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a3d6c1dd20
* tests(datalake): use minio 1. use minio instead of moto for mimicking s3 behavior. 2. removed moto dependency as it is not compatible with aiobotocore (https://github.com/getmoto/moto/issues/7070#issuecomment-1828484982) * - moved test_datalake_profiler_e2e.py to datalake/test_profiler - use minio instead of moto * fixed tests * fixed tests * removed default name for minio container
90 lines
3.3 KiB
Python
90 lines
3.3 KiB
Python
# Copyright 2021 Collate
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Datalake ingestion integration tests"""
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import pytest
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from ingestion.tests.integration.datalake.conftest import BUCKET_NAME
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from metadata.generated.schema.entity.data.table import DataType, Table
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from metadata.ingestion.ometa.models import EntityList
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from metadata.ingestion.ometa.ometa_api import OpenMetadata
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class TestDatalake:
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"""datalake profiler E2E test"""
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metadata: OpenMetadata = None
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s3_client = None
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@pytest.fixture(autouse=True)
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def set_metadata(self, metadata):
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self.metadata = metadata
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@pytest.mark.order(10000)
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def test_ingestion(self, run_ingestion):
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"""test ingestion of datalake data"""
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# Ingest our S3 data
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resp: EntityList[Table] = self.metadata.list_entities(
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entity=Table, params={"database": "datalake_for_integration_tests.default"}
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) # type: ignore
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entities = resp.entities
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assert len(entities) == 5
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names = [entity.name.root for entity in entities]
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assert {
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"names.json",
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"names.jsonl",
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"new_users.parquet",
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"users.csv",
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"profiler_test_.csv",
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} == set(names)
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for entity in entities:
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columns = entity.columns
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for column in columns:
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if column.dataType == DataType.JSON:
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assert column.children
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def test_profiler(self, run_profiler):
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"""Also excluding the test for parquet files until the above is fixed"""
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csv_ = self.metadata.get_by_name(
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entity=Table,
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fqn=f'datalake_for_integration_tests.default.{BUCKET_NAME}."users.csv"',
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fields=["tableProfilerConfig"],
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)
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# parquet_ = self.metadata.get_by_name(
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# entity=Table,
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# fqn='datalake_for_integration_tests.default.MyBucket."new_users.parquet"',
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# fields=["tableProfilerConfig"],
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# )
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json_ = self.metadata.get_by_name(
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entity=Table,
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fqn=f'datalake_for_integration_tests.default.{BUCKET_NAME}."names.json"',
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fields=["tableProfilerConfig"],
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)
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jsonl_ = self.metadata.get_by_name(
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entity=Table,
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fqn=f'datalake_for_integration_tests.default.{BUCKET_NAME}."names.jsonl"',
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fields=["tableProfilerConfig"],
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)
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csv_sample_data = self.metadata.get_sample_data(csv_)
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# parquet_sample_data = self.metadata.get_sample_data(parquet_)
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json_sample_data = self.metadata.get_sample_data(json_)
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jsonl_sample_data = self.metadata.get_sample_data(jsonl_)
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assert csv_sample_data.sampleData.rows
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# assert parquet_sample_data.sampleData.rows
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assert json_sample_data.sampleData.rows
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assert jsonl_sample_data.sampleData.rows
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