文章目录
- [es8 API基础配置和bean注入](#es8 API基础配置和bean注入)
- 高阶使用
- DSL查询
-
- 1:matchAll查询所有文档
- [2:match 根据字段查询](#2:match 根据字段查询)
- 3:多id查询
- [4:term 不分词查询](#4:term 不分词查询)
- 5:范围查询
- [6: 前缀查询](#6: 前缀查询)
- 7:匹配查询
- 8:模糊查询
- 9:多条件查询
- 10:多字段查询-multiMatch
- 11:高亮显示
- 12:分页查询
- 12-1:使用分页时,最多返回10000条。需要进行设置
- 13:排序
- 14:指定字段查询
- 15:聚合查询-求最大值
- [16:桶聚合查询-劣势 group by](#16:桶聚合查询-劣势 group by)
es8 API基础配置和bean注入
Elasticsearch-06-Elasticsearch Java API Client-Elasticsearch 8.0 的基础配置和使用
高阶使用
1:引入elasticsearchClient
通过之前的配置,目前已经将elasticsearchClient 注入了容器中,后续只要引入即可
java
@Autowired
ElasticsearchClient elasticsearchClient;
还不知道怎么注入elasticsearchClient的去看我上篇文章
Elasticsearch-06-Elasticsearch Java API Client-Elasticsearch 8.0 的基础配置和使用
2:查询所有索引
java
//省略连接...
final GetIndexResponse all = client.indices().get(query -> query.index("_all"));
System.out.println(all.toString());
//省略关闭...
3:查询某个索引
java
//查询某个索引
final GetIndexResponse products = client.indices().get(query -> query.index("products"));
System.err.println(products.toString());
4:创建索引
java
//查询某个索引是否存在
boolean exists = client.indices().exists(query -> query.index("products")).value();
System.out.println(exists);
if (exists) {
System.err.println("索引已存在");
} else {
final CreateIndexResponse products = client.indices().create(builder -> builder.index("products"));
System.err.println(products.acknowledged());
}
5:删除指定索引
java
//删除指定索引
boolean exists = client.indices().exists(query -> query.index("products")).value();
System.out.println(exists);
if (exists) {
DeleteIndexResponse response = client.indices().delete(query -> query.index("products"));
System.err.println(response.acknowledged());
} else {
System.err.println("索引不存在");
}
6:查询索引的映射
java
//查询映射信息
final GetIndexResponse response = client.indices().get(builder -> builder.index("produces"));
System.err.println(response.result().get("produces").mappings());
7:创建索引指定映射
numberOfReplicas("1"):设置副本
numberOfShards("1"):设置分片
java
//创建索引指定映射,分片和副本信息
final CreateIndexResponse response = client.indices().create(builder ->
builder.settings(indexSetting -> indexSetting.numberOfReplicas("1").numberOfShards("1")).mappings(
map -> map
.properties("name", propertyBuilder -> propertyBuilder.keyword(keywordProperty -> keywordProperty))
.properties("price", propertyBuilder -> propertyBuilder.double_(doubleNumProperty -> doubleNumProperty))
.properties("des", propertyBuilder -> propertyBuilder.text(textProperty -> textProperty.analyzer("ik_smart").searchAnalyzer("ik_smart")))
).index("produces")
);
8:创建文档
使用HashMap作为数据存储容器
java
//创建文档
//1.创建HashMap进行存储数据,文档要对应映射
final HashMap<String, Object> doc = new HashMap<>();
doc.put("name","辣条");
doc.put("age",12);
doc.put("id","11111");
//2.将文档存入索引中
final IndexResponse response = client.index(builder -> builder.index("produces").id(doc.get("id")).document(doc));
System.err.println(response.version());
使用自定义类作为数据存储容器
实体类
java
@Data
@AllArgsConstructor
@NoArgsConstructor
@ToString
public class Produce {
private String id;
private String name;
private double age;
}
java
//创建文档
final Produce produce = new Produce("123", "小明", 18);
final IndexResponse response = client.index(builder -> builder.index("produces").id(produce.getId()).document(produce));
System.err.println(response.version());
使用外部JSON数据创建
这里要注意我们需要使用StringReader进行读取时使用replace函数将设置的'改为",当然这在真实的业务中肯定不会有,因为真实业务中一定是标准的JSON数据,无需使用replace进行替换了
java
//创建文档
final StringReader input = new StringReader(
"{'name':'农夫三拳','price':3.00,'des':'农夫三拳有点甜'}".replace('\'', '"')
);
final IndexResponse response = client.index(builder -> builder.index("produces").id("44514").withJson(input));
System.err.println(response.version());
9: 查询所有文档
java
final SearchResponse<Object> response = client.search(builder -> builder.index("produces"), Object.class);
final List<Hit<Object>> hits = response.hits().hits();
hits.forEach(
x-> System.err.println(x)
);
10:根据ID查询文档
使用HashMap对应查询
java
//查询文档
final GetResponse<Map> response = client.get(builder -> builder.index("produces").id("116677"), Map.class);
final Map source = response.source();
source.forEach((x,y)->{
System.err.println(x+":"+y);
});
使用自定义类对应查询
java
