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Feat cache residual evaluator #2695
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@@ -14,9 +14,11 @@ | |
| # KIND, either express or implied. See the License for the | ||
| # specific language governing permissions and limitations | ||
| # under the License. | ||
| import copy | ||
| import math | ||
| import threading | ||
| from abc import ABC, abstractmethod | ||
| from collections.abc import Callable | ||
| from collections.abc import Callable, Hashable | ||
| from functools import singledispatch | ||
| from typing import ( | ||
| Any, | ||
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@@ -25,6 +27,9 @@ | |
| TypeVar, | ||
| ) | ||
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| from cachetools import LRUCache, cached | ||
| from cachetools.keys import hashkey | ||
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| from pyiceberg.conversions import from_bytes | ||
| from pyiceberg.expressions import ( | ||
| AlwaysFalse, | ||
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@@ -1970,11 +1975,37 @@ def residual_for(self, partition_data: Record) -> BooleanExpression: | |
| return self.expr | ||
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| def residual_evaluator_of( | ||
| _DEFAULT_RESIDUAL_EVALUATOR_CACHE_SIZE = 128 | ||
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| def _residual_evaluator_cache_key( | ||
| spec: PartitionSpec, expr: BooleanExpression, case_sensitive: bool, schema: Schema | ||
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Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Why not pass in |
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| ) -> tuple[Hashable, ...]: | ||
| return hashkey(spec.spec_id, repr(expr), case_sensitive, schema.schema_id) | ||
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Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Building the |
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| @cached( | ||
| cache=LRUCache(maxsize=_DEFAULT_RESIDUAL_EVALUATOR_CACHE_SIZE), | ||
| key=_residual_evaluator_cache_key, | ||
| lock=threading.RLock(), | ||
| ) | ||
| def _cached_residual_evaluator_template( | ||
| spec: PartitionSpec, expr: BooleanExpression, case_sensitive: bool, schema: Schema | ||
| ) -> ResidualEvaluator: | ||
| return ( | ||
| UnpartitionedResidualEvaluator(schema=schema, expr=expr) | ||
| if spec.is_unpartitioned() | ||
| else ResidualEvaluator(spec=spec, expr=expr, schema=schema, case_sensitive=case_sensitive) | ||
| ) | ||
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| def residual_evaluator_of( | ||
| spec: PartitionSpec, expr: BooleanExpression, case_sensitive: bool, schema: Schema | ||
| ) -> ResidualEvaluator: | ||
| """Create a residual evaluator. | ||
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| Always returns a fresh evaluator instance because evaluators are stateful | ||
| (they set `self.struct` during evaluation) and may be used from multiple | ||
| threads. | ||
| """ | ||
| return copy.copy(_cached_residual_evaluator_template(spec=spec, expr=expr, case_sensitive=case_sensitive, schema=schema)) | ||
|
Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Why do we need the copy here? |
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@@ -88,6 +88,19 @@ def test_identity_transform_residual() -> None: | |
| assert residual == AlwaysFalse() | ||
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| def test_residual_evaluator_of_returns_fresh_instance() -> None: | ||
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Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Thanks for adding the test 👍 |
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| schema = Schema(NestedField(50, "dateint", IntegerType()), NestedField(51, "hour", IntegerType())) | ||
| spec = PartitionSpec(PartitionField(50, 1050, IdentityTransform(), "dateint_part")) | ||
| predicate = LessThan("dateint", 20170815) | ||
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| res_eval_1 = residual_evaluator_of(spec=spec, expr=predicate, case_sensitive=True, schema=schema) | ||
| res_eval_2 = residual_evaluator_of(spec=spec, expr=predicate, case_sensitive=True, schema=schema) | ||
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| assert res_eval_1 is not res_eval_2 | ||
| assert res_eval_1.residual_for(Record(20170814)) == AlwaysTrue() | ||
| assert res_eval_2.residual_for(Record(20170816)) == AlwaysFalse() | ||
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| def test_case_insensitive_identity_transform_residuals() -> None: | ||
| schema = Schema(NestedField(50, "dateint", IntegerType()), NestedField(51, "hour", IntegerType())) | ||
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Why 128? I think this is pretty high, and would probably go a bit lower (32?)
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I probably should have put this in my initial PR reasoning; my guiding star here was that this feature should lean toward performance safety rather than super-tight memory tuning.
Residual evaluators are on the hot path for pruning, so if we miss the cache we end up rebinding expressions — and that’s relatively expensive in Python. A cache size of 128 lines up with common LRU defaults, and in practice it helps cut down query time and unnecessary I/O.
In my own experience, PyIceberg usually runs on instances with plenty of RAM (multiple GBs), so using a bit more memory to get more predictable performance feels like a good trade-off. I’ll also acknowledge that this comes from my experience, so there may be some bias there — but I think it’s a reasonable default for most real-world workloads. I'm happy to adjust if you feel strongly, but maybe we go with 64?