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@Order List Monthly Report Screen_Requirements Specification I would like to design a daily batch to aggregate data for display on the screen. Please output it according to the @Batch Design Template format.

</aside>

Template

## 1. Basic Information

| Item          | Content                    |
| ------------- | -------------------------- |
| Batch ID      | \\[Unique batch identifier] |
| Batch Name    | \\[Name of batch process]   |
| Author        | \\[Author name]             |
| Creation Date | \\[Creation date]           |
| Last Updated  | \\[Last updated date]       |
| Version       | \\[Document version]        |

## 2. Overview

### 2.1 Purpose

\\[Briefly describe the purpose and role of this batch process]

### 2.2 Process Overview

\\[Describe the overall flow and main functions of the batch process]

### 2.3 Execution Frequency

- Execution Timing: \\[Daily/Weekly/Monthly/Other]
- Execution Time: \\[HH:MM]
- Schedule Details: \\[Cron expression or specific conditions]

## 3. Prerequisites and Dependencies

### 3.1 Prerequisites

\\[List the prerequisites required to execute the batch]

### 3.2 Dependent Systems/Batches

\\[Other systems or batch processes this batch depends on]

### 3.3 Execution Order Constraints

\\[Constraints regarding execution order with other batches]

## 4. Input Information

### 4.1 Input Files

| File Name    | Format               | Location | Description    |
| ------------ | -------------------- | -------- | -------------- |
| \\[File name] | \\[CSV/XML/JSON etc.] | \\[Path]  | \\[Description] |

### 4.2 Input Parameters

| Parameter Name | Data Type | Required | Default Value | Description    |
| -------------- | --------- | -------- | ------------- | -------------- |
| \\[Parameter]   | \\[Type]   | \\[Y/N]   | \\[Default]    | \\[Description] |

### 4.3 Database Input

| Table Name    | Main Columns | Retrieval Conditions | Description    |
| ------------- | ------------ | -------------------- | -------------- |
| \\[Table name] | \\[Columns]   | \\[WHERE conditions]  | \\[Description] |

## 5. Process Flow

### 5.1 Overall Flowchart

Create the flowchart for this process using Mermaid according to the following legend.

```mermaid
flowchart TD
    subgraph Legend
        A((Start/End Node)) 
        B[Process Step/Action]
        C{Branch/Condition}
        D[[Database Operation]]
        E[[File Input/Output]]
        F[/Error Handling/]
        G((Subprocess/Function Call))
        H[(Database)]
        
        style A fill:#e0e0e0,stroke:#333,stroke-width:2
        style B fill:#2196f3,stroke:#0d47a1,stroke-width:2,color:#fff
        style C fill:#ff9800,stroke:#e65100,stroke-width:2,color:#fff
        style D fill:#43a047,stroke:#1b5e20,stroke-width:2,color:#fff
        style E fill:#ffd600,stroke:#fbc02d,stroke-width:2,color:#333
        style F fill:#d32f2f,stroke:#b71c1c,stroke-width:2,stroke-dasharray: 5 5,color:#fff
        style G fill:#8e24aa,stroke:#4a148c,stroke-width:2,color:#fff
        style H fill:#0097a7,stroke:#006064,stroke-width:2,color:#fff

        noteA[Start/End]
        noteB[Main Process]
        noteC[Condition]
        noteD[DB Operation]
        noteE[File I/O]
        noteF[Error Handling]
        noteG[Subprocess]
        noteH[Database]
        
        A-->|Example|noteA
        B-->|Example|noteB
        C-->|Example|noteC
        D-->|Example|noteD
        E-->|Example|noteE
        F-->|Example|noteF
        G-->|Example|noteG
        H-->|Example|noteH
    end

5.2 Process Steps

1. \[Description of Step 1]
2. \[Description of Step 2]
3. \[Description of Step 3]

5.3 Main Algorithms

\[Description of complex logic or important algorithms]

6. Output Information

6.1 Output Files

6.2 Database Updates

6.3 Log Output

7. Error Handling

7.1 Expected Errors

7.2 Retry Settings

• Retry Count: \[Count]
• Retry Interval: \[Interval]
• Retry Conditions: \[Conditions]

7.3 Abnormal Termination Handling

\[Details of handling abnormal termination, notification methods, rollback procedures, etc.]

8. Performance Requirements

8.1 Processing Time

• Expected Processing Time: \[Time]
• Timeout Setting: \[Setting]

8.2 Resource Requirements

• Memory Usage: \[Size]
• CPU Usage: \[Usage]
• Disk Capacity: \[Size]

8.3 Concurrency

\[Whether concurrent execution is possible, methods of exclusive control, etc.]

9. Monitoring and Operations

9.1 Monitoring Items

9.2 Operation Procedures

• Normal Operation: \[Procedure]
• Abnormal Response: \[Procedure]
• Manual Execution Method: \[Procedure]

9.3 Backup and Recovery

\[Backup methods, recovery procedures]

10. Security Requirements

10.1 Access Permissions

\[Permissions required for execution, access control]

10.2 Handling Confidential Data

\[Handling of confidential data, encryption requirements, etc.]

11. Change History

## Output Image

```markdown
# Daily Aggregation Batch Design Document for Order List Monthly Report Screen

## 1. Basic Information

| Item         | Content                                      |
| ------------ | -------------------------------------------- |
| Batch ID     | order-monthly-report-daily-summary           |
| Batch Name   | Order Monthly Report Daily Aggregation Batch |
| Author       | Takaaki Fujino                               |
| Created Date | 2025/08/14                                   |
| Last Updated | 2025/08/14                                   |
| Version      | 1.0                                          |

## 2. Overview

### 2.1 Purpose

To create aggregated data daily for the order list monthly report screen (administrator dashboard), enabling faster data analysis and load distribution.

