[Datasets] Streaming executor fixes #5 (ray-project#32951)

python/ray/data/_internal/lazy_block_list.py

@@ -2,14 +2,13 @@
 import uuid
 from typing import Any, Dict, Iterable, Iterator, List, Optional, Tuple, Union
 
-import numpy as np
-
 import ray
 from ray.data._internal.block_list import BlockList
 from ray.data._internal.progress_bar import ProgressBar
 from ray.data._internal.remote_fn import cached_remote_fn
 from ray.data._internal.memory_tracing import trace_allocation
 from ray.data._internal.stats import DatasetStats, _get_or_create_stats_actor
+from ray.data._internal.util import _split_list
 from ray.data.block import (
     Block,
     BlockAccessor,
@@ -162,22 +161,22 @@ def _check_if_cleared(self):
     # Note: does not force execution prior to splitting.
     def split(self, split_size: int) -> List["LazyBlockList"]:
         num_splits = math.ceil(len(self._tasks) / split_size)
-        tasks = np.array_split(self._tasks, num_splits)
-        block_partition_refs = np.array_split(self._block_partition_refs, num_splits)
-        block_partition_meta_refs = np.array_split(
+        tasks = _split_list(self._tasks, num_splits)
+        block_partition_refs = _split_list(self._block_partition_refs, num_splits)
+        block_partition_meta_refs = _split_list(
             self._block_partition_meta_refs, num_splits
         )
-        cached_metadata = np.array_split(self._cached_metadata, num_splits)
+        cached_metadata = _split_list(self._cached_metadata, num_splits)
         output = []
         for t, b, m, c in zip(
             tasks, block_partition_refs, block_partition_meta_refs, cached_metadata
         ):
             output.append(
                 LazyBlockList(
-                    t.tolist(),
-                    b.tolist(),
-                    m.tolist(),
-                    c.tolist(),
+                    t,
+                    b,
+                    m,
+                    c,
                     owned_by_consumer=self._owned_by_consumer,
                 )
             )

python/ray/data/_internal/util.py

@@ -1,7 +1,7 @@
 import importlib
 import logging
 import os
-from typing import List, Union, Optional, TYPE_CHECKING
+from typing import Any, List, Union, Optional, TYPE_CHECKING
 from types import ModuleType
 import sys
 
@@ -380,3 +380,20 @@ def ConsumptionAPI(*args, **kwargs):
     if len(args) == 1 and len(kwargs) == 0 and callable(args[0]):
         return _consumption_api()(args[0])
     return _consumption_api(*args, **kwargs)
+
+
+def _split_list(arr: List[Any], num_splits: int) -> List[List[Any]]:
+    """Split the list into `num_splits` lists.
+
+    The splits will be even if the `num_splits` divides the length of list, otherwise
+    the remainder (suppose it's R) will be allocated to the first R splits (one for
+    each).
+    This is the same as numpy.array_split(). The reason we make this a separate
+    implementation is to allow the heterogeneity in the elements in the list.
+    """
+    assert num_splits > 0
+    q, r = divmod(len(arr), num_splits)
+    splits = [
+        arr[i * q + min(i, r) : (i + 1) * q + min(i + 1, r)] for i in range(num_splits)
+    ]
+    return splits

python/ray/data/tests/test_dataset.py

@@ -4581,9 +4581,19 @@ def test_warning_execute_with_no_cpu(ray_start_cluster):
             ds = ray.data.range(10)
             ds = ds.map_batches(lambda x: x)
             ds.take()
-        except LoggerWarningCalled:
-            logger_args, logger_kwargs = mock_logger.call_args
-            assert "Warning: The Ray cluster currently does not have " in logger_args[0]
+        except Exception as e:
+            if ray.data.context.DatasetContext.get_current().use_streaming_executor:
+                assert isinstance(e, ValueError)
+                assert "exceeds the execution limits ExecutionResources(cpu=0.0" in str(
+                    e
+                )
+            else:
+                assert isinstance(e, LoggerWarningCalled)
+                logger_args, logger_kwargs = mock_logger.call_args
+                assert (
+                    "Warning: The Ray cluster currently does not have "
+                    in logger_args[0]
+                )
 
 
 def test_nowarning_execute_with_cpu(ray_start_cluster_init):

python/ray/data/tests/test_util.py

@@ -2,7 +2,7 @@
 import ray
 import numpy as np
 
-from ray.data._internal.util import _check_pyarrow_version
+from ray.data._internal.util import _check_pyarrow_version, _split_list
 from ray.data._internal.memory_tracing import (
     trace_allocation,
     trace_deallocation,
@@ -72,6 +72,21 @@ def test_memory_tracing(enabled):
         assert "test5" not in report, report
 
 
+def test_list_splits():
+    with pytest.raises(AssertionError):
+        _split_list(list(range(5)), 0)
+
+    with pytest.raises(AssertionError):
+        _split_list(list(range(5)), -1)
+
+    assert _split_list(list(range(5)), 7) == [[0], [1], [2], [3], [4], [], []]
+    assert _split_list(list(range(5)), 2) == [[0, 1, 2], [3, 4]]
+    assert _split_list(list(range(6)), 2) == [[0, 1, 2], [3, 4, 5]]
+    assert _split_list(list(range(5)), 1) == [[0, 1, 2, 3, 4]]
+    assert _split_list(["foo", 1, [0], None], 2) == [["foo", 1], [[0], None]]
+    assert _split_list(["foo", 1, [0], None], 3) == [["foo", 1], [[0]], [None]]
+
+
 if __name__ == "__main__":
     import sys