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cdaa5c10af
* feat(data-quality): use sampling config in data diff - get the table profiling config - use hashing to sample deterministically the same ids from each table - use dirty-equals to assert results of stochastic processes * - reverted missing md5 - added missing database service type * - use a custom substr sql function * fixed nounce * added failure for mssql with sampling because it requires a larger change in the data-diff library * fixed unit tests * updated range for sampling
27 lines
676 B
Python
27 lines
676 B
Python
"""Models for the TableDiff test case"""
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from typing import List, Optional
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from pydantic import BaseModel
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from metadata.generated.schema.entity.data.table import Column, TableProfilerConfig
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from metadata.generated.schema.entity.services.databaseService import (
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DatabaseServiceType,
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)
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class TableParameter(BaseModel):
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serviceUrl: str
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path: str
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columns: List[Column]
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database_service_type: DatabaseServiceType
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class TableDiffRuntimeParameters(BaseModel):
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table1: TableParameter
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table2: TableParameter
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keyColumns: List[str]
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extraColumns: List[str]
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whereClause: Optional[str]
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table_profile_config: Optional[TableProfilerConfig]
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