### 2.2 Processing Overview

- Aggregate order details, sales, status distribution, etc. for the previous day from the EC-CUBE order database and store them in a dedicated summary table.
- Also perform aggregation by day, status, customer/product.
- The screen/API will reference the pre-aggregated data.

### 2.3 Execution Frequency

- Execution Timing: Daily (recommended at 2:00 AM)
- Execution Time: 02:00
- Schedule Details: cron expression `0 2 * * *`

## 3. Prerequisites and Dependencies

### 3.1 Prerequisites

- Order tables and related master data must be correctly updated by the day.
- The batch execution user must have the necessary DB access permissions.

### 3.2 Dependent Systems/Batches

- Order data update batch (cannot execute while other batches are stopped)
- Sales and customer-related master data

### 3.3 Execution Order Constraints

- Execute after sales reflection/cancellation is completed

## 4. Input Information

### 4.1 Input Files

No file input for this batch (DB only)

### 4.2 Input Parameters

| Parameter Name | Data Type | Required | Default Value | Description      |
| -------------- | --------- | -------- | ------------- | ---------------- |
| target\\_date   | DATE      | Y        | Previous day  | Aggregation date |

### 4.3 Database Input

| Table Name         | Main Columns                            | Retrieval Condition        | Description          |
| ------------------ | --------------------------------------- | -------------------------- | -------------------- |
| dtb\\_order         | order\\_id, customer\\_id, status, total  | order\\_date = target\\_date | Order data           |
| dtb\\_order\\_detail | order\\_id, product\\_id, price, quantity | order\\_date = target\\_date | Order details        |
| mtb\\_order\\_status | status\\_id, name                        | All                        | Order status master  |
| dtb\\_customer      | customer\\_id, name                      | All                        | Customer information |
| dtb\\_product       | product\\_id, name                       | All                        | Product information  |

## 5. Processing Flow

### 5.1 Overall Flow Diagram

```mermaid
flowchart TD
    A((Batch Start))
    B[Determine Aggregation Date]
    C[Retrieve Orders, Details, Masters]
    D{Check for Order Data}
    E[Aggregation Processing - Each Analysis Item]
    F[Insert/Update Aggregation Results to Dedicated Table]
    G[/Error Handling/]
    H((Batch End))

    A --> B --> C --> D
    D -- Yes --> E --> F --> H
    D -- No --> H
    E --Error--> G --> H

5.2 Processing Steps

1. Determine aggregation target date (previous day)
2. Retrieve order data, details, status master, customer, and product information
3. Check for existence of target data
4. Aggregate total sales, number of orders, count by status, daily sales, customer/product ranking
5. Insert/Update aggregation results to dedicated summary table
6. Log and notify in case of errors

5.3 Main Algorithms

• Number of orders and total sales: Aggregate totals from the order table
• Aggregation by status: Group and aggregate by order.status
• Ranking: Rank by sales and number of orders
• Data for CSV output is stored in the table and downloaded from the screen

6. Output Information

6.1 Output Files

No file output in principle (DB storage. CSV export is handled by the screen function)

6.2 Database Update

6.3 Log Output

7. Error Handling

7.1 Expected Errors

7.2 Retry Settings

• Retry count: 3 times
• Retry interval: 5 minutes
• Retry condition: DB connection errors

7.3 Processing on Abnormal Termination

• Output error log
• Notify administrator by email
• Rollback processing as needed

8. Performance Requirements

8.1 Processing Time

• Expected processing time: Within 10 minutes (target 2 minutes)
• Timeout setting: 15 minutes

8.2 Resource Requirements

• Memory usage: Less than 512MB
• CPU usage: Less than 50%
• Disk space: No need to store large amounts of data

8.3 Concurrency

• Exclusive control enabled (no concurrent execution)

9. Monitoring and Operation

9.1 Monitoring Items

9.2 Operation Procedure

• Normal operation: Scheduler automatic execution/result confirmation
• Abnormal response: Refer to logs, re-execute, notify administrator
• Manual execution method: Can be executed from console

9.3 Backup and Recovery

• Daily backup of summary table
• Recovery with previous day's data in case of abnormality

10. Security Requirements

10.1 Access Permissions

• Restrict scope of DB account for batch execution (only necessary tables for aggregation)

10.2 Confidential Data Handling

• Confidential information (such as customer names) is encrypted on the DB side
• No plain data held in the batch

11. Change History