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Posted to commits@spark.apache.org by jk...@apache.org on 2015/12/12 03:02:28 UTC
spark git commit: [SPARK-11978][ML] Move dataset_example.py to
examples/ml and rename to dataframe_example.py
Repository: spark
Updated Branches:
refs/heads/master aea676ca2 -> a0ff6d16e
[SPARK-11978][ML] Move dataset_example.py to examples/ml and rename to dataframe_example.py
Since ```Dataset``` has a new meaning in Spark 1.6, we should rename it to avoid confusion.
#9873 finished the work of Scala example, here we focus on the Python one.
Move dataset_example.py to ```examples/ml``` and rename to ```dataframe_example.py```.
BTW, fix minor missing issues of #9873.
cc mengxr
Author: Yanbo Liang <yb...@gmail.com>
Closes #9957 from yanboliang/SPARK-11978.
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/a0ff6d16
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/a0ff6d16
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/a0ff6d16
Branch: refs/heads/master
Commit: a0ff6d16ef4bcc1b6ff7282e82a9b345d8449454
Parents: aea676c
Author: Yanbo Liang <yb...@gmail.com>
Authored: Fri Dec 11 18:02:24 2015 -0800
Committer: Joseph K. Bradley <jo...@databricks.com>
Committed: Fri Dec 11 18:02:24 2015 -0800
----------------------------------------------------------------------
.../src/main/python/ml/dataframe_example.py | 75 ++++++++++++++++++++
.../src/main/python/mllib/dataset_example.py | 63 ----------------
.../spark/examples/ml/DataFrameExample.scala | 8 +--
3 files changed, 79 insertions(+), 67 deletions(-)
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http://git-wip-us.apache.org/repos/asf/spark/blob/a0ff6d16/examples/src/main/python/ml/dataframe_example.py
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diff --git a/examples/src/main/python/ml/dataframe_example.py b/examples/src/main/python/ml/dataframe_example.py
new file mode 100644
index 0000000..d2644ca
--- /dev/null
+++ b/examples/src/main/python/ml/dataframe_example.py
@@ -0,0 +1,75 @@
+#
+# 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.
+#
+
+"""
+An example of how to use DataFrame for ML. Run with::
+ bin/spark-submit examples/src/main/python/ml/dataframe_example.py <input>
+"""
+from __future__ import print_function
+
+import os
+import sys
+import tempfile
+import shutil
+
+from pyspark import SparkContext
+from pyspark.sql import SQLContext
+from pyspark.mllib.stat import Statistics
+
+if __name__ == "__main__":
+ if len(sys.argv) > 2:
+ print("Usage: dataframe_example.py <libsvm file>", file=sys.stderr)
+ exit(-1)
+ sc = SparkContext(appName="DataFrameExample")
+ sqlContext = SQLContext(sc)
+ if len(sys.argv) == 2:
+ input = sys.argv[1]
+ else:
+ input = "data/mllib/sample_libsvm_data.txt"
+
+ # Load input data
+ print("Loading LIBSVM file with UDT from " + input + ".")
+ df = sqlContext.read.format("libsvm").load(input).cache()
+ print("Schema from LIBSVM:")
+ df.printSchema()
+ print("Loaded training data as a DataFrame with " +
+ str(df.count()) + " records.")
+
+ # Show statistical summary of labels.
+ labelSummary = df.describe("label")
+ labelSummary.show()
+
+ # Convert features column to an RDD of vectors.
+ features = df.select("features").map(lambda r: r.features)
+ summary = Statistics.colStats(features)
+ print("Selected features column with average values:\n" +
+ str(summary.mean()))
+
+ # Save the records in a parquet file.
+ tempdir = tempfile.NamedTemporaryFile(delete=False).name
+ os.unlink(tempdir)
+ print("Saving to " + tempdir + " as Parquet file.")
+ df.write.parquet(tempdir)
+
+ # Load the records back.
+ print("Loading Parquet file with UDT from " + tempdir)
+ newDF = sqlContext.read.parquet(tempdir)
+ print("Schema from Parquet:")
+ newDF.printSchema()
+ shutil.rmtree(tempdir)
+
+ sc.stop()
http://git-wip-us.apache.org/repos/asf/spark/blob/a0ff6d16/examples/src/main/python/mllib/dataset_example.py
----------------------------------------------------------------------
diff --git a/examples/src/main/python/mllib/dataset_example.py b/examples/src/main/python/mllib/dataset_example.py
deleted file mode 100644
index e23ecc0..0000000
--- a/examples/src/main/python/mllib/dataset_example.py
+++ /dev/null
@@ -1,63 +0,0 @@
-#
-# 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.
-#
-
-"""
-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
-import tempfile
-import shutil
-
-from pyspark import SparkContext
-from pyspark.sql import SQLContext
-from pyspark.mllib.util import MLUtils
-from pyspark.mllib.stat import Statistics
-
-
-def summarize(dataset):
- print("schema: %s" % dataset.schema().json())
- labels = dataset.map(lambda r: r.label)
- print("label average: %f" % labels.mean())
- features = dataset.map(lambda r: r.features)
- summary = Statistics.colStats(features)
- print("features average: %r" % summary.mean())
-
-if __name__ == "__main__":
- if len(sys.argv) > 2:
- print("Usage: dataset_example.py <libsvm file>", file=sys.stderr)
- exit(-1)
- sc = SparkContext(appName="DatasetExample")
- sqlContext = SQLContext(sc)
- if len(sys.argv) == 2:
- input = sys.argv[1]
- else:
- input = "data/mllib/sample_libsvm_data.txt"
- points = MLUtils.loadLibSVMFile(sc, input)
- dataset0 = sqlContext.inferSchema(points).setName("dataset0").cache()
- summarize(dataset0)
- tempdir = tempfile.NamedTemporaryFile(delete=False).name
- os.unlink(tempdir)
- print("Save dataset as a Parquet file to %s." % tempdir)
- dataset0.saveAsParquetFile(tempdir)
- print("Load it back and summarize it again.")
- dataset1 = sqlContext.parquetFile(tempdir).setName("dataset1").cache()
- summarize(dataset1)
- shutil.rmtree(tempdir)
http://git-wip-us.apache.org/repos/asf/spark/blob/a0ff6d16/examples/src/main/scala/org/apache/spark/examples/ml/DataFrameExample.scala
----------------------------------------------------------------------
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/DataFrameExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/DataFrameExample.scala
index 424f001..0a477ab 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/DataFrameExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/DataFrameExample.scala
@@ -44,10 +44,10 @@ object DataFrameExample {
def main(args: Array[String]) {
val defaultParams = Params()
- val parser = new OptionParser[Params]("DatasetExample") {
- head("Dataset: an example app using DataFrame as a Dataset for ML.")
+ val parser = new OptionParser[Params]("DataFrameExample") {
+ head("DataFrameExample: an example app using DataFrame for ML.")
opt[String]("input")
- .text(s"input path to dataset")
+ .text(s"input path to dataframe")
.action((x, c) => c.copy(input = x))
checkConfig { params =>
success
@@ -88,7 +88,7 @@ object DataFrameExample {
// Save the records in a parquet file.
val tmpDir = Files.createTempDir()
tmpDir.deleteOnExit()
- val outputDir = new File(tmpDir, "dataset").toString
+ val outputDir = new File(tmpDir, "dataframe").toString
println(s"Saving to $outputDir as Parquet file.")
df.write.parquet(outputDir)
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