Implement a CSV dataset join

Implement joinDataSet(fieldName, customerFile, processorFile, skipUnmatched).

You are given two datasets represented as List<String>, where:

• customerFile[0] is the header row for the customer dataset.
• processorFile[0] is the header row for the processor dataset.
• Every remaining element is a data row.
• Columns are separated by commas.
• You may assume values do not contain escaped commas or quoted commas.

Inputs:

• fieldName: String — the column name used as the join key.
• customerFile: List<String>
• processorFile: List<String>
• skipUnmatched: boolean

Return a new List<String> representing the joined dataset:

• The first element is the output header.
• The remaining elements are the output rows.

Requirements:

1. The join key fieldName exists in both headers.
2. Sort the customer rows and processor rows by fieldName before joining.
3. Perform a join from customerFile to processorFile using fieldName .
4. If a customer row has multiple matching processor rows, output multiple joined rows, one for each match.
5. If a customer row has no matching processor row:
   • when skipUnmatched == false , include the customer row and fill the processor-side columns with empty strings;
   • when skipUnmatched == true , omit that customer row entirely.
6. Processor rows with no matching customer row should not appear in the output.
7. The output should contain all customer columns followed by all processor columns from the processor file. If the join key would appear twice, include it only once in the output.

In short, this problem evolves through four stages:

• Part 1: basic join on fieldName
• Part 2: left join behavior for unmatched customer rows
• Part 3: support multiple matches on the processor side
• Part 4: optionally skip unmatched customer rows when skipUnmatched is true

Write the function that produces the joined CSV-style dataset.