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115 lines
3.5 KiB
Python
115 lines
3.5 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import Any, TYPE_CHECKING
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if TYPE_CHECKING:
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from superset.common.query_context import QueryContext
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NANOSECONDS_PER_MILLISECOND: int = 1_000_000
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CHART_DATA_TIMING_VERSION: int = 1
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def to_ms(value_ns: int | None) -> float | None:
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"""Convert nanoseconds to rounded milliseconds for public output."""
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if value_ns is None:
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return None
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return round(value_ns / NANOSECONDS_PER_MILLISECOND, 2)
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@dataclass(frozen=True)
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class QueryAcquisitionTiming:
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"""Timing captured by the dataframe payload owner."""
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query_planning_ns: int
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cache_resolution_ns: int
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data_acquisition_ns: int | None
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payload_assembly_ns: int
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@dataclass(frozen=True)
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class QueryTiming:
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"""Completed timing for one query in a chart-data execution."""
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query_planning_ns: int | None
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cache_resolution_ns: int | None
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data_acquisition_ns: int | None
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payload_assembly_ns: int | None
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total_ns: int
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def as_public_dict(self) -> dict[str, Any]:
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"""Return the versioned chart-data API representation."""
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return {
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"version": CHART_DATA_TIMING_VERSION,
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"query": {
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"query_planning_ms": to_ms(self.query_planning_ns),
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"cache_resolution_ms": to_ms(self.cache_resolution_ns),
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"data_acquisition_ms": to_ms(self.data_acquisition_ns),
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"payload_assembly_ms": to_ms(self.payload_assembly_ns),
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"total_ms": to_ms(self.total_ns),
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},
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}
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@dataclass(frozen=True)
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class QueryAcquisitionResult:
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"""A dataframe payload paired with acquisition timing."""
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payload: dict[str, Any]
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timing: QueryAcquisitionTiming
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@dataclass(frozen=True)
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class QueryDataResult:
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"""A query payload paired with completed timing."""
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payload: dict[str, Any]
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timing: QueryTiming
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@dataclass(frozen=True)
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class QueryContextExecutionResult:
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"""Typed query-context result with timing outside query payloads."""
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queries: tuple[QueryDataResult, ...]
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cache_key: str | None = None
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@dataclass(frozen=True)
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class ChartDataExecutionResult:
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"""Typed result of executing a chart-data command."""
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query_context: QueryContext
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queries: tuple[QueryDataResult, ...]
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cache_key: str | None = None
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def materialize(self) -> dict[str, Any]:
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"""Return the historical command payload shape."""
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queries: list[dict[str, Any]] = []
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for query_result in self.queries:
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queries.append(dict(query_result.payload))
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result: dict[str, Any] = {
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"query_context": self.query_context,
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"queries": queries,
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}
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if self.cache_key is not None:
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result["cache_key"] = self.cache_key
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return result
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