Slick is a modern database query and access library for Scala that allows working with stored data like Scala collections while controlling database access. It provides easy, concise, scalable, and safe database access. Slick supports many databases and can be set up by adding dependencies to a build file. Queries are processed by compiling them to SQL and lifting query types for translation. Queries support filtering, dropping rows, deletion, and creation.

1. SLICKSLICK
2.0.12.0.1

2. INTRODUCTION
●
Slick is Typesafe‘s modern database query and
access library for Scala.
●
It allows you to work with stored data almost as
if you were using Scala collections while at the
same time giving you full control over when a
database access happens and which data is
transferred.
●
You can also use SQL directly.
sql"select COF_NAME from COFFEES where PRICE < $limit".as[String].list

3. FEATURESFEATURES
●
Easy :-
Access stored data just like Scala collections.
Unified session management based on JDBC Connections.
Supports SQL if you need it.
Simple setup.
●
Concise:-
Scala syntax
Fetch results without pain

4. ●
Scales naturally :-
Stateless.
Explicit control of execution time and transferred data.
●
Safe :-
No SQL-injections.
Compile-time safety (types, names, no typos, etc.).
Type-safe support of stored procedures.
●
Composable :-
It‘s Scala code: abstract and re-use with ease
Slick requires scala 2.10.
Scala 2.9 use ScalaQuery, the predecessor of Slick

5. Supported Database
1.DB2 (via slick-extensions)
2.Derby/JavaDB
3.H2
4.HSQLDB/HyperSQL
5.Microsoft SQL Server
6.MySQL
7.PostgreSQL etc.

6. Set UpSet Up
●
First of all, you need to add Slick and the
embedded databases or drivers for external
databases to your project.
●
If you are using sbt, you do this in your main
build.sbt file.
libraryDependencies ++= List(
// use the right Slick version here:
"com.typesafe.slick" %% "slick" % "2.0.1",
"org.slf4j" % "slf4j-nop" % "1.6.4",
"postgresql" % "postgresql" % "9.1-901.jdbc4"
)
Add Dependency in Build.sbt

7. SLF4JSLF4J
●
Slick uses SLF4J for its own debug logging
so you also need to add an SLF4J
implementation.
●
Here we are using slf4j-nop to disable
logging.
●
You have to replace this with a real logging
framework like Logback if you want to see
log output.

8. ImportsImports
●
Since we are using Postgresql as our database
system, we need to import features from Slick’s
PostgresDriver.
●
A driver’s simple object contains all commonly
needed imports from the driver and other parts
of Slick such as session handling.
import scala.slick.driver.PostgresDriver.simple._

9. Lifted Embedding
●
The name Lifted Embedding refers to the fact
that you are not working with standard Scala
types (as in the direct embedding) but with
types that are lifted into a Rep type constructor.
●
This becomes clear when you compare the
types of a simple Scala collections example
with the types of similar code using the lifted
embedding

10. ●
Direct Embedding
●
Lifted Embedding
case class Coffee(name: String, price: Double)
val coffees: List[Coffee] = //...
val l = coffees.filter(_.price > 8.0).map(_.name)
class Coffees(tag: Tag) extends Table[(String, Double)](tag, "COFFEES") {
def name = column[String]("COF_NAME")
def price = column[Double]("PRICE")
def * = (name, price)
}
val coffees = TableQuery[Coffees]
val q = coffees.filter(_.price > 8.0).map(_.name)

11. FUNCTIONAL PROGRAMMING

12. Reason Behind Lifting
●
This lifting is necessary because the
lifted types allow us to generate a syntax
tree that captures the query
computations.
●
Getting plain Scala functions and values
would not give us enough information for
translating those computations to SQL.

13. QUERY PROCESSING

14. SLICK QUERY PROCESSING

15. QUERIES IN SLICK
●
Filtering Query:-
// compiles to SQL (simplified):
// select "COF_NAME", "SUP_ID", "PRICE", "SALES",
"TOTAL"
// from "COFFEES"
// where "SUP_ID" = 101
val q1 = coffees.filter(_.supID === 101)

16. ●
Drop Query :-
// compiles to SQL (simplified):
// select "COF_NAME", "SUP_ID", "PRICE",
"SALES", "TOTAL"
// from "COFFEES"
// limit 5 offset 10
val q2 = coffees.drop(10).take(5)
Coffee.ddl.dropStatements

17. ●
Deleting:-
●
Create:-
val affectedRowsCount = q.delete
users2.ddl.create

18. References
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References :-
●
http://slick.typesafe.com/talks/scalax2012/Sli
ck_ScalaExchange_2012.pdf
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http://slick.typesafe.com/doc/2.0.1/migration.htm
l
●
Database System Concepts(Abraham
Silberschatz ,Henry f. Korth, S. Sudarshan)

19. THANK YOU :)