分组聚合及嵌套查询
聚合查询可以理解为SQL中的求和、求最大值、最小值以及求均值的需求
嵌套可以理解为es存值的某一个字段为对象属性的值做处理.
Elasticsearch Java API分组与聚合结合
- 其中对字段field_one进行分组,分组的别名为fieldOne,取2^31-1组数据.如果不设置size,查询的结果会返回默认size大小.
AggregationBuilder oneAgg =
AggregationBuilders.terms(“fieldOne”) .field(“field_one”).size(2^31-1);
- 需要对多个字段分组
// 再创建一个
AggregationBuilder twoAgg
= AggregationBuilders.terms(“fieldTwo”) .field(“field_two”).size(2^31-1);
// 将两个分组结合
searchSourceBuilder.aggregation(oneAgg.subAggregation(twoAgg));
- 需要将分组结果的其他字段再进行统计的sum、min、max、avg聚合
AggregationBuilder threeAgg =
AggregationBuilders.sum(“fieldThree”).field(“field_three”);
// 将数据通过field_one、field_two字段进行分组,对field_three进行求和聚合
searchSourceBuilder.aggregation(oneAgg.subAggregation(twoAgg.subAggregation(threeAgg)));
- 只聚合不分组
searchSourceBuilder.aggregation(threeAgg);
简单的分组查询
// 分页设置
private Integer start = 0;
private Integer length = 20;
EsPage esPage = new EsPage(start,length);
// 排序设置
List<EsSort> esSorts = Lists.newArrayList(new EsSort("userId", SortOrder.ASC),
new EsSort(id, SortOrder.DESC));
// 查询条件
BoolQueryBuilder queryBuilder = new BoolQueryBuilder();
queryBuilder.must(new TermQueryBuilder("userName","xxxx" ));
// 组装查询对象
SearchRequest searchRequest = new SearchRequest("user_list");
// 1、添加普通查询条件
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder()
.query(queryBuilder)
// 聚合无视query筛选出的数据
.size(0)
.from(0)
.fetchSource(false);
// 组装聚合查询的条件
TermsAggregationBuilder aggregationBuilder = AggregationBuilders.terms("group_by_userId")
// 需要查询的字段
.field("userId")
// 分页
.size(page.getPage() + page.getSize());
// 2、添加聚合查询条件
searchSourceBuilder.aggregation(aggregationBuilder);
// 3、添加排序条件
searchSourceBuilder.sort(sort.getSortFiled(), sort.getSortOrder());
searchRequest.source(searchSourceBuilder);
try {
SearchResponse searchResponse = restClient.search(searchRequest, RequestOptions.DEFAULT);
// 获取总数
long sumTotal = searchResponse.getHits().getTotalHits().value;
if (sumTotal >= MAX_PAGE_DEPTH) {
throw new EsDataException("目前暂不支持超过10000条的数据进行视图聚合，请修改聚合任务的数量");
}
// sumTotal:查询出来的总数
// searchResponse.getAggregations():聚合之后查询出来的数据
return Pair.of(sumTotal, searchResponse.getAggregations());
} catch (IOException e) {
EsExceptionUtil.dealIOException(e);
} catch (ElasticsearchException e1) {
EsExceptionUtil.dealElasticsearchException(e1);
}
解析查聚合结果
// 查询出来的总数
int count = pair.getLeft().intValue();
// 聚合之后查询出来的数据
Aggregations aggregations = pair.getRight();
// 根据聚合时的聚合名称,获取数据
Terms terms = aggregations.get("group_by_userId");
List<Long> userIds = Lists.newArrayList();
if (terms != null && CollectionUtils.isNotEmpty(terms.getBuckets())) {
// terms.getBuckets():就是聚合之后的每条数据桶
for (Terms.Bucket bucket : terms.getBuckets()) {
// 遍历得到桶中的key,就是聚合后,查询的字段L:userId
long key = NumberUtils.toLong(bucket.getKeyAsString(), 0);
if (key == 0) {
continue;
}
userIds.add(key);
}
}
上面是最简单的一层聚合查询,其实其他复杂的聚合也都是大同小异,就是一个套娃的操作.
