code: def sequenceFile(self, path, keyClass=None, valueClass=None, keyConverter=None,
                       valueConverter=None, minSplits=None, batchSize=0):
          
          minSplits = minSplits or min(self.defaultParallelism, 2)
          jrdd = self._jvm.PythonRDD.sequenceFile(self._jsc, path, keyClass, valueClass,
                                                  keyConverter, valueConverter, minSplits, batchSize)
          return RDD(jrdd, self)
docs: Read a Hadoop SequenceFile with arbitrary key and value Writable class from HDFS,
          a local file system (available on all nodes), or any Hadoop-supported file system URI.
          The mechanism is as follows:
  
              1. A Java RDD is created from the SequenceFile or other InputFormat, and the key
                 and value Writable classes
              2. Serialization is attempted via Pyrolite pickling
              3. If this fails, the fallback is to call 'toString' on each key and value
              4. C{PickleSerializer} is used to deserialize pickled objects on the Python side
  
          :param path: path to sequncefile
          :param keyClass: fully qualified classname of key Writable class
                 (e.g. "org.apache.hadoop.io.Text")
          :param valueClass: fully qualified classname of value Writable class
                 (e.g. "org.apache.hadoop.io.LongWritable")
          :param keyConverter:
          :param valueConverter:
          :param minSplits: minimum splits in dataset
                 (default min(2, sc.defaultParallelism))
          :param batchSize: The number of Python objects represented as a single
                 Java object. (default 0, choose batchSize automatically)