NOTE: This code now uses Spark 2.0.0 and beyond -- if you are still using an earlier version of Spark you may want to work off the before_spark2.0.0 branch.
This project contains snippets of Scala code for illustrating various Apache Spark concepts. It is intended to help you get started with learning Apache Spark (as a Scala programmer) by providing a super easy on-ramp that doesn't involve Unix, cluster configuration, building from sources or installing Hadoop. Many of these activities will be necessary later in your learning experience, after you've used these examples to achieve basic familiarity.
It is intended to accompany a number of posts on the blog A River of Bytes.
The project was created with IntelliJ Idea 14 Community Edition, JDK 1.7, Scala 2.11.2 and Spark 2.0.0 on Ubuntu Linux.
Versions of these examples for other configurations (older versions of Scala and Spark) can be found in various branches.
These are much less developed than the Scala examples below. Note that they use Java 7 and Spark 2.0.0 only -- if you go back to the before_spark2.0.0 branch you won't find any Java examples at all. I'm adding these partly out of curiosity (because I like Java almost as much as Scala) and partly because of a realization that lots of Spark programmers use Java. There are a number of things it's important to realize I'm not promising to do:
- Rush to catch up with the Scala examples
- Keep the two sets of examples perfectly matched
- Keep working on the Java examples
- Add Python and R as well (this is really unlikely)
| Package | What's Illustrated |
|---|---|
| rdd | The JavaRDD: core Spark data structure -- see the local README.md in that directory for details. |
| dataset | A range of Dataset examples (queryable collection that is statically typed) -- see the local README.md in that directory for details. |
| dataframe | A range of DataFrame/Dataset examples (queryable collection that is dynamically typed) -- see the local README.md in that directory for details. |
The examples can be found under src/main/scala. The best way to use them is to start by reading the code and its comments. Then, since each file contains an object definition with a main method, run it and consider the output. Relevant blog posts and StackOverflow answers are listed in the various package README.md files.
| Package or File | What's Illustrated |
|---|---|
| Ex1_SimpleRDD | How to execute your first, very simple, Spark Job. See also An easy way to start learning Spark. |
| Ex2_Computations | How RDDs work in more complex computations. See also Spark computations. |
| Ex3_CombiningRDDs | Operations on multiple RDDs |
| Ex4_MoreOperationsOnRDDs | More complex operations on individual RDDs |
| Ex5_Partitions | Explicit control of partitioning for performance and scalability. |
| Ex6_Accumulators | How to use Spark accumulators to efficiently gather the results of distributed computations. |
| hiveql | Using HiveQL features in a HiveContext. See the local README.md in that directory for details. |
| special | Special/adbanced RDD examples -- see the local README.md in that directory for details. |
| dataset | A range of Dataset examples (queryable collection that is statically typed) -- see the local README.md in that directory for details. |
| dataframe | A range of DataFrame examples (queryable collection that is dynamically -- and weakly -- typed)-- see the local README.md in that directory for details. |
| sql | A range of SQL examples -- see the local README.md in that directory for details. |
| streaming | Streaming examples -- see the local README.md in that directory for details. |
| graphx | A range of GraphX examples -- see the local README.md in that directory for details. |
Additional Scala code is "work in progress".