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[Fix][Docs] Perfect expected_value and formula docs (#27)
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zixi0825 authored Oct 3, 2023
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---
id: 'expected-value-none'
title: 'expected-value-none'
title: 'none'
---
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---
id: 'expected-value-fix-value'
title: 'fix'
---

This file was deleted.

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---
id: 'expected-value-daily-avg'
title: 'expected-value-daily-avg'
title: 'daily-avg'
---
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---
id: 'expected-value-weekly-avg'
title: 'expected-value-weekly-avg'
title: 'weekly-avg'
---
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---
id: 'expected-value-monthly-avg'
title: 'expected-value-monthly-avg'
title: 'monthly-avg'
---
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---
id: 'expected-value-last7day-avg'
title: 'expected-value-last7day-avg'
title: 'last7day-avg'
---
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---
id: 'expected-value-last30day-avg'
title: 'expected-value-last30day-avg'
title: 'last30day-avg'
---
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---
id: 'expected-value-table-rows'
title: 'expected-value-table-rows'
title: 'table-rows'
---
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---
id: 'expected-value-target-table-rows'
title: 'expected-value-target-table-rows'
title: 'target-table-rows'
---
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Expand Up @@ -5,7 +5,7 @@ title: 'PostgreSQL'

## 介绍

`MySQL` 连接器用于与 `MySQL` 类型的数据源建立连接,获取元数据和执行数据质量检查。
`PostgreSQL` 连接器用于与 `PostgreSQL` 类型的数据源建立连接,获取元数据和执行数据质量检查。

## 参数
### Options
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Expand Up @@ -5,7 +5,7 @@ title: 'Impala'

## 介绍

`Presto` 连接器用于与 `Presto` 类型的数据源建立连接,获取元数据和执行数据质量检查。
`Impala` 连接器用于与 `Impala` 类型的数据源建立连接,获取元数据和执行数据质量检查。

## 参数
### Options
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---
id: 'expected-value-none'
title: '期望值-'
title: ''
---

## 概念解释
Expand All @@ -9,14 +9,3 @@ title: '期望值-无'
## 使用方法
- 点击创建规则作业,选择数据质量作业
- 在期望值中选择 ``

## 使用案例

### 场景
...

### 思路
...

### 步骤
...
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---
id: 'expected-value-fix'
title: '期望值-固定值'
id: 'expected-value-fix-value'
title: '固定值'
---

## 概念解释
Expand All @@ -9,14 +9,3 @@ title: '期望值-固定值'
## 使用方法
- 点击创建规则作业,选择数据质量作业
- 在期望值中选择 `固定值`,在固定值输入框中输入期望值。

## 使用案例

### 场景
...

### 思路
...

### 步骤
...
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---
id: 'expected-value-daily-avg'
title: '期望值-日均值'
title: '日均值'
---

## 概念解释
Expand Down Expand Up @@ -31,15 +31,4 @@ from dv_actual_values
where data_time >=date_format(${data_time}, 'yyyy-MM-dd')
and data_time < date_add(date_format(${data_time}, 'yyyy-MM-dd'),1)
and unique_code = ${unique_code}
```

## 使用案例

### 场景
...

### 思路
...

### 步骤
...
```
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---
id: 'expected-value-weekly-avg'
title: '期望值-周均值'
title: '周均值'
---

## 概念解释
Expand Down Expand Up @@ -31,15 +31,4 @@ from dv_actual_values
where data_time >= date_sub(date_format(${data_time},'yyyy-MM-dd'), (7- datediff(next_day(date_format(${data_time}, 'yyyy-MM-dd'),'Sunday'),date_format(${data_time}, 'yyyy-MM-dd')))-1)
and data_time < date_add(date_format(${data_time}, 'yyyy-MM-dd'),1)
and unique_code = ${unique_code}
```

## 使用案例

### 场景
...

### 思路
...

### 步骤
...
```
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---
id: 'expected-value-monthly-avg'
title: '期望值-月均值'
title: '月均值'
---

## 概念解释
Expand Down Expand Up @@ -30,15 +30,4 @@ from dv_actual_values
where data_time >= date_format(${data_time}, 'yyyy-MM-01')
and data_time < date_add(date_format(${data_time}, 'yyyy-MM-dd'),1)
and unique_code = ${unique_code}
```

## 使用案例

### 场景
...

### 思路
...

### 步骤
...
```
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---
id: 'expected-value-last7day-avg'
title: '期望值-最近7天均值'
title: '最近7天均值'
---

## 概念解释
Expand Down Expand Up @@ -29,15 +29,4 @@ select round(avg(actual_value),2) as expected_value_${uniqueKey}
from dv_actual_values
where data_time >= date_add(date_format(${data_time}, 'yyyy-MM-dd'),-7)
and data_time < date_add(date_format(${data_time}, 'yyyy-MM-dd'),1) and unique_code = ${unique_code}
```

## 使用案例

### 场景
...

### 思路
...

### 步骤
...
```
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---
id: 'expected-value-last30day-avg'
title: '期望值-最近30天均值'
title: '最近30天均值'
---

## 概念解释
Expand Down Expand Up @@ -29,14 +29,4 @@ select round(avg(actual_value),2) as expected_value_${uniqueKey}
from dv_actual_values
where data_time >= date_add(date_format(${data_time}, 'yyyy-MM-dd'),-30)
and data_time < date_add(date_format(${data_time}, 'yyyy-MM-dd'),1) and unique_code = ${unique_code}
```
## 使用案例

### 场景
...

### 思路
...

### 步骤
...
```
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---
id: 'expected-value-table-rows'
title: '期望值-表总行数'
title: '表总行数'
---

## 概念解释
Expand All @@ -17,15 +17,4 @@ title: '期望值-表总行数'
- `Local`&`Spark`&`Livy` 引擎
```
select count(1) as expected_value_${uniqueKey} from ${table}
```

## 使用案例

### 场景
...

### 思路
...

### 步骤
...
```
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---
id: 'expected-value-target-table-rows'
title: '期望值-目标表总行数'
title: '目标表总行数'
---

## 概念解释
Expand All @@ -17,15 +17,4 @@ title: '期望值-目标表总行数'
- `Local`&`Spark`&`Livy` 引擎
```
select count(1) as expected_value_${uniqueKey} from ${target_table}
```

## 使用案例

### 场景
...

### 思路
...

### 步骤
...
```
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---
id: 'formula-intro'
title: '比对公式介绍'
title: 公式介绍'
---

## 概念解释
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---
id: 'formula-count'
title: '比对公式-实际值'
title: '实际值'
---

## 概念解释
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---
id: 'formula-diff'
title: '比对公式-|实际值-期望值|'
title: '|实际值-期望值|'
---

## 概念解释
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---
id: 'formula-diff-actual-expected'
title: '比对公式-实际值-期望值'
title: '实际值-期望值'
---

## 概念解释
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---
id: 'formula-diff-percentage'
title: '比对公式-|实际值-期望值|/期望值*100%'
title: '|实际值-期望值|/期望值*100%'
---

## 概念解释
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---
id: 'formula-percentage'
title: '比对公式-实际值/期望值*100%'
title: '实际值/期望值*100%'
---

## 概念解释
Expand Down

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