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238 lines
8.2 KiB
Python
238 lines
8.2 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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# isort:skip_file
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"""Unit tests for Superset CSV upload"""
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import json
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import logging
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import os
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import shutil
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from typing import Optional
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from unittest import mock
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import pandas as pd
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import pytest
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import superset.utils.database
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from superset.sql_parse import Table
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from tests.integration_tests.conftest import ADMIN_SCHEMA_NAME # noqa: F401
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from superset import db
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from superset import security_manager
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from superset.models.core import Database
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from superset.utils import core as utils
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from tests.integration_tests.test_app import app, login
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from tests.integration_tests.base_tests import get_resp, SupersetTestCase
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logger = logging.getLogger(__name__)
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test_client = app.test_client()
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CSV_UPLOAD_DATABASE = "csv_explore_db"
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EXCEL_FILENAME = "testExcel.xlsx"
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PARQUET_FILENAME1 = "testZip/testParquet1.parquet"
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PARQUET_FILENAME2 = "testZip/testParquet2.parquet"
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ZIP_DIRNAME = "testZip"
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ZIP_FILENAME = "testZip.zip"
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EXCEL_UPLOAD_TABLE = "excel_upload"
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CSV_UPLOAD_TABLE = "csv_upload"
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PARQUET_UPLOAD_TABLE = "parquet_upload"
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CSV_UPLOAD_TABLE_W_SCHEMA = "csv_upload_w_schema"
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CSV_UPLOAD_TABLE_W_EXPLORE = "csv_upload_w_explore"
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def _setup_csv_upload():
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upload_db = superset.utils.database.get_or_create_db(
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CSV_UPLOAD_DATABASE, app.config["SQLALCHEMY_EXAMPLES_URI"]
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)
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extra = upload_db.get_extra()
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extra["explore_database_id"] = superset.utils.database.get_example_database().id
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upload_db.extra = json.dumps(extra)
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upload_db.allow_file_upload = True
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db.session.commit()
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yield
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upload_db = get_upload_db()
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with upload_db.get_sqla_engine() as engine:
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engine.execute(f"DROP TABLE IF EXISTS {EXCEL_UPLOAD_TABLE}")
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engine.execute(f"DROP TABLE IF EXISTS {CSV_UPLOAD_TABLE}")
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engine.execute(f"DROP TABLE IF EXISTS {PARQUET_UPLOAD_TABLE}")
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engine.execute(f"DROP TABLE IF EXISTS {CSV_UPLOAD_TABLE_W_SCHEMA}")
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engine.execute(f"DROP TABLE IF EXISTS {CSV_UPLOAD_TABLE_W_EXPLORE}")
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db.session.delete(upload_db)
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db.session.commit()
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@pytest.fixture(scope="module")
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def setup_csv_upload(login_as_admin):
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yield from _setup_csv_upload()
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@pytest.fixture(scope="module")
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def setup_csv_upload_with_context():
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with app.app_context():
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login(test_client, username="admin")
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yield from _setup_csv_upload()
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@pytest.fixture()
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def create_columnar_files():
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os.mkdir(ZIP_DIRNAME)
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pd.DataFrame({"a": ["john", "paul"], "b": [1, 2]}).to_parquet(PARQUET_FILENAME1)
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pd.DataFrame({"a": ["max", "bob"], "b": [3, 4]}).to_parquet(PARQUET_FILENAME2)
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shutil.make_archive(ZIP_DIRNAME, "zip", ZIP_DIRNAME)
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yield
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os.remove(ZIP_FILENAME)
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shutil.rmtree(ZIP_DIRNAME)
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def get_upload_db():
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return db.session.query(Database).filter_by(database_name=CSV_UPLOAD_DATABASE).one()
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def upload_columnar(
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filename: str, table_name: str, extra: Optional[dict[str, str]] = None
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):
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columnar_upload_db_id = get_upload_db().id
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form_data = {
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"columnar_file": open(filename, "rb"),
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"name": table_name,
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"database": columnar_upload_db_id,
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"if_exists": "fail",
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"index_label": "test_label",
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}
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if schema := utils.get_example_default_schema():
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form_data["schema"] = schema
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if extra:
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form_data.update(extra)
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return get_resp(test_client, "/columnartodatabaseview/form", data=form_data)
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def mock_upload_to_s3(filename: str, upload_prefix: str, table: Table) -> str:
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"""
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HDFS is used instead of S3 for the unit tests.integration_tests.
