我通过指定分区数从文本文件创建rdd（spark 1.6）。但它给出的分区数与指定的分区数不同。
案例1

scala> val people = sc.textFile("file:///home/pvikash/data/test.txt", 1)
people: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[50] at textFile at <console>:27

scala> people.getNumPartitions
res36: Int = 1

scala> val people = sc.textFile("file:///home/pvikash/data/test.txt", 2)
people: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[52] at textFile at <console>:27

scala> people.getNumPartitions
res37: Int = 2

scala> val people = sc.textFile("file:///home/pvikash/data/test.txt", 3)
people: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[54] at textFile at <console>:27

scala> people.getNumPartitions
res38: Int = 3

scala> val people = sc.textFile("file:///home/pvikash/data/test.txt", 4)
people: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[56] at textFile at <console>:27

scala> people.getNumPartitions
res39: Int = 4

案例2

scala> val people = sc.textFile("file:///home/pvikash/data/test.txt", 0)
people: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[72] at textFile at <console>:27

scala> people.getNumPartitions
res47: Int = 1

案例3

scala> val people = sc.textFile("file:///home/pvikash/data/test.txt", 5)
people: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[58] at textFile at <console>:27

scala> people.getNumPartitions
res40: Int = 6

scala> val people = sc.textFile("file:///home/pvikash/data/test.txt", 6)
people: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[60] at textFile at <console>:27

scala> people.getNumPartitions
res41: Int = 7

scala> val people = sc.textFile("file:///home/pvikash/data/test.txt", 7)
people: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[62] at textFile at <console>:27

scala> people.getNumPartitions
res42: Int = 8

scala> val people = sc.textFile("file:///home/pvikash/data/test.txt", 8)
people: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[64] at textFile at <console>:27

scala> people.getNumPartitions
res43: Int = 9

scala> val people = sc.textFile("file:///home/pvikash/data/test.txt", 10)
people: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[68] at textFile at <console>:27

scala> people.getNumPartitions
res45: Int = 11

案例4

scala> val people = sc.textFile("file:///home/pvikash/data/test.txt", 9)
people: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[66] at textFile at <console>:27

scala> people.getNumPartitions
res44: Int = 11

scala> val people = sc.textFile("file:///home/pvikash/data/test.txt", 11)
people: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[70] at textFile at <console>:27

scala> people.getNumPartitions
res46: Int = 13

文件/home/pvikash/data/test.txt的内容如下：
这是一个测试文件。将用于rdd分区
基于以上案例，我有几个问题。
对于情况2，显式指定的分区数是0，但实际分区数是1（即使默认最小分区数是2），为什么实际分区数是1？
对于情况3，为什么在指定数量的分区上实际的分区数更改了+1？
对于情况4，为什么在指定数量的分区上实际的分区数更改了+2？
为什么spark在案例1、案例2、案例3和案例4中表现不同？
如果输入数据的大小很小（可以很容易地放入单个分区），那么为什么spark会创建空分区呢？
如有任何解释，将不胜感激。