################################################################################ # 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. ################################################################################ import logging import sys import pandas as pd import numpy as np from pyflink.table import (DataTypes, TableEnvironment, EnvironmentSettings) def conversion_from_dataframe(): t_env = TableEnvironment.create(EnvironmentSettings.in_streaming_mode()) t_env.get_config().set("parallelism.default", "1") # define the source with watermark definition pdf = pd.DataFrame(np.random.rand(1000, 2)) table = t_env.from_pandas( pdf, schema=DataTypes.ROW([DataTypes.FIELD("a", DataTypes.DOUBLE()), DataTypes.FIELD("b", DataTypes.DOUBLE())])) print(table.to_pandas()) if __name__ == '__main__': logging.basicConfig(stream=sys.stdout, level=logging.INFO, format="%(message)s") conversion_from_dataframe()