Native Parquet write of a zero-partition RDD produces no output file #5303

Found while reviewing #5293 against the Iceberg split-writer work in #4658.

Describe the bug

Spark's WriteFilesExec.doExecuteWrite guards against a child RDD with zero partitions (SPARK-23271):

val rddWithNonEmptyPartitions = if (rdd.partitions.length == 0) {
  session.sparkContext.parallelize(Array.empty[InternalRow], 1)
} else {
  rdd
}

Without it no write task runs at all, so the output directory ends up with no data file — not even the schema-only file Spark produces. IcebergWriteExec added in #4658 carries the same guard.

CometWriteFilesExec.doExecuteWrite has no equivalent: it calls child.executeColumnar() and goes straight to mapPartitionsInternal. With zero partitions, FileFormatWriter.writeAndCommit collects zero WriteTaskResults and commits an empty job. The result is a _SUCCESS marker over an empty directory, where Spark writes one file carrying the schema.

Note this is not a regression from #5293 — the CometNativeWriteExec it replaced had the same hole.

Steps to reproduce

Any write whose input plan yields a zero-partition RDD (for example a scan over an empty relation), with spark.comet.parquet.write.enabled=true.

Expected behavior

Match Spark: run one write task so the output carries the schema.

Harder here than in the Iceberg case because the dummy RDD must be columnar — parallelize(Array.empty[InternalRow], 1) is row-based, and CometWriteFilesExec feeds batches into an Arrow stream. Options are a single-partition empty ColumnarBatch RDD, or bypassing the native writer for this case and writing the schema-only file on the JVM.