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Scala for Data Science

You're reading from  Scala for Data Science

Product type Book
Published in Jan 2016
Publisher
ISBN-13 9781785281372
Pages 416 pages
Edition 1st Edition
Languages
Author (1):
Pascal Bugnion Pascal Bugnion
Profile icon Pascal Bugnion

Table of Contents (22) Chapters

Scala for Data Science
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Scala and Data Science 2. Manipulating Data with Breeze 3. Plotting with breeze-viz 4. Parallel Collections and Futures 5. Scala and SQL through JDBC 6. Slick – A Functional Interface for SQL 7. Web APIs 8. Scala and MongoDB 9. Concurrency with Akka 10. Distributed Batch Processing with Spark 11. Spark SQL and DataFrames 12. Distributed Machine Learning with MLlib 13. Web APIs with Play 14. Visualization with D3 and the Play Framework Pattern Matching and Extractors Index

Safer JDBC connections with the loan pattern


We have already seen how to connect to a JDBC database and send statements to the database for execution. This technique, however, is somewhat error prone: you have to remember to close statements; otherwise, you will quickly run out of memory. In more traditional imperative style, we write the following try-finally block around every connection:

// WARNING: poor Scala code
val connection = DriverManager.getConnection(url, user, password)
try {
  // do something with connection
}
finally {
  connection.close()
}

Scala, with first-class functions, provides us with an alternative: the loan pattern. We write a function that is responsible for opening the connection, loaning it to the client code to do something interesting with it, and then closing it when the client code is done. Thus, the client code is not responsible for closing the connection any more.

Let's create a new SqlUtils object with a usingConnection method that leverages the loan pattern...

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