我目前有一个ES查询，它使用geohash_grid和date_histogram为我提供了“geo buckets”列表:
"aggregations": {
"zoomedInView": {
"filter": {
"geo_bounding_box": {
"location": {
"top_left": "-37, 140",
"bottom_right": "-38, 146"
}
}
},
"aggregations": {
"zoom1": {
"geohash_grid": {
"field": "location",
"precision": 6
},
"aggs": {
"ts": {
"date_histogram": {
"min_doc_count" : 1,
"field": "dateTime",
"interval": "1m",
"format": "DDD HH:mm"
}
},
"map_zoom": {
"geo_bounds": {
"field": "location"
}
}
}
}
}
}
这给我的结果看起来像:
{
"key": "r1r0fu",
"map_zoom": {
"bounds": {
"top_left": {
"lat": -38.81073913909495,
"lon": 124.96536672115326
},
"bottom_right": {
"lat": -38.81329075805843,
"lon": 124.96823584660888
}
}
},
"ts": {
"buckets": [
{
"key_as_string": "136 20:15",
"key": 1463354100000,
},
{
"key_as_string": "137 04:30",
"key": 1463365800000,
"doc_count": 1
},
....
{
"key": "r1r0gx",
"map_zoom": {
"bounds": {
"top_left": {
"lat": -38.798130828887224,
"lon": 124.99871227890253
},
"bottom_right": {
"lat": -38.79820383526385,
"lon": 124.99872468411922
}
}
},
"ts": {
"buckets": [
{
"key_as_string": "136 23:21",
"key": 1463354460000,
},
{
"key_as_string": "137 02:30",
"key": 1463365800000,
},
{
"key_as_string": "137 03:31",
"key": 1463369460000,
}
]
}
},
在上面的示例中，结果按地理位置存储区
r1r0fu和r1r0gx排序，并且在存储区中按顺序排序了事件的时间(按年HHH:mm格式)及其计数。我真正想要的是:
1)结果按时间排序，这可能意味着同一存储桶将出现多次。
2)仅在每个存储桶内显示最短和最大时间(如果可能)
因此，上面的结果理想情况下将如下所示:
{
"key": "r1r0fu",
"map_zoom": {
"bounds": {
"top_left": {
"lat": -38.81073913909495,
"lon": 124.96536672115326
},
"bottom_right": {
"lat": -38.81329075805843,
"lon": 124.96823584660888
}
}
},
"ts": {
"buckets": [
{
"key_as_string": "136 20:15",
"key": 1463354100000,
},
]
}
},
{
"key": "r1r0gx",
"map_zoom": {
"bounds": {
"top_left": {
"lat": -38.798130828887224,
"lon": 124.99871227890253
},
"bottom_right": {
"lat": -38.79820383526385,
"lon": 124.99872468411922
}
}
},
"ts": {
"buckets": [
{
"key_as_string": "136 23:21",
"key": 1463354460000,
},
{
"key_as_string": "137 03:31",
"key": 1463369460000,
},
}
},
{
"key": "r1r0fu",
"map_zoom": {
"bounds": {
"top_left": {
"lat": -38.81073913909495,
"lon": 124.96536672115326
},
"bottom_right": {
"lat": -38.81329075805843,
"lon": 124.96823584660888
}
}
},
"ts": {
"buckets": [
{
"key_as_string": "137 04:30",
"key": 1463365800000,
}
]
}
},
...
结果按时间排序，因此在这种情况下，存储段
r1r0fu出现两次。事件"key_as_string": "137 02:30",已被隐藏，因为它不是最小或最大日期。反正有可能吗？
非常感谢!
最佳答案
如果您希望按时间排序结果，则最好将date_histogram聚合与geohash_grid交换为更好，如下所示:
{
"aggregations": {
"zoomedInView": {
"filter": {
"geo_bounding_box": {
"location": {
"top_left": "-37, 140",
"bottom_right": "-38, 146"
}
}
},
"aggregations": {
"ts": {
"date_histogram": {
"min_doc_count": 1,
"field": "dateTime",
"interval": "1m",
"format": "DDD HH:mm"
},
"aggs": {
"zoom1": {
"geohash_grid": {
"field": "location",
"precision": 6
}
},
"map_zoom": {
"geo_bounds": {
"field": "location"
}
}
}
}
}
}
}
}
这将解决问题1)。但是，由于现在每个主存储区都将是一个时间存储区，因此您将不再具有最小和最大时间。试试看，看看它是否适合您的需求。
关于elasticsearch - 使用 Elasticsearch 地理功能查找按时间排序的最常见位置，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/37381322/