painless语法入门[通俗易懂]

全栈程序员站长

发布于 2022-08-01 15:16:21

1.6K0

大家好，又见面了，我是你们的朋友全栈君。

painless语法

painless基础结构

  "script": { 
   
    "lang":   "...",
    "source" | "id": "...",
    "params": { 
    ... }
  }

lang: 定义脚本使用的语言, 默认painless
source, id: 脚本的主体, source后面跟着内联的脚本代码, id后面跟着脚本的id, 具体代码存在于脚本id对应的代码中
params: 定义一些变量的值, 使用params可以减少脚本的编译次数. 因为如果变量的值硬编码到代码中, 每次进行变量值得更改都会对脚本进行重新编译. 使用params则不会重新编译脚本.

script.context.field.max_compilations_rate=75/5m 脚本的默认编译频率, 定义脚本的编译频率为5分钟75个, 当超过75个时会抛出circuit_breaking_exception异常.

脚本代码的存储

// POST _scripts/{id}
POST _scripts/calculate-score
{ 
   
  "script": { 
   
    "lang": "painless",
    "source": "Math.log(_score * 2) + params['my_modifier']"
  }
}

// 脚本使用
GET my-index-000001/_search
{ 
   
  "query": { 
   
    "script_score": { 
   
      "query": { 
   
        "match": { 
   
            "message": "some message"
        }
      },
      "script": { 
   
        "id": "calculate-score", 
        "params": { 
   
          "my_modifier": 2
        }
      }
    }
  }
}

使用脚本对文档进行更新

PUT my-index-000001/_doc/1
{ 
   
  "counter" : 1,
  "tags" : ["red"]
}

// 将count加上4
POST my-index-000001/_update/1
{ 
   
  "script" : { 
   
    "source": "ctx._source.counter += params.count",
    "lang": "painless",
    "params" : { 
   
      "count" : 4
    }
  }
}

// 增加tags的元素
POST my-index-000001/_update/1
{ 
   
  "script": { 
   
    "source": "ctx._source.tags.add(params['tag'])",
    "lang": "painless",
    "params": { 
   
      "tag": "blue"
    }
  }
}

// If the list contains duplicates of the tag, this script just removes one occurrence.
// 如果集合中有多个相同的值, 只删除第一个
POST my-index-000001/_update/1
{ 
   
  "script": { 
   
    "source": "if (ctx._source.tags.contains(params['tag'])) { ctx._source.tags.remove(ctx._source.tags.indexOf(params['tag'])) }",
    "lang": "painless",
    "params": { 
   
      "tag": "blue"
    }
  }
}

// 增加新的字段
POST my-index-000001/_update/1
{ 
   
  "script" : "ctx._source.new_field = 'value_of_new_field'"
}

// 删除字段
POST my-index-000001/_update/1
{ 
   
  "script" : "ctx._source.remove('new_field')"
}

// 如果tags字段中包含green, 则删除该文档, 否则不做操作
POST my-index-000001/_update/1
{ 
   
  "script": { 
   
    "source": "if (ctx._source.tags.contains(params['tag'])) { ctx.op = 'delete' } else { ctx.op = 'none' }",
    "lang": "painless",
    "params": { 
   
      "tag": "green"
    }
  }
}

// doc.containsKey('field')

脚本变量

ctx._source.field: add, contains, remove, indexOf, length
ctx.op: The operation that should be applied to the document: index or delete
ctx._index: Access to document metadata fields
_score 只在script_score中有效
doc[‘field’], doc[‘field’].value: add, contains, remove, indexOf, length

脚本缓存

You can change this behavior by using the script.cache.expire setting. Use the script.cache.max_size setting to configure the size of the cache.The size of scripts is limited to 65,535 bytes. Set the value of script.max_size_in_bytes to increase that soft limit.
Cache sizing is important. Your script cache should be large enough to hold all of the scripts that users need to be accessed concurrently.

脚本优化

使用脚本缓存, 预先缓存可以节省第一次的查询时间
使用ingest pipeline进行预先计算
相比于_source.field_name使用doc[‘field_name’]语法速度更快, doc语法使用doc value , 列存储

// 根据分数相加结果进行排序
GET /my_test_scores/_search
{ 
   
  "query": { 
   
    "term": { 
   
      "grad_year": "2099"
    }
  },
  "sort": [
    { 
   
      "_script": { 
   
        "type": "number",
        "script": { 
   
          "source": "doc['math_score'].value + doc['verbal_score'].value"
        },
        "order": "desc"
      }
    }
  ]
}

// 在索引中新加一个字段存储计算结果
PUT /my_test_scores/_mapping
{ 
   
  "properties": { 
   
    "total_score": { 
   
      "type": "long"
    }
  }
}

// 使用ingest pipeline先将计算结果作为值存储起来
PUT _ingest/pipeline/my_test_scores_pipeline
{ 
   
  "description": "Calculates the total test score",
  "processors": [
    { 
   
      "script": { 
   
        "source": "ctx.total_score = (ctx.math_score + ctx.verbal_score)"
      }
    }
  ]
}

// 重新索引时使用ingest pipeline
POST /_reindex
{ 
   
  "source": { 
   
    "index": "my_test_scores"
  },
  "dest": { 
   
    "index": "my_test_scores_2",
    "pipeline": "my_test_scores_pipeline"
  }
}

// 索引新文档时使用ingest pipeline
POST /my_test_scores_2/_doc/?pipeline=my_test_scores_pipeline
{ 
   
  "student": "kimchy",
  "grad_year": "2099",
  "math_score": 1200,
  "verbal_score": 800
}

// 查询
GET /my_test_scores_2/_search
{ 
   
  "query": { 
   
    "term": { 
   
      "grad_year": "2099"
    }
  },
  "sort": [
    { 
   
      "total_score": { 
   
        "order": "desc"
      }
    }
  ]
}


// stored field 用法
PUT my-index-000001
{ 
   
  "mappings": { 
   
    "properties": { 
   
      "full_name": { 
   
        "type": "text",
        "store": true
      },
      "title": { 
   
        "type": "text",
        "store": true
      }
    }
  }
}

PUT my-index-000001/_doc/1?refresh
{ 
   
  "full_name": "Alice Ball",
  "title": "Professor"
}

GET my-index-000001/_search
{ 
   
  "script_fields": { 
   
    "name_with_title": { 
   
      "script": { 
   
        "lang": "painless",
        "source": "params._fields['title'].value + ' ' + params._fields['full_name'].value"
      }
    }
  }
}