在下面的查询中，我偶尔会收到“NaN”响应（请参阅查询下方的回复）。
我假设，偶尔会有一些无效数据进入“金额”字段（正在聚合的字段）。如果这是一个有效的假设，我如何找到那些包含无效“金额”字段的文档，以便我可以对它们进行故障排除？
如果这不是一个有效的假设，我如何解决偶尔返回的“NaN”值？
REQUEST：
POST /_msearch
{
"search_type": "query_then_fetch",
"ignore_unavailable": true,
"index": [
"view-2017-10-22",
"view-2017-10-23"
]
}
{
"size": 0,
"query": {
"bool": {
"filter": [
{
"range": {
"handling-time": {
"gte": "1508706273585",
"lte": "1508792673586",
"format": "epoch_millis"
}
}
},
{
"query_string": {
"analyze_wildcard": true,
"query": "+page:\"checkout order confirmation\" +pageType:\"d\""
}
}
]
}
},
"aggs": {
"2": {
"date_histogram": {
"interval": "1h",
"field": "time",
"min_doc_count": 0,
"extended_bounds": {
"min": "1508706273585",
"max": "1508792673586"
},
"format": "epoch_millis"
},
"aggs": {
"1": {
"sum": {
"field": "amount"
}
}
}
}
}
}
响应：
{
"responses": [
{
"took": 12,
"timed_out": false,
"_shards": {
"total": 10,
"successful": 10,
"failed": 0
},
"hits": {
"total": 44587,
"max_score": 0,
"hits": []
},
"aggregations": {
"2": {
"buckets": [
{
"1": {
"value": "NaN"
},
"key_as_string": "1508706000000",
"key": 1508706000000,
"doc_count": 2915
},
{
"1": {
"value": 300203.74
},
"key_as_string": "1508709600000",
"key": 1508709600000,
"doc_count": 2851
},
{
"1": {
"value": 348139.5600000001
},
"key_as_string": "1508713200000",
"key": 1508713200000,
"doc_count": 3197
},
{
"1": {
"value": "NaN"
},
"key_as_string": "1508716800000",
"key": 1508716800000,
"doc_count": 3449
},
{
"1": {
"value": "NaN"
},
"key_as_string": "1508720400000",
"key": 1508720400000,
"doc_count": 3482
},
{
"1": {
"value": 364449.60999999987
},
"key_as_string": "1508724000000",
"key": 1508724000000,
"doc_count": 3103
},
{
"1": {
"value": 334914.68
},
"key_as_string": "1508727600000",
"key": 1508727600000,
"doc_count": 2722
},
{
"1": {
"value": 315368.09000000014
},
"key_as_string": "1508731200000",
"key": 1508731200000,
"doc_count": 2161
},
{
"1": {
"value": 102244.34
},
"key_as_string": "1508734800000",
"key": 1508734800000,
"doc_count": 742
},
{
"1": {
"value": 37178.63
},
"key_as_string": "1508738400000",
"key": 1508738400000,
"doc_count": 333
},
{
"1": {
"value": 25345.68
},
"key_as_string": "1508742000000",
"key": 1508742000000,
"doc_count": 233
},
{
"1": {
"value": 85454.47000000002
},
"key_as_string": "1508745600000",
"key": 1508745600000,
"doc_count": 477
},
{
"1": {
"value": 24102.719999999994
},
"key_as_string": "1508749200000",
"key": 1508749200000,
"doc_count": 195
},
{
"1": {
"value": 23352.309999999994
},
"key_as_string": "1508752800000",
"key": 1508752800000,
"doc_count": 294
},
{
"1": {
"value": 44353.409999999996
},
"key_as_string": "1508756400000",
"key": 1508756400000,
"doc_count": 450
},
{
"1": {
"value": 80129.89999999998
},
"key_as_string": "1508760000000",
"key": 1508760000000,
"doc_count": 867
},
{
"1": {
"value": 122797.11
},
"key_as_string": "1508763600000",
"key": 1508763600000,
"doc_count": 1330
},
{
"1": {
"value": 157442.29000000004
},
"key_as_string": "1508767200000",
"key": 1508767200000,
"doc_count": 1872
},
{
"1": {
"value": 198831.71
},
"key_as_string": "1508770800000",
"key": 1508770800000,
"doc_count": 2251
},
{
"1": {
"value": 218384.08000000002
},
"key_as_string": "1508774400000",
"key": 1508774400000,
"doc_count": 2305
},
{
"1": {
"value": 229829.22000000006
},
"key_as_string": "1508778000000",
"key": 1508778000000,
"doc_count": 2381
},
{
"1": {
"value": 217157.56000000006
},
"key_as_string": "1508781600000",
"key": 1508781600000,
"doc_count": 2433
},
{
"1": {
"value": 208877.13
},
"key_as_string": "1508785200000",
"key": 1508785200000,
"doc_count": 2223
},
{
"1": {
"value": "NaN"
},
"key_as_string": "1508788800000",
"key": 1508788800000,
"doc_count": 2166
},
{
"1": {
"value": 18268.14
},
"key_as_string": "1508792400000",
"key": 1508792400000,
"doc_count": 155
}
]
}
},
"status": 200
}
]
}
答案 0 :(得分：0)
您可以搜索<fieldName>:NaN（在数字字段上）以查找设置为NaN的数字。
显然，一旦找到这些，您可以修复设置为NaN的字段的根本原因，也可以通过向查询添加-<fieldName>:NaN来从聚合中排除这些记录。
（事实证明，每隔几百万个文档就会输入一些垃圾字符。）