Github user joan38 commented on a diff in the pull request:

    https://github.com/apache/spark/pull/12157#discussion_r58728708
  
    --- Diff: core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala ---
    @@ -53,14 +53,22 @@ import org.apache.spark.util.{NextIterator, 
SerializableConfiguration, ShutdownH
     /**
      * A Spark split class that wraps around a Hadoop InputSplit.
      */
    -private[spark] class HadoopPartition(rddId: Int, idx: Int, s: InputSplit)
    +private[spark] class HadoopPartition(rddId: Int, override val index: Int, 
s: InputSplit)
       extends Partition {
     
       val inputSplit = new SerializableWritable[InputSplit](s)
     
    -  override def hashCode(): Int = 41 * (41 + rddId) + idx
    +  override def hashCode(): Int = 41 * (41 + rddId) + index
     
    -  override val index: Int = idx
    +  def canEqual(other: Any): Boolean = other.isInstanceOf[HadoopPartition]
    +
    +  override def equals(other: Any): Boolean = other match {
    +    case that: HadoopPartition =>
    +      super.equals(that) &&
    +        (that canEqual this) &&
    +        index == that.index
    --- End diff --
    
    Right. So I feel like there is many cases where we might have this 
ambiguity and this might be out of the scope for this Jira/PR which is to 
enable the style check.
    
    So would it be ok if we just do `override def equals(other: Any): Boolean = 
super.equals(other)` where ever there is an ambiguity in order to enable the 
stylecheck and avoid further implementation of orphan hashCode/equals?


---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastruct...@apache.org or file a JIRA ticket
with INFRA.
---

---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org

Reply via email to