# Examples for python and Spark
[Link](https://github.com/apache/spark/tree/branch-1.2/examples/src/main/python)
- Word Count
```python
import sys
from operator import add
from pyspark import SparkContext

if __name__ == "__main__":
    if len(sys.argv) != 2:
        print >> sys.stderr, "Usage: wordcount <file>"
        exit(-1)
    sc = SparkContext(appName="PythonWordCount")
    lines = sc.textFile(sys.argv[1], 1)
    counts = lines.flatMap(lambda x: x.split(' ')) \
                  .map(lambda x: (x, 1)) \
                  .reduceByKey(add)
    output = counts.collect()
    for (word, count) in output:
        print "%s: %i" % (word, count)

    sc.stop()
```
- Word Count by Streaming
```python
"""
 Counts words in new text files created in the given directory
 Usage: hdfs_wordcount.py <directory>
   <directory> is the directory that Spark Streaming will use to find and read new text files.

 To run this on your local machine on directory `localdir`, run this example
    $ bin/spark-submit examples/src/main/python/streaming/hdfs_wordcount.py localdir

 Then create a text file in `localdir` and the words in the file will get counted.
"""
import sys
from pyspark import SparkContext
from pyspark.streaming import StreamingContext

if __name__ == "__main__":
    if len(sys.argv) != 2:
        print >> sys.stderr, "Usage: hdfs_wordcount.py <directory>"
        exit(-1)

    sc = SparkContext(appName="PythonStreamingHDFSWordCount")
    ssc = StreamingContext(sc, 1)

    lines = ssc.textFileStream(sys.argv[1])
    counts = lines.flatMap(lambda line: line.split(" "))\
                  .map(lambda x: (x, 1))\
                  .reduceByKey(lambda a, b: a+b)
    counts.pprint()

    ssc.start()
    ssc.awaitTermination()
```
- Sort 
```python
import sys
from pyspark import SparkContext

if __name__ == "__main__":
    if len(sys.argv) != 2:
        print >> sys.stderr, "Usage: sort <file>"
        exit(-1)
    sc = SparkContext(appName="PythonSort")
    lines = sc.textFile(sys.argv[1], 1)
    sortedCount = lines.flatMap(lambda x: x.split(' ')) \
        .map(lambda x: (int(x), 1)) \
        .sortByKey(lambda x: x)
    # This is just a demo on how to bring all the sorted data back to a single node.
    # In reality, we wouldn't want to collect all the data to the driver node.
    output = sortedCount.collect()
    for (num, unitcount) in output:
        print num

    sc.stop()
```