def predict(dataset, fitmodel_url, save_results=True, show=False):
    """
    Function starts a job that makes predictions to input data with a given model.

    Parameters
    ----------
    input - dataset object with input urls and other parameters
    fitmodel_url - model created in fit phase
    save_results - save results to ddfs
    show - show info about job execution

    Returns
    -------
    Urls with predictions on ddfs
    """
    from disco.worker.pipeline.worker import Worker, Stage
    from disco.core import Job, result_iterator

    if "linsvm_fitmodel" not in fitmodel_url:
        raise Exception("Incorrect fit model.")

    job = Job(worker=Worker(save_results=save_results))
    # job parallelizes execution of mappers
    job.pipeline = [
        ("split", Stage("map", input_chain=dataset.params["input_chain"], init=simple_init, process=map_predict))]

    job.params = dataset.params
    job.params["fit_params"] = [v for _, v in result_iterator(fitmodel_url["linsvm_fitmodel"])][0]
    job.run(name="linsvm_predict", input=dataset.params["data_tag"])

    return job.wait(show=show)