Add JavaParquetSink execution operator for the Java platform

[gknz]

Java Parquet Sink

Hey everyone! I built a Java platform execution operator for the existing ParquetSink logical operator, which previously only had a Spark implementation (SparkParquetSink). Now, the optimizer can choose between Java and Spark when writing Parquet files.

What this PR adds

JavaParquetSink (wayang-java/operators/)

• Writes Wayang Records to Parquet files using the parquet-avro library
• Follows the same pattern/logic as SparkParquetSink
• Infers Avro schema automatically by sampling up to 50 records
• Uses RecordType field names when available, falls back to field0, field1, etc.
• Uses Snappy compression
• Handles file overwrite mode

ParquetSinkMapping (wayang-java/mapping/)

• Connects the logical ParquetSink to JavaParquetSink
• Registered in Java platform Mappings.java

Fluent API (DataQuantaBuilder.scala)

• Added writeParquet method to DataQuantaBuilder so users can call it from the fluent API (from my understanding, this was missing — only the DataQuanta.scala layer existed)

Unit Tests (JavaParquetSinkTest.java)

• testWriteStringRecords: verifies basic write and read-back
• testWriteMixedTypeRecords: verifies type inference (Int, String, Double)
• testWriteWithRecordType: verifies column names from RecordType are preserved in the Parquet schema
• testOverwriteExistingFile: verifies overwrite mode replaces data

Testing

All 4 unit tests pass. I also tested the operator in a different pipeline (not included here) that writes hourly aggregated data to Parquet and reads it back for further processing, and it was working as intended,

[zkaoudi]

maybe we do not need the metals twice

[gknz]

Hello @zkaoudi, I removed the duplicate.

[zkaoudi]

Thank you @gknz and congrats on your first contribution :)