Understand how to create and execute SQL queries in Scala using JDBC.
- [Narrator] So, let's continue our discussion…about how we select using strings.…Now, recall we had to find a value called resultSet,…and resultSet was set to the statement object,…which executed a query,…and the query we had executed was "Select * from emps,"…and then this return to cursor,…so we wanted to move that along to the…next item in the list, and then we're able to look up…individual columns on this particular row.…
So, for example, we could look…up the resultSet, get string,…and I'm just going to show all of the options…with getS, and we'll look up department.…And this first person works in the Computer Department.…Let's change that, let's just up arrow…and change department to last name…so we can see who we're talking about.…Ah, okay, that's right, it's Kelley,…and let's just check the start date.…
Okay, so we figured out that the…person whose last name is Kelley,…we know what department they work in…and what their start date is, so that's great.…It's a little inconvenient to work…with just one column at a time,…
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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