ElasticSearch
Springboot2.x整合ElasticSearch
1.学习的本位的条件：必须安装es：elasticsearch和kibana的Linux安装
Windows的安装大家自己搜索吧
2.maven配置：详细的请看下面的源码
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-elasticsearch</artifactId>
</dependency>
yml配置
server:
port: 9099
#开发配置
spring:
datasource:
# 使用druid数据源
type: com.alibaba.druid.pool.DruidDataSource
driver-class-name: com.mysql.cj.jdbc.Driver
url: jdbc:mysql://127.0.0.1:3306/es_db?serverTimezone=GMT%2B8
username: root
password: ls123
## Elasticsearch配置文件（必须）
## 该配置和Elasticsearch的elasticsearch.yml中的配置信息有关
data:
elasticsearch:
cluster-name: my-application
cluster-nodes: 192.168.221.132:9300
mybatis-plus:
map-underscore-to-camel-case: true
mapper-locations: classpath:mappers/*.xml
type-aliases-package: com.ls.pojo
configuration: #配置打印mysql日志
log-impl: org.apache.ibatis.logging.stdout.StdOutImpl
logging:
level:
com.ls.dao.es: debug
ItemRepository不要加注解
public interface ItemRepository extends ElasticsearchRepository<Item,Long > {
}
test类
@RunWith(SpringRunner.class)
@SpringBootTest
@MapperScan("com.ls.dao")
public class EsDemoTest01 {
@Autowired
private ElasticsearchTemplate elasticsearchTemplate;
@Autowired
private ItemRepository itemRepository;
@Autowired
private ItemMapper itemMapper;
}
es的JavaAPI学习
@Data
@Accessors(chain = true)
@ApiModel(value = "Item对象", description = "商品表")
@TableName("tb_item")
@Document(indexName = "item", type = "docs", shards = 1, replicas = 0)
public class Item{
public Item(String itemName, String sellPoint, Long price, Integer num, String brand,
String image, Long cid) {
this.itemName = itemName;
this.sellPoint = sellPoint;
this.price = price;
this.num = num;
this.brand = brand;
this.image = image;
this.cid = cid;
}
public Item() {
}
private static final long serialVersionUID = 1L;
@ApiModelProperty("id")
@TableId(type = IdType.AUTO)
private Long id;
@ApiModelProperty(value = "商品名称")
private String itemName;
@ApiModelProperty(value = "商品卖点")
private String sellPoint;
@ApiModelProperty(value = "商品价格，单位为：分")
private Long price;
@ApiModelProperty(value = "库存数量")
private Integer num;
@ApiModelProperty(value = "商品条形码")
private String brand;
@ApiModelProperty(value = "商品图片")
private String image;
@ApiModelProperty(value = "所属类目，叶子类目")
private Long cid;
@ApiModelProperty(value = "商品状态，1-正常，2-下架，3-删除")
private Integer status;
@ApiModelProperty(value = "创建时间")
private Date createTime;
@ApiModelProperty(value = "更新时间")
private Date modifyTime;
}
1.存入向es单条数据
/**
* 存入单条
*/
@Test
public void testSave() {
Item item = new Item("奔驰s400", "双排气", 666666666l, 5, "奔驰",
"https://www.mercedes-benz.com.cn/?smtid=570962679z32cmz2dt02z1pdz0z", 5L);
int rows = itemMapper.insert(item);
Long id = item.getId();
Item dnItem = itemMapper.selectById(id);
if (rows < 1) {
throw new RuntimeException();
}
//api
itemRepository.save(dnItem);
}
kibana查看所有的
GET _search
{
"query": {
"match_all": {}
}
}
2.存入多条
/**
* 保存多条
*/
@Test
public void testSaveAll() {
List<Long> ids = new ArrayList<>();
ids.add(1L);
ids.add(2L);
ids.add(3L);
List<Item> items = itemMapper.selectBatchIds(ids);
for (Item item : items) {
System.out.println(item);
}
itemRepository.saveAll(items);
}
3.创建索引和删除
/**
* 创建索引，会根据Item类的@Document注解信息来创建
*/
@Test
public void testCreateIndex() {
elasticsearchTemplate.createIndex(Item.class);
}
/**
* 删除索引
*/
@Test
public void testDeleteIndex() {
elasticsearchTemplate.deleteIndex(Item.class);
}
/**
* 删除所有的()
*/
@Test
public void testDeleteAll() {
itemRepository.deleteAll();
}
4.查找所有的
/**
* 查找所有的
*/
@Test
public void testFindAll() {
Iterable<Item> all = itemRepository.findAll();
for (Item item : all) {
System.out.println(item);
}
}
5.配置映射
/**
* 配置映射，会根据Item类中的id、Field等字段来自动完成映射
*/
@Test
public void testPutMapping() {
elasticsearchTemplate.putMapping(Item.class);
}
6.查询按价格排序从高到低
/**
* 查询按价格排序从高到低
*/
@Test
public void testSort() {
Iterable<Item> all = itemRepository.findAll(Sort.by("price").descending());
for (Item item : all) {
System.out.println(item);
}
}
7.自定义查询，在ItemRepository添加方法
/**
* 根据商品标题查询：如
* @param itemName
* @return
*/
List<Item> findByItemName(String itemName );
/**
* 区间查找
* @param
* @param
* @return
*/
List<Item> findByPriceBetween(Long minPrice, Long maxPrice);
测试
/**
* 自定义方法查询，方法名要遵循命名规则，方法名要符合一定的约定
