我有此查询来计算每个存储桶中的事件数。如何计算value大于0的存储桶总数？
GET myindex/_search?
{
"size": 0,
"query": {
"bool": {
"must": [
{
"match": {
"PlateNumber": "111"
}
}
]
}
},
"aggs": {
"daily_intensity": {
"date_histogram": {
"field": "Datetime",
"interval": "day"
},
"aggs": {
"count_of_events": {
"value_count": {
"field": "Monthday"
}
}
}
}
}
}
这是我得到的输出。我想要得到的预期答案是
26，因为存储桶中总共有26个元素的value大于0。基本上，我不需要所有存储桶的输出，我只需要这个总数。{
"took": 237,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 98,
"max_score": 0,
"hits": []
},
"aggregations": {
"daily_intensity": {
"buckets": [
{
"key_as_string": "2017-05-01T00:00:00.000Z",
"key": 1493596800000,
"doc_count": 3,
"count_of_events": {
"value": 3
}
},
{
"key_as_string": "2017-05-02T00:00:00.000Z",
"key": 1493683200000,
"doc_count": 1,
"count_of_events": {
"value": 1
}
},
{
"key_as_string": "2017-05-03T00:00:00.000Z",
"key": 1493769600000,
"doc_count": 4,
"count_of_events": {
"value": 4
}
},
{
"key_as_string": "2017-05-04T00:00:00.000Z",
"key": 1493856000000,
"doc_count": 6,
"count_of_events": {
"value": 6
}
},
{
"key_as_string": "2017-05-05T00:00:00.000Z",
"key": 1493942400000,
"doc_count": 0,
"count_of_events": {
"value": 0
}
},
{
"key_as_string": "2017-05-06T00:00:00.000Z",
"key": 1494028800000,
"doc_count": 1,
"count_of_events": {
"value": 1
}
},
{
"key_as_string": "2017-05-07T00:00:00.000Z",
"key": 1494115200000,
"doc_count": 5,
"count_of_events": {
"value": 5
}
},
{
"key_as_string": "2017-05-08T00:00:00.000Z",
"key": 1494201600000,
"doc_count": 6,
"count_of_events": {
"value": 6
}
},
{
"key_as_string": "2017-05-09T00:00:00.000Z",
"key": 1494288000000,
"doc_count": 2,
"count_of_events": {
"value": 2
}
},
{
"key_as_string": "2017-05-10T00:00:00.000Z",
"key": 1494374400000,
"doc_count": 3,
"count_of_events": {
"value": 3
}
},
{
"key_as_string": "2017-05-11T00:00:00.000Z",
"key": 1494460800000,
"doc_count": 0,
"count_of_events": {
"value": 0
}
},
{
"key_as_string": "2017-05-12T00:00:00.000Z",
"key": 1494547200000,
"doc_count": 3,
"count_of_events": {
"value": 3
}
},
{
"key_as_string": "2017-05-13T00:00:00.000Z",
"key": 1494633600000,
"doc_count": 0,
"count_of_events": {
"value": 0
}
},
{
"key_as_string": "2017-05-14T00:00:00.000Z",
"key": 1494720000000,
"doc_count": 1,
"count_of_events": {
"value": 1
}
},
{
"key_as_string": "2017-05-15T00:00:00.000Z",
"key": 1494806400000,
"doc_count": 3,
"count_of_events": {
"value": 3
}
},
{
"key_as_string": "2017-05-16T00:00:00.000Z",
"key": 1494892800000,
"doc_count": 0,
"count_of_events": {
"value": 0
}
},
{
"key_as_string": "2017-05-17T00:00:00.000Z",
"key": 1494979200000,
"doc_count": 1,
"count_of_events": {
"value": 1
}
},
{
"key_as_string": "2017-05-18T00:00:00.000Z",
"key": 1495065600000,
"doc_count": 3,
"count_of_events": {
"value": 3
}
},
{
"key_as_string": "2017-05-19T00:00:00.000Z",
"key": 1495152000000,
"doc_count": 2,
"count_of_events": {
"value": 2
}
},
{
"key_as_string": "2017-05-20T00:00:00.000Z",
"key": 1495238400000,
"doc_count": 1,
"count_of_events": {
"value": 1
}
},
{
"key_as_string": "2017-05-21T00:00:00.000Z",
"key": 1495324800000,
"doc_count": 1,
"count_of_events": {
"value": 1
}
},
{
"key_as_string": "2017-05-22T00:00:00.000Z",
"key": 1495411200000,
"doc_count": 5,
"count_of_events": {
"value": 5
}
},
{
"key_as_string": "2017-05-23T00:00:00.000Z",
"key": 1495497600000,
"doc_count": 16,
"count_of_events": {
"value": 16
}
},
{
"key_as_string": "2017-05-24T00:00:00.000Z",
"key": 1495584000000,
"doc_count": 4,
"count_of_events": {
"value": 4
}
},
{
"key_as_string": "2017-05-25T00:00:00.000Z",
"key": 1495670400000,
"doc_count": 6,
"count_of_events": {
"value": 6
}
},
{
"key_as_string": "2017-05-26T00:00:00.000Z",
"key": 1495756800000,
"doc_count": 1,
"count_of_events": {
"value": 1
}
},
{
"key_as_string": "2017-05-27T00:00:00.000Z",
"key": 1495843200000,
"doc_count": 5,
"count_of_events": {
"value": 5
}
},
{
"key_as_string": "2017-05-28T00:00:00.000Z",
"key": 1495929600000,
"doc_count": 4,
"count_of_events": {
"value": 4
}
},
{
"key_as_string": "2017-05-29T00:00:00.000Z",
"key": 1496016000000,
"doc_count": 5,
"count_of_events": {
"value": 5
}
},
{
"key_as_string": "2017-05-30T00:00:00.000Z",
"key": 1496102400000,
"doc_count": 2,
"count_of_events": {
"value": 2
}
},
{
"key_as_string": "2017-05-31T00:00:00.000Z",
"key": 1496188800000,
"doc_count": 4,
"count_of_events": {
"value": 4
}
}
]
}
}
}
最佳答案
您可以使用Bucket Script Aggregation和Sum Bucket Aggregation来实现。请尝试以下查询。
GET myindex/_search?
{
"size": 0,
"query": {
"bool": {
"must": [
{
"match": {
"PlateNumber": "111"
}
}
]
}
},
"aggs": {
"daily_intensity": {
"date_histogram": {
"field": "Datetime",
"interval": "day"
},
"aggs": {
"count_of_events": {
"value_count": {
"field": "Monthday"
}
},
"check": {
"bucket_script": {
"buckets_path": {
"count": "count_of_events"
},
"script": "return (params.count > 0 ? 1 : 0)"
}
}
}
},
"bucket_count": {
"sum_bucket": {
"buckets_path": "daily_intensity>check"
}
}
}
}
关于elasticsearch - 如何计算 “value”大于0的存储桶总数？，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/46871700/