sbt Tutorial

We use sbt for building, testing, running and programming exercises. This tutorial explains all sbt commands that you will be needing here.

You should have already completed:

If not, then first complete the setup and preparation instructions.

The toolsSetups.md file explains how to install sbt.

You will be doing the following steps:

  1. Starting up sbt
    • Running the Scala Interpreter

1. Starting up sbt

In order to start sbt, go to dockerCompose/ directory from a terminal/console. Make sure the hadoop service is running (if you stopped the service then start it again using the container-id from docker ps and if you took it down then bring it back up as we did before).

Now, you can execute the commands to navigate to an a directory inside programs that was mounted into the container with read and write access, and call sbt to open the sbt command prompt sbt:ex1> as shown below.

:dockerCompose raazsainudiin$ docker-compose exec hadoop bash
root@4bf966fb974f:~# ls
data  hadoop-2.9.2  programs  spark-2.3.0-bin-hadoop2.7  start.sh
root@4bf966fb974f:~# cd programs/exercises/tutorialSbtScalaSpark/
root@4bf966fb974f:~/programs/exercises/tutorialSbtScalaSpark# ls
README.md  build.sbt  project  src  target
root@4bf966fb974f:~/programs/exercises/tutorialSbtScalaSpark# pwd
/root/programs/exercises/tutorialSbtScalaSpark

Now you should be inside /root/programs/exercises/tutorialSbtScalaSpark directory of the container/servicae.

Next type sbt as follows:

root@4bf966fb974f:~/programs/exercises/tutorialSbtScalaSpark# sbt
[info] Loading settings for project tutorialsbtscalaspark-build from plugins.sbt,buildSettings.sbt ...
[info] Loading project definition from /root/programs/exercises/tutorialSbtScalaSpark/project
[info] Loading settings for project tutorialsbtscalaspark from build.sbt ...
[info] Set current project to tutorialsbtscalaspark (in build file:/root/programs/exercises/tutorialSbtScalaSpark/)
[info] sbt server started at local:///root/.sbt/1.0/server/39ce2246899aa258b9c5/sock
sbt:tutorialsbtscalaspark> 

Now, you are in the sbt shell of project tutorialsbtscalaspark as indicated by sbt:tutorialsbtscalaspark> .

2. Running the Scala Interpreter

You can start the Scala interpreter inside sbt using the console task. The interpreter (also called REPL, for “read-eval-print loop”) is useful for trying out snippets of Scala code. Note that the interpreter can only be started if there are no compilation errors in your code.

sbt:tutorialsbtscalaspark> console
[info] Starting scala interpreter...
Welcome to Scala 2.11.12 (OpenJDK 64-Bit Server VM, Java 1.8.0_191).
Type in expressions for evaluation. Or try :help.

scala> 

Let’s just try some Scala code next.

scala> println("this is the Scala REPL or read-evaluate-print-loop")
this is the Scala REPL or read-evaluate-print-loop

scala> println("this is the ideal place to learn and play with Scala - Eclipse and other GUI IDEs have a similar REPL too.")
this is the ideal place to learn and play with Scala - Eclipse and other GUI IDEs have a similar REPL too.

scala> 1+1
res2: Int = 2

scala> List(1,2,3,4,5,6,7)
res3: List[Int] = List(1, 2, 3, 4, 5, 6, 7)

scala> val a = 1 to 7
a: scala.collection.immutable.Range.Inclusive = Range(1, 2, 3, 4, 5, 6, 7)

scala> 

The Scala REPL is a great place to try out code snippets.

Now exit the REPL by typing [ctrl+d] and get back to sbt shell of our project.

scala> 
[success] Total time: 175 s, completed Apr 8, 2019 6:17:38 AM
sbt:tutorialsbtscalaspark> 

3. Compiling your Code

The compile task will compile the source code of the example project which is located in the directory src/main/scala.

sbt:tutorialsbtscalaspark> compile
[success] Total time: 1 s, completed Apr 8, 2019 6:18:46 AM

If the source code contains errors, the error messages from the compiler will be displayed.

4. Testing your Code

The directory src/test/scala contains unit tests for the project. In order to run these tests in sbt, you can use the test command.

sbt:tutorialsbtscalaspark> test
[info] ListReduceSuite:
[info] - one plus one is two
[info] - one plus one is three? *** FAILED ***
[info]   org.scalatest.exceptions.TestFailedException was thrown. (ListReduceSuite.scala:57)
[info] - details why one plus one is not three *** FAILED ***
[info]   2 did not equal 3 (ListReduceSuite.scala:82)
[info] - intNotZero throws an exception if its argument is 0
[info] - sum of a few numbers
[info] - max of a few numbers
[info] - min of a few numbers *** FAILED ***
[info]   7 did not equal 0 (ListReduceSuite.scala:132)
[info] Run completed in 972 milliseconds.
[info] Total number of tests run: 7
[info] Suites: completed 1, aborted 0
[info] Tests: succeeded 4, failed 3, canceled 0, ignored 0, pending 0
[info] *** 3 TESTS FAILED ***
[error] Failed tests:
[error] 	org.lamastex.ex01.ListReduceSuite
[error] (Test / test) sbt.TestsFailedException: Tests unsuccessful
[error] Total time: 2 s, completed Apr 8, 2019 6:19:22 AM
sbt:tutorialsbtscalaspark> 

You should now fix these errors in:

  • `dockerCompose/programs/exercises/tutorialSbtScalaSpark/src/test/scala/example/ListReduceSuite.scala’
  • dockerCompose/programs/exercises/tutorialSbtScalaSpark/src/main/scala/example/ListReduce.scala

and run test again. One of the errors can only be fixed in the main function.

First let’s run the program.

5. Running your Code

If your project has an object with a main method (or an object extending the trait App), then you can run the code in sbt easily by typing run. In case sbt finds multiple main methods, it will ask you which one you want to execute.

sbt:tutorialsbtscalaspark> run
[info] Running org.lamastex.ex01.ListReduce 
please fix one character in min(xs) to get the right minimum
For the List = List(42, 24, 3, 6, 9, -3, 26, 9)
 its sum, max and min respectively are:
 116, 42, and 42
[success] Total time: 2 s, completed Apr 8, 2019 6:22:53 AM
sbt:tutorialsbtscalaspark> 

Fix the min function in src/main/scala/example/ListReduce.scala so the minimum is -3 instead of 42 when you run again.

6. Strongly Recommended for Engineers/Developers

Spend several hours reading details of docs by starting from here:

Note that you can have sbt installed on your system outside the dockerCompose folder (even using Eclipse or IntelliJ) and can play with spark on the local file system in standalone model.

But having the project directory inside dockerCompose/programs directory will allow for testing and developing code in an environemnt with the docker-composed services.