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[英]elasticsearch - comparing a nested field with another field in the document
[英]Comparing the different document field values in elasticsearch index
只是想知道如何比較 2 個不同文檔的值。 我正在索引中攝取以下值。
我希望查詢和比較每個 plugin_instance 的“allocated-mb”>“max-mb”的每個文檔字段“type_instance”值。
POST test/_bulk
{"index":{"_id":1}}
{"plugin_instance": "root-yarn-queue-name-1", "type_instance": "allocated-mb", "value": 4024}
{"index":{"_id":2}}
{ "plugin_instance": "root-yarn-queue-name-1", "type_instance": "max-mb", "value": 2048}
{"index":{"_id":3}}
{"plugin_instance": "root-yarn-queue-name-2", "type_instance": "max-mb", "value": 3048}
{"index":{"_id":4}}
{"root-yarn-queue-name-2", "type_instance": "allocated-mb", "value": 1028}
{"index":{"_id":5}}
{"plugin_instance": "some-random-queue-name-2", "type_instance": "allocated-mb", "value": 2028}
{"index":{"_id":6}}
{"plugin_instance": "some-random-queue-name-2", "type_instance": "max-mb", "value": 2028}
只是想知道實現以下目標的簡單方法是什么
到目前為止,我已經設法根據 plugin_instance 對文檔進行存儲。 想知道根據“type_instance”比較每個存儲桶的文檔的簡單方法是什么
GET test/_search
{
"query": {
"query_string": {
"fields": [
"plugin_instance.keyword",
"type_instance.keyword"
],
"query": "root-yarn-queue-name-* AND (max-mb OR allocated-mb)"
}
},
"aggs": {
"byField": {
"terms": {
"field": "plugin_instance.keyword"
}
}
}
}
解決上述問題的一種方法是在客戶端獲取文檔和執行過濾。 第二個將涉及使用bucket_selector 聚合
映射
{
"index60" : {
"mappings" : {
"properties" : {
"plugin_instance" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"type_instance" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"value" : {
"type" : "long"
}
}
}
}
}
數據:
"hits" : [
{
"_index" : "index60",
"_type" : "_doc",
"_id" : "vCN--3AB_Wo5Rvhl5c7f",
"_score" : 1.0,
"_source" : {
"plugin_instance" : "root-yarn-queue-name-1",
"type_instance" : "max-vcore",
"value" : 1000
}
},
{
"_index" : "index60",
"_type" : "_doc",
"_id" : "vSN--3AB_Wo5Rvhl9M6R",
"_score" : 1.0,
"_source" : {
"plugin_instance" : "root-yarn-queue-name-1",
"type_instance" : "max-mb",
"value" : 2048
}
},
{
"_index" : "index60",
"_type" : "_doc",
"_id" : "viN--3AB_Wo5Rvhl_s5m",
"_score" : 1.0,
"_source" : {
"plugin_instance" : "root-yarn-queue-name-2",
"type_instance" : "max-mb",
"value" : 3048
}
},
{
"_index" : "index60",
"_type" : "_doc",
"_id" : "wCN_-3AB_Wo5Rvhlhc53",
"_score" : 1.0,
"_source" : {
"plugin_instance" : "root-yarn-queue-name-2",
"type_instance" : "allocated-mb",
"value" : 1028
}
},
{
"_index" : "index60",
"_type" : "_doc",
"_id" : "wSOA-3AB_Wo5RvhlCc5r",
"_score" : 1.0,
"_source" : {
"plugin_instance" : "root-yarn-queue-name-1",
"type_instance" : "allocated-mb",
"value" : 3000
}
}
]
詢問:
{
"size": 0,
"aggs": {
"plugin_instance": {
"terms": {
"field": "plugin_instance.keyword",
"include": "root-yarn-queue-name-.*", --> pattern
"size": 10000
},
"aggs": {
"instance": {
"terms": {
"field": "type_instance.keyword",
"include": [ --> create a bucket of these two
"max-mb",
"allocated-mb"
],
"size": 10
}
},
"maxValue": {
"max": {
"field": "value"
}
},
"allocated-mb": {
"filter": {
"term": {
"type_instance.keyword": "allocated-mb"
}
},
"aggs": {
"filtered_maxValue": {
"max": {
"field": "value"
}
}
}
},
"my_bucket": {
"bucket_selector": {
"buckets_path": {
"filteredValue": "allocated-mb>filtered_maxValue",
"maxValue": "maxValue"
},
"script": "params.filteredValue==params.maxValue"
}
}
}
}
}
}
結果:
"aggregations" : {
"plugin_instance" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "root-yarn-queue-name-1",
"doc_count" : 3,
"instance" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "allocated-mb",
"doc_count" : 1
},
{
"key" : "max-mb",
"doc_count" : 1
}
]
},
"maxValue" : {
"value" : 3000.0
},
"allocated-mb" : {
"doc_count" : 1,
"filtered_maxValue" : {
"value" : 3000.0
}
}
}
]
}
}
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