pyspark.RDD.saveAsSequenceFile#

RDD.saveAsSequenceFile(path, compressionCodecClass=None)[source]#

Output a Python RDD of key-value pairs (of form RDD[(K, V)]) to any Hadoop file system, using the “org.apache.hadoop.io.Writable” types that we convert from the RDD’s key and value types. The mechanism is as follows:

  1. Pickle is used to convert pickled Python RDD into RDD of Java objects.

  2. Keys and values of this Java RDD are converted to Writables and written out.

New in version 1.1.0.

Parameters
pathstr

path to sequence file

compressionCodecClassstr, optional

fully qualified classname of the compression codec class i.e. “org.apache.hadoop.io.compress.GzipCodec” (None by default)

See also

SparkContext.sequenceFile()
RDD.saveAsHadoopFile()
RDD.saveAsNewAPIHadoopFile()
RDD.saveAsHadoopDataset()
RDD.saveAsNewAPIHadoopDataset()
RDD.saveAsSequenceFile()

Examples

>>> import os
>>> import tempfile

Set the related classes

>>> with tempfile.TemporaryDirectory(prefix="saveAsSequenceFile") as d:
...     path = os.path.join(d, "sequence_file")
...
...     # Write a temporary sequence file
...     rdd = sc.parallelize([(1, ""), (1, "a"), (3, "x")])
...     rdd.saveAsSequenceFile(path)
...
...     # Load this sequence file as an RDD
...     loaded = sc.sequenceFile(path)
...     sorted(loaded.collect())
[(1, ''), (1, 'a'), (3, 'x')]