chore: update questions.json

[eltociear]

fucntion -> function

[llamapreview]

Auto Pull Request Review from LlamaPReview

1. Overview

1.1 PR Summary

• Business value and requirements alignment: The PR aims to correct a typographical error in the questions.json file, ensuring the readability and accuracy of training data, which is critical for accurate Text-to-SQL generation.
• Key components modified: The training_data/similarweb/questions.json file.
• Impact assessment: The change improves data accuracy and readability without introducing any new functionality or dependencies.
• System dependencies and integration impacts: None. The change is isolated to a single file and does not affect system dependencies or integration points.

1.2 Architecture Changes

• System design modifications: None. The change is a simple correction in a JSON file and does not affect the system architecture.
• Component interactions: None. The change does not alter how components interact within the system.
• Integration points: None. The file is used for training data and does not impact integration points.

2. Detailed Technical Analysis

2.1 Code Logic Deep-Dive

Core Logic Changes

Example 1: Correction in questions.json

• File Path: training_data/similarweb/questions.json
  • Submitted PR Code:

    [
        {

•      "question":"what are the year on year total visits on Tesla and ford from 2018 to 2023 ? Convert varchar to date using to date fucntion , Plot a line chart ",
  

•      "question":"what are the year on year total visits on Tesla and ford from 2018 to 2023 ? Convert varchar to date using to date function , Plot a line chart ",
        "answer":"SELECT company_name, extract(year FROM to_date(date, 'YYYY-MM-DD')) as year, sum(total_visits) as total_visits FROM s__p_500_by_domain_and_aggregated_by_tickers_sample.datafeeds.sp_500 WHERE (company_name ilike '%Tesla%' or company_name = 'Ford') and to_date(date, 'YYYY-MM-DD') between '2018-01-01' and '2023-12-31' GROUP BY company_name, extract(year FROM to_date(date, 'YYYY-MM-DD')) ORDER BY company_name, year;"
    },
    ...
  

  ]

  - **Analysis**:
  - **Current logic and potential issues**: The change corrects a typo from "fucntion" to "function." No functional issues are observed with this change.
  - **Edge cases and error handling**: None applicable for this change.
  - **Cross-component impact **: None.
  - **Business logic considerations **: None.
  - **LlamaPReview Suggested Improvements**: None required. The change is straightforward and corrects a typo.
  - **Improvement rationale **: None.
  
  

Example 2: Another Correction in questions.json

• File Path: training_data/similarweb/questions.json
  • Submitted PR Code:

    [
        {

•      "question":"what are the year on year total visits on ebay and amazon from 2018 to 2021? Convert varchar to date using to date fucntion , Plot a line chart ",
  

•      "question":"what are the year on year total visits on ebay and amazon from 2018 to 2021? Convert varchar to date using to date function , Plot a line chart ",
        "answer":"SELECT company_name, extract(year FROM to_date(date, 'YYYY-MM-DD')) as year, sum(total_visits) as total_visits FROM s__p_500_by_domain_and_aggregated_by_tickers_sample.datafeeds.sp_500 WHERE (company_name ilike '%ebay%' or company_name ilike '%amazon%') and to_date(date, 'YYYY-MM-DD') between '2018-01-01' and '2021-12-31' GROUP BY company_name, extract(year FROM to_date(date, 'YYYY-MM-DD')) ORDER BY company_name, year;"
    },
    ...
  

  ]

  - **Analysis**:
  - **Current logic and potential issues**: Similar to the previous example, this change corrects a typo from "fucntion" to "function." No functional issues are observed with this change.
  - **Edge cases and error handling**: None applicable for this change.
  - **Cross-component impact **: None.
  - **Business logic considerations **: None.
  - **LlamaPReview Suggested Improvements**: None required. The change is straightforward and corrects a typo.
  - **Improvement rationale **: None.
  
  

Cross-cutting Concerns

• Data flow analysis: Not applicable for this change.
• State management implications: Not applicable for this change.
• Error propagation paths: Not applicable for this change.
• Edge case handling across components: Not applicable for this change.

Algorithm & Data Structure Analysis

• Complexity analysis: Not applicable for this change.
• Performance implications: Not applicable for this change.
• Memory usage considerations: Not applicable for this change.

2.2 Implementation Quality

• Code organization and structure: The questions.json file is well-organized, and the changes are isolated to the specific questions that needed correction.
• Design patterns usage: Not applicable for JSON files.
• Error handling approach: Not applicable for this change.
• Resource management: Not applicable for this change.

3. Critical Findings

3.1 Potential Issues

• 🔴 Critical Issues: None
• 🟡 Warnings: None

3.2 Code Quality Concerns

• Maintainability aspects: The corrections improve readability and maintainability by ensuring consistency in terminology.
• Readability issues: None.
• Performance bottlenecks: None applicable for this change.

4. Security Assessment

4.1 Security Considerations

• Authentication/Authorization impacts: Not applicable for this change.
• Data handling concerns: Not applicable for this change.
• Input validation: Not applicable for this change.
• Security best practices: Not applicable for this change.

4.2 Vulnerability Analysis

• Potential security risks: None.
• Mitigation strategies: Not applicable for this change.
• Security testing requirements: Not applicable for this change.

5. Testing Strategy

5.1 Test Coverage

• Unit test analysis: Not applicable for this change.
• Integration test requirements: Not applicable for this change.
• Edge cases coverage: Not applicable for this change.

5.2 Test Recommendations

Suggested Test Cases

[
  {
    "question":"what are the year on year total visits on Tesla and ford from 2018 to 2023 ? Convert varchar to date using to date function , Plot a line chart ",
    "answer":"SELECT company_name, extract(year FROM to_date(date, 'YYYY-MM-DD')) as year, sum(total_visits) as total_visits FROM s__p_500_by_domain_and_aggregated_by_tickers_sample.datafeeds.sp_500 WHERE (company_name ilike '%Tesla%' or company_name = 'Ford') and to_date(date, 'YYYY-MM-DD') between '2018-01-01' and '2023-12-31' GROUP BY company_name, extract(year FROM to_date(date, 'YYYY-MM-DD')) ORDER BY company_name, year;"
  },
  ...
]

• Coverage improvements: Not applicable for this change.
• Performance testing needs: Not applicable for this change.

6. Documentation & Maintenance

• Documentation updates needed (API, architecture, configuration): None.
• Long-term maintenance considerations: The correction improves maintainability by ensuring consistency in terminology.
• Technical debt and monitoring requirements: None.

7. Deployment & Operations

• Deployment impact and strategy: None. The change is isolated to a single file and does not affect deployment processes.
• Key operational considerations: None. The change does not affect operational processes.

8. Summary & Recommendations

8.1 Key Action Items

1. Critical changes required: None
2. Important improvements suggested: None
3. Best practices to implement: None
4. Cross-cutting concerns to address: None

8.2 Future Considerations

• Technical evolution path: Continue to monitor and correct any inconsistencies in training data to ensure accuracy.
• Business capability evolution: Maintain high standards of data quality to support accurate Text-to-SQL generation.
• System integration impacts: None. The change is isolated and does not affect system integration.