Learn about types of collections and when to use them.
- [Instructor] In data science,…we often have to work with collections of data…such as arrays of numbers or sets of labels.…Scala provides a comprehensive set of collection types…that include sequences, sets, and maps.…Each of these have subsets.…Sequences which are known as seqs for short…include things like streams and lists and queues.…Sets can be sorted, tree based, or based on a hash.…Maps can have HashMaps, SortedMaps, ListMaps.…
We won't go into the details of each of these here,…but we will describe the basic characteristics of each type…and discuss when to use each kind of collection.…It's worth nothing that collections…are either mutable or immutable.…Mutable collections can be changed.…For example, by adding or removing an item.…Immutable collections do not change once they are created.…Scala simulates changes to an immutable collection…by making a new version of the collection with the change.…
For example, deleting an element of an immutable set…will result in a new set identical to the original…
Dan also focuses on using Scala with Spark, a distributed processing platform. He first describes how to work with Resilient Distributed Datasets (RDDs)—a fundamental Spark data structure—and then explains how to use Scala with Spark DataFrames, a new class of data structure specially designed for analytic processing. He wraps up the course by providing a summary of advantages of using Scala for data science.
- The advantages of Scala for data science
- Scala data types
- Scala arrays, vectors, and ranges
- Parallel processing in Scala
- Mapping functions over parallel collections
- When and when not to use parallel collections
- Using SQL in Scala
- Scala and Spark RDDs
- Scala and Spark DataFrames
- Creating DataFrames
Skill Level Intermediate
Java for Data Scientists Essential Trainingwith Charles Kelly2h 43m Intermediate
1. Introduction to Scala
2. Parallel Processing in Scala
3. Using SQL in Scala
4. Scala and Spark RDDs
5. Scala and Spark DataFrames
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