ProcessPoolExecutor workers will hold onto the return value of their last task in memory until the next task is received. Since the return value has already been propagated to the parent process's `Future` or else effectively discarded, this is holding onto objects unnecessarily.

Simple case to reproduce:

    import concurrent.futures
    import time

    executor = concurrent.futures.ProcessPoolExecutor(max_workers=1)

    def big_val():
        return [{1:1} for i in range(1, 1000000)]

    executor.submit(big_val)

    # Observe the memory usage of the process worker during the sleep interval
    time.sleep(10)


This should be easily fixed by having the worker explicitly `del r` after calling `_sendback_result` as it already does this for `call_item`