聚合查询不是直接查询文档数据，而是对文档数据按照某些维度进行统计，如果你熟悉 MySql 的聚合查询，这个也就好理解了。之前我们已经学习了使用 RESTful API 聚合查询，现在学 Java High Level REST Client 的聚合查询也就很简单了，
我们还是使用上一篇的文档数据学习聚合查询：
我们一般可以使用AggregationBuilders类的静态方法来构建需要的聚合方式。它会返回一个 Builder 类，当然你也可以直接new一个指定聚合方式的 Builder 类。
1、avg
public void avg() throws IOException {
SearchRequest request = new SearchRequest("user");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 统计文档中age字段的平均值，avgAge相当于统计结果的名称
AvgAggregationBuilder avgBuilder = AggregationBuilders.avg("avgAge").field("age");
// 设置聚合查询
searchSourceBuilder.aggregation(avgBuilder);
request.source(searchSourceBuilder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 取出统计结果
Avg avg = response.getAggregations().get("avgAge");
double value = avg.getValue();
System.out.println(value);
}
上边是统计age的平均值，注意，由于没有添加其它查询条件，则会统计索引中所有文档。
2、max
统计age的最大值：
public void max() throws IOException {
SearchRequest request = new SearchRequest("user");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 统计文档中age字段的最大值
MaxAggregationBuilder maxBuilder = AggregationBuilders.max("maxAge").field("age");
searchSourceBuilder.aggregation(maxBuilder);
request.source(searchSourceBuilder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 取出统计结果
Max max = response.getAggregations().get("maxAge");
double value = max.getValue();
System.out.println(value);
}
3、min、sum
统计最小值以及求和的实现上边的类似，就不详细说了：
MinAggregationBuilder minBuilder = AggregationBuilders.min("minAge").field("age");
SumAggregationBuilder sumBuilder = AggregationBuilders.sum("sumAge").field("age");
4、range
range表示按区间统计，比如指定时间范围，指定大小区间等。如下统计age在(-∞, 30)、[30,40]、(40,+∞)三个区间的人数：
public void range() throws IOException {
SearchRequest request = new SearchRequest("user");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 统计文档中age字段的最大值
RangeAggregationBuilder rangeBuilder = AggregationBuilders.range("rangeAge")
.field("age")
.addUnboundedTo(30)
.addRange(30, 40)
.addUnboundedFrom(40);
searchSourceBuilder.aggregation(rangeBuilder);
request.source(searchSourceBuilder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 取出统计结果
Range range = response.getAggregations().get("rangeAge");
for (Range.Bucket bucket : range.getBuckets()) {
// 打印每个区间的人数
System.out.println("age区间 " + bucket.getKeyAsString() + " 的人数：" + bucket.getDocCount());
}
统计的结果如下：
5、filter
filter可以按指定的查询条件过滤数据，如下统计姓school是北大的人数：
public void filter() throws IOException {
SearchRequest request = new SearchRequest("user");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 统计文档中school是北大的人数
// 先构建查询条件
TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("school.keyword", "北大");
// 设置过滤统计的查询条件
FilterAggregationBuilder filterBuilder = AggregationBuilders.filter("count", termQueryBuilder);
searchSourceBuilder.aggregation(filterBuilder);
request.source(searchSourceBuilder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 取出统计结果
Filter filter = response.getAggregations().get("count");
double value = filter.getDocCount();
System.out.println(value);
}
6、count
count是统计数量的，如下根据文档 id 统计索引中的文档数：
public void valueCount() throws IOException {
SearchRequest request = new SearchRequest("user");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 根据文档id统计索引的文档数
ValueCountAggregationBuilder valueCountBuilder = AggregationBuilders.count("count").field("_id");
searchSourceBuilder.aggregation(valueCountBuilder);
request.source(searchSourceBuilder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 取出统计结果
ValueCount valueCount = response.getAggregations().get("count");
double value = valueCount.getValue();
System.out.println(value);
}
7、terms
terms是按指定字段对文档数据进行分组，如下按school字段进行分组，统计出前20组（默认10组），并按每组的数据量升序排列（默认降序）：
public void terms() throws IOException {
SearchRequest request = new SearchRequest("user");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 按照school分组
TermsAggregationBuilder termsBuilder = AggregationBuilders.terms("schoolGroup")
.field("school.keyword")
// 按每组的数据量升序排列
.order(BucketOrder.aggregation("_count", true))
// 最多统计出20组数据
.size(20);
searchSourceBuilder.aggregation(termsBuilder);
request.source(searchSourceBuilder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 取出统计结果
Terms terms = response.getAggregations().get("schoolGroup");
for (Terms.Bucket bucket : terms.getBuckets()) {
System.out.println(bucket.getKeyAsString() + " 的人数：" + bucket.getDocCount());
}
}
8、子统计
上边我们使用terms对文档数据按照school字段进行了分组，我们还可以对组内的数据进行其它统计，例如统计age的最小值，这就是子统计。代码如下：
public void sub() throws IOException {
SearchRequest request = new SearchRequest("user");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 按照school分组
TermsAggregationBuilder termsBuilder = AggregationBuilders.terms("schoolGroup")
.field("school.keyword")
// 按每组的数据量升序排列
.order(BucketOrder.aggregation("_count", true))
// 最多统计出20组数据
.size(20)
// 添加子统计
.subAggregation(AggregationBuilders.min("minAge").field("age"));
searchSourceBuilder.aggregation(termsBuilder);
request.source(searchSourceBuilder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 取出统计结果
Terms terms = response.getAggregations().get("schoolGroup");
for (Terms.Bucket bucket : terms.getBuckets()) {
// 取出子统计的结果
Min min = bucket.getAggregations().get("minAge");
System.out.println(bucket.getKeyAsString() + " 的人数：" + bucket.getDocCount() + "，age的最小值：" + min.getValue());
}
}
9、topHits
前边的各种聚合查询只能统计出最终的结果，我们并不能知道那些文档数据参与了统计，topHits可以用来跟踪正在参与分组聚合统计的文档数据，我在前边terms例子的基础上继续修改，来跟踪每组内的前20条数据（默认10条数据），并按age升序排列：
public void topHits() throws IOException {
SearchRequest request = new SearchRequest("user");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 跟踪正在参与分组聚合统计的文档数据
TopHitsAggregationBuilder topHitsBuilder = AggregationBuilders.topHits("groupData")
// 跟踪前20条数据
.size(20)
// 按age升序排列
.sort("age", SortOrder.ASC);
// 按照school分组
TermsAggregationBuilder termsBuilder = AggregationBuilders.terms("schoolGroup")
.field("school.keyword")
// 按每组的数据量升序排列
.order(BucketOrder.aggregation("_count", true))
// 最多统计出20组数据
.size(20)
// 添加文档数据跟踪
.subAggregation(topHitsBuilder);
searchSourceBuilder.aggregation(termsBuilder);
request.source(searchSourceBuilder);
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 取出统计结果
Terms terms = response.getAggregations().get("schoolGroup");
for (Terms.Bucket bucket : terms.getBuckets()) {
System.out.println(bucket.getKeyAsString() + " 的人数：" + bucket.getDocCount());
// 取出topHits跟踪的文档数据
TopHits groupData = bucket.getAggregations().get("groupData");
for (SearchHit hit : groupData.getHits()) {
System.out.println(hit.getSourceAsString());
}
System.out.println("---------------------------------------------------------------------------");
}
}
聚合查询的相关内容就介绍这么多了，更多的可以查看官方文档。
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