elasticsearch 如何识别哪些字段具有共同的聚合值
elasticsearch how to identify which fields have the common aggregated values
我有一个场景，对于文档中的聚合值，我希望每个聚合响应都有聚合值，例如在下面的文档中，如果我按项目、目的地位置、源位置、传输模式、到达日期聚合，发货日期我有 2 个相同的文档，id 为 1，另一个文档具有相同的属性，但 id 为 2，所以我在响应中需要这两个唯一的 id，并且我已经附加了查询。
{
"id": "1",
"exceptionId": "1",
"shipmentId": "123",
"primaryRecommendation": true,
"priority": 1,
"sourceLocation": "DC4",
"transferQuantity": 40,
"destinationLocation":"DC1",
"shipDate": "2019-01-11T05:30:00.000+0530",
"arrivalDate": "2019-01-12T05:30:00.000+0530",
"transportMode": "Road",
"transferCost": 200.0,
"maxQtyAvailableForTransfer": 40,
"totalQtyAtSource": 40,
"operation": "Road-Item1-from-DC3-to-DC1",
"peggedStockDemandIds": "",
"revenueRecovered": 20000.0
}
{
"id": "1",
"exceptionId": "1",
"shipmentId": "123",
"primaryRecommendation": true,
"priority": 1,
"sourceLocation": "DC4",
"destinationLocation":"DC1",
"transferQuantity": 40,
"shipDate": "2019-01-11T05:30:00.000+0530",
"arrivalDate": "2019-01-12T05:30:00.000+0530",
"transportMode": "Road",
"transferCost": 200.0,
"maxQtyAvailableForTransfer": 40,
"totalQtyAtSource": 40,
"operation": "Road-Item1-from-DC3-to-DC1",
"peggedStockDemandIds": "",
"revenueRecovered": 20000.0
}
{
"id": "2",
"exceptionId": "1",
"shipmentId": "123",
"primaryRecommendation": true,
"priority": 1,
"sourceLocation": "DC4",
"destinationLocation":"DC1",
"transferQuantity": 40,
"shipDate": "2019-01-11T05:30:00.000+0530",
"arrivalDate": "2019-01-12T05:30:00.000+0530",
"transportMode": "Road",
"transferCost": 200.0,
"maxQtyAvailableForTransfer": 40,
"totalQtyAtSource": 40,
"operation": "Road-Item1-from-DC3-to-DC1",
"peggedStockDemandIds": "",
"revenueRecovered": 20000.0
}
{
"query": {
"bool": {
"must": {
"query_string": {
"default_field": "shipmentId",
"query": "\"123\""
}
},
"filter": {
"terms": {
"exceptionId": [
"2",
"1"
]
}
},
"must_not": {
"terms": {
"id": [
""
]
}
}
}
},
"aggregations": {
"by_item": {
"terms": {
"field": "item.keyword",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_destination": {
"terms": {
"field": "destinationLocation.keyword",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_trans": {
"terms": {
"field": "transportMode.keyword",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_sourcelocation": {
"terms": {
"field": "sourceLocation.keyword",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_shipdate": {
"terms": {
"field": "shipDate",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_arrival": {
"terms": {
"field": "arrivalDate",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"quantity": {
"sum": {
"field": "transferQuantity"
}
},
"transfercost": {
"sum": {
"field": "transferCost"
}
},
"revenueRecovered": {
"sum": {
"field": "revenueRecovered"
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}
您可以使用 top_hits 聚合，它将 return 该聚合中涉及的所有文档
{
"aggregations": {
"by_destination": {
"terms": {
"field": "destinationLocation.keyword",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_trans": {
"terms": {
"field": "transportMode.keyword",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_sourcelocation": {
"terms": {
"field": "sourceLocation.keyword",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_shipdate": {
"terms": {
"field": "shipDate",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_arrival": {
"terms": {
"field": "arrivalDate",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"docs":{
"top_hits": {
"size": 10,
"_source": ["id"]
}
},
"quantity": {
"sum": {
"field": "transferQuantity"
}
},
"transfercost": {
"sum": {
"field": "transferCost"
}
},
"revenueRecovered": {
"sum": {
"field": "revenueRecovered"
}
}
}
}
