[jira] [Created] (SPARK-25906) spark-shell cannot handle `-i` option correctly

["Dongjoon Hyun (JIRA)" <ji...@apache.org>]

Dongjoon Hyun created SPARK-25906:
-------------------------------------

             Summary: spark-shell cannot handle `-i` option correctly
                 Key: SPARK-25906
                 URL: https://issues.apache.org/jira/browse/SPARK-25906
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 2.4.0
            Reporter: Dongjoon Hyun


This is a regression on Spark 2.4.0 RC5.

*Spark 2.3.2*
{code}
$ cat test.scala
spark.version
case class Record(key: Int, value: String)
spark.sparkContext.parallelize((1 to 2).map(i => Record(i, s"val_$i"))).toDF.show

$ bin/spark-shell -i test.scala
18/10/31 23:22:43 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Spark context Web UI available at http://localhost:4040
Spark context available as 'sc' (master = local[*], app id = local-1541053368478).
Spark session available as 'spark'.
Loading test.scala...
res0: String = 2.3.2
defined class Record
18/10/31 23:22:56 WARN ObjectStore: Failed to get database global_temp, returning NoSuchObjectException
+---+-----+
|key|value|
+---+-----+
|  1|val_1|
|  2|val_2|
+---+-----+
{code}

*Spark 2.4.0 RC5*
{code}
$ bin/spark-shell -i test.scala
2018-10-31 23:23:14 WARN  NativeCodeLoader:62 - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Spark context Web UI available at http://localhost:4040
Spark context available as 'sc' (master = local[*], app id = local-1541053400312).
Spark session available as 'spark'.
test.scala:17: error: value toDF is not a member of org.apache.spark.rdd.RDD[Record]
Error occurred in an application involving default arguments.
       spark.sparkContext.parallelize((1 to 2).map(i => Record(i, s"val_$i"))).toDF.show
{code}



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