final GetResponse<Produce> response1 = client.get(builder -> builder.index("produces").id("aabbcc123"), Produce.class);
final Produce source1 = response1.source();
System.err.println(source1.toString());
11:删除文档
java
final GetResponse<Produce> response1 = client.get(builder -> builder.index("produces").id("aabbcc123"), Produce.class);
final Produce source1 = response1.source();
System.err.println(source1.toString());
12:修改文档
全覆盖
java
//修改文档(覆盖)
final Produce produce = new Produce("ccaabb123", "旺仔摇滚洞", "旺仔摇滚洞乱摇乱滚", 10.23D);
final UpdateResponse<Produce> response = client.update(builder -> builder.index("produces").id("aabbcc123").doc(produce), Produce.class);
System.err.println(response.shards().successful());
修改部分文档
区别在于我们需要设置.docAsUpsert(true)表明是修改部分而不是覆盖
java
//修改文档(部分修改)
// final Produce produce = new Produce("ccaabb123", "旺仔摇滚洞", "旺仔摇滚洞乱摇乱滚", 10.23D);
final Produce produce = new Produce();
produce.setName("旺仔摇不动");
final UpdateResponse<Produce> response = client.update(builder -> builder.index("produces").id("aabbcc123").doc(produce).docAsUpsert(true), Produce.class);
System.err.println(response.shards().successful());
13:批量操作
批量新增
java
produceList.add(produce1);
produceList.add(produce2);
produceList.add(produce3);
//构建BulkRequest
final BulkRequest.Builder br = new BulkRequest.Builder();
for (Produce produce : produceList) {
br.operations(op->op.index(idx->idx.index("produces").id(produce.getSku()).document(produce)));
}
final BulkResponse response = client.bulk(br.build());
批量删除
java
List<BulkOperation> bulkOperations = new ArrayList<>();
// 向集合中添加需要删除的文档id信息
for (int i = 0; i < dto.getIds().size(); i++) {
int finalI = i;
bulkOperations.add(BulkOperation.of(b -> b
.delete((d -> d
.index(dto.getIndex())
.id(dto.getIds().get(finalI))
))
));
}
// 调用客户端的bulk方法,并获取批量操作响应结果
BulkResponse response = client
.bulk(e -> e
.index(dto.getIndex())
.operations(bulkOperations));
批量更新
java
JSONObject jsonObject = new JSONObject();
jsonObject.put("id", deleteIds);
jsonObject.put("status", 1);
BulkRequest.Builder br = new BulkRequest.Builder();
for (String deleteId : deleteIds) {
br.operations(op -> op
.update(idx ->
idx.index(EsIndexConstants.opinion_information)
.id(deleteId)
.action(a -> a
.doc(jsonObject)//局部修改
.docAsUpsert(true)//局部修改
)
)).refresh(Refresh.True);
}
BulkRequest bulkRequest = br.build();
BulkResponse result = null;
try {
result = elasticsearchClient.bulk(bulkRequest);
} catch (IOException e) {
throw new RuntimeException(e);
}
DSL查询
1:matchAll查询所有文档
java
//matchAll
final SearchResponse<Produce> response = client.search(builder ->
builder.index("produces")
.query(q ->
q.matchAll(
v->v
)), Produce.class);
System.err.println(response.hits().hits());
2:match 根据字段查询
java
//简单query方式查询
final SearchResponse<Produce> response = client.search(builder ->
builder.index("produces")
.query(q ->
q.match(t ->
t.field("name")
.query("龙虎万精油"))), Produce.class);
System.err.println(response.hits().hits());
3:多id查询
java
//多ID查询
final SearchResponse<Produce> response = client.search(builder ->
builder.index("produces")
.query(q ->
q.ids(sid->sid.values("1000","1001"))), Produce.class);
System.err.println(response.hits().hits());
4:term 不分词查询
java
//term不分词条件查询
final SearchResponse<Produce> response = client.search(builder -> builder.index("produces")
.query(q -> q.term(t -> t.field("name").value("风油精"))), Produce.class);
System.err.println(response.hits().hits());
5:范围查询
java
//范围查询
final SearchResponse<Produce> response = client.search(builder ->
builder.index("produces").query(q ->
q.range(r ->
r.field("price").gt(JsonData.of(5D)).lt(JsonData.of(15D)))),
Produce.class);
System.err.println(response.hits().hits());
6: 前缀查询
java
final SearchResponse<Produce> response = client.search(builder ->
builder.index("produces").query(q ->q.prefix(p->p.field("name").value("六"))),
Produce.class);
System.err.println(response.hits().hits());
7:匹配查询
//匹配查询
java
final SearchResponse<Produce> response = client.search(builder ->
builder.index("produces").query(q ->q.wildcard(w->w.field("name").value("风*"))),
Produce.class);
System.err.println(response.hits().hits());
?单字符匹配
java
//匹配查询
