elasticsearch 将Vega与包含嵌套聚合的Elasticsearch数据一起使用(或在Elasticsearch中将一个聚合除以另一个聚合)
我正在尝试用Elasticsearch做一些简单的事情。我有一个包含以下形状的文档的索引:{“timestamp”:int,“pricePerUnit”:int,“units”:int}。我想在柱状图中直观地显示一段时间内的平均价格。请注意,我不想要“pricePerUnit”的平均值,我想要的是每单位支付的平均价格,这意味着通过将“pricePerUnit”乘以每个文档的“units”来计算每个时间段中的总价值,并将每个文档中售出的总价值相加,然后除以时间段内售出的总单位之和,得到每单位的平均支付价格。标准的Kibana折线图不起作用。我可以得到“pricePerUnit*单位”的平均值,但不能将这个加总除以总单位之和。也不能在TSVB中完成,因为这不允许脚本/脚本字段。不能使用timelon,因为“timestamp”字段不是时间字段(我知道,但对此我无能为力)。因此,我尝试使用织女星。但是,我遇到了嵌套聚合的问题。以下是我正在运行的ES查询:elasticsearch 将Vega与包含嵌套聚合的Elasticsearch数据一起使用(或在Elasticsearch中将一个聚合除以另一个聚合),elasticsearch,kibana,vega,elasticsearch,Kibana,Vega,我正在尝试用Elasticsearch做一些简单的事情。我有一个包含以下形状的文档的索引:{“timestamp”:int,“pricePerUnit”:int,“units”:int}。我想在柱状图中直观地显示一段时间内的平均价格。请注意,我不想要“pricePerUnit”的平均值,我想要的是每单位支付的平均价格,这意味着通过将“pricePerUnit”乘以每个文档的“units”来计算每个时间段中的总价值,并将每个文档中售出的总价值相加,然后除以时间段内售出的总单位之和,得到每单位的平均
{
"$schema": "https://vega.github.io/schema/vega/v3.json",
"data": {
"name": "vals",
"url": {
"index": "index_name",
"body": {
"aggs": {
"2": {
"histogram": {
"field": "timestamp",
"interval": 2000,
"min_doc_count": 1
},
"aggs": {
"1": {
"avg": {
"field": "pricePerUnit",
"script": {
"inline": "doc['pricePerUnit'].value * doc['units'].value",
"lang": "painless"
}
}
}
}
}
},
"size": 0,
"stored_fields": [
"*"
],
"script_fields": {
"spend": {
"script": {
"source": "doc['pricePerUnit'].value * doc['units'].value",
"lang": "painless"
}
}
},
"docvalue_fields": [],
"_source": {
"excludes": []
},
"query": {
"bool": {
"must": [],
"filter": [
{
"match_all": {}
},
{
"range": {
"timeslot.startTime": {
"gte": 1621292400,
"lt": 1621428349
}
}
}
],
"should": [],
"must_not": []
}
}
},
"format": {"property": "aggregations.2.buckets"}
}
}
,
"scales": [
{
"name": "yscale",
"type": "linear",
"zero": true,
"domain": {"data": "vals", "field": "1.value"},
"range": "height"
},
{
"name": "xscale",
"type": "time",
"range": "width"
}
],
"axes": [
{"scale": "yscale", "orient": "left"},
{"scale": "xscale", "orient": "bottom"}
],
"marks": [
{
"type": "line",
"encode": {
"update": {
"x": {"scale": "xscale", "field": "key"},
"y": {"scale": "yscale", "field": "1.value"}
}
}
}
]
}
它给出了以下结果集:
"took": 1,
"timed_out": false,
"_shards": {
"total": 4,
"successful": 4,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 401,
"max_score": null,
"hits": []
},
"aggregations": {
"2": {
"buckets": [
{
"1": {
"value": 86340
},
"key": 1621316000,
"doc_count": 7
},
{
"1": {
"value": 231592.92307692306
},
"key": 1621318000,
"doc_count": 13
},
{
"1": {
"value": 450529.23529411765
},
"key": 1621320000,
"doc_count": 17
},
{
"1": {
"value": 956080.0555555555
},
"key": 1621322000,
"doc_count": 18
},
{
"1": {
"value": 1199865.5714285714
},
