ElasticSearch-Ingest Pipeline Painless Script

• Ingest Node & Pipeline & Processor
  • Ingest Node
  • Pipeline & Processor
  • 内置的 Processors
  • 创建 pipeline
  • 使用 pipeline 更新数据
  • 借助 update_by_query 更新已存在的文档
  • Ingest Node VS Logstash
• Painless

Ingest Node & Pipeline & Processor

• 应用场景： 修复与增强写入数据

• Ingest Node

  • 默认配置下，每个节点都是 Ingest Node（Elasticsearch 5.0后）
  • 具有预处理数据的能力，可拦截lndex或 Bulk API的请求
  • 对数据进行转换，并重新返回给Index或 Bulk APl
  • 无需Logstash，就可以进行数据的预处理
    • 为某个字段设置默认值
    • 重命名某个字段的字段名
    • 对字段值进行Split 操作
    • 支持设置Painless脚本，对数据进行更加复杂的加工

• Pipeline & Processor

  • Pipeline：管道会对通过的数据(文档)，按照顺序进行加工
  • Processor：Elasticsearch 对一些加工的行为进行了抽象包装
    • Elasticsearch 有很多内置的Processors，也支持通过插件的方式，实现自己的Processor
  • 

• 内置的 Processors

  • Split Processor ： 将给定字段值分成一个数组
  • Remove / Rename Processor ：移除一个重命名字段
  • Append ： 为商品增加一个新的标签
  • Convert：将商品价格，从字符串转换成float 类型
  • Date / JSON：日期格式转换，字符串转JSON对象
  • Date lndex Name Processor︰将通过该处理器的文档,分配到指定时间格式的索引中
  • Fail Processor︰一旦出现异常，该Pipeline 指定的错误信息能返回给用户
  • Foreach Process︰数组字段，数组的每个元素都会使用到一个相同的处理器
  • Grok Processor︰日志的日期格式切割
  • Gsub / Join / Split︰字符串替换│数组转字符串/字符串转数组
  • Lowercase / upcase︰大小写转换

# 测试 split tags
POST _ingest/pipeline/_simulate
{"pipeline":{"description":"to split blog tags","processors": [{"split":{"field":"tags","separator":","}}]},"docs": [{"_index": "index","_id": "id","_source": {"title": "Introducing big data......", "tags": "hadoop,elasticsearch,spark", "content": "You konw, for big data"}},{"_index":"index","_id":"idxx","_source":{"title":"Introducing cloud computering", "tags":"openstack,k8s","content":"You konw, for cloud"}}]}
# 同时为文档增加一个字段
POST _ingest/pipeline/_simulate
{"pipeline":{"description":"to split blog tags","processors":[{"split":{"field":"tags","separator":","}},{"set":{"field":"views","value":0}}]},"docs": [{"_index":"index","_id":"id","_source":{"title":"Introducing big data......","tags":"hadoop,elasticsearch,spark","content":"You konw, for big data"}},{"_index":"index","_id":"idxx","_source":{"title":"Introducing cloud computering", "tags":"openstack,k8s","content":"You konw, for cloud"}}]}

• 创建 pipeline

# 为 ES 添加一个 Pipeline
PUT _ingest/pipeline/blog_pipeline 
{"description":"a blog pipeline","processors":[{"split":{"field":"tags","separator":","}},{"set":{"field":"views","value":0}}]}

• 使用 pipeline 更新数据

# 使用 pipeline 更新数据
PUT tech_blogs/_doc/2?pipeline=blog_pipeline 
{"title":"Introducing cloud computering","tags":"openstack,k8s","content":"You konw, for cloud"}

• 借助 update_by_query 更新已存在的文档

#增加update_by_query的条件
POST tech_blogs/_update_by_query?pipeline=blog_pipeline 
{"query":{"bool":{"must_not":{"exists":{"field":"views"}}}}}

• Ingest Node VS Logstash

Painless

• Painless 支持所有 Java 的数据类型及 Java API 子集
• Painless Script 具备以下特性
  • 高性能/安全
  • 支持显示类型或者动态定义类型
• Painless 的用途
  • 可以对文档字段进行加工处理
    • 更新或删除字段，处理数据聚合操作
    • Script Field: 对返回的字段提前进行计算
    • Function Score: 对文档的算分进行处理
  • 在lngest Pipeline中执行脚本
  • 在Reindex APl，Update By Query时，对数据进行处理
• 通过Painless脚本访问字段
  • Ingestion: ctx.field_name
  • Update: ctx._source.field_name
  • Search & Aggregation: doc["field_name"]

# 增加一个 Script Prcessor
POST _ingest/pipeline/_simulate
{"pipeline":{"description":"to split blog tags","processors":[{"split":{"field":"tags","separator":","}},{"script":{"source":"""if(ctx.containsKey("content")){ctx.content_length = ctx.content.length(); }else{ctx.content_length=0;}"""}},{"set":{"field":"views","value":0}}]},"docs": [{"_index":"index","_id":"id","_source":{"title":"Introducing big data......", "tags":"hadoop,elasticsearch,spark", "content":"You konw, for big data"}},{"_index":"index","_id":"idxx","_source":{"title":"Introducing cloud computering", "tags":"openstack,k8s","content":"You konw, for cloud"}}]}
PUT tech_blogs/_doc/1
{"title":"Introducing big data......", "tags":"hadoop,elasticsearch,spark", "content":"You konw, for big data","views":0}

POST tech_blogs/_update/1
{"script":{"params":{"new_views":100},"source":"ctx._source.views += params.new_views"}}
# 查看 views 计数
POST tech_blogs/_search

# 保存脚本在 Cluster State
POST _scripts/update_views
{"script":{"lang":"painless","source":"ctx._source.views += params.new_views"}}

GET tech_blogs/_search
{"script_fields":{"rnd_views":{"script":{"lang":"painless","source":"""java.util.Random rnd = new Random(); doc['views'].value+rnd.nextInt(1000);"""}}},"query":{"match_all":{}}}

• 脚本缓存：脚本编译的开销较大，Elasticsearch会将脚本编译后缓存在Cache 中

  • Inline scripts和 Stored Scripts都会被缓存
  • 默认缓存100个脚本

• script.cache.max_size 设置最大缓存数

• script.cache.expire 设置缓存超时

• script.max_compilations_rate 默认5分钟最多75次编译 (75/5m)