final SearchResponse<Produce> response = client.search(builder ->
builder.index("produces").query(q ->q.wildcard(w->w.field("name").value("风?精"))),
Produce.class);
System.err.println(response.hits().hits());
8:模糊查询
java
//模糊查询
final SearchResponse<Produce> response = client.search(builder ->
builder.index("produces").query(q ->q.fuzzy(f->f.field("name").value("六仙花露水"))),
Produce.class);
System.err.println(response.hits().hits());
9:多条件查询
使用bool关键字配合must,should,must_not
- must:所有条件必须同时成立
- must_not:所有条件必须同时不成立
- should:所有条件中成立一个即可
java
//多条件
final SearchResponse<Produce> response = client.search(builder ->
builder.index("produces").query(q ->
q.bool(b ->
b.must(t ->
t.term(v ->
v.field("name")
.value("旺仔摇不动")))
.must(t2 ->
t2.term(v2 ->
v2.field("price")
.value(0.0D))))),
Produce.class);
System.err.println(response.hits().hits());
或者创建BoolQuery.Builder,以便进行业务判断是否增加查询条件
java
List<FieldValue> fieldValues = new ArrayList<>();
fieldValues.add(FieldValue.of(10));
fieldValues.add(FieldValue.of(100));
BoolQuery.Builder boolQuery = new BoolQuery.Builder();
boolQuery.must(t->
t.terms(v->
v.field("label")
.terms(term->
term.value(fieldValues))));
boolQuery.must(t->
t.match(f->
f.field("name")
.query("旺仔")));
SearchResponse<Object> search = elasticsearchClient.search(builder -> builder.index("my_test_index")
.query(q->
q.bool(boolQuery.build())),Object.class);
10:多字段查询-multiMatch
java
//多字段查询
final SearchResponse<Produce> response = client.search(builder ->
builder.index("produces").query(q->q.multiMatch(qs->qs.query("蚊虫叮咬 辣眼睛").fields("name","des"))),
Produce.class);
System.err.println(response.hits().hits());
11:高亮显示
我们注意要设置前缀和后缀
java
//高亮显示
final SearchResponse<Produce> response = client.search(builder ->
builder.index("produces")
.query(q -> q.match(v -> v.field("name").query("风油精")))
.highlight(h -> h.preTags("<span>").postTags("<span>").fields("name", hf -> hf)),
Produce.class);
System.err.println(response.toString());
12:分页查询
我们使用match_all进行全部搜索的时候使用size关键字设置每一页的大小,使用from关键字设置页码
from的计算公式:(页码-1)*size
java
//分页查询
final SearchResponse<Produce> response = client.search(builder ->
builder.index("produces")
.query(q->q.matchAll(v->v)).size(2).from(0),
Produce.class);
System.err.println(response.hits().hits());
12-1:使用分页时,最多返回10000条。需要进行设置
java
//分页查询
final SearchResponse<Produce> response = client.search(builder ->
builder.index("produces")
.query(q->q.matchAll(v->v))
.size(2)
.from(0)
.trackTotalHits(t->t.enabled(true)),
Produce.class);
System.err.println(response.hits().hits());
13:排序
使用sort关键字指定需要进行排序的字段设置排序类型即可,我们这里会使用到SortOrder枚举类来进行指定排序方式
desc:降序
asc:升序
java
//排序
final SearchResponse<Produce> response = client.search(builder ->
builder.index("produces")
.query(q->q.matchAll(v->v))
.sort(builder1 -> builder1.field(f->f.field("price").order(SortOrder.Asc))),
Produce.class);
System.err.println(response.hits().hits());
14:指定字段查询
使用_source关键字在数组中设置需要展示的字段
值得注意的是在source方法中需要我们写filter去指定是include包含或是exclude去除xx字段
java
//指定字段查询
final SearchResponse<Produce> response = client.search(builder ->
builder.index("produces")
.query(q->q.matchAll(v->v))
.source(s->s.filter(v->v.includes("price","des"))),
Produce.class);
System.err.println(response.hits().hits());
15:聚合查询-求最大值
java
SearchResponse<Object> search = elasticsearchClient.search(builder ->
builder.index("my_test_index")
.from(0)
.size(1)
.aggregations("aa", t ->
t.max(f->
f.field("type"))), Object.class);
EsResult esResult = EsUtils.searchAnalysis(search);
Aggregate aa = esResult.getAggregations().get("aa");
LongTermsAggregate lterms = aa.lterms();
Buckets<LongTermsBucket> buckets = lterms.buckets();
List<LongTermsBucket> array = buckets.array();
16:桶聚合查询-劣势 group by
java
SearchResponse<JSONObject> search = elasticsearchClient.search(builder ->
builder.index(EsIndexConstants.article_info)
.query(t->
t.range(f->
f.field("create_time")
.gte(JsonData.of(startDate))
.lte(JsonData.of(endDate))))
.from(0)
.size(1)
.aggregations("countValue", t ->
t.terms(f -> f.field("ata_type.keyword")))
, JSONObject.class);
Aggregate countValue = search .getAggregations().get("countValue");
List<StringTermsBucket> array = countValue.sterms().buckets().array();