blob: f815dd26823d15cb58a96d31e3b0cd7edd6141e7 (
plain) (
blame)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
|
#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
"""
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.
"""
from __future__ import print_function
import sys
from pyspark import SparkContext
from pyspark.streaming import StreamingContext
if __name__ == "__main__":
if len(sys.argv) != 2:
print("Usage: hdfs_wordcount.py <directory>", file=sys.stderr)
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()
|
