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[Datasets] [Hotfix] Fix stats construction for from_* APIs. #25601

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Jun 9, 2022
Merged

[Datasets] [Hotfix] Fix stats construction for from_* APIs. #25601

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23 changes: 14 additions & 9 deletions python/ray/data/read_api.py
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Original file line number Diff line number Diff line change
Expand Up @@ -821,20 +821,24 @@ def from_pandas_refs(
context = DatasetContext.get_current()
if context.enable_pandas_block:
get_metadata = cached_remote_fn(_get_metadata)
metadata = [get_metadata.remote(df) for df in dfs]
metadata = ray.get([get_metadata.remote(df) for df in dfs])
return Dataset(
ExecutionPlan(BlockList(dfs, ray.get(metadata)), DatasetStats.TODO()),
ExecutionPlan(
BlockList(dfs, metadata),
DatasetStats(stages={"from_pandas_refs": metadata}, parent=None),
),
0,
False,
)

df_to_block = cached_remote_fn(_df_to_block, num_returns=2)

res = [df_to_block.remote(df) for df in dfs]
blocks, metadata = zip(*res)
blocks, metadata = map(list, zip(*res))
metadata = ray.get(metadata)
return Dataset(
ExecutionPlan(
BlockList(blocks, ray.get(list(metadata))),
BlockList(blocks, metadata),
DatasetStats(stages={"from_pandas_refs": metadata}, parent=None),
),
0,
Expand Down Expand Up @@ -888,11 +892,12 @@ def from_numpy_refs(
ndarray_to_block = cached_remote_fn(_ndarray_to_block, num_returns=2)

res = [ndarray_to_block.remote(ndarray) for ndarray in ndarrays]
blocks, metadata = zip(*res)
blocks, metadata = map(list, zip(*res))
metadata = ray.get(metadata)
return Dataset(
ExecutionPlan(
BlockList(blocks, ray.get(list(metadata))),
DatasetStats(stages={"from_numpy": metadata}, parent=None),
BlockList(blocks, metadata),
DatasetStats(stages={"from_numpy_refs": metadata}, parent=None),
),
0,
False,
Expand Down Expand Up @@ -939,10 +944,10 @@ def from_arrow_refs(
tables = [tables]

get_metadata = cached_remote_fn(_get_metadata)
metadata = [get_metadata.remote(t) for t in tables]
metadata = ray.get([get_metadata.remote(t) for t in tables])
return Dataset(
ExecutionPlan(
BlockList(tables, ray.get(metadata)),
BlockList(tables, metadata),
DatasetStats(stages={"from_arrow_refs": metadata}, parent=None),
),
0,
Expand Down
20 changes: 20 additions & 0 deletions python/ray/data/tests/test_dataset_formats.py
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Original file line number Diff line number Diff line change
Expand Up @@ -77,13 +77,17 @@ def test_from_pandas(ray_start_regular_shared, enable_pandas_block):
values = [(r["one"], r["two"]) for r in ds.take(6)]
rows = [(r.one, r.two) for _, r in pd.concat([df1, df2]).iterrows()]
assert values == rows
# Check that metadata fetch is included in stats.
assert "from_pandas_refs" in ds.stats()

# test from single pandas dataframe
ds = ray.data.from_pandas(df1)
assert ds._dataset_format() == "pandas" if enable_pandas_block else "arrow"
values = [(r["one"], r["two"]) for r in ds.take(3)]
rows = [(r.one, r.two) for _, r in df1.iterrows()]
assert values == rows
# Check that metadata fetch is included in stats.
assert "from_pandas_refs" in ds.stats()
finally:
ctx.enable_pandas_block = old_enable_pandas_block

Expand All @@ -101,13 +105,17 @@ def test_from_pandas_refs(ray_start_regular_shared, enable_pandas_block):
values = [(r["one"], r["two"]) for r in ds.take(6)]
rows = [(r.one, r.two) for _, r in pd.concat([df1, df2]).iterrows()]
assert values == rows
# Check that metadata fetch is included in stats.
assert "from_pandas_refs" in ds.stats()

# test from single pandas dataframe ref
ds = ray.data.from_pandas_refs(ray.put(df1))
assert ds._dataset_format() == "pandas" if enable_pandas_block else "arrow"
values = [(r["one"], r["two"]) for r in ds.take(3)]
rows = [(r.one, r.two) for _, r in df1.iterrows()]
assert values == rows
# Check that metadata fetch is included in stats.
assert "from_pandas_refs" in ds.stats()
finally:
ctx.enable_pandas_block = old_enable_pandas_block

Expand All @@ -123,6 +131,8 @@ def test_from_numpy(ray_start_regular_shared, from_ref):
ds = ray.data.from_numpy(arrs)
values = np.stack(ds.take(8))
np.testing.assert_array_equal(values, np.concatenate((arr1, arr2)))
# Check that conversion task is included in stats.
assert "from_numpy_refs" in ds.stats()

# Test from single NumPy ndarray.
if from_ref:
Expand All @@ -131,6 +141,8 @@ def test_from_numpy(ray_start_regular_shared, from_ref):
ds = ray.data.from_numpy(arr1)
values = np.stack(ds.take(4))
np.testing.assert_array_equal(values, arr1)
# Check that conversion task is included in stats.
assert "from_numpy_refs" in ds.stats()


def test_from_arrow(ray_start_regular_shared):
Expand All @@ -140,12 +152,16 @@ def test_from_arrow(ray_start_regular_shared):
values = [(r["one"], r["two"]) for r in ds.take(6)]
rows = [(r.one, r.two) for _, r in pd.concat([df1, df2]).iterrows()]
assert values == rows
# Check that metadata fetch is included in stats.
assert "from_arrow_refs" in ds.stats()

# test from single pyarrow table
ds = ray.data.from_arrow(pa.Table.from_pandas(df1))
values = [(r["one"], r["two"]) for r in ds.take(3)]
rows = [(r.one, r.two) for _, r in df1.iterrows()]
assert values == rows
# Check that metadata fetch is included in stats.
assert "from_arrow_refs" in ds.stats()


def test_from_arrow_refs(ray_start_regular_shared):
Expand All @@ -157,12 +173,16 @@ def test_from_arrow_refs(ray_start_regular_shared):
values = [(r["one"], r["two"]) for r in ds.take(6)]
rows = [(r.one, r.two) for _, r in pd.concat([df1, df2]).iterrows()]
assert values == rows
# Check that metadata fetch is included in stats.
assert "from_arrow_refs" in ds.stats()

# test from single pyarrow table ref
ds = ray.data.from_arrow_refs(ray.put(pa.Table.from_pandas(df1)))
values = [(r["one"], r["two"]) for r in ds.take(3)]
rows = [(r.one, r.two) for _, r in df1.iterrows()]
assert values == rows
# Check that metadata fetch is included in stats.
assert "from_arrow_refs" in ds.stats()


def test_to_pandas(ray_start_regular_shared):
Expand Down