# # 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 * 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.assertEquals(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.assertEquals(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.assertEquals(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.assertRaisesRegexp( 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.assertEquals(readback.schema, schema) finally: shutil.rmtree(path) if __name__ == "__main__": import unittest from pyspark.sql.tests.test_datasources import * try: import xmlrunner unittest.main(testRunner=xmlrunner.XMLTestRunner(output='target/test-reports'), verbosity=2) except ImportError: unittest.main(verbosity=2)