Not able to display parquet file output using Spark - scala

Question

Installed Spark on local (on Linux file system with no HADOOP), Everything seems to be working fine except reading parquet file and displaying results on console. After reading parquet file, when I do dataframe.show() it just this Indefinnitely:
[Stage 4:> (0 + 1) / 1]
Not sure if I need to configure anything specific on local installation?
Can some one please help me on this?
Installed spark on local(on Linux) and followed below steps using spark/scala:
scala> val columns = Seq("firstname","middlename","lastname","dob","gender","salary")
val columns: Seq[String] = List(firstname, middlename, lastname, dob, gender, salary)
scala> val data = Seq(("James ","x","Smith","36636","M",3000),
| ("Michael ","Rose","cc","40288","M",4000),
| ("Robert ","c","Williams","42114","M",4000),
| ("Maria ","Anne","Jones","39192","F",4000),
| ("Jen","Mary","Brown","34552","F",-1)
| )
|
val data: Seq[(String, String, String, String, String, Int)] = List(("James ",x,Smith,36636,M,3000), ("Michael ",Rose,cc,40288,M,4000), ("Robert ",c,Williams,42114,M,4000), ("Maria ",Anne,Jones,39192,F,4000), (Jen,Mary,Brown,34552,F,-1))
scala> val df1 = data.toDF(columns:_*)
val df1: org.apache.spark.sql.DataFrame = [firstname: string, middlename: string ... 4 more fields]
scala> df1.show()
+---------+----------+--------+-----+------+------+
|firstname|middlename|lastname| dob|gender|salary|
+---------+----------+--------+-----+------+------+
| James | x| Smith|36636| M| 3000|
| Michael | Rose| cc|40288| M| 4000|
| Robert | c|Williams|42114| M| 4000|
| Maria | Anne| Jones|39192| F| 4000|
| Jen| Mary| Brown|34552| F| -1|
+---------+----------+--------+-----+------+------+
scala> df1.printSchema()
root
|-- firstname: string (nullable = true)
|-- middlename: string (nullable = true)
|-- lastname: string (nullable = true)
|-- dob: string (nullable = true)
|-- gender: string (nullable = true)
|-- salary: integer (nullable = false)
scala> df1.write.partitionBy("gender","salary").parquet("/home/usalla/spark_test/emppq.parquet")
scala> val parqDF2 = spark.read.parquet("/home/usalla/spark_test/emppq.parquet")
val parqDF2: org.apache.spark.sql.DataFrame = [firstname: string, middlename: string ... 4 more fields]
scala> parqDF2.createOrReplaceTempView("ParquetTable2")
scala> val df3 = spark.sql("select * from ParquetTable2 where gender='M' and salary >= 4000")
val df3: org.apache.spark.sql.DataFrame = [firstname: string, middlename: string ... 4 more fields]
scala> df3.explain
warning: 1 deprecation (since 2.13.3); for details, enable `:setting -deprecation` or `:replay -deprecation`
== Physical Plan ==
*(1) ColumnarToRow
+- FileScan parquet [firstname#144,middlename#145,lastname#146,dob#147,gender#148,salary#149] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex(1 paths)[file:/home/usalla/spark_test/emppq.parquet], PartitionFilters: [isnotnull(gender#148), isnotnull(salary#149), (gender#148 = M), (salary#149 >= 4000)], PushedFilters: [], ReadSchema: struct<firstname:string,middlename:string,lastname:string,dob:string>
scala> df3.printSchema()
root
|-- firstname: string (nullable = true)
|-- middlename: string (nullable = true)
|-- lastname: string (nullable = true)
|-- dob: string (nullable = true)
|-- gender: string (nullable = true)
|-- salary: integer (nullable = true)
scala> df3.show()
[Stage 4:> (0 + 1) / 1]
^Z