如何对无自定义对象及函数的U-SQL脚本进行单元测试？

Great question! Testing U-SQL scripts that don’t rely on custom user-defined objects (UDOs) or functions (UDFs) is totally feasible—here are practical, hands-on approaches I’ve used in real-world projects:

The simplest way to get started is to run your U-SQL script locally using mock test data instead of your production Azure Data Lake Storage (ADLS) sources. Here’s how:

• Prepare test input: Create small, focused datasets (CSV, Parquet, etc.) that cover typical cases, edge cases (empty input, null values, duplicates), and any specific scenarios your script handles. Store these locally (e.g., C:\U-SQL-Tests\Input\sales_data_test.csv).
• Adjust the script for local execution: Replace references to Azure data sources with local file paths. For example, if your original script uses REFERENCE DataSource MyProductionADLS;, swap it for a direct local path like @"C:\U-SQL-Tests\Input\sales_data_test.csv".
• Run the script locally: Use Azure Data Lake Tools for Visual Studio or the Azure.DataLake.Store PowerShell module to execute the script on your local machine. This generates output files in your specified local directory.
• Compare output to expected results: Manually or programmatically check if the output matches your pre-defined expected dataset (e.g., C:\U-SQL-Tests\Expected\aggregated_sales_expected.csv).

If you’re using Azure Data Lake Tools for Visual Studio, the built-in U-SQL Test Framework works great even for scripts without custom UDOs/UDFs:

• Create a U-SQL Test Project: In Visual Studio, add a new U-SQL Test Project to your solution.
• Add a test method: Right-click the project > Add > Test Method. In the test code, specify:
  • The path to your target U-SQL script.
  • Mock input data (you can use local files or even in-memory data tables for simple cases).
  • The expected output schema and values.
• Run the test: Use the Test Explorer to execute the test. The framework will run your script, capture the output, and validate it against your assertions. For example, you can use Assert.AreEqual(expectedRowCount, actualRowCount) to check row counts, or verify specific field values with Assert.IsTrue(outputRows.Any(r => r["TotalSales"].Equals(1500.00))).

Don’t skip static checks—these help catch syntax errors, invalid references, or logical issues before running the script:

• Visual Studio syntax check: Right-click your U-SQL script in Solution Explorer > Check Syntax. This will flag any invalid keywords, missing brackets, or incorrect data source references.
• CLI validation: Use the Azure CLI to validate your script programmatically with the command:

  az u-sql script validate --script-path "path/to/your/script.usql"
  

  This is great for integrating into CI/CD pipelines to catch issues early.

To make testing repeatable, automate the comparison between actual output and expected results:

• PowerShell script: Write a simple script to read both the actual output file and expected file, then compare line-by-line. For example:

  $actual = Get-Content "C:\U-SQL-Tests\Output\actual_results.csv"
  $expected = Get-Content "C:\U-SQL-Tests\Expected\expected_results.csv"
  Compare-Object -ReferenceObject $expected -DifferenceObject $actual
  

• C# utility: Use File.ReadAllLines() to load both files, then use LINQ to compare each line, or load the data into DataTable instances to validate column values more granularly.

Pro Tips #

• Keep test datasets small—this keeps test runs fast and makes it easier to debug failures.
• Test all edge cases: empty input, malformed records, null values, and boundary values (e.g., maximum/minimum numeric values).
• Sync tests with script changes: If you update your main U-SQL script, make sure to update your test input and expected output to match the new logic.

内容的提问来源于stack exchange，提问作者Rahul Wagh