So, let's sum up this chapter. Firstly, we used Spark transformations to defer computation to a later time, and then we learned which transformations should be avoided. Next, we looked at how to use reduceByKey and reduce to calculate our result globally and per specific key. After that, we performed actions that triggered computations then learned that every action means a call to the loading data. To alleviate that problem, we learned how to reduce the same rdd for different actions.

In the next chapter, we'll be looking at the immutable design of the Spark engine.