Usage of Junit in Spark shell - scala

Question

I am struggling to make junit work in my Spark shell.
When trying to import Assert from junit I geet the following error message:
scala> import org.junit.Assert._
<console>:23: error: object junit is not a member of package org
import org.junit.Assert._
Any way of having this fixed? Any idea of how can I download org.junit from the scala shell?
EDIT:
After following the recomendation from zsxwing, I have used spark-shell --packages junit:junit:4.12 with the following output:
C:\spark>spark-shell --packages junit:junit:4.12
Ivy Default Cache set to: C:\xxx\.ivy2\cache
The jars for the packages stored in: C:\xxxx\.ivy2\jars
:: loading settings :: url = jar:file:/C:/spark/jars/ivy-2.4.0.jar!/org/apache/i
vy/core/settings/ivysettings.xml
junit#junit added as a dependency
:: resolving dependencies :: org.apache.spark#spark-submit-parent;1.0
confs: [default]
found junit#junit;4.12 in central
found org.hamcrest#hamcrest-core;1.3 in central
:: resolution report :: resolve 365ms :: artifacts dl 7ms
:: modules in use:
junit#junit;4.12 from central in [default]
org.hamcrest#hamcrest-core;1.3 from central in [default]
---------------------------------------------------------------------
| | modules || artifacts |
| conf | number| search|dwnlded|evicted|| number|dwnlded|
---------------------------------------------------------------------
| default | 2 | 0 | 0 | 0 || 2 | 0 |
---------------------------------------------------------------------
:: retrieving :: org.apache.spark#spark-submit-parent
confs: [default]
0 artifacts copied, 2 already retrieved (0kB/20ms)
Setting default log level to "WARN".
Spark context Web UI available at http://xxxxx
Spark context available as 'sc' (master = local[*], app id = local-xxx
).
Spark session available as 'spark'.
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.0.0
/_/
However still facing the same issue when trying to import org.junit.Assert._

Answer 1

JUnit is a test dependency and it's not included in the Spark shell's classpath. You can use the --packages parameter add any dependency such as,
bin/spark-shell --packages junit:junit:4.12