特定格式文本数据加工示例_日志服务(SLS)-阿里云帮助中心

文档中的实践案例主要是根据实际工作中的工单需求产生。本文档将从工单需求，加工编排等方面介绍如何使用LOG DSL编排解决任务需求。

非标准JSON对象转JSON对象并展开

需要对收集的dict数据进行二次嵌套展开操作。首先将dict数据转成JSON数据，再使用e_json函数进行展开即可。

原始日志

content: {
  'referer': '-',
  'request': 'GET /phpMyAdmin',
  'status': 404,
  'data-1': {
    'aaa': 'Mozilla',
    'bbb': 'asde'
  },
  'data-2': {
    'up_adde': '-',
    'up_host': '-'
  }
}

数据加工语句

将上述content内容中的单引号转换成双引号，转换成JSON格式数据。

e_set("content_json",str_replace(ct_str(v("content")),"'",'"'))

处理后的日志为：

content: {
  'referer': '-',
  'request': 'GET /phpMyAdmin',
  'status': 404,
  'data-1': {
    'aaa': 'Mozilla',
    'bbb': 'asde'
  },
  'data-2': {
    'up_adde': '-',
    'up_host': '-'
  }
}
content_json:  {
  "referer": "-",
  "request": "GET /phpMyAdmin",
  "status": 404,
  "data-1": {
    "aaa": "Mozilla",
    "bbb": "asde"
  },
  "data-2": {
    "up_adde": "-",
    "up_host": "-"
  }
}

对经过处理后的标准化的content_json数据进行展开。例如要展开第一层只需要设定JSON中的depth参数为1即可。

e_json("content_json",depth=1,fmt='full')

展开的日志为：

content_json.data-1.data-1:  {"aaa": "Mozilla", "bbb": "asde"}
content_json.data-2.data-2:  {"up_adde": "-", "up_host": "-"}
content_json.referer:  -
content_json.request:  GET /phpMyAdmin
content_json.status:  404

如果depth设置为2，则展开的日志为：

content_json.data-1.aaa:  Mozilla
content_json.data-1.bbb:  asde
content_json.data-2.up_adde:  -
content_json.data-2.up_host:  -
content_json.referer:  -
content_json.request:  GET /phpMyAdmin
content_json.status:  404

综上LOG DSL规则可以如以下形式：

e_set("content_json",str_replace(ct_str(v("content")),"'",'"'))
e_json("content_json",depth=2,fmt='full')

加工后数据

加工后的数据是按照depth为2处理的，具体形式如下：

content:  {
  'referer': '-',
  'request': 'GET /phpMyAdmin',
  'status': 404,
  'data-1': {
    'aaa': 'Mozilla',
    'bbb': 'asde'
  },
  'data-2': {
    'up_adde': '-',
    'up_host': '-'
  }
}
content_json:  {
  "referer": "-",
  "request": "GET /phpMyAdmin",
  "status": 404,
  "data-1": {
    "aaa": "Mozilla",
    "bbb": "asde"
  },
  "data-2": {
    "up_adde": "-",
    "up_host": "-"
  }
}
content_json.data-1.aaa:  Mozilla
content_json.data-1.bbb:  asde
content_json.data-2.up_adde:  -
content_json.data-2.up_host:  -
content_json.referer:  -
content_json.request:  GET /phpMyAdmin
content_json.status:  404

其他格式文本转JSON展开

对一些非标准的JSON格式数据，如果进行展开可以通过组合规则的形式进行操作。

原始日志

content : {
  "pod" => {
    "name" => "crm-learning-follow-7bc48f8b6b-m6kgb"
  }, "node" => {
    "name" => "tw5"
  }, "labels" => {
    "pod-template-hash" => "7bc48f8b6b", "app" => "crm-learning-follow"
  }, "container" => {
    "name" => "crm-learning-follow"
  }, "namespace" => "testing1"
}

数据加工语句
1. 首先将日志格式转换为JSON形式，可以使用str_logtash_config_normalize函数进行转换，操作如下：
```
e_set("normalize_data",str_logtash_config_normalize(v("content")))
```
2. 可以使用JSON函数进行展开操作，具体如下：
```
e_json("normalize_data",depth=1,fmt='full')
```
3. 综上LOG DSL规则可以如以下形式：
```
e_set("normalize_data",str_logtash_config_normalize(v("content")))
e_json("normalize_data",depth=1,fmt='full')
```

