Understand how to use prepared statements for more efficient query executions.
- [Instructor] Now let's take a look…at working with prepared statements.…A prepared statement allows us…to execute a query repeatedly…without forcing the database to parse…and build a query execution plan…each time we execute that statement.…So prepared statements are especially useful…when we're using O Statement repeatedly.…So the first thing I want to do is to find a query string.…And I'll just type in val, query, STR.…And I'll say that this statement is select…star, from…company,…regions…where…region ID…is greater than some number.…
And I want to put in, essentially a parameter here.…So I'll be able to change it.…So we'll use a question mark for that.…Now, what I will do is actually to create,…using that query string, a prepared statement.…And I'll just use PS for the name of the value for that.…And to do that we specify our connection,…and use the prepare statement method.…And we pass in our query string.…Okay so now we have a prepared statement.…
And that means the database has parsed the string,…built a query execution plan,…
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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