}
}
}
}
}
}
}
}
}
}
我有一个场景，对于文档中的聚合值，我希望每个聚合响应都有聚合值，例如在下面的文档中，如果我按项目、目的地位置、源位置、传输模式、到达日期聚合，发货日期我有 2 个相同的文档，id 为 1，另一个文档具有相同的属性，但 id 为 2，所以我在响应中需要这两个唯一的 id，并且我已经附加了查询。
{
"id": "1",
"exceptionId": "1",
"shipmentId": "123",
"primaryRecommendation": true,
"priority": 1,
"sourceLocation": "DC4",
"transferQuantity": 40,
"destinationLocation":"DC1",
"shipDate": "2019-01-11T05:30:00.000+0530",
"arrivalDate": "2019-01-12T05:30:00.000+0530",
"transportMode": "Road",
"transferCost": 200.0,
"maxQtyAvailableForTransfer": 40,
"totalQtyAtSource": 40,
"operation": "Road-Item1-from-DC3-to-DC1",
"peggedStockDemandIds": "",
"revenueRecovered": 20000.0
}
{
"id": "1",
"exceptionId": "1",
"shipmentId": "123",
"primaryRecommendation": true,
"priority": 1,
"sourceLocation": "DC4",
"destinationLocation":"DC1",
"transferQuantity": 40,
"shipDate": "2019-01-11T05:30:00.000+0530",
"arrivalDate": "2019-01-12T05:30:00.000+0530",
"transportMode": "Road",
"transferCost": 200.0,
"maxQtyAvailableForTransfer": 40,
"totalQtyAtSource": 40,
"operation": "Road-Item1-from-DC3-to-DC1",
"peggedStockDemandIds": "",
"revenueRecovered": 20000.0
}
{
"id": "2",
"exceptionId": "1",
"shipmentId": "123",
"primaryRecommendation": true,
"priority": 1,
"sourceLocation": "DC4",
"destinationLocation":"DC1",
"transferQuantity": 40,
"shipDate": "2019-01-11T05:30:00.000+0530",
"arrivalDate": "2019-01-12T05:30:00.000+0530",
"transportMode": "Road",
"transferCost": 200.0,
"maxQtyAvailableForTransfer": 40,
"totalQtyAtSource": 40,
"operation": "Road-Item1-from-DC3-to-DC1",
"peggedStockDemandIds": "",
"revenueRecovered": 20000.0
}
{
"query": {
"bool": {
"must": {
"query_string": {
"default_field": "shipmentId",
"query": "\"123\""
}
},
"filter": {
"terms": {
"exceptionId": [
"2",
"1"
]
}
},
"must_not": {
"terms": {
"id": [
""
]
}
}
}
},
"aggregations": {
"by_item": {
"terms": {
"field": "item.keyword",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_destination": {
"terms": {
"field": "destinationLocation.keyword",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_trans": {
"terms": {
"field": "transportMode.keyword",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_sourcelocation": {
"terms": {
"field": "sourceLocation.keyword",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_shipdate": {
"terms": {
"field": "shipDate",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_arrival": {
"terms": {
"field": "arrivalDate",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"quantity": {
"sum": {
"field": "transferQuantity"
}
},
"transfercost": {
"sum": {
"field": "transferCost"
}
},
"revenueRecovered": {
"sum": {
"field": "revenueRecovered"
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}
您可以使用 top_hits 聚合，它将 return 该聚合中涉及的所有文档
{
"aggregations": {
"by_destination": {
"terms": {
"field": "destinationLocation.keyword",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_trans": {
"terms": {
"field": "transportMode.keyword",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_sourcelocation": {
"terms": {
"field": "sourceLocation.keyword",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_shipdate": {
"terms": {
"field": "shipDate",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"by_arrival": {
"terms": {
"field": "arrivalDate",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [
{
"_count": "desc"
},
{
"_key": "asc"
}
]
},
"aggregations": {
"docs":{
"top_hits": {
"size": 10,
"_source": ["id"]
}
},
"quantity": {
"sum": {
"field": "transferQuantity"
}
},
"transfercost": {
"sum": {
"field": "transferCost"
}
},
"revenueRecovered": {
"sum": {
"field": "revenueRecovered"
}
}
}
}
}
}
}
}
}
}
}
}
}
}