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__init__.py
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27 lines (23 loc) · 942 Bytes
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"""
Tiling for efficient time-windowed aggregations.
This module provides tiling algorithms and interfaces
that can be implemented by any compute engine (Spark, Ray, etc.).
Architecture:
1. Engine nodes: Convert to pandas (e.g., dataset.to_pandas(), toPandas())
2. orchestrator.py: Generate cumulative tiles
3. tile_subtraction.py: Convert cumulative tiles to windowed aggregations
4. Engine nodes: Convert back to engine format (e.g., from_pandas(), createDataFrame())
"""
from feast.aggregation.tiling.base import IRMetadata, get_ir_metadata_for_aggregation
from feast.aggregation.tiling.orchestrator import apply_sawtooth_window_tiling
from feast.aggregation.tiling.tile_subtraction import (
convert_cumulative_to_windowed,
deduplicate_keep_latest,
)
__all__ = [
"IRMetadata",
"get_ir_metadata_for_aggregation",
"apply_sawtooth_window_tiling",
"convert_cumulative_to_windowed",
"deduplicate_keep_latest",
]