Introduction (101)

Click

Repository

https://github.com/pdolega/slick-101

Preso

http://slides.com/pdolega/slick-101

pdole.ga

Who am I?

twitter: @pdolega

github: github.com/pdolega

Software Engineer /

Entrepreneur

What is Slick?

Not an ORM

ORM problems

N+1 problem (lazy / eager fetching)

Session context scope

Execution under the cover (cache)

O-R impedance mismatch

False promise

Leaky abstraction

FRM

Embrace database model through a functional paradigm.

If you come from ORM world:

http://slick.lightbend.com/doc/3.2.0-M1/orm-to-slick.html

Reactive (™?)

...wait a minute, JDBC is blocking anyway

Everything is async...

db_pool_connections =

(core_count * 2) + effective_spindle_count

source: postgres docs

Brilliant presentation by @StefanZeiger: Reactive Slick for Database Programming

Server handling 10 000 client connections may need not more than 10 connection

It's still viable

Async drivers?

postgres-async-driver ?

The point being...

Use less threads / let CPU be busy

Threads are expensive

Yet traditionally they are wasted on IO

Don't block general threads / use designated thread pool

Description

vs

execution

transactions.stream()
    .filter(t -> t.getType() == Transaction.GROCERY)
    .sorted(comparing(Transaction::getValue).reversed())
    .map(Transaction::getId) // up to this line - description
    .collect(toList()) // execution

Java 8 streams

db.run(                      // execution
    (StudentCourseSegmentTable              // description
          join CourseTable on (_.courseId === _.id)
          join StudentTable on (_._1.studentId === _.id)).result
)

Scala / Slick

Last but not least

Type-Safe







db.run(                      // execution
    (StudentCourseSegmentTable              // description
          join CourseTable on (_.courseId === _.id)
          join StudentTable on (_._1.studentId === _.id))
    .result
)

If you were to remember only one thing

Monadic Trio

DBIO

Query

description of a DB query

description of 1...N DB operations

Future

gimme a break...

The other thing worth to remember

It's (mostly) all about DBIO composition

And...

The best approach to write queries using Slick’s type-safe API is thinking in terms of Scala collections.

Click

Overview

Tables
Actions
Queries
Composition / Transactions

Code samples:

SmokeSpec

    




    "correctly open db" in {
      val db = Database.forConfig("memoryDb")
      val results = db.run(sql"SELECT 2 + 3".as[(Int)])

      // option 1 - bad
      blockingWait(results).head shouldBe 5

      // option 2 - better
      results.map { r =>
        r.head shouldBe (5)
      }.futureValue    // this is only for unit tests to work
    }



    memoryDb = {
      connectionPool = disabled
      url = "jdbc:h2:mem:slick-101"
      driver = "org.h2.Driver"
      user = ""
      password = ""
      keepAliveConnection = true
    }

Config

Tables

Code samples 2:

TableSpec


  // in-application respresentation of table's tuple
  case class University(name: String,
                        id: Long = -1L)

  // definition of table
  class UniversityTable(tag: Tag) extends Table[University](
    tag, "university") {
    
    def name = column[String]("name")
    def id = column[Long]("id", O.PrimaryKey, O.AutoInc)

    // default projection
    def * = (name, id) <> (University.tupled, 
                           University.unapply)
  }

  // 'table' object used for interacting with in app
  lazy val UniversityTable = TableQuery[UniversityTable]

    "be insertable and retrievable - poor version" in {
      // read everything from a table
      blockingWait(db.run(UniversityTable.result)) should 
                    have size 0

      // insert into table
      blockingWait(db.run(
        UniversityTable ++= Seq(
          University("Hogwart"),
          University("Scala University")
        )
      ))

      // read again
      val results = blockingWait(
            db.run(UniversityTable.result)
      )

      results.map(_.name) should contain theSameElementsAs
        Seq("Hogwart", "Scala University")
    }

