假设我具有以下类型：
{
"2019-11-04": {
"mappings": {
"_doc": {
"properties": {
"labels": {
"type": "nested",
"properties": {
"confidence": {
"type": "float"
},
"created_at": {
"type": "date",
"format": "strict_date_optional_time||date_time||epoch_millis"
},
"label": {
"type": "keyword"
},
"updated_at": {
"type": "date",
"format": "strict_date_optional_time||date_time||epoch_millis"
},
"value": {
"type": "keyword",
"fields": {
"numeric": {
"type": "float",
"ignore_malformed": true
}
}
}
}
},
"params": {
"type": "object"
},
"type": {
"type": "keyword"
}
}
}
}
}
}
我想按labels数组的大小/长度进行过滤。我已经尝试了以下（as the official docs suggest）：
{
"query": {
"bool": {
"filter": {
"script": {
"script": {
"source": "doc['labels'].size > 10"
}
}
}
}
}
}
但我不断得到：
{
"error": {
"root_cause": [
{
"type": "script_exception",
"reason": "runtime error",
"script_stack": [
"org.elasticsearch.search.lookup.LeafDocLookup.get(LeafDocLookup.java:81)",
"org.elasticsearch.search.lookup.LeafDocLookup.get(LeafDocLookup.java:39)",
"doc['labels'].size > 10",
" ^---- HERE"
],
"script": "doc['labels'].size > 10",
"lang": "painless"
}
],
"type": "search_phase_execution_exception",
"reason": "all shards failed",
"phase": "query",
"grouped": true,
"failed_shards": [
{
"shard": 0,
"index": "2019-11-04",
"node": "kk5MNRPoR4SYeQpLk2By3A",
"reason": {
"type": "script_exception",
"reason": "runtime error",
"script_stack": [
"org.elasticsearch.search.lookup.LeafDocLookup.get(LeafDocLookup.java:81)",
"org.elasticsearch.search.lookup.LeafDocLookup.get(LeafDocLookup.java:39)",
"doc['labels'].size > 10",
" ^---- HERE"
],
"script": "doc['labels'].size > 10",
"lang": "painless",
"caused_by": {
"type": "illegal_argument_exception",
"reason": "No field found for [labels] in mapping with types []"
}
}
}
]
},
"status": 500
}
答案 0 :(得分：1)
恐怕这是不可能的，因为字段labels不是ES保存的字段，也不是albiet在其上创建反向索引的字段。
Doc doc['fieldname']仅适用于创建反向索引的字段，Elasticsearch的Query DSL也仅适用于创建反向索引的字段，但不幸的是，nested type不是有效字段创建哪个反向索引。
话虽如此，我有以下两种方式。
为简单起见，我创建了示例映射，文档和两个可能对您有帮助的解决方案。
PUT my_sample_index
{
"mappings": {
"properties": {
"myfield": {
"type": "nested",
"properties": {
"label": {
"type": "keyword"
}
}
}
}
}
}
// single field inside 'myfield'
POST my_sample_index/_doc/1
{
"myfield": {
"label": ["New York", "LA", "Austin"]
}
}
// two fields inside 'myfield'
POST my_sample_index/_doc/2
{
"myfield": {
"label": ["London", "Leicester", "Newcastle", "Liverpool"],
"country": "England"
}
}
我有一个变通办法来获取所需的东西，虽然不完全正确，但可以帮助您在服务层或应用程序上进行过滤。
POST my_sample_index/_search
{
"_source": "*",
"query": {
"bool": {
"must": [
{
"match_all": {}
}
]
}
},
"script_fields": {
"label_size": {
"script": {
"lang": "painless",
"source": "params['_source']['labels'].size() > 1"
}
}
}
}
您会注意到，作为响应，将使用label_size或true值创建一个单独的字段false。
示例响应如下：
{
"took" : 5,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "my_sample_index",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"myfield" : {
"label" : [
"New York",
"LA",
"Austin"
]
}
},
"fields" : {
"label_size" : [ <---- Scripted Field
false
]
}
},
{
"_index" : "my_sample_index",
"_type" : "_doc",
"_id" : "2",
"_score" : 1.0,
"_source" : {
"myfield" : {
"country" : "England",
"label" : [
"London",
"Leicester",
"Newcastle",
"Liverpool"
]
}
},
"fields" : { <---- Scripted Field
"label_size" : [
true <---- True because it has two fields 'labels' and 'country'
]
}
}
]
}
}
请注意，只有第二个文档才有意义，因为它具有两个字段，即country和labels。但是，如果只希望将label_size和true一起使用，则必须在应用程序层进行管理。
创建新索引，如下所示：
PUT my_sample_index_temp
{
"mappings": {
"properties": {
"myfield": {
"type": "nested",
"properties": {
"label": {
"type": "keyword"
}
}
},
"labels_size":{ <---- New Field where we'd store the size
"type": "integer"
}
}
}
}
创建以下管道：
PUT _ingest/pipeline/set_labels_size
{
"description": "sets the value of labels size",
"processors": [
{
"script": {
"source": """
ctx.labels_size = ctx.myfield.size();
"""
}
}
]
}
使用Reindex API从my_sample_index索引中重新编制索引
POST _reindex
{
"source": {
"index": "my_sample_index"
},
"dest": {
"index": "my_sample_index_temp",
"pipeline": "set_labels_size"
}
}
使用my_sample_index_temp验证GET my_sample_index_temp/_search中的文档
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "my_sample_index_temp",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"labels_size" : 1, <---- New Field Created
"myfield" : {
"label" : [
"New York",
"LA",
"Austin"
]
}
}
},
{
"_index" : "my_sample_index_temp",
"_type" : "_doc",
"_id" : "2",
"_score" : 1.0,
"_source" : {
"labels_size" : 2, <----- New Field Created
"myfield" : {
"country" : "England",
"label" : [
"London",
"Leicester",
"Newcastle",
"Liverpool"
]
}
}
}
]
}
}
现在，您只需在查询中使用此字段labels_size，它的方式就更容易（更不用说高效了）。
希望这会有所帮助！