*/
@Test
public void testFindByTitle() {
List<Item> item = itemRepository.findByItemName("三");
for (Item item1 : item) {
System.out.println(item1);
}
}
/**
* 价格区间查询
*/
@Test
public void testFindByPriceBetween() {
List<Item> item = itemRepository.findByPriceBetween(3000L, 6000L);
for (Item item1 : item) {
System.out.println(item1);
}
}
8.matchQuery的使用
/**
* matchQuery底层采用的是词条匹配查询
*/
@Test
public void testMatchQuery() {
NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
queryBuilder.withQuery(QueryBuilders.matchQuery("itemName", "奔驰"));
Page<Item> page = itemRepository.search(queryBuilder.build());
long totalElements = page.getTotalElements();
System.out.println("共有：" + totalElements);
for (Item item : page) {
System.out.println(item);
}
}
9.termQuery的查询
/**
* 词条匹配查询
*/
@Test
public void testTermQuery() {
NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
queryBuilder.withQuery(QueryBuilders.termQuery("price", 3000));
Page<Item> page = itemRepository.search(queryBuilder.build());
for (Item item : page) {
System.out.println(item);
}
}
10.BooleanQuery的查询
@Test
public void testBooleanQuery() {
NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
queryBuilder.withQuery(QueryBuilders.boolQuery().must(QueryBuilders.matchQuery("itemName", "华为"))
.must(QueryBuilders.matchQuery("num", 100)));
Page<Item> page = itemRepository.search(queryBuilder.build());
for (Item item : page) {
System.out.println(item);
}
}
11.模糊查询FuzzyQuery
/**
* 模糊查询,最多错2次
*/
@Test
public void testFuzzyQuery() {
NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
queryBuilder.withQuery(QueryBuilders.fuzzyQuery("itemName", "华"));
Page<Item> page = itemRepository.search(queryBuilder.build());
for (Item item : page) {
System.out.println(item);
}
}
12.分页查询
@Test
public void testPage() {
int pageNum = 0;
int pageSize = 11;
NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
queryBuilder.withQuery(QueryBuilders.matchQuery("cid", 3));
queryBuilder.withPageable(PageRequest.of(pageNum, pageSize));
Page<Item> page = itemRepository.search(queryBuilder.build());
for (Item item : page) {
System.out.println(item);
}
}
聚合查询
/**
* 以品牌分组，求组内情况
*/
@Test
public void testAgg() {
NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
// 不查询任何结果
queryBuilder.withSourceFilter(new FetchSourceFilter(new String[]{""}, null));
// 1、添加一个新的聚合，聚合类型为terms，聚合名称为brands，聚合字段为brand
queryBuilder.addAggregation(
AggregationBuilders.terms("brands").field("brand.keyword"));
// 2、查询,需要把结果强转为AggregatedPage类型
AggregatedPage<Item> aggPage = (AggregatedPage<Item>) this.itemRepository
.search(queryBuilder.build());
// 3、解析
// 3.1、从结果中取出名为brands的那个聚合，
// 因为是利用String类型字段来进行的term聚合，所以结果要强转为StringTerm类型
StringTerms agg = (StringTerms) aggPage.getAggregation("brands");
// 3.2、获取桶
List<StringTerms.Bucket> buckets = agg.getBuckets();
// 3.3、遍历
for (StringTerms.Bucket bucket : buckets) {
// 3.4、获取桶中的key，即品牌名称
System.out.println(bucket.getKeyAsString());
// 3.5、获取桶中的文档数量
System.out.println(bucket.getDocCount());
}
}
/**
* 分组和平均值计算
*/
@Test
public void testSubAgg() {
NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
// 不查询任何结果
queryBuilder.withSourceFilter(new FetchSourceFilter(new String[]{""}, null));
// 1、添加一个新的聚合，聚合类型为terms，聚合名称为brands，聚合字段为brand
queryBuilder.addAggregation(
AggregationBuilders.terms("brands").field("brand.keyword")
.subAggregation(AggregationBuilders.avg("priceAvg").field("price"))
// 在品牌聚合桶内进行嵌套聚合，求平均值
);
// 2、查询,需要把结果强转为AggregatedPage类型
AggregatedPage<Item> aggPage = (AggregatedPage<Item>) this.itemRepository
.search(queryBuilder.build());
// 3、解析
// 3.1、从结果中取出名为brands的那个聚合，
// 因为是利用String类型字段来进行的term聚合，所以结果要强转为StringTerm类型
StringTerms agg = (StringTerms) aggPage.getAggregation("brands");
// 3.2、获取桶
List<StringTerms.Bucket> buckets = agg.getBuckets();
// 3.3、遍历
for (StringTerms.Bucket bucket : buckets) {
// 3.4、获取桶中的key，即品牌名称 3.5、获取桶中的文档数量
System.out.println(bucket.getKeyAsString() + "，共" + bucket.getDocCount() + "台");
// 3.6.获取子聚合结果：
InternalAvg avg = (InternalAvg) bucket.getAggregations().asMap().get("priceAvg");
System.out.println("平均售价：" + avg.getValue());
}
}
GitHub的源码和SQL：https://github.com/smileLs66/es
可参考：https://www.cnblogs.com/leeSmall/p/9218779.html
更多的学习请访问官网文档