Poor version

Actions

Monadic Trio






memDb.run(
    UniversityTable                            
    .filter(_.name === "Hogwarth") // Query
    .result               // DBIOAction (DBIO)
)    // Future

      db.run(    // first all within this block is constructed
                 // and the resulting DBIO is passed to db.run
                 // to be executed
          for {
            emptyResults <- UniversityTable.result
            _ <- insertUnis
            nonEmptyResults <- UniversityTable.result
          } yield {
            emptyResults should have size 0
            nonEmptyResults.map(_.name) should 
                    contain theSameElementsAs
              Seq("Hogwart", "Scala University")
          }
      )
...
      def insertUnis = UniversityTable ++= Seq(
          University("Hogwart"),
          University("Scala University")
      )

Better version

DBIOAction / DBIO

DBIOAction[R, S, E]

R - type of result
S - streaming / not streaming
E - what kind of effect

DBIO[R] =

DBIOAction[R, NoStream, Effect.All]

R - type of result

  def executeReadOnly[R, S <: dbio.NoStream](
    readOnlyOper: DBIOAction[R, S, Effect.Read] // param decl
  ): Future[Unit] = { // result type
    db.run(readOnlyOper).map { results =>
      log.info(s"Results are: $results")
    }
  }

// this works
executeReadOnly(UniversityTable.result)

// this won't even compile
executeReadOnly(UniversityTable += University("Nice try!"))

// DBIOAction[Seq[University], Stream, Effect.Read]
db.run(
    UniversityTable.result
)
...

// DBIOAction[Option[Int], NoStream, Effect.Write]
db.run(
    UniversityTable += University("Nice try!")
)
...

// DBIOAction[Option[Int], NoStream, 
// Effect.Write with Effect.Transactional]
db.run(
    (UniversityTable += University("Nice try!"))
    .transactionally
)
...
// DBIOAction[Unit, NoStream, Effect.Schema]
db.run(
    UniversityTable.schema.create
)

Queries

Query

Query[M, U, C]

M - mixed type

U - unpacked type

C - collection type


UniversityTable                            
    .filter(_.name === "Hogwarth")

What are unpacked (U), mixed (M) and collection (C) types?


UniversityTable                            
    .filter(_.name === "Hogwarth")    
    // _ above is UniverityTable (M)


  // unpacked type
  case class University(name: String,
                        id: Long = -1L)

  // mixed type
  class UniversityTable(tag: Tag) extends Table[University](
    tag, "university") {
    
    def name = column[String]("name")
    def id = column[Long]("id", O.PrimaryKey, O.AutoInc)

    // default projection
    def * = (name, id) <> (University.tupled, 
                           University.unapply)
  }








db.run(    // Future[Seq[University]]

   UniversityTable.filter(uni => // Query[UniversityTable,
                                 // University, Seq]
       uni.name === "Hogwarth"
   )
   .result    // DBIO[Seq[University]]

)

Code samples:

QueriesSpec

      // here we get Future[Seq[Student]]
      db.run(CourseModel.StudentTable.result) 
        // here I map over Future
        // within map we have results: Seq[Student]
        .map { results => 
            // we map it to (String, String)
            results.map(student => (student.name, 
                                    student.surname))    
      }
      // we end up with Future[Seq[(String, String)]]

select "NAME", "MIDDLE_NAME", "SURNAME", "NATIONALITY", "ID" 
from "STUDENT"

Actual query


      db.run(
        CourseModel.StudentTable.map { student =>
            // here I map over query!
            (student.name, student.surname)
        }
        .result
      )
      // we end up with Future[Seq[(String, String)]]

select "NAME" "SURNAME"
from "STUDENT"

Actual query

Do you speak it?!

Queries

    select  "NAME", 
            "MIDDLE_NAME", 
            "SURNAME", 
            "NATIONALITY", 
            "ID" 
    
    from    "STUDENT"




    StudentTable

// or

    for {student <- StudentTable }
        yield student





execQuery(
    StudentTable
)


def execQuery[E, U, C[_]](q: Query[E, U, C]): Future[C[U]] = 
    db.run(    // convert into Future
        q.result    // convert into DBIO
    )

      


    StudentTable
        .map(_.name)

    

    select "NAME" 
    
    from "STUDENT"




    StudentTable
        .map(s => 
            (s.name, s.middleName.ifNull("*no-middlename*"))
        )
        .sortBy(_.name)

    select  "NAME", 
            ifnull("MIDDLE_NAME",'*no-middlename*') 
    
    from "STUDENT" 
    order by "NAME"

Wrong!