复杂聚合查询
public Map<String, Map<String, Long>> aggTwoArgs(String indices, QueryBuilder queryBuilder, String args1, String args2, int i) throws IOException {
Map<String, Map<String, Long>> map = new HashMap<>();
//设置要查询的索引
SearchRequest request = new SearchRequest().indices(indices);
//构建搜索
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
//添加搜索长度
sourceBuilder.size(0);
//添加搜索条件
sourceBuilder.query(queryBuilder);
//设置要聚合的字段以及条数
//设置该次聚合的名称 terms(args1)
//以及要聚合的字段field(args1 + ".keyword") 添加keyword是对字段进行不分词查询。
TermsAggregationBuilder agg1 = AggregationBuilders.terms(args1).field(args1 + ".keyword").size(i);
//设置子聚合以及条数，设置返回数据中该聚合的名称 terms(args2)，以及要聚合的字段field(args2 + ".keyword")
TermsAggregationBuilder agg2 = AggregationBuilders.terms(args2).field(args2 + ".keyword").size(i);
//合并子聚合
agg1.subAggregation(agg2);
//添加聚合查询
sourceBuilder.aggregation(agg1);
//创建请求
request.source(sourceBuilder);
//发送请求
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
Aggregations aggregations = response.getAggregations();
// 取第一个分组
Terms terms1 = aggregations.get(args1);
for (Terms.Bucket bucket1 : terms1.getBuckets()) {
// 取分组下的分组
Terms terms2 = bucket1.getAggregations().get(args2);
Map<String, Long> map1 = new HashMap<>();
for (Terms.Bucket bucket2 : terms2.getBuckets()) {
map1.put(bucket2.getKeyAsString(), bucket2.getDocCount());
}
// bucket1.getKeyAsString():第一个分组的值
// map1:第二个分组下的map值
map.put(bucket1.getKeyAsString(), map1);
}
return map;
}
ElasticSearch Java API嵌套文章来源：https://www.toymoban.com/news/detail-503681.html
public static final String MAPPING = ""
+ "{\n"
+ " \"properties\": {\n"
+ " \"itemAttributes\": {\n"
+ " \"type\": \"nested\",\n"
+ " \"properties\": {\n"
+ " \"specId\": {\n"
+ " \"type\": \"long\"\n"
+ " },\n"
+ " \"value\": {\n"
+ " \"type\": \"text\",\n"
+ " \"analyzer\": \"ngram_analyzer\",\n"
+ " \"fields\": {\n"
+ " \"value_keyword\": {\n"
+ " \"type\": \"keyword\"\n"
+ " }\n"
+ " }\n"
+ " },\n"
+ " \"key\": {\n"
+ " \"type\": \"long\"\n"
+ " },\n"
+ " \"ip\": {\n"
+ " \"type\": \"long\"\n"
+ " }\n"
+ " }\n"
+ " }\n"
+ " }\n"
+ "}";
上面ES的mapping中的itemAttributes字段就是一个嵌套式的数据结构.
所以上面的分组和聚合对itemAttributes对象下的属性不适用,需要再做一层处理.文章来源地址https://www.toymoban.com/news/detail-503681.html
// 对于嵌套的聚合,需要新建一个NestedAggregationBuilder 对象”nestedAgg”为别名
NestedAggregationBuilder nestedAggregationBuilder =
AggregationBuilders.nested(“nestedAgg”, “itemAttributes”);
// 分别对nested对象下的属性建分组
AggregationBuilder specIdAgg =
AggregationBuilders.terms(“fieldSpecId”).field(“itemAttributes.specId”).size(2 ^ 31 - 1);
AggregationBuilder valueAgg =
AggregationBuilders.terms(“fieldValue”).field(“itemAttributes.value”).size(2 ^ 31 - 1);
AggregationBuilder keyAgg =
AggregationBuilders.terms(“fieldKey”).field(“itemAttributes.key”).size(2 ^ 31 - 1);
AggregationBuilder ipAgg =
AggregationBuilders.terms(“fieldIp”).field(“itemAttributes.ip”).size(2 ^ 31 - 1);
// 再将上面写的一个个聚合体放入nestedAggregationBuilder,需要将上面的specIdAgg、valueAgg、keyAgg聚合相互之间有关联需要一层一层关联如下
nestedAggregationBuilder.subAggregation(
specIdAgg.subAggregation(valueAgg.subAggregation(ipAgg.subAggregation(
AggregationBuilders.sum(“keyAgg”).field(“itemAttributes.key”)))));
searchSourceBuilder.query(boolQueryBuilder).size(0);
searchSourceBuilder.aggregation(nestedAggregationBuilder);
searchRequest.source(searchSourceBuilder);
// 注意searchSourceBuilder.aggregation(nestedAggregationBuilder);
// 这个段代码这是定义聚合方式的。
// searchSourceBuilder
//.aggregation(specIdAgg)
//.aggregation(valueAgg)
//.aggregation(ipAgg)
//.aggregation(keyAgg);
// 和上方聚合方式完全不一样,单一将数据分组,聚合相互之间没有关联.
try {
SearchResponse searchResponse = restHighLevelClient.search(searchRequest);
Nested nested = searchResponse.getAggregations().get(“nestedAgg”);
Aggregations nestedAggregations = nested.getAggregations();
Aggregation nestedAggregation = nestedAggregations.asList().get(0);
// 取第一个分组
List<? extends Terms.Bucket> specIdBuckets = (
(ParsedStringTerms) nestedAggregation).getBuckets();
for (Terms.Bucket specIdBucket : specIdBuckets ) {
// 第一个分组的值
String specId = specIdBucket .getKey().toString();
// 取第二个分组
List<Aggregation> valueAggregations = specIdBucket .getAggregations().asList();
List<? extends Terms.Bucket> valueBuckets = ((ParsedStringTerms) valueAggregations .get(0)).getBuckets();
for (Terms.Bucket valueBucket : valueBuckets ) {
// 第二个分组的值
String vlaue = valueBucket .getKey().toString();
// 取第三个分组
List<Aggregation> ipAggregations = valueBucket.getAggregations()
.asList();
List<? extends Terms.Bucket> ipBuckets =
((ParsedStringTerms)ipAggregations .get(0)).getBuckets();
for (Terms.Bucket ipBucket : ipBuckets ) {
// 第三个分组的值
String ip= ipBucket .getKey().toString();
// 第四个分组
Aggregation keyeAggregation = ipBucket .getAggregations().asList().get(0);
// 第四个分组的值
Integer count = (int) ((ParsedSum) keyAggregation ).getValue();
System.out.print(fieldOne);
System.out.print(filedtwo);
System.out.print(ip);
System.out.print(count );
}
}
}
} catch (IOException e) {
log.error("数据解析错误:{}", e);
}
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