加工后数据

content : {
  "pod" => {
    "name" => "crm-learning-follow-7bc48f8b6b-m6kgb"
  }, "node" => {
    "name" => "tw5"
  }, "labels" => {
    "pod-template-hash" => "7bc48f8b6b", "app" => "crm-learning-follow"
  }, "container" => {
    "name" => "crm-learning-follow"
  }, "namespace" => "testing1"
}
normalize_data:  {
  "pod": {
    "name": "crm-learning-follow-7bc48f8b6b-m6kgb"
  },
  "node": {
    "name": "tw5"
  },
  "labels": {
    "pod-template-hash": "7bc48f8b6b",
    "app": "crm-learning-follow"
  },
  "container": {
    "name": "crm-learning-follow"
  },
  "namespace": "testing1"
}
normalize_data.container.container:  {"name": "crm-learning-follow"}
normalize_data.labels.labels:  {"pod-template-hash": "7bc48f8b6b", "app": "crm-learning-follow"}
normalize_data.namespace:  testing1
normalize_data.node.node:  {"name": "tw5"}
normalize_data.pod.pod:  {"name": "crm-learning-follow-7bc48f8b6b-m6kgb"}

部分文本特殊编码转换

在日常工作环境中，会遇到一些十六进制字符，需要对其解码才能正常阅读。可以使用str_hex_escape_encode函数对一些十六进制字符进行转义操作。

原始日志
```
content : "\xe4\xbd\xa0\xe5\xa5\xbd"
```

LOG DSL编排

e_set("hex_encode",str_hex_escape_encode(v("content")))

加工后数据

content : "\xe4\xbd\xa0\xe5\xa5\xbd"
hex_encode : "你好"

XML字段展开

在工作中会遇到各种类型数据，例如xml数据。如果要展开xml数据可以使用xml_to_json函数处理。

测试日志

str : <?xmlversion="1.0"?>
<data>
    <countryname="Liechtenstein">
        <rank>1</rank>
        <year>2008</year>
        <gdppc>141100</gdppc>
        <neighborname="Austria"direction="E"/>
        <neighborname="Switzerland"direction="W"/>
    </country>
    <countryname="Singapore">
        <rank>4</rank>
        <year>2011</year>
        <gdppc>59900</gdppc>
        <neighborname="Malaysia"direction="N"/>
    </country>
    <countryname="Panama">
        <rank>68</rank>
        <year>2011</year>
        <gdppc>13600</gdppc>
        <neighborname="Costa Rica"direction="W"/>
        <neighborname="Colombia"direction="E"/>
    </country>
</data>

LOG DSL编排
```
e_set("str_json",xml_to_json(v("str")))
```

加工后的日志

str : <?xmlversion="1.0"?>
<data>
    <countryname="Liechtenstein">
        <rank>1</rank>
        <year>2008</year>
        <gdppc>141100</gdppc>
        <neighborname="Austria"direction="E"/>
        <neighborname="Switzerland"direction="W"/>
    </country>
    <countryname="Singapore">
        <rank>4</rank>
        <year>2011</year>
        <gdppc>59900</gdppc>
        <neighborname="Malaysia"direction="N"/>
    </country>
    <countryname="Panama">
        <rank>68</rank>
        <year>2011</year>
        <gdppc>13600</gdppc>
        <neighborname="Costa Rica"direction="W"/>
        <neighborname="Colombia"direction="E"/>
    </country>
</data>
str_dict :{
  "data": {
    "country": [{
      "@name": "Liechtenstein",
      "rank": "1",
      "year": "2008",
      "gdppc": "141100",
      "neighbor": [{
        "@name": "Austria",
        "@direction": "E"
      }, {
        "@name": "Switzerland",
        "@direction": "W"
      }]
    }, {
      "@name": "Singapore",
      "rank": "4",
      "year": "2011",
      "gdppc": "59900",
      "neighbor": {
        "@name": "Malaysia",
        "@direction": "N"
      }
    }, {
      "@name": "Panama",
      "rank": "68",
      "year": "2011",
      "gdppc": "13600",
      "neighbor": [{
        "@name": "Costa Rica",
        "@direction": "W"
      }, {
        "@name": "Colombia",
        "@direction": "E"
      }]
    }]
  }
}