[data] Add take_all() and raise error if to_pandas() drops records (#19619)

python/ray/data/dataset.py

@@ -944,6 +944,26 @@ class Dataset(Generic[T]):
                 break
         return output
 
+    def take_all(self, limit: int = 100000) -> List[T]:
+        """Take all the records in the dataset.
+
+        Time complexity: O(dataset size)
+
+        Args:
+            limit: Raise an error if the size exceeds the specified limit.
+
+        Returns:
+            A list of all the records in the dataset.
+        """
+        output = []
+        for row in self.iter_rows():
+            output.append(row)
+            if len(output) > limit:
+                raise ValueError(
+                    "The dataset has more than the given limit of {} records.".
+                    format(limit))
+        return output
+
     def show(self, limit: int = 20) -> None:
         """Print up to the given number of records from the dataset.
 
@@ -1624,16 +1644,19 @@ class Dataset(Generic[T]):
         return raydp.spark.ray_dataset_to_spark_dataframe(
             spark, self.schema(), self.get_internal_block_refs(), locations)
 
-    def to_pandas(self, limit: int = 1000) -> "pandas.DataFrame":
+    def to_pandas(self, limit: int = 100000) -> "pandas.DataFrame":
         """Convert this dataset into a single Pandas DataFrame.
 
-        This is only supported for datasets convertible to Arrow records. This
-        limits the number of records returned to the provided limit.
+        This is only supported for datasets convertible to Arrow records. An
+        error is raised if the number of records exceeds the provided limit.
+        Note that you can use ``.limit()`` on the dataset beforehand to
+        truncate the dataset manually.
 
-        Time complexity: O(limit)
+        Time complexity: O(dataset size)
 
         Args:
-            limit: The maximum number of records to return.
+            limit: The maximum number of records to return. An error will be
+                raised if the limit is exceeded.
 
         Returns:
             A Pandas DataFrame created from this dataset, containing a limited
@@ -1641,10 +1664,10 @@ class Dataset(Generic[T]):
         """
 
         if self.count() > limit:
-            logger.warning(f"Only returning the first {limit} records from "
-                           "to_pandas()")
-        limited_ds = self.limit(limit)
-        blocks = limited_ds.get_internal_block_refs()
+            raise ValueError(
+                "The dataset has more than the given limit of {} records.".
+                format(limit))
+        blocks = self.get_internal_block_refs()
         output = DelegatingArrowBlockBuilder()
         for block in ray.get(blocks):
             output.add_block(block)

python/ray/data/dataset_pipeline.py

@@ -25,7 +25,9 @@ PER_DATASET_OUTPUT_OPS = [
 ]
 
 # Operations that operate over the stream of output batches from the pipeline.
-OUTPUT_ITER_OPS = ["take", "show", "iter_rows", "to_tf", "to_torch"]
+OUTPUT_ITER_OPS = [
+    "take", "take_all", "show", "iter_rows", "to_tf", "to_torch"
+]
 
 
 @PublicAPI(stability="beta")

python/ray/data/tests/test_dataset.py

@@ -1138,14 +1138,21 @@ def test_to_pandas(ray_start_regular_shared):
     assert df.equals(dfds)
 
     # Test limit.
+    with pytest.raises(ValueError):
         dfds = ds.to_pandas(limit=3)
-    assert df[:3].equals(dfds)
 
     # Test limit greater than number of rows.
     dfds = ds.to_pandas(limit=6)
     assert df.equals(dfds)
 
 
+def test_take_all(ray_start_regular_shared):
+    assert ray.data.range(5).take_all() == [0, 1, 2, 3, 4]
+
+    with pytest.raises(ValueError):
+        assert ray.data.range(5).take_all(4)
+
+
 def test_to_pandas_refs(ray_start_regular_shared):
     n = 5
     df = pd.DataFrame({"value": list(range(n))})