126 lines
5.1 KiB
Markdown
126 lines
5.1 KiB
Markdown
<!-- toc -->
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## 输入数据变换
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本教程将演示如何使用转换规范在接收期间过滤和转换输入数据
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本教程我们假设您已经按照[单服务器部署](../GettingStarted/chapter-3.md)中描述下载了Druid，并运行在本地机器上。
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完成[加载本地文件](./chapter-1.md)、[数据查询](./chapter-4.md)和[roll-up](./chapter-5.md)部分内容也是非常有帮助的
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### 样例数据
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我们在 `quickstart/tutorial/transform-data.json` 中包括了样例数据，为了方便我们展示一下：
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```json
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{"timestamp":"2018-01-01T07:01:35Z","animal":"octopus", "location":1, "number":100}
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{"timestamp":"2018-01-01T05:01:35Z","animal":"mongoose", "location":2,"number":200}
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{"timestamp":"2018-01-01T06:01:35Z","animal":"snake", "location":3, "number":300}
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{"timestamp":"2018-01-01T01:01:35Z","animal":"lion", "location":4, "number":300}
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```
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### 使用转换规范加载数据
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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：
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```json
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{
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"type" : "index_parallel",
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"spec" : {
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"dataSchema" : {
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"dataSource" : "transform-tutorial",
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"timestampSpec": {
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"column": "timestamp",
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"format": "iso"
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},
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"dimensionsSpec" : {
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"dimensions" : [
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"animal",
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{ "name": "location", "type": "long" }
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]
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},
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"metricsSpec" : [
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{ "type" : "count", "name" : "count" },
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{ "type" : "longSum", "name" : "number", "fieldName" : "number" },
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{ "type" : "longSum", "name" : "triple-number", "fieldName" : "triple-number" }
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],
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"granularitySpec" : {
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"type" : "uniform",
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"segmentGranularity" : "week",
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"queryGranularity" : "minute",
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"intervals" : ["2018-01-01/2018-01-03"],
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"rollup" : true
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},
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"transformSpec": {
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"transforms": [
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{
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"type": "expression",
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"name": "animal",
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"expression": "concat('super-', animal)"
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},
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{
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"type": "expression",
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"name": "triple-number",
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"expression": "number * 3"
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}
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],
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"filter": {
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"type":"or",
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"fields": [
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{ "type": "selector", "dimension": "animal", "value": "super-mongoose" },
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{ "type": "selector", "dimension": "triple-number", "value": "300" },
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{ "type": "selector", "dimension": "location", "value": "3" }
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]
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}
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}
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},
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"ioConfig" : {
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"type" : "index_parallel",
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"inputSource" : {
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"type" : "local",
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"baseDir" : "quickstart/tutorial",
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"filter" : "transform-data.json"
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},
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"inputFormat" : {
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"type" :"json"
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},
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"appendToExisting" : false
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},
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"tuningConfig" : {
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"type" : "index_parallel",
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"maxRowsPerSegment" : 5000000,
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"maxRowsInMemory" : 25000
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}
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}
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}
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```
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在转换规范中，我们有两个表达式转换：
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* `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`
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* `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
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另外，我们有一个包含三个子句的OR过滤器：
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* `super-animal` 值匹配"super-mongoose"
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* `triple-number` 值匹配300
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* `location`值匹配3
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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。请注意，过滤器是在转换之后应用的。
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现在提交位于 `quickstart/tutorial/transform-index.json` 的任务：
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```json
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bin/post-index-task --file quickstart/tutorial/transform-index.json --url http://localhost:8081
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```
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### 查询已转换的数据
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运行 `bin/dsql` 提交 `select * from "transform-tutorial"` 查询来看摄入的数据：
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```json
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dsql> select * from "transform-tutorial";
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┌──────────────────────────┬────────────────┬───────┬──────────┬────────┬───────────────┐
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│ __time │ animal │ count │ location │ number │ triple-number │
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├──────────────────────────┼────────────────┼───────┼──────────┼────────┼───────────────┤
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│ 2018-01-01T05:01:00.000Z │ super-mongoose │ 1 │ 2 │ 200 │ 600 │
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│ 2018-01-01T06:01:00.000Z │ super-snake │ 1 │ 3 │ 300 │ 900 │
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│ 2018-01-01T07:01:00.000Z │ super-octopus │ 1 │ 1 │ 100 │ 300 │
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└──────────────────────────┴────────────────┴───────┴──────────┴────────┴───────────────┘
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Retrieved 3 rows in 0.03s.
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```
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"Lion"列被丢弃，`animal`列被转换，我们既有原始列，也有转换后的数字列。 |