@@ -900,6 +900,11 @@ def register_batch(self, name: str, batch: pa.RecordBatch) -> None:
900900 Args:
901901 name: Name of the resultant table.
902902 batch: Record batch to register as a table.
903+
904+ Examples:
905+ >>> batch = pa.RecordBatch.from_pydict({"a": [1, 2, 3]})
906+ >>> ctx.register_batch("my_table", batch)
907+ >>> ctx.sql("SELECT * FROM my_table").show()
903908 """
904909 self .ctx .register_batch (name , batch )
905910
@@ -1120,6 +1125,10 @@ def register_arrow(
11201125 schema: The data source schema.
11211126 file_extension: File extension to select.
11221127 table_partition_cols: Partition columns.
1128+
1129+ Examples:
1130+ >>> ctx.register_arrow("my_table", "data.arrow")
1131+ >>> ctx.sql("SELECT * FROM my_table").show()
11231132 """
11241133 if table_partition_cols is None :
11251134 table_partition_cols = []
@@ -1381,6 +1390,10 @@ def read_arrow(
13811390
13821391 Returns:
13831392 DataFrame representation of the read Arrow IPC file.
1393+
1394+ Examples:
1395+ >>> df = ctx.read_arrow("data.arrow")
1396+ >>> df.show()
13841397 """
13851398 if file_partition_cols is None :
13861399 file_partition_cols = []
@@ -1396,6 +1409,11 @@ def read_empty(self) -> DataFrame:
13961409
13971410 Returns:
13981411 An empty DataFrame.
1412+
1413+ Examples:
1414+ >>> df = ctx.read_empty()
1415+ >>> df.collect()
1416+ [pyarrow.RecordBatch]
13991417 """
14001418 return self .empty_table ()
14011419
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