1. 根据价格分组统计数量，每组区间为2000，

filter_path=aggregations 设置查询结果只展示函数结果

也有date_histogram函数根据日期分组等等

GET order/_search?filter_path=aggregations
{"aggs": {"hist_price": {"histogram": {"field": "price","interval": 2000,# "min_doc_count": 1  # 设置只有数量大于1的才会展示}}}
}
查询结果：
{"aggregations" : {"hist_price" : {"buckets" : [{"key" : 0.0,"doc_count" : 1},{"key" : 2000.0,"doc_count" : 4},{"key" : 4000.0,"doc_count" : 0},{"key" : 6000.0,"doc_count" : 1}]}}
}

 2. 查询20%之内，50%之内，100%之内的价格都在多少钱之下

查询结果为近似值跟ES的算法有关

GET order/_search?filter_path=aggregations
{"aggs": {"percent_price": {"percentiles": {"field": "price","percents": [20,50,100]}}}
}
查询结果：
{"aggregations" : {"percent_price" : {"values" : {"20.0" : 1700.0000000000002,"50.0" : 2500.0,"100.0" : 6000.0}}}
}

3. 查询2的相反情况，例：查询2000,和 6000之内的占比

GET order/_search?filter_path=aggregations
{"aggs": {"percent_price": {"percentile_ranks": {"field": "price","values": [2000,6000]}}}
}
查询结果：
{"aggregations" : {"percent_price" : {"values" : {"2000.0" : 16.666666666666664,"6000.0" : 82.73866923818709}}}
}