2018-11-14 23:30:52 -05:00
|
|
|
#
|
|
|
|
|
# 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.
|
|
|
|
|
#
|
|
|
|
|
import os
|
|
|
|
|
import shutil
|
|
|
|
|
import tempfile
|
|
|
|
|
import unittest
|
|
|
|
|
|
|
|
|
|
from pyspark.testing.utils import ReusedPySparkTestCase, SPARK_HOME
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
class InputFormatTests(ReusedPySparkTestCase):
|
|
|
|
|
|
|
|
|
|
@classmethod
|
|
|
|
|
def setUpClass(cls):
|
|
|
|
|
ReusedPySparkTestCase.setUpClass()
|
|
|
|
|
cls.tempdir = tempfile.NamedTemporaryFile(delete=False)
|
|
|
|
|
os.unlink(cls.tempdir.name)
|
|
|
|
|
cls.sc._jvm.WriteInputFormatTestDataGenerator.generateData(cls.tempdir.name, cls.sc._jsc)
|
|
|
|
|
|
|
|
|
|
@classmethod
|
|
|
|
|
def tearDownClass(cls):
|
|
|
|
|
ReusedPySparkTestCase.tearDownClass()
|
|
|
|
|
shutil.rmtree(cls.tempdir.name)
|
|
|
|
|
|
|
|
|
|
def test_oldhadoop(self):
|
|
|
|
|
basepath = self.tempdir.name
|
|
|
|
|
ints = sorted(self.sc.hadoopFile(basepath + "/sftestdata/sfint/",
|
|
|
|
|
"org.apache.hadoop.mapred.SequenceFileInputFormat",
|
|
|
|
|
"org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"org.apache.hadoop.io.Text").collect())
|
|
|
|
|
ei = [(1, u'aa'), (1, u'aa'), (2, u'aa'), (2, u'bb'), (2, u'bb'), (3, u'cc')]
|
|
|
|
|
self.assertEqual(ints, ei)
|
|
|
|
|
|
|
|
|
|
hellopath = os.path.join(SPARK_HOME, "python/test_support/hello/hello.txt")
|
|
|
|
|
oldconf = {"mapreduce.input.fileinputformat.inputdir": hellopath}
|
|
|
|
|
hello = self.sc.hadoopRDD("org.apache.hadoop.mapred.TextInputFormat",
|
|
|
|
|
"org.apache.hadoop.io.LongWritable",
|
|
|
|
|
"org.apache.hadoop.io.Text",
|
|
|
|
|
conf=oldconf).collect()
|
|
|
|
|
result = [(0, u'Hello World!')]
|
|
|
|
|
self.assertEqual(hello, result)
|
|
|
|
|
|
|
|
|
|
def test_newhadoop(self):
|
|
|
|
|
basepath = self.tempdir.name
|
|
|
|
|
ints = sorted(self.sc.newAPIHadoopFile(
|
|
|
|
|
basepath + "/sftestdata/sfint/",
|
|
|
|
|
"org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat",
|
|
|
|
|
"org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"org.apache.hadoop.io.Text").collect())
|
|
|
|
|
ei = [(1, u'aa'), (1, u'aa'), (2, u'aa'), (2, u'bb'), (2, u'bb'), (3, u'cc')]
|
|
|
|
|
self.assertEqual(ints, ei)
|
|
|
|
|
|
|
|
|
|
hellopath = os.path.join(SPARK_HOME, "python/test_support/hello/hello.txt")
|
|
|
|
|
newconf = {"mapreduce.input.fileinputformat.inputdir": hellopath}
|
|
|
|
|
hello = self.sc.newAPIHadoopRDD("org.apache.hadoop.mapreduce.lib.input.TextInputFormat",
|
|
|
|
|
"org.apache.hadoop.io.LongWritable",
|
|
|
|
|
"org.apache.hadoop.io.Text",
|
|
|
|
|
conf=newconf).collect()
|
|
|
|
|
result = [(0, u'Hello World!')]
