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81 lines
3.1 KiB
Python
81 lines
3.1 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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import logging
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from typing import Any, Dict, Optional
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from superset import security_manager
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from superset.commands.base import BaseCommand
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from superset.common.chart_data import ChartDataResultType
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from superset.common.query_context_factory import QueryContextFactory
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from superset.common.utils.query_cache_manager import QueryCacheManager
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from superset.connectors.sqla.models import SqlaTable
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from superset.constants import CacheRegion
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from superset.datasets.commands.exceptions import (
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DatasetForbiddenError,
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DatasetNotFoundError,
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DatasetSamplesFailedError,
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)
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from superset.datasets.dao import DatasetDAO
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from superset.exceptions import SupersetSecurityException
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from superset.utils.core import QueryStatus
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logger = logging.getLogger(__name__)
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class SamplesDatasetCommand(BaseCommand):
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def __init__(self, model_id: int, force: bool):
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self._model_id = model_id
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self._force = force
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self._model: Optional[SqlaTable] = None
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def run(self) -> Dict[str, Any]:
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self.validate()
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if not self._model:
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raise DatasetNotFoundError()
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qc_instance = QueryContextFactory().create(
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datasource={
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"type": self._model.type,
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"id": self._model.id,
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},
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queries=[{}],
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result_type=ChartDataResultType.SAMPLES,
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force=self._force,
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)
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results = qc_instance.get_payload()
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try:
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sample_data = results["queries"][0]
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error_msg = sample_data.get("error")
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if sample_data.get("status") == QueryStatus.FAILED and error_msg:
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cache_key = sample_data.get("cache_key")
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QueryCacheManager.delete(cache_key, region=CacheRegion.DATA)
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raise DatasetSamplesFailedError(error_msg)
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return sample_data
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except (IndexError, KeyError) as exc:
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raise DatasetSamplesFailedError from exc
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def validate(self) -> None:
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# Validate/populate model exists
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self._model = DatasetDAO.find_by_id(self._model_id)
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if not self._model:
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raise DatasetNotFoundError()
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# Check ownership
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try:
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security_manager.raise_for_ownership(self._model)
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except SupersetSecurityException as ex:
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raise DatasetForbiddenError() from ex
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