def newAPIHadoopFile(self, path, inputFormatClass, keyClass, valueClass, keyConverter=None,
                         valueConverter=None, conf=None, batchSize=0):
        """
        Read a 'new API' Hadoop InputFormat with arbitrary key and value class from HDFS,
        a local file system (available on all nodes), or any Hadoop-supported file system URI.
        The mechanism is the same as for sc.sequenceFile.

        A Hadoop configuration can be passed in as a Python dict. This will be converted into a
        Configuration in Java

        :param path: path to Hadoop file
        :param inputFormatClass: fully qualified classname of Hadoop InputFormat
               (e.g. "org.apache.hadoop.mapreduce.lib.input.TextInputFormat")
        :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: (None by default)
        :param valueConverter: (None by default)
        :param conf: Hadoop configuration, passed in as a dict
               (None by default)
        :param batchSize: The number of Python objects represented as a single
               Java object. (default 0, choose batchSize automatically)
        """
        jconf = self._dictToJavaMap(conf)
        jrdd = self._jvm.PythonRDD.newAPIHadoopFile(self._jsc, path, inputFormatClass, keyClass,
                                                    valueClass, keyConverter, valueConverter,
                                                    jconf, batchSize)
        return RDD(jrdd, self)
def newAPIHadoopFile ( self , path , inputFormatClass , keyClass , valueClass , keyConverter = None , valueConverter = None , conf = None , batchSize = 0 ) : jconf = self . _dictToJavaMap ( conf ) jrdd = self . _jvm . PythonRDD . newAPIHadoopFile ( self . _jsc , path , inputFormatClass , keyClass , valueClass , keyConverter , valueConverter , jconf , batchSize ) return RDD ( jrdd , self )
Read a 'new API' Hadoop InputFormat with arbitrary key and value class from HDFS,
        a local file system (available on all nodes), or any Hadoop-supported file system URI.
        The mechanism is the same as for sc.sequenceFile.

        A Hadoop configuration can be passed in as a Python dict. This will be converted into a
        Configuration in Java

        :param path: path to Hadoop file
        :param inputFormatClass: fully qualified classname of Hadoop InputFormat
               (e.g. "org.apache.hadoop.mapreduce.lib.input.TextInputFormat")
        :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: (None by default)
        :param valueConverter: (None by default)
        :param conf: Hadoop configuration, passed in as a dict
               (None by default)
        :param batchSize: The number of Python objects represented as a single
               Java object. (default 0, choose batchSize automatically)