albertlockett commented on code in PR #8069:
URL: https://github.com/apache/arrow-rs/pull/8069#discussion_r2322747346
##########
parquet/src/arrow/arrow_writer/mod.rs:
##########
@@ -4293,4 +4304,50 @@ mod tests {
assert_eq!(get_dict_page_size(col0_meta), 1024 * 1024);
assert_eq!(get_dict_page_size(col1_meta), 1024 * 1024 * 4);
}
+
+ #[test]
+ fn arrow_writer_run_end_encoded() {
+ // Create a run array of strings
+ let mut builder = StringRunBuilder::<Int16Type>::new();
+ builder.extend(
+ vec![Some("alpha"); 1000]
+ .into_iter()
+ .chain(vec![Some("beta"); 1000]),
+ );
+ let run_array: RunArray<Int16Type> = builder.finish();
+ println!("run_array type: {:?}", run_array.data_type());
+ let schema = Arc::new(Schema::new(vec![Field::new(
+ "ree",
+ run_array.data_type().clone(),
+ run_array.is_nullable(),
+ )]));
+
+ // Write to parquet
+ let mut parquet_bytes: Vec<u8> = Vec::new();
+ let mut writer = ArrowWriter::try_new(&mut parquet_bytes,
schema.clone(), None).unwrap();
+ let batch = RecordBatch::try_new(schema.clone(),
vec![Arc::new(run_array)]).unwrap();
+ writer.write(&batch).unwrap();
+ writer.close().unwrap();
+
+ // Schema of output is plain, not dictionary or REE encoded!!
Review Comment:
@alamb related to your comment here:
https://github.com/apache/arrow-rs/issues/3520#issuecomment-3254515876
In the discussion above, we were tentatively thinking that the shortest path
to getting REE support would be to decode the column to the native arrow array
using the existing readers, and then cast it to a `RunArray`. Then, maybe
adding the dedicated REE reader as a followup. Does that sound like a workable
approach?
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