tests/tasks/test_spark.py

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.

"""Test Task Spark."""

from unittest.mock import patch

from pydolphinscheduler.tasks.spark import DeployMode, ProgramType, Spark


@patch(
    "pydolphinscheduler.core.engine.Engine.get_resource_info",
    return_value=({"id": 1, "name": "test"}),
)
def test_spark_get_define(mock_resource):
    """Test task spark function get_define."""
    code = 123
    version = 1
    name = "test_spark_get_define"
    main_class = "org.apache.spark.test_main_class"
    main_package = "test_main_package"
    program_type = ProgramType.JAVA
    deploy_mode = DeployMode.LOCAL

    expect_task_params = {
        "mainClass": main_class,
        "mainJar": {
            "id": 1,
        },
        "programType": program_type,
        "deployMode": deploy_mode,
        "driverCores": 1,
        "driverMemory": "512M",
        "numExecutors": 2,
        "executorMemory": "2G",
        "executorCores": 2,
        "appName": None,
        "mainArgs": None,
        "others": None,
        "localParams": [],
        "resourceList": [],
        "dependence": {},
        "conditionResult": {"successNode": [""], "failedNode": [""]},
        "waitStartTimeout": {},
    }
    with patch(
        "pydolphinscheduler.core.task.Task.gen_code_and_version",
        return_value=(code, version),
    ):
        task = Spark(name, main_class, main_package, program_type, deploy_mode)
        assert task.task_params == expect_task_params