Read a distributed Tab delimited CSV

Let's try a simple example. For convenience I'll be using handy toolz library but it is not really required here.

import sysimport base64if sys.version_info < (3, ):    import cPickle as pickleelse:    import picklefrom toolz.functoolz import composerdd = sc.parallelize([(1, {"foo": "bar"}), (2, {"bar": "foo"})])

Now, your code is not exactly portable right now. In Python 2 base64.b64encode returns str, while in Python 3 it returns bytes. Lets illustrate that:

• Python 2

  type(base64.b64encode(pickle.dumps({"foo": "bar"})))## str

• Python 3

  type(base64.b64encode(pickle.dumps({"foo": "bar"})))## bytes

So lets add decoding to the pipeline:

# Equivalent to # def pickle_and_b64(x):#     return base64.b64encode(pickle.dumps(x)).decode("ascii")pickle_and_b64 = compose(    lambda x: x.decode("ascii"),    base64.b64encode,    pickle.dumps)

Please note that this doesn't assume any particular shape of the data. Because of that, we'll use mapValues to serialize only keys:

serialized = rdd.mapValues(pickle_and_b64)serialized.first()## 1, u'KGRwMApTJ2ZvbycKcDEKUydiYXInCnAyCnMu')

Now we can follow it with simple format and save:

from tempfile import mkdtempimport osoutdir = os.path.join(mkdtemp(), "foo")serialized.map(lambda x: "{0}\t{1}".format(*x)).saveAsTextFile(outdir)

To read the file we reverse the process:

# Equivalent to# def  b64_and_unpickle(x):#     return pickle.loads(base64.b64decode(x))b64_and_unpickle = compose(    pickle.loads,    base64.b64decode)decoded = (sc.textFile(outdir)    .map(lambda x: x.split("\t"))  # In Python 3 we could simply use str.split    .mapValues(b64_and_unpickle))decoded.first()## (u'1', {'foo': 'bar'})