出5道关于Spark RDD相关的读代码的填空题并给出答案

val rdd = sc.parallelize(Seq((1, "a"), (2, "b"), (3, "c")))
val result = rdd.mapValues(x => x + "x").collect()
println(result.mkString(", "))
// Output: (1,ax), (2,bx), (3,cx)

填空：rdd.map______(x => x + "x").collect()

答案：mapValues

val rdd1 = sc.parallelize(Seq((1, "a"), (2, "b"), (3, "c")))
val rdd2 = sc.parallelize(Seq((1, "d"), (2, "e"), (4, "f")))
val result = rdd1.fullOuterJoin(rdd2).collect()
println(result.mkString(", "))
// Output: (4,(None,Some(f))), (1,(Some(a),Some(d))), (2,(Some(b),Some(e))), (3,(Some(c),None))

填空：rdd1.fullOuter______(rdd2).collect()

答案：Join

val rdd = sc.parallelize(Seq((1, "a"), (2, "b"), (3, "c")))
val result = rdd.filter(x => x._1 % 2 == 0).collect()
println(result.mkString(", "))
// Output: (2,b)

填空：rdd.filter(x => x._1 ____ 2 == 0).collect()

答案：%

val rdd = sc.parallelize(Seq((1, "a"), (2, "b"), (3, "c")))
val result = rdd.reduceByKey((x, y) => x + y).collect()
println(result.mkString(", "))
// Output: (1,a), (2,b), (3,c)

填空：rdd.reduce______((x, y) => x + y).collect()

答案：reduceByKey

val rdd = sc.parallelize(Seq((1, "a"), (2, "b"), (3, "c")))
val result = rdd.flatMapValues(x => x + "x").collect()
println(result.mkString(", "))
// Output: (1,a), (1,x), (2,b), (2,x), (3,c), (3,x)

填空：rdd.flatMap______(x => x + "x").collect()

答案：flatMapValue