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#
# 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 shutil
import tempfile
from pyspark.sql import Row
from pyspark.sql.types import IntegerType, StructField, StructType, LongType, StringType
from pyspark.testing.sqlutils import ReusedSQLTestCase
class DataSourcesTests(ReusedSQLTestCase):
def test_linesep_text(self):
df = self.spark.read.text("python/test_support/sql/ages_newlines.csv", lineSep=",")
expected = [Row(value=u'Joe'), Row(value=u'20'), Row(value=u'"Hi'),
Row(value=u'\nI am Jeo"\nTom'), Row(value=u'30'),
Row(value=u'"My name is Tom"\nHyukjin'), Row(value=u'25'),
Row(value=u'"I am Hyukjin\n\nI love Spark!"\n')]
self.assertEqual(df.collect(), expected)
tpath = tempfile.mkdtemp()
shutil.rmtree(tpath)
try:
df.write.text(tpath, lineSep="!")
expected = [Row(value=u'Joe!20!"Hi!'), Row(value=u'I am Jeo"'),
Row(value=u'Tom!30!"My name is Tom"'),
Row(value=u'Hyukjin!25!"I am Hyukjin'),
Row(value=u''), Row(value=u'I love Spark!"'),
Row(value=u'!')]
readback = self.spark.read.text(tpath)
self.assertEqual(readback.collect(), expected)
finally:
shutil.rmtree(tpath)
def test_multiline_json(self):
people1 = self.spark.read.json("python/test_support/sql/people.json")
people_array = self.spark.read.json("python/test_support/sql/people_array.json",
multiLine=True)
self.assertEqual(people1.collect(), people_array.collect())
def test_encoding_json(self):
people_array = self.spark.read\
.json("python/test_support/sql/people_array_utf16le.json",
multiLine=True, encoding="UTF-16LE")
expected = [Row(age=30, name=u'Andy'), Row(age=19, name=u'Justin')]
self.assertEqual(people_array.collect(), expected)
def test_linesep_json(self):
df = self.spark.read.json("python/test_support/sql/people.json", lineSep=",")
expected = [Row(_corrupt_record=None, name=u'Michael'),
Row(_corrupt_record=u' "age":30}\n{"name":"Justin"', name=None),
Row(_corrupt_record=u' "age":19}\n', name=None)]
self.assertEqual(df.collect(), expected)
tpath = tempfile.mkdtemp()
shutil.rmtree(tpath)
try:
df = self.spark.read.json("python/test_support/sql/people.json")
df.write.json(tpath, lineSep="!!")
readback = self.spark.read.json(tpath, lineSep="!!")
self.assertEqual(readback.collect(), df.collect())
finally:
shutil.rmtree(tpath)
def test_multiline_csv(self):
ages_newlines = self.spark.read.csv(
"python/test_support/sql/ages_newlines.csv", multiLine=True)
expected = [Row(_c0=u'Joe', _c1=u'20', _c2=u'Hi,\nI am Jeo'),
Row(_c0=u'Tom', _c1=u'30', _c2=u'My name is Tom'),
Row(_c0=u'Hyukjin', _c1=u'25', _c2=u'I am Hyukjin\n\nI love Spark!')]
self.assertEqual(ages_newlines.collect(), expected)
def test_ignorewhitespace_csv(self):
tmpPath = tempfile.mkdtemp()
shutil.rmtree(tmpPath)
self.spark.createDataFrame([[" a", "b ", " c "]]).write.csv(
tmpPath,
ignoreLeadingWhiteSpace=False,
ignoreTrailingWhiteSpace=False)
expected = [Row(value=u' a,b , c ')]
readback = self.spark.read.text(tmpPath)
self.assertEqual(readback.collect(), expected)
shutil.rmtree(tmpPath)
def test_read_multiple_orc_file(self):
df = self.spark.read.orc(["python/test_support/sql/orc_partitioned/b=0/c=0",
"python/test_support/sql/orc_partitioned/b=1/c=1"])
self.assertEqual(2, df.count())
def test_read_text_file_list(self):
df = self.spark.read.text(['python/test_support/sql/text-test.txt',
'python/test_support/sql/text-test.txt'])
count = df.count()
self.assertEqual(count, 4)
def test_json_sampling_ratio(self):
rdd = self.spark.sparkContext.range(0, 100, 1, 1) \
.map(lambda x: '{"a":0.1}' if x == 1 else '{"a":%s}' % str(x))
schema = self.spark.read.option('inferSchema', True) \
.option('samplingRatio', 0.5) \
.json(rdd).schema
self.assertEqual(schema, StructType([StructField("a", LongType(), True)]))
def test_csv_sampling_ratio(self):
rdd = self.spark.sparkContext.range(0, 100, 1, 1) \
.map(lambda x: '0.1' if x == 1 else str(x))
schema = self.spark.read.option('inferSchema', True)\
.csv(rdd, samplingRatio=0.5).schema
self.assertEqual(schema, StructType([StructField("_c0", IntegerType(), True)]))
def test_checking_csv_header(self):
path = tempfile.mkdtemp()
shutil.rmtree(path)
try:
self.spark.createDataFrame([[1, 1000], [2000, 2]])\
.toDF('f1', 'f2').write.option("header", "true").csv(path)
schema = StructType([
StructField('f2', IntegerType(), nullable=True),
StructField('f1', IntegerType(), nullable=True)])
df = self.spark.read.option('header', 'true').schema(schema)\
.csv(path, enforceSchema=False)
self.assertRaisesRegex(
Exception,
"CSV header does not conform to the schema",
lambda: df.collect())
finally:
shutil.rmtree(path)
def test_ignore_column_of_all_nulls(self):
path = tempfile.mkdtemp()
shutil.rmtree(path)
try:
df = self.spark.createDataFrame([["""{"a":null, "b":1, "c":3.0}"""],
["""{"a":null, "b":null, "c":"string"}"""],
["""{"a":null, "b":null, "c":null}"""]])
df.write.text(path)
schema = StructType([
StructField('b', LongType(), nullable=True),
StructField('c', StringType(), nullable=True)])
readback = self.spark.read.json(path, dropFieldIfAllNull=True)
self.assertEqual(readback.schema, schema)
finally:
shutil.rmtree(path)
if __name__ == "__main__":
import unittest
from pyspark.sql.tests.test_datasources import * # noqa: F401
try:
import xmlrunner # type: ignore[import]
testRunner = xmlrunner.XMLTestRunner(output='target/test-reports', verbosity=2)
except ImportError:
testRunner = None
unittest.main(testRunner=testRunner, verbosity=2)
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