|
|
|
|
|
self.assertEqual(hello, result)
|
|
|
|
|
|
|
|
|
|
def test_newolderror(self):
|
|
|
|
|
basepath = self.tempdir.name
|
|
|
|
|
self.assertRaises(Exception, lambda: self.sc.hadoopFile(
|
|
|
|
|
basepath + "/sftestdata/sfint/",
|
|
|
|
|
"org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat",
|
|
|
|
|
"org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"org.apache.hadoop.io.Text"))
|
|
|
|
|
|
|
|
|
|
self.assertRaises(Exception, lambda: self.sc.newAPIHadoopFile(
|
|
|
|
|
basepath + "/sftestdata/sfint/",
|
|
|
|
|
"org.apache.hadoop.mapred.SequenceFileInputFormat",
|
|
|
|
|
"org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"org.apache.hadoop.io.Text"))
|
|
|
|
|
|
|
|
|
|
def test_bad_inputs(self):
|
|
|
|
|
basepath = self.tempdir.name
|
|
|
|
|
self.assertRaises(Exception, lambda: self.sc.sequenceFile(
|
|
|
|
|
basepath + "/sftestdata/sfint/",
|
|
|
|
|
"org.apache.hadoop.io.NotValidWritable",
|
|
|
|
|
"org.apache.hadoop.io.Text"))
|
|
|
|
|
self.assertRaises(Exception, lambda: self.sc.hadoopFile(
|
|
|
|
|
basepath + "/sftestdata/sfint/",
|
|
|
|
|
"org.apache.hadoop.mapred.NotValidInputFormat",
|
|
|
|
|
"org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"org.apache.hadoop.io.Text"))
|
|
|
|
|
self.assertRaises(Exception, lambda: self.sc.newAPIHadoopFile(
|
|
|
|
|
basepath + "/sftestdata/sfint/",
|
|
|
|
|
"org.apache.hadoop.mapreduce.lib.input.NotValidInputFormat",
|
|
|
|
|
"org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"org.apache.hadoop.io.Text"))
|
|
|
|
|
|
|
|
|
|
def test_converters(self):
|
|
|
|
|
# use of custom converters
|
|
|
|
|
basepath = self.tempdir.name
|
|
|
|
|
maps = sorted(self.sc.sequenceFile(
|
|
|
|
|
basepath + "/sftestdata/sfmap/",
|
|
|
|
|
"org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"org.apache.hadoop.io.MapWritable",
|
|
|
|
|
keyConverter="org.apache.spark.api.python.TestInputKeyConverter",
|
|
|
|
|
valueConverter="org.apache.spark.api.python.TestInputValueConverter").collect())
|
|
|
|
|
em = [(u'\x01', []),
|
|
|
|
|
(u'\x01', [3.0]),
|
|
|
|
|
(u'\x02', [1.0]),
|
|
|
|
|
(u'\x02', [1.0]),
|
|
|
|
|
(u'\x03', [2.0])]
|
|
|
|
|
self.assertEqual(maps, em)
|
|
|
|
|
|
|
|
|
|
def test_binary_files(self):
|
|
|
|
|
path = os.path.join(self.tempdir.name, "binaryfiles")
|
|
|
|
|
os.mkdir(path)
|
|
|
|
|
data = b"short binary data"
|
|
|
|
|
with open(os.path.join(path, "part-0000"), 'wb') as f:
|
|
|
|
|
f.write(data)
|
|
|
|
|
[(p, d)] = self.sc.binaryFiles(path).collect()
|
|
|
|
|
self.assertTrue(p.endswith("part-0000"))
|
|
|
|
|
self.assertEqual(d, data)
|
|
|
|
|
|
|
|
|
|
def test_binary_records(self):
|
|
|
|
|
path = os.path.join(self.tempdir.name, "binaryrecords")
|
|
|
|
|
os.mkdir(path)
|
|
|
|
|
with open(os.path.join(path, "part-0000"), 'w') as f:
|
|
|
|
|
for i in range(100):
|
|
|
|
|
f.write('%04d' % i)
|
|
|
|
|
