本文介绍了elasticsearch copy_to字段的行为不如预期的聚合的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我有一个索引映射,两个字符串字段 field1 field2 ,都被声明为copy_to到另一个字段称为 all_fields all_fields 被索引为not_analyzed。



当我在 all_fields上创建一个桶聚合时,我期待着具有field1和field2的键的不同的桶连接在一起。相反,我得到了不相关的字段1和field2的关键字桶。



示例:
映射:

  {
mappings:{
myobject:{
properties:{
field1:{
type:string,
index:analyze,
copy_to:all_fields
},
field2:{
type:string,
index:analyze,
copy_to:all_fields
},
all_fields:{
type:string,
index:not_analyzed
}
}
}
}
}

数据:

  {
field1:晚餐胡萝卜马铃薯西兰花,
field2:这里的东西,
}

  {
field1:鱼鸡肉g,
field2:晚餐,
}

  {
aggs:{
t:{
:{
field:all_fields
}
}
}
}

结果:

  ... 
聚合 {
t:{
doc_count_error_upper_bound:0,
sum_other_doc_count:0,
buckets:[
{
:晚餐,
doc_count:1
},
{
key:晚餐胡萝卜马铃薯西兰花,
doc_count:1
},
{
key:fish chicken something,
doc_count:1
},
{
关键:这里的东西,
doc_count:1
}
]
}
}

我期待只有2个桶, fish chicken somethingdinner 晚餐胡萝卜马铃薯broccolisomethinghere



我做错了什么?

解决方案

您要查找的是两个字符串的连接。 copy_to 即使它似乎是这样做,它不是。在 copy_to 中,您在概念上创建了一组来自 field1 field2 ,不连接它们。



对于您的用例,您有两个选项:


  1. 使用

  2. 执行脚本聚合

我会推荐 _source 转换,因为我认为它比执行脚本更有效率。意思是,您在索引时支付一小笔费用,而不是做一个沉重的脚本集合。



对于 _source 转换

  PUT / lastseen 
{
mappings:{
test:{
transform:{
script:ctx._source ['all_fields'] = ctx._source ['field1'] +''+ ctx._source [' field2']
},
properties:{
field1:{
type:string
},
field2:{
type:string
},
lastseen:{
type:long
},
all_fields:{
type:string,
index:not_analyzed
}
}
}
}
}

查询:

  GET / lastseen / test / _search 
{
aggs:{
NAME:{
terms:{
field:all_fields,
size:10
}
}
}
}
pre>

对于脚本聚合,更容易做(意思是使用 doc ['field']。 而不是更昂贵的 _source.field )将 .raw 子字段添加到 field1 field2

  PUT / lastseen 
{
mappings:{
test:{
properties:{
field1:{
type:string,
fields:{
raw:{
type:string,
index:not_analyzed
}
}
},
field2:{
type:string,
fields:{
raw:{
type:string,
index:not_analyzed
}
}
},
lastseen : {
type:long
}
}
}
}
}
pre>

脚本将使用这些 .raw 子字段:



$ $ $ $ $ $ $ $ $ $ $ $ $ $$ {
doc''+''+ doc ['field2.raw']。value,
size:10,
lang:groovy
}
}
}
}

没有code> .raw 子字段(以 not_analyzed 作为目的),您将需要执行此操作,这是更贵:

  {
aggs:{
NAME:{
terms:{
script:_source.field1 +''+ _source.field2,
size:10,
lang:groovy
}
}
}
}


I have an index mapping with two string fields, field1 and field2, both being declared as copy_to to another field called all_fields. all_fields is indexed as "not_analyzed".

When I create a bucket aggregation on all_fields, I was expecting distinct buckets with keys of field1 and field2 concatenated together. Instead, I get separate buckets with keys of field1 and field2 unconcatenated.

Example:mapping:

  {
    "mappings": {
      "myobject": {
        "properties": {
          "field1": {
            "type": "string",
            "index": "analyzed",
            "copy_to": "all_fields"
          },
          "field2": {
            "type": "string",
            "index": "analyzed",
            "copy_to": "all_fields"
          },
          "all_fields": {
            "type": "string",
            "index": "not_analyzed"
          }
        }
      }
    }
  }

data in:

  {
    "field1": "dinner carrot potato broccoli",
    "field2": "something here",
  }

and

  {
    "field1": "fish chicken something",
    "field2": "dinner",
  }

aggregation:

{
  "aggs": {
    "t": {
      "terms": {
        "field": "all_fields"
      }
    }
  }
}

results:

...
"aggregations": {
    "t": {
        "doc_count_error_upper_bound": 0,
        "sum_other_doc_count": 0,
        "buckets": [
            {
                "key": "dinner",
                "doc_count": 1
            },
            {
                "key": "dinner carrot potato broccoli",
                "doc_count": 1
            },
            {
                "key": "fish chicken something",
                "doc_count": 1
            },
            {
                "key": "something here",
                "doc_count": 1
            }
        ]
    }
}

I was expecting only 2 buckets, fish chicken somethingdinner and dinner carrot potato broccolisomethinghere

What am I doing wrong?

解决方案

What you are looking for is concatenation of two strings. copy_to even if it seems is doing this, it is not. With copy_to you are, conceptually, creating a set of values from both field1 and field2, not concatenating them.

For your use case, you have two options:

  1. use _source transformation
  2. perform a script aggregation

I would recommend _source transformation as I think it's more efficient than doing the scripting. Meaning, you pay a little price at indexing time than doing a heavy scripting aggregation.

For _source transformation:

PUT /lastseen
{
  "mappings": {
    "test": {
      "transform": {
        "script": "ctx._source['all_fields'] = ctx._source['field1'] + ' ' + ctx._source['field2']"
      }, 
      "properties": {
        "field1": {
          "type": "string"
        },
        "field2": {
          "type": "string"
        },
        "lastseen": {
          "type": "long"
        },
        "all_fields": {
          "type": "string",
          "index": "not_analyzed"
        }
      }
    }
  }
}

And the query:

GET /lastseen/test/_search
{
  "aggs": {
    "NAME": {
      "terms": {
        "field": "all_fields",
        "size": 10
      }
    }
  }
}

For script aggregation, to be easier to do (meaning, using doc['field'].value rather than the more expensive _source.field) add .raw sub-fields to field1 and field2:

PUT /lastseen
{
  "mappings": {
    "test": { 
      "properties": {
        "field1": {
          "type": "string",
          "fields": {
            "raw": {
              "type": "string",
              "index": "not_analyzed"
            }
          }
        },
        "field2": {
          "type": "string",
          "fields": {
            "raw": {
              "type": "string",
              "index": "not_analyzed"
            }
          }
        },
        "lastseen": {
          "type": "long"
        }
      }
    }
  }
}

And the script will use these .raw subfields:

{
  "aggs": {
    "NAME": {
      "terms": {
        "script": "doc['field1.raw'].value + ' ' + doc['field2.raw'].value", 
        "size": 10,
        "lang": "groovy"
      }
    }
  }
}

Without the .raw sub-fields (which are made on purpose as not_analyzed) you would have needed to do something like this, which is more expensive:

{
  "aggs": {
    "NAME": {
      "terms": {
        "script": "_source.field1 + ' ' + _source.field2", 
        "size": 10,
        "lang": "groovy"
      }
    }
  }
}

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09-17 13:59