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from __future__ import absolute_import

# 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.

from .utils import add_pyspark_path_if_needed, quiet_py4j

from .pathmagic import *

from .testcase import SparkTestingBaseReuse

import os

import sys

from itertools import chain

import operator

import tempfile

import random

from functools import reduce

from pyspark.context import SparkConf, SparkContext, RDD

from pyspark.sql import SQLContext

class SQLTestCase(SparkTestingBaseReuse):

"""Basic common test case for Spark SQL tests. Provides a

Spark SQL context as well as some helper methods for comparing

results."""

@classmethod

def setUpClass(cls):

super(SQLTestCase, cls).setUpClass()

@classmethod

def tearDownClass(cls):

super(SQLTestCase, cls).tearDownClass()

def getConf(self):

"""Override this to specify any custom configuration."""

return {}

def setUp(self):

try:

from pyspark.sql import Session

self.session = Session.Builder.config(self.getConf())

self.sqlCtx = self.session._wrapped

except Exception:

self.sqlCtx = SQLContext(self.sc)

def assertDataFrameEqual(self, expected, result, tol=0):

"""Assert that two DataFrames contain the same data.

When comparing inexact fields uses tol.

"""

self.assertEqual(expected.schema, result.schema)

try:

expectedRDD = expected.rdd.cache()

resultRDD = result.rdd.cache()

self.assertEqual(expectedRDD.count(), resultRDD.count())

def zipWithIndex(rdd):

"""Zip with index (idx, data)"""

return rdd.zipWithIndex().map(lambda x: (x[1], x[0]))

def equal(x, y):

if (len(x) != len(y)):

return False

elif (x == y):

return True

else:

for idx in range(len(x)):

a = x[idx]

b = y[idx]

if isinstance(a, float):

if (abs(a - b) > tol):

return False

else:

if a != b:

return False

return True

expectedIndexed = zipWithIndex(expectedRDD)

resultIndexed = zipWithIndex(resultRDD)

joinedRDD = expectedIndexed.join(resultIndexed)

unequalRDD = joinedRDD.filter(

lambda x: not equal(x[1][0], x[1][1]))

differentRows = unequalRDD.take(10)

self.assertEqual([], differentRows)

finally:

expectedRDD.unpersist()

resultRDD.unpersist()

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