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fix: Fix too many cluster columns requested by caching #2155

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Merged
merged 2 commits into from
Oct 9, 2025
Merged

fix: Fix too many cluster columns requested by caching #2155

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0c0f6a3
fix: Fix too many cluster columns requested by caching
TrevorBergeron Oct 8, 2025
c1d8e3e
fix cluster type filter, test
TrevorBergeron Oct 9, 2025
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8 changes: 6 additions & 2 deletions bigframes/session/bq_caching_executor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -637,14 +637,18 @@ def _execute_plan_gbq(

create_table = True
if not cache_spec.cluster_cols:
assert len(cache_spec.cluster_cols) <= _MAX_CLUSTER_COLUMNS
offsets_id = bigframes.core.identifiers.ColumnId(
bigframes.core.guid.generate_guid()
)
plan = nodes.PromoteOffsetsNode(plan, offsets_id)
cluster_cols = [offsets_id.sql]
else:
cluster_cols = cache_spec.cluster_cols
cluster_cols = [
col
for col in cache_spec.cluster_cols
if bigframes.dtypes.is_clusterable(plan.schema.get_type(col))
]
cluster_cols = cluster_cols[:_MAX_CLUSTER_COLUMNS]

compiled = compile.compile_sql(
compile.CompileRequest(
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17 changes: 17 additions & 0 deletions tests/system/small/test_dataframe.py
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Expand Up @@ -5537,6 +5537,23 @@ def test_df_cached(scalars_df_index):
pandas.testing.assert_frame_equal(df.to_pandas(), df_cached_copy.to_pandas())


def test_df_cached_many_index_cols(scalars_df_index):
index_cols = [
"int64_too",
"time_col",
"int64_col",
"bool_col",
"date_col",
"timestamp_col",
"string_col",
]
df = scalars_df_index.set_index(index_cols)
df = df[df["rowindex_2"] % 2 == 0]

df_cached_copy = df.cache()
pandas.testing.assert_frame_equal(df.to_pandas(), df_cached_copy.to_pandas())


def test_assign_after_binop_row_joins():
pd_df = pd.DataFrame(
{
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