Switch to arrow builder

oo-method-test.py

@@ -2,6 +2,9 @@
 
 import datasets
 
+import pyarrow as pa
+import pyarrow.parquet as pq
+
 _DATA_FILES = ['data/combined-00009-of-00013-97a88bccf4215954.parquet',
  'data/combined-00004-of-00013-119d653561443d7b.parquet',
  'data/combined-00007-of-00013-ab54cce4ee6331d0.parquet',
@@ -16,25 +19,21 @@ _DATA_FILES = ['data/combined-00009-of-00013-97a88bccf4215954.parquet',
  'data/combined-00011-of-00013-4c21766cedd5a4a0.parquet',
  'data/combined-00008-of-00013-674f74b6f2288c61.parquet']
 
-class OOMethodTestDataset(datasets.packaged_modules.parquet.Parquet):
-	def __init__(self, *args, **kwargs):
-		if 'data_files' not in kwargs or kwargs['data_files'] is None:
-			kwargs['data_files'] = _DATA_FILES
-		super().__init__(*args, **kwargs)
+class OOMethodTestDataset(datasets.ArrowBasedBuilder):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
 
-		# Yuck
-		self.config.data_files = _DATA_FILES
+    def _info(self):
+        return datasets.DatasetInfo()
 
-	def _split_generators(self, dl_manager, *args, **kwargs):
-		files = self.config.data_files
-		files = files['train'] # This is hard-coded in the Parquet builder
-		downloaded_files = dl_manager.download(files)
-		downloaded_files = [dl_manager.iter_files(file) for file in files]
+    def _split_generators(self, dl_manager):
+        files = _DATA_FILES
+        downloaded_files = dl_manager.download(files)
 
-		print(files)
-		print(downloaded_files)
+        #print(files)
+        #print(downloaded_files)
 
-		return [
+        return [
             datasets.SplitGenerator(
                 name="combined",
                 gen_kwargs={
@@ -42,4 +41,21 @@ class OOMethodTestDataset(datasets.packaged_modules.parquet.Parquet):
                 },
             ),
         ]
+    
+    def _generate_tables(self, files):
+        for file_idx, file in enumerate(files):
+            with open(file, "rb") as f:
+                parquet_file = pq.ParquetFile(f)
+                try:
+                    for batch_idx, record_batch in enumerate(
+                        parquet_file.iter_batches(batch_size=10_000)
+                    ):
+                        pa_table = pa.Table.from_batches([record_batch])
+                        # Uncomment for debugging (will print the Arrow table size and elements)
+                        # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
+                        # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
+                        yield f"{file_idx}_{batch_idx}", pa_table
+                except ValueError as e:
+                    #logger.error(f"Failed to read file '{file}' with error {type(e)}: {e}")
+                    raise