diff options
Diffstat (limited to 'examples/src/main/python/mllib/dataset_example.py')
| -rw-r--r-- | examples/src/main/python/mllib/dataset_example.py | 13 |
1 files changed, 7 insertions, 6 deletions
diff --git a/examples/src/main/python/mllib/dataset_example.py b/examples/src/main/python/mllib/dataset_example.py index fcbf56cbf0..e23ecc0c5d 100644 --- a/examples/src/main/python/mllib/dataset_example.py +++ b/examples/src/main/python/mllib/dataset_example.py @@ -19,6 +19,7 @@ An example of how to use DataFrame as a dataset for ML. Run with:: bin/spark-submit examples/src/main/python/mllib/dataset_example.py """ +from __future__ import print_function import os import sys @@ -32,16 +33,16 @@ from pyspark.mllib.stat import Statistics def summarize(dataset): - print "schema: %s" % dataset.schema().json() + print("schema: %s" % dataset.schema().json()) labels = dataset.map(lambda r: r.label) - print "label average: %f" % labels.mean() + print("label average: %f" % labels.mean()) features = dataset.map(lambda r: r.features) summary = Statistics.colStats(features) - print "features average: %r" % summary.mean() + print("features average: %r" % summary.mean()) if __name__ == "__main__": if len(sys.argv) > 2: - print >> sys.stderr, "Usage: dataset_example.py <libsvm file>" + print("Usage: dataset_example.py <libsvm file>", file=sys.stderr) exit(-1) sc = SparkContext(appName="DatasetExample") sqlContext = SQLContext(sc) @@ -54,9 +55,9 @@ if __name__ == "__main__": summarize(dataset0) tempdir = tempfile.NamedTemporaryFile(delete=False).name os.unlink(tempdir) - print "Save dataset as a Parquet file to %s." % tempdir + print("Save dataset as a Parquet file to %s." % tempdir) dataset0.saveAsParquetFile(tempdir) - print "Load it back and summarize it again." + print("Load it back and summarize it again.") dataset1 = sqlContext.parquetFile(tempdir).setName("dataset1").cache() summarize(dataset1) shutil.rmtree(tempdir) |