"key": 1621324000,
"doc_count": 14
},
{
"1": {
"value": 875300.7368421053
},
"key": 1621326000,
"doc_count": 19
},
{
"1": {
"value": 926738.8
},
"key": 1621328000,
"doc_count": 20
},
{
"1": {
"value": 3239475.3333333335
},
"key": 1621330000,
"doc_count": 18
},
{
"1": {
"value": 3798063.714285714
},
"key": 1621332000,
"doc_count": 21
},
{
"1": {
"value": 482089.5
},
"key": 1621334000,
"doc_count": 4
},
{
"1": {
"value": 222952.33333333334
},
"key": 1621336000,
"doc_count": 12
},
{
"1": {
"value": 742225.75
},
"key": 1621338000,
"doc_count": 8
},
{
"1": {
"value": 204203.25
},
"key": 1621340000,
"doc_count": 4
},
{
"1": {
"value": 294886
},
"key": 1621342000,
"doc_count": 4
},
{
"1": {
"value": 284393.75
},
"key": 1621344000,
"doc_count": 4
},
{
"1": {
"value": 462800.5
},
"key": 1621346000,
"doc_count": 4
},
{
"1": {
"value": 233321.2
},
"key": 1621348000,
"doc_count": 5
},
{
"1": {
"value": 436757.8
},
"key": 1621350000,
"doc_count": 5
},
{
"1": {
"value": 4569021
},
"key": 1621352000,
"doc_count": 1
},
{
"1": {
"value": 368489.5
},
"key": 1621354000,
"doc_count": 4
},
{
"1": {
"value": 208359.4
},
"key": 1621356000,
"doc_count": 5
},
{
"1": {
"value": 7827146.375
},
"key": 1621358000,
"doc_count": 8
},
{
"1": {
"value": 63873.5
},
"key": 1621360000,
"doc_count": 6
},
{
"1": {
"value": 21300
},
"key": 1621364000,
"doc_count": 1
},
{
"1": {
"value": 138500
},
"key": 1621366000,
"doc_count": 2
},
{
"1": {
"value": 5872400
},
"key": 1621372000,
"doc_count": 1
},
{
"1": {
"value": 720200
},
"key": 1621374000,
"doc_count": 1
},
{
"1": {
"value": 208634.33333333334
},
"key": 1621402000,
"doc_count": 3
},
{
"1": {
"value": 306248.5
},
"key": 1621404000,
"doc_count": 10
},
{
"1": {
"value": 328983.77777777775
},
"key": 1621406000,
"doc_count": 18
},
{
"1": {
"value": 1081724
},
"key": 1621408000,
"doc_count": 10
},
{
"1": {
"value": 2451076.785714286
},
"key": 1621410000,
"doc_count": 14
},
{
"1": {
"value": 1952910.2857142857
},
"key": 1621412000,
"doc_count": 14
},
{
"1": {
"value": 2294818.1875
},
"key": 1621414000,
"doc_count": 16
},
{
"1": {
"value": 2841910.388888889
},
"key": 1621416000,
"doc_count": 18
},
{
"1": {
"value": 2401278.9523809524
},
"key": 1621418000,
"doc_count": 21
},
{
"1": {
"value": 4311845.4
},
"key": 1621420000,
"doc_count": 5
},
{
"1": {
"value": 617102.5333333333
},
"key": 1621422000,
"doc_count": 15
},
{
"1": {
"value": 590469.7142857143
},
"key": 1621424000,
"doc_count": 14
},
{
"1": {
"value": 391918.85714285716
},
"key": 1621426000,
"doc_count": 14
},
{
"1": {
"value": 202163.66666666666
},
"key": 1621428000,
"doc_count": 3
}
]
}
}
}
问题是我无法从“1”子聚合中提取“value”字段。我尝试过使用展平变换,但它似乎不起作用。如果任何人可以:
a) 告诉我如何用Vega解决这个具体问题;或
b) 告诉我另一种解决我原来问题的方法
我将不胜感激