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Use drop_duplicates() instead of groupby (about 1.5~2x faster) #1617

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feast-ci-bot merged 2 commits into from
Jun 4, 2021
Merged

Use drop_duplicates() instead of groupby (about 1.5~2x faster) #1617

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Use drop_duplicates() instead of groupby (about 1.5~2x faster)
rightx2 Jun 3, 2021
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rightx2 Jun 3, 2021
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15 changes: 9 additions & 6 deletions sdk/python/feast/infra/offline_stores/file.py
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Original file line number Diff line number Diff line change
Expand Up @@ -153,8 +153,12 @@ def evaluate_historical_retrieval():
]

df_to_join.sort_values(by=right_entity_key_sort_columns, inplace=True)
df_to_join = df_to_join.groupby(by=right_entity_key_columns).last()
df_to_join.reset_index(inplace=True)
df_to_join.drop_duplicates(
right_entity_key_sort_columns,
keep="last",
ignore_index=True,
inplace=True,
)

# Select only the columns we need to join from the feature dataframe
df_to_join = df_to_join[right_entity_key_columns + feature_names]
Expand Down Expand Up @@ -231,10 +235,9 @@ def pull_latest_from_table_or_query(
(source_df[event_timestamp_column] >= start_date)
& (source_df[event_timestamp_column] < end_date)
]
last_values_df = filtered_df.groupby(by=join_key_columns).last()

# make driver_id a normal column again
last_values_df.reset_index(inplace=True)
last_values_df = filtered_df.drop_duplicates(
join_key_columns, keep="last", ignore_index=True
)

columns_to_extract = set(join_key_columns + feature_name_columns + ts_columns)
table = pyarrow.Table.from_pandas(last_values_df[columns_to_extract])
Expand Down