Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/16739
Let me rewrite the test cases in Scala.
```Scala
val df = spark.range(0, 10000, 1, 5)
assert(df.rdd.getNumPartitions == 5)
assert(df.coalesce(3).rdd.getNumPartitions == 3)
assert(df.coalesce(6).rdd.getNumPartitions == 5)
val df1 = df.coalesce(3)
assert(df1.rdd.getNumPartitions == 3)
assert(df1.coalesce(6).rdd.getNumPartitions == 5)
assert(df1.coalesce(4).rdd.getNumPartitions == 4)
assert(df1.coalesce(2).rdd.getNumPartitions == 2)
val df2 = df.repartition(10)
assert(df2.rdd.getNumPartitions == 10)
assert(df2.coalesce(13).rdd.getNumPartitions == 5)
assert(df2.coalesce(7).rdd.getNumPartitions == 5)
assert(df2.coalesce(3).rdd.getNumPartitions == 3)
```
The question is why the second one is `5` instead of `10`. If we do the
explain, we got the following plan
```
== Parsed Logical Plan ==
Repartition 13, false
+- Repartition 10, true
+- Range (0, 10000, step=1, splits=Some(5))
== Analyzed Logical Plan ==
id: bigint
Repartition 13, false
+- Repartition 10, true
+- Range (0, 10000, step=1, splits=Some(5))
== Optimized Logical Plan ==
Repartition 13, false
+- Range (0, 10000, step=1, splits=Some(5))
== Physical Plan ==
Coalesce 13
+- *Range (0, 10000, step=1, splits=Some(5))
```
Ok... `Repartition 10, true` is removed by our Optimizer rule
`CollapseRepartition`. It is a bug, I think. Your question is valid. Let me fix
it.
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