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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.
*/
package spark.rdd
import scala.collection.immutable.NumericRange
import org.scalatest.FunSuite
import org.scalatest.prop.Checkers
import org.scalacheck.Arbitrary._
import org.scalacheck.Gen
import org.scalacheck.Prop._
class ParallelCollectionSplitSuite extends FunSuite with Checkers {
test("one element per slice") {
val data = Array(1, 2, 3)
val slices = ParallelCollectionRDD.slice(data, 3)
assert(slices.size === 3)
assert(slices(0).mkString(",") === "1")
assert(slices(1).mkString(",") === "2")
assert(slices(2).mkString(",") === "3")
}
test("one slice") {
val data = Array(1, 2, 3)
val slices = ParallelCollectionRDD.slice(data, 1)
assert(slices.size === 1)
assert(slices(0).mkString(",") === "1,2,3")
}
test("equal slices") {
val data = Array(1, 2, 3, 4, 5, 6, 7, 8, 9)
val slices = ParallelCollectionRDD.slice(data, 3)
assert(slices.size === 3)
assert(slices(0).mkString(",") === "1,2,3")
assert(slices(1).mkString(",") === "4,5,6")
assert(slices(2).mkString(",") === "7,8,9")
}
test("non-equal slices") {
val data = Array(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)
val slices = ParallelCollectionRDD.slice(data, 3)
assert(slices.size === 3)
assert(slices(0).mkString(",") === "1,2,3")
assert(slices(1).mkString(",") === "4,5,6")
assert(slices(2).mkString(",") === "7,8,9,10")
}
test("splitting exclusive range") {
val data = 0 until 100
val slices = ParallelCollectionRDD.slice(data, 3)
assert(slices.size === 3)
assert(slices(0).mkString(",") === (0 to 32).mkString(","))
assert(slices(1).mkString(",") === (33 to 65).mkString(","))
assert(slices(2).mkString(",") === (66 to 99).mkString(","))
}
test("splitting inclusive range") {
val data = 0 to 100
val slices = ParallelCollectionRDD.slice(data, 3)
assert(slices.size === 3)
assert(slices(0).mkString(",") === (0 to 32).mkString(","))
assert(slices(1).mkString(",") === (33 to 66).mkString(","))
assert(slices(2).mkString(",") === (67 to 100).mkString(","))
}
test("empty data") {
val data = new Array[Int](0)
val slices = ParallelCollectionRDD.slice(data, 5)
assert(slices.size === 5)
for (slice <- slices) assert(slice.size === 0)
}
test("zero slices") {
val data = Array(1, 2, 3)
intercept[IllegalArgumentException] { ParallelCollectionRDD.slice(data, 0) }
}
test("negative number of slices") {
val data = Array(1, 2, 3)
intercept[IllegalArgumentException] { ParallelCollectionRDD.slice(data, -5) }
}
test("exclusive ranges sliced into ranges") {
val data = 1 until 100
val slices = ParallelCollectionRDD.slice(data, 3)
assert(slices.size === 3)
assert(slices.map(_.size).reduceLeft(_+_) === 99)
assert(slices.forall(_.isInstanceOf[Range]))
}
test("inclusive ranges sliced into ranges") {
val data = 1 to 100
val slices = ParallelCollectionRDD.slice(data, 3)
assert(slices.size === 3)
assert(slices.map(_.size).reduceLeft(_+_) === 100)
assert(slices.forall(_.isInstanceOf[Range]))
}
test("large ranges don't overflow") {
val N = 100 * 1000 * 1000
val data = 0 until N
val slices = ParallelCollectionRDD.slice(data, 40)
assert(slices.size === 40)
for (i <- 0 until 40) {
assert(slices(i).isInstanceOf[Range])
val range = slices(i).asInstanceOf[Range]
assert(range.start === i * (N / 40), "slice " + i + " start")
assert(range.end === (i+1) * (N / 40), "slice " + i + " end")
assert(range.step === 1, "slice " + i + " step")
}
}
test("random array tests") {
val gen = for {
d <- arbitrary[List[Int]]
n <- Gen.choose(1, 100)
} yield (d, n)
val prop = forAll(gen) {
(tuple: (List[Int], Int)) =>
val d = tuple._1
val n = tuple._2
val slices = ParallelCollectionRDD.slice(d, n)
("n slices" |: slices.size == n) &&
("concat to d" |: Seq.concat(slices: _*).mkString(",") == d.mkString(",")) &&
("equal sizes" |: slices.map(_.size).forall(x => x==d.size/n || x==d.size/n+1))
}
check(prop)
}
test("random exclusive range tests") {
val gen = for {
a <- Gen.choose(-100, 100)
b <- Gen.choose(-100, 100)
step <- Gen.choose(-5, 5) suchThat (_ != 0)
n <- Gen.choose(1, 100)
} yield (a until b by step, n)
val prop = forAll(gen) {
case (d: Range, n: Int) =>
val slices = ParallelCollectionRDD.slice(d, n)
("n slices" |: slices.size == n) &&
("all ranges" |: slices.forall(_.isInstanceOf[Range])) &&
("concat to d" |: Seq.concat(slices: _*).mkString(",") == d.mkString(",")) &&
("equal sizes" |: slices.map(_.size).forall(x => x==d.size/n || x==d.size/n+1))
}
check(prop)
}
test("random inclusive range tests") {
val gen = for {
a <- Gen.choose(-100, 100)
b <- Gen.choose(-100, 100)
step <- Gen.choose(-5, 5) suchThat (_ != 0)
n <- Gen.choose(1, 100)
} yield (a to b by step, n)
val prop = forAll(gen) {
case (d: Range, n: Int) =>
val slices = ParallelCollectionRDD.slice(d, n)
("n slices" |: slices.size == n) &&
("all ranges" |: slices.forall(_.isInstanceOf[Range])) &&
("concat to d" |: Seq.concat(slices: _*).mkString(",") == d.mkString(",")) &&
("equal sizes" |: slices.map(_.size).forall(x => x==d.size/n || x==d.size/n+1))
}
check(prop)
}
test("exclusive ranges of longs") {
val data = 1L until 100L
val slices = ParallelCollectionRDD.slice(data, 3)
assert(slices.size === 3)
assert(slices.map(_.size).reduceLeft(_+_) === 99)
assert(slices.forall(_.isInstanceOf[NumericRange[_]]))
}
test("inclusive ranges of longs") {
val data = 1L to 100L
val slices = ParallelCollectionRDD.slice(data, 3)
assert(slices.size === 3)
assert(slices.map(_.size).reduceLeft(_+_) === 100)
assert(slices.forall(_.isInstanceOf[NumericRange[_]]))
}
test("exclusive ranges of doubles") {
val data = 1.0 until 100.0 by 1.0
val slices = ParallelCollectionRDD.slice(data, 3)
assert(slices.size === 3)
assert(slices.map(_.size).reduceLeft(_+_) === 99)
assert(slices.forall(_.isInstanceOf[NumericRange[_]]))
}
test("inclusive ranges of doubles") {
val data = 1.0 to 100.0 by 1.0
val slices = ParallelCollectionRDD.slice(data, 3)
assert(slices.size === 3)
assert(slices.map(_.size).reduceLeft(_+_) === 100)
assert(slices.forall(_.isInstanceOf[NumericRange[_]]))
}
}
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