result = self.sc.binaryRecords(path, 4).map(int).collect()
|
|
|
|
|
self.assertEqual(list(range(100)), result)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
class OutputFormatTests(ReusedPySparkTestCase):
|
|
|
|
|
|
|
|
|
|
def setUp(self):
|
|
|
|
|
self.tempdir = tempfile.NamedTemporaryFile(delete=False)
|
|
|
|
|
os.unlink(self.tempdir.name)
|
|
|
|
|
|
|
|
|
|
def tearDown(self):
|
|
|
|
|
shutil.rmtree(self.tempdir.name, ignore_errors=True)
|
|
|
|
|
|
|
|
|
|
def test_oldhadoop(self):
|
|
|
|
|
basepath = self.tempdir.name
|
|
|
|
|
dict_data = [(1, {}),
|
|
|
|
|
(1, {"row1": 1.0}),
|
|
|
|
|
(2, {"row2": 2.0})]
|
|
|
|
|
self.sc.parallelize(dict_data).saveAsHadoopFile(
|
|
|
|
|
basepath + "/oldhadoop/",
|
|
|
|
|
"org.apache.hadoop.mapred.SequenceFileOutputFormat",
|
|
|
|
|
"org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"org.apache.hadoop.io.MapWritable")
|
|
|
|
|
result = self.sc.hadoopFile(
|
|
|
|
|
basepath + "/oldhadoop/",
|
|
|
|
|
"org.apache.hadoop.mapred.SequenceFileInputFormat",
|
|
|
|
|
"org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"org.apache.hadoop.io.MapWritable").collect()
|
|
|
|
|
for v in result:
|
|
|
|
|
self.assertTrue(v, dict_data)
|
|
|
|
|
|
|
|
|
|
conf = {
|
|
|
|
|
"mapred.output.format.class": "org.apache.hadoop.mapred.SequenceFileOutputFormat",
|
|
|
|
|
"mapreduce.job.output.key.class": "org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"mapreduce.job.output.value.class": "org.apache.hadoop.io.MapWritable",
|
|
|
|
|
"mapreduce.output.fileoutputformat.outputdir": basepath + "/olddataset/"
|
|
|
|
|
}
|
|
|
|
|
self.sc.parallelize(dict_data).saveAsHadoopDataset(conf)
|
|
|
|
|
input_conf = {"mapreduce.input.fileinputformat.inputdir": basepath + "/olddataset/"}
|
|
|
|
|
result = self.sc.hadoopRDD(
|
|
|
|
|
"org.apache.hadoop.mapred.SequenceFileInputFormat",
|
|
|
|
|
"org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"org.apache.hadoop.io.MapWritable",
|
|
|
|
|
conf=input_conf).collect()
|
|
|
|
|
for v in result:
|
|
|
|
|
self.assertTrue(v, dict_data)
|
|
|
|
|
|
|
|
|
|
def test_newhadoop(self):
|
|
|
|
|
basepath = self.tempdir.name
|
|
|
|
|
data = [(1, ""),
|
|
|
|
|
(1, "a"),
|
|
|
|
|
(2, "bcdf")]
|
|
|
|
|
self.sc.parallelize(data).saveAsNewAPIHadoopFile(
|
|
|
|
|
basepath + "/newhadoop/",
|
|
|
|
|
"org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat",
|
|
|
|
|
"org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"org.apache.hadoop.io.Text")
|
|
|
|
|
result = sorted(self.sc.newAPIHadoopFile(
|
|
|
|
|
basepath + "/newhadoop/",
|
|
|
|
|
"org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat",
|
|
|
|
|
"org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"org.apache.hadoop.io.Text").collect())
|
|
|
|
|
self.assertEqual(result, data)
|
|
|
|
|
|
|
|
|
|
conf = {
|
|
|
|
|
"mapreduce.job.outputformat.class":
|
|
|
|
|