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:param filename: The file to upload
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:param upload_prefix: The S3 prefix
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:param table: The table that will be created
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:returns: The HDFS path to the directory with external table files
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"""
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# only needed for the hive tests
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import docker
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client = docker.from_env() # type: ignore
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container = client.containers.get("namenode")
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# docker mounted volume that contains csv uploads
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src = os.path.join("/tmp/superset_uploads", os.path.basename(filename))
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# hdfs destination for the external tables
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dest_dir = os.path.join("/tmp/external/superset_uploads/", str(table))
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container.exec_run(f"hdfs dfs -mkdir -p {dest_dir}")
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dest = os.path.join(dest_dir, os.path.basename(filename))
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container.exec_run(f"hdfs dfs -put {src} {dest}")
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# hive external table expects a directory for the location
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return dest_dir
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def escaped_double_quotes(text):
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return rf"\"{text}\""
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def escaped_parquet(text):
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return escaped_double_quotes(f"['{text}']")
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@pytest.mark.usefixtures("setup_csv_upload_with_context")
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@pytest.mark.usefixtures("create_columnar_files")
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@mock.patch("superset.db_engine_specs.hive.upload_to_s3", mock_upload_to_s3)
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@mock.patch("superset.views.database.views.event_logger.log_with_context")
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def test_import_parquet(mock_event_logger):
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if utils.backend() == "hive":
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pytest.skip("Hive doesn't allow parquet upload.")
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schema = utils.get_example_default_schema()
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full_table_name = (
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f"{schema}.{PARQUET_UPLOAD_TABLE}" if schema else PARQUET_UPLOAD_TABLE
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)
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test_db = get_upload_db()
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success_msg_f1 = f"Columnar file {escaped_parquet(PARQUET_FILENAME1)} uploaded to table {escaped_double_quotes(full_table_name)}"
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# initial upload with fail mode
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resp = upload_columnar(PARQUET_FILENAME1, PARQUET_UPLOAD_TABLE)
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assert success_msg_f1 in resp
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# upload again with fail mode; should fail
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fail_msg = f"Unable to upload Columnar file {escaped_parquet(PARQUET_FILENAME1)} to table {escaped_double_quotes(PARQUET_UPLOAD_TABLE)}"
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resp = upload_columnar(PARQUET_FILENAME1, PARQUET_UPLOAD_TABLE)
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assert fail_msg in resp
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if utils.backend() != "hive":
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# upload again with append mode
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resp = upload_columnar(
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PARQUET_FILENAME1, PARQUET_UPLOAD_TABLE, extra={"if_exists": "append"}
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)
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assert success_msg_f1 in resp
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mock_event_logger.assert_called_with(
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action="successful_columnar_upload",
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database=test_db.name,
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schema=schema,
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table=PARQUET_UPLOAD_TABLE,
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)
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# upload again with replace mode and specific columns
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resp = upload_columnar(
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PARQUET_FILENAME1,
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PARQUET_UPLOAD_TABLE,
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extra={"if_exists": "replace", "usecols": '["a"]'},
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)
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assert success_msg_f1 in resp
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table = SupersetTestCase.get_table(name=PARQUET_UPLOAD_TABLE, schema=None)
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# make sure only specified column name was read
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assert "b" not in table.column_names
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# ensure user is assigned as an owner
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assert security_manager.find_user("admin") in table.owners
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# upload again with replace mode
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resp = upload_columnar(
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PARQUET_FILENAME1, PARQUET_UPLOAD_TABLE, extra={"if_exists": "replace"}
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)
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assert success_msg_f1 in resp
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with test_db.get_sqla_engine() as engine:
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data = engine.execute(
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f"SELECT * from {PARQUET_UPLOAD_TABLE} ORDER BY b"
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).fetchall()
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assert data == [("john", 1), ("paul", 2)]
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# replace table with zip file
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resp = upload_columnar(
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ZIP_FILENAME, PARQUET_UPLOAD_TABLE, extra={"if_exists": "replace"}
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)
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success_msg_f2 = f"Columnar file {escaped_parquet(ZIP_FILENAME)} uploaded to table {escaped_double_quotes(full_table_name)}"
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assert success_msg_f2 in resp
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with test_db.get_sqla_engine() as engine:
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data = engine.execute(
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f"SELECT * from {PARQUET_UPLOAD_TABLE} ORDER BY b"
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).fetchall()
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assert data == [("john", 1), ("paul", 2), ("max", 3), ("bob", 4)]
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