Druid入门指南 数据过滤与转换


本教程将演示如何在接收数据期间使用转换规范过滤和转换输入的数据。

1 样例数据

我们在quickstart/tutorial/transform-data.json中包括了样例数据:

{"timestamp":"2018-01-01T07:01:35Z","animal":"octopus",  "location":1, "number":100}
{"timestamp":"2018-01-01T05:01:35Z","animal":"mongoose", "location":2,"number":200}
{"timestamp":"2018-01-01T06:01:35Z","animal":"snake", "location":3, "number":300}
{"timestamp":"2018-01-01T01:01:35Z","animal":"lion", "location":4, "number":300}

2 使用转换规范加载数据

我们将使用以下规范摄取示例数据,该规范演示了转换规范的使用:

{
  "type" : "index_parallel",
  "spec" : {
    "dataSchema" : {
      "dataSource" : "transform-tutorial",
      "timestampSpec": {
        "column": "timestamp",
        "format": "iso"
      },
      "dimensionsSpec" : {
        "dimensions" : [
          "animal",
          { "name": "location", "type": "long" }
        ]
      },
      "metricsSpec" : [
        { "type" : "count", "name" : "count" },
        { "type" : "longSum", "name" : "number", "fieldName" : "number" },
        { "type" : "longSum", "name" : "triple-number", "fieldName" : "triple-number" }
      ],
      "granularitySpec" : {
        "type" : "uniform",
        "segmentGranularity" : "week",
        "queryGranularity" : "minute",
        "intervals" : ["2018-01-01/2018-01-03"],
        "rollup" : true
      },
      "transformSpec": {
        "transforms": [
          {
            "type": "expression",
            "name": "animal",
            "expression": "concat('super-', animal)"
          },
          {
            "type": "expression",
            "name": "triple-number",
            "expression": "number * 3"
          }
        ],
        "filter": {
          "type":"or",
          "fields": [
            { "type": "selector", "dimension": "animal", "value": "super-mongoose" },
            { "type": "selector", "dimension": "triple-number", "value": "300" },
            { "type": "selector", "dimension": "location", "value": "3" }
          ]
        }
      }
    },
    "ioConfig" : {
      "type" : "index_parallel",
      "inputSource" : {
        "type" : "local",
        "baseDir" : "quickstart/tutorial",
        "filter" : "transform-data.json"
      },
      "inputFormat" : {
        "type" :"json"
      },
      "appendToExisting" : false
    },
    "tuningConfig" : {
      "type" : "index_parallel",
      "maxRowsPerSegment" : 5000000,
      "maxRowsInMemory" : 25000
    }
  }
}

在转换规范中,我们有两个表达式转换:

  • super-animal: 在 "animal" 列的值前加上super-。这将用转换后的版本覆盖animal列,因为转换的名称是animal
  • triple-number: 将数字列乘以3, 这将创建一个新的三位数列。注意,我们同时接收原始列和转换列

另外,我们有一个包含三个子句的OR过滤器:

  • super-animal值匹配super-mongoose
  • triple-number值匹配300
  • location值匹配3

这个过滤器选择前3行,它将排除输入数据中的最后一个lion行。

注意:过滤器是在转换之后应用的。

现在提交位于quickstart/tutorial/transform-index.json的任务:

bin/post-index-task --file quickstart/tutorial/transform-index.json --url http://localhost:8081

3 查询已转换的数据

运行bin/dsql提交select * from "transform-tutorial"查询来看摄入的数据:

dsql> select * from "transform-tutorial";
┌──────────────────────────┬────────────────┬───────┬──────────┬────────┬───────────────┐
│ __time                   │ animal         │ count │ location │ number │ triple-number │
├──────────────────────────┼────────────────┼───────┼──────────┼────────┼───────────────┤
│ 2018-01-01T05:01:00.000Z │ super-mongoose │     1 │        2 │    200 │           600 │
│ 2018-01-01T06:01:00.000Z │ super-snake    │     1 │        3 │    300 │           900 │
│ 2018-01-01T07:01:00.000Z │ super-octopus  │     1 │        1 │    100 │           300 │
└──────────────────────────┴────────────────┴───────┴──────────┴────────┴───────────────┘
Retrieved 3 rows in 0.03s.

Lion列被丢弃,animal列被转换,结果既有原始列,也有转换后的数字列。