"org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat",
|
|
|
|
|
"mapreduce.job.output.key.class": "org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"mapreduce.job.output.value.class": "org.apache.hadoop.io.Text",
|
|
|
|
|
"mapreduce.output.fileoutputformat.outputdir": basepath + "/newdataset/"
|
|
|
|
|
}
|
|
|
|
|
self.sc.parallelize(data).saveAsNewAPIHadoopDataset(conf)
|
|
|
|
|
input_conf = {"mapreduce.input.fileinputformat.inputdir": basepath + "/newdataset/"}
|
|
|
|
|
new_dataset = sorted(self.sc.newAPIHadoopRDD(
|
|
|
|
|
"org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat",
|
|
|
|
|
"org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"org.apache.hadoop.io.Text",
|
|
|
|
|
conf=input_conf).collect())
|
|
|
|
|
self.assertEqual(new_dataset, data)
|
|
|
|
|
|
|
|
|
|
def test_newolderror(self):
|
|
|
|
|
basepath = self.tempdir.name
|
|
|
|
|
rdd = self.sc.parallelize(range(1, 4)).map(lambda x: (x, "a" * x))
|
|
|
|
|
self.assertRaises(Exception, lambda: rdd.saveAsHadoopFile(
|
|
|
|
|
basepath + "/newolderror/saveAsHadoopFile/",
|
|
|
|
|
"org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat"))
|
|
|
|
|
self.assertRaises(Exception, lambda: rdd.saveAsNewAPIHadoopFile(
|
|
|
|
|
basepath + "/newolderror/saveAsNewAPIHadoopFile/",
|
|
|
|
|
"org.apache.hadoop.mapred.SequenceFileOutputFormat"))
|
|
|
|
|
|
|
|
|
|
def test_bad_inputs(self):
|
|
|
|
|
basepath = self.tempdir.name
|
|
|
|
|
rdd = self.sc.parallelize(range(1, 4)).map(lambda x: (x, "a" * x))
|
|
|
|
|
self.assertRaises(Exception, lambda: rdd.saveAsHadoopFile(
|
|
|
|
|
basepath + "/badinputs/saveAsHadoopFile/",
|
|
|
|
|
"org.apache.hadoop.mapred.NotValidOutputFormat"))
|
|
|
|
|
self.assertRaises(Exception, lambda: rdd.saveAsNewAPIHadoopFile(
|
|
|
|
|
basepath + "/badinputs/saveAsNewAPIHadoopFile/",
|
|
|
|
|
"org.apache.hadoop.mapreduce.lib.output.NotValidOutputFormat"))
|
|
|
|
|
|
|
|
|
|
def test_converters(self):
|
|
|
|
|
# use of custom converters
|
|
|
|
|
basepath = self.tempdir.name
|
|
|
|
|
data = [(1, {3.0: u'bb'}),
|
|
|
|
|
(2, {1.0: u'aa'}),
|
|
|
|
|
(3, {2.0: u'dd'})]
|
|
|
|
|
self.sc.parallelize(data).saveAsNewAPIHadoopFile(
|
|
|
|
|
basepath + "/converters/",
|
|
|
|
|
"org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat",
|
|
|
|
|
keyConverter="org.apache.spark.api.python.TestOutputKeyConverter",
|
|
|
|
|
valueConverter="org.apache.spark.api.python.TestOutputValueConverter")
|
|
|
|
|
converted = sorted(self.sc.sequenceFile(basepath + "/converters/").collect())
|
|
|
|
|
expected = [(u'1', 3.0),
|
|
|
|
|
(u'2', 1.0),
|
|
|
|
|
(u'3', 2.0)]
|
|
|
|
|
self.assertEqual(converted, expected)
|
|
|
|
|
|
|
|
|
|
def test_reserialization(self):
|
|
|
|
|
basepath = self.tempdir.name
|
|
|
|
|
x = range(1, 5)
|
|
|
|
|
y = range(1001, 1005)
|
|
|
|
|
data = list(zip(x, y))
|
|
|
|
|
rdd = self.sc.parallelize(x).zip(self.sc.parallelize(y))