    StudentTable
        .map(s => 
            (s.name, s.middleName.ifNull("*no-middlename*"))
        )
        .sortBy(_._1)

    select  "NAME", 
            ifnull("MIDDLE_NAME",'*no-middlename*') 
    
    from "STUDENT" 
    order by "NAME"

OK!




    StudentTable
        .sortBy(_.name)
        .map(s => 
            (s.name, s.middleName.ifNull("*no-middlename*"))
        )

    select  "NAME", 
            ifnull("MIDDLE_NAME",'*no-middlename*') 
    
    from "STUDENT" 
    order by "NAME"


      StudentTable
        .map(nat => nat.nationality ++ "  ")
        .map(_.toUpperCase)
        .map(_.trim)
        .map((_, currentTime, pi))
        .map(row => 
            row._1 ++ " " ++ 
            row._2.asColumnOf[String] ++ " " ++ 
            row._3.asColumnOf[String]
        )

    select  (((ltrim(rtrim(ucase("NATIONALITY"||'  ')))||' ') 
            || cast(curtime() as VARCHAR))||' ') 
            || cast(pi() as VARCHAR) 
    from "STUDENT"



    StudentTable
        .filter(_.name === "Tom")

    // or

    for {
        student <- StudentTable if student.name === "Tom"
    } yield student


    select  "NAME", "MIDDLE_NAME", "SURNAME", ... 

    from    "STUDENT" 

    where   "NAME" = 'Tom'

    StudentTable
        .filterNot(student => 
            student.name === "Tom" && 
            student.surname.startsWith("Smi")
    )
    // or
    for {
        student <- StudentTable if !(
                student.name === "Tom" && 
                student.surname.startsWith("Smi"))
    } yield student


    select "NAME", 
           "MIDDLE_NAME", 
           "SURNAME", 
           "NATIONALITY", 
           "ID" 

    from "STUDENT" 
    
    where not (("NAME" = 'Tom') and 
               ("SURNAME" like 'Smi%' escape '^'))



    StudentTable
        .filter(student => student.middleName.nonEmpty)
        .sortBy(s => (s.name.desc, s.middleName.asc))
        .distinct


    select distinct "NAME", ... 

    from "STUDENT" 

    where "MIDDLE_NAME" is not null 

    order by "NAME" desc, "MIDDLE_NAME"



      StudentTable
        .map(s => (s.name, s.surname))
        .drop(2)
        .take(3)


    select ... 

    from "STUDENT" 

    limit 3 offset 2



      StudentTable
        .map(s => (s.name, s.surname))
        .take(3)
        .drop(2)


    select ... 

    from "STUDENT" 

    limit 1 offset 3


    StudentTable
        .filter(_.surname =!= "Test")
        .groupBy(_.surname)
        .map { case (surname, group) =>
          (surname, group.map(_.name).countDistinct)
        }
        .filter(row => row._2 > 5)


    select "SURNAME", count(distinct "NAME") 

    from "STUDENT" 

    where not ("SURNAME" = 'Test') 

    group by "SURNAME" 

    having count(distinct "NAME") > 5

Joins

Monadic

applicative


  // student course segment
  case class StudentCourseSegment(studentId: Id[Student],
                                  courseId: Id[Course],
                                  semesterId: Id[Semester],
                                  id: Id[StudentCourseSegment] = Id.none)

  class StudentCourseSegmentTable(tag: Tag) extends 
    Table[StudentCourseSegment](tag, "STUDENT_COURSE_SEGMENT") {
    def studentId = column[Id[Student]]("STUDENT_ID")
    def courseId = column[Id[Course]]("COURSE_ID")
    def semesterId = column[Id[Semester]]("SEMESTER_ID")
    def id = column[Id[StudentCourseSegment]]("ID", O.PrimaryKey, O.AutoInc)

    def * = (studentId, courseId, semesterId, id) <> (StudentCourseSegment.tupled, 
                                                      StudentCourseSegment.unapply)

