Python BigQuery performance much worse than Java

# <cut imports>

options = PipelineOptions()
options.view_as(StandardOptions).runner = 'DataflowRunner'
# <cut more options>

pipeline = Pipeline(options=options)
(pipeline
    | 'Read' >> beam.io.Read(beam.io.BigQuerySource(query='SELECT weight_pounds FROM [bigquery-public-data:samples.natality]'))
    | 'MapToFloat' >> beam.Map(lambda elem: elem['weight_pounds'])
    | 'Top' >> beam.combiners.Top.Largest(100)
    | 'MapToString' >> beam.Map(lambda elem: str(elem))
    | 'Write' >> beam.io.WriteToText("<output-file>"))

pipeline.run()

// <cut imports>

public class Natality {
    public static void main(String[] args) {
        DataflowPipelineOptions options = PipelineOptionsFactory.create().as(DataflowPipelineOptions.class);
        options.setRunner(DataflowRunner.class);
        // <cut more options>
        
        Pipeline pipeline = Pipeline.create(options);

        pipeline.apply("Read", BigQueryIO.readTableRows()
            .fromQuery("SELECT weight_pounds FROM [bigquery-public-data:samples.natality]"))
            .apply("MapToDouble", MapElements
                .into(TypeDescriptors.doubles())
                .via(row -> {
                     Object obj = row.get("weight_pounds");
                     return (obj == null ? 0.0 : (Double) obj);
                }))
            .apply("Top", Top.largest(100))
            .apply("MapToString", MapElements
                .into(TypeDescriptors.strings())
                .via(weight -> weight.toString()))
            .apply("Write", TextIO.write().to("<output-file>"));

        pipeline.run().waitUntilFinish();
    }
}