|
|
|
|
|
rdd.saveAsSequenceFile(basepath + "/reserialize/sequence")
|
|
|
|
|
result1 = sorted(self.sc.sequenceFile(basepath + "/reserialize/sequence").collect())
|
|
|
|
|
self.assertEqual(result1, data)
|
|
|
|
|
|
|
|
|
|
rdd.saveAsHadoopFile(
|
|
|
|
|
basepath + "/reserialize/hadoop",
|
|
|
|
|
"org.apache.hadoop.mapred.SequenceFileOutputFormat")
|
|
|
|
|
result2 = sorted(self.sc.sequenceFile(basepath + "/reserialize/hadoop").collect())
|
|
|
|
|
self.assertEqual(result2, data)
|
|
|
|
|
|
|
|
|
|
rdd.saveAsNewAPIHadoopFile(
|
|
|
|
|
basepath + "/reserialize/newhadoop",
|
|
|
|
|
"org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat")
|
|
|
|
|
result3 = sorted(self.sc.sequenceFile(basepath + "/reserialize/newhadoop").collect())
|
|
|
|
|
self.assertEqual(result3, data)
|
|
|
|
|
|
|
|
|
|
conf4 = {
|
|
|
|
|
"mapred.output.format.class": "org.apache.hadoop.mapred.SequenceFileOutputFormat",
|
|
|
|
|
"mapreduce.job.output.key.class": "org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"mapreduce.job.output.value.class": "org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"mapreduce.output.fileoutputformat.outputdir": basepath + "/reserialize/dataset"}
|
|
|
|
|
rdd.saveAsHadoopDataset(conf4)
|
|
|
|
|
result4 = sorted(self.sc.sequenceFile(basepath + "/reserialize/dataset").collect())
|
|
|
|
|
self.assertEqual(result4, data)
|
|
|
|
|
|
|
|
|
|
conf5 = {"mapreduce.job.outputformat.class":
|
|
|
|
|
"org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat",
|
|
|
|
|
"mapreduce.job.output.key.class": "org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"mapreduce.job.output.value.class": "org.apache.hadoop.io.IntWritable",
|
|
|
|
|
"mapreduce.output.fileoutputformat.outputdir": basepath + "/reserialize/newdataset"
|
|
|
|
|
}
|
|
|
|
|
rdd.saveAsNewAPIHadoopDataset(conf5)
|
|
|
|
|
result5 = sorted(self.sc.sequenceFile(basepath + "/reserialize/newdataset").collect())
|
|
|
|
|
self.assertEqual(result5, data)
|
|
|
|
|
|
|
|
|
|
def test_malformed_RDD(self):
|
|
|
|
|
basepath = self.tempdir.name
|
|
|
|
|
# non-batch-serialized RDD[[(K, V)]] should be rejected
|
|
|
|
|
data = [[(1, "a")], [(2, "aa")], [(3, "aaa")]]
|
|
|
|
|
rdd = self.sc.parallelize(data, len(data))
|
|
|
|
|
self.assertRaises(Exception, lambda: rdd.saveAsSequenceFile(
|
|
|
|
|
basepath + "/malformed/sequence"))
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
if __name__ == "__main__":
|
2020-08-08 11:51:57 -04:00
|
|
|
from pyspark.tests.test_readwrite import * # noqa: F401
|
2018-11-14 23:30:52 -05:00
|
|
|
|
|
|
|
|
try:
|
|
|
|
|
import xmlrunner
|
2019-06-23 20:58:17 -04:00
|
|
|
testRunner = xmlrunner.XMLTestRunner(output='target/test-reports', verbosity=2)
|
2018-11-14 23:30:52 -05:00
|
|
|
except ImportError:
|
|
|
|
|
testRunner = None
|
|
|
|
|
unittest.main(testRunner=testRunner, verbosity=2)
|
