Hi mates ! I'm very new at pyflink and trying to register a custom UDF function using python API. Currently I faced an issue in both server env and my local IDE environment.
When I'm trying to execute the example below I got an error message: *The configured Task Off-Heap Memory 0 bytes is less than the least required Python worker Memory 79 mb. The Task Off-Heap Memory can be configured using the configuration key 'taskmanager.memory.task.off-heap.size* Of course I've added required property into *flink-conf.yaml *and checked that *pyflink-shell.sh *initializes env using specified configuration but it doesn't make any sense and I still have an error. I've also attached my flink-conf.yaml file Thx for your help ! *Here is an example:* from pyflink.dataset import ExecutionEnvironment from pyflink.table import BatchTableEnvironment, DataTypes from pyflink.table.udf import udf @udf(input_types=[DataTypes.STRING()], result_type=DataTypes.STRING()) def test_udf(i): return i if __name__ == "__main__": env = ExecutionEnvironment.get_execution_environment() env.set_parallelism(1) bt_env = BatchTableEnvironment.create(env) bt_env.register_function("test_udf", test_udf) my_table = bt_env.from_elements( [ ("user-1", "http://url/1"), ("user-2", "http://url/2"), ("user-1", "http://url/3"), ("user-3", "http://url/4"), ("user-1", "http://url/3") ], [ "uid", "url" ] ) my_table_grouped_by_uid = my_table.group_by("uid").select("uid, collect(url) as urls") bt_env.create_temporary_view("my_temp_table", my_table_grouped_by_uid) bt_env.execute_sql("select test_udf(uid) as uid, urls from my_temp_table").print()