    // foreign keys
    def student = foreignKey("fk_segment_student", studentId, StudentTable)(_.id)
    def course = foreignKey("fk_segment_course", courseId, CourseTable)(_.id)
    def semester = foreignKey("fk_segment_semester", semesterId, SemesterTable)(_.id)
  }

  lazy val StudentCourseSegmentTable = TableQuery[StudentCourseSegmentTable]




def student = 
    foreignKey("fk_segment_student", 
        studentId, StudentTable)(_.id)
def course = 
    foreignKey("fk_segment_course", 
        courseId, CourseTable)(_.id)
def semester = 
    foreignKey("fk_segment_semester", 
        semesterId, SemesterTable)(_.id)





... 
    // in my table mapping
    def id = column[Id[StudentCourseSegment]]("ID", 
        O.PrimaryKey, O.AutoInc)
...
    // in my case class
    case class StudentCourseSegment(studentId: Id[Student],
                        courseId: Id[Course],
                        semesterId: Id[Semester],
                        id: Id[StudentCourseSegment] = Id.none)
...

db.run((
    for {
      segment <- StudentCourseSegmentTable
      course <- segment.course // foreign key
      student <- segment.student // foreign key
    } yield (course, student)
)

db.run(
        StudentCourseSegmentTable
          join CourseTable on (_.courseId === _.id)
          join StudentTable on (_._1.studentId === _.id)
        ).map {
            case ((segment, course), student) => 
                (course, student)
        }
)

Monadic

Applicative





    StudentCourseSegmentTable
          join CourseTable on (_.studentId === _.id)    // WTF
          join StudentTable on (_._1.courseId === _.id)

Type-safety again

Wrong!

More complicated join

Applicative vs monadic

StudentCourseSegmentTable
    .join(StudentTable)
        .on { case (segment, student) => 
            student.id === segment.studentId }
    .join(CourseTable)
        .on { case ((segment, _), course) => 
            course.id === segment.courseId }
    .join(SemesterTable)
        .on { case (((segment, _), _), semester) => 
            semester.id === segment.semesterId }
    .filter { case (((_, student), _), _) =>
        student.name === "Tim"
    }

    select x2."NAME",
           ...
    from    "STUDENT_COURSE_SEGMENT" x2, 
            "STUDENT" x3, 
            "COURSE" x4, 
            "SEMESTER" x5 

    where   (x3."NAME" = 'Tim') and 
            (((x3."ID" = x2."STUDENT_ID") and 
            (x4."ID" = x2."COURSE_ID")) and 
            (x5."ID" = x2."SEMESTER_ID"))

    for {
      segment <- StudentCourseSegmentTable
      student <- segment.student if student.name === "Tim"
      course <- segment.course
      semester <- segment.semester
    } yield (segment, student, course, semester)

    select x2."NAME",
           ...
    from    "STUDENT_COURSE_SEGMENT" x2, 
            "STUDENT" x3, 
            "COURSE" x4, 
            "SEMESTER" x5 

    where   (x3."NAME" = 'Tim') and 
            (((x3."ID" = x2."STUDENT_ID") and 
            (x4."ID" = x2."COURSE_ID")) and 
            (x5."ID" = x2."SEMESTER_ID"))

Sometimes one form is more elegant than the other

Outer joins

// document
case class Document(studentId: Option[Id[Student]],
                    name: String,
                    uuid: String,
                    id: Id[Document] = Id.none)

class DocumentTable(tag: Tag) extends Table[Document]
    (tag, "DOCUMENT") {
    def studentId = column[Option[Id[Student]]]("STUDENT_ID")
    def name = column[String]("NAME")
    def uuid = column[String]("UUID")
    def id = column[Id[Document]]("ID", 
                        O.PrimaryKey, O.AutoInc)
    
    def * = (studentId, name, uuid, id) <> 
            (Document.tupled, Document.unapply)

    def student = foreignKey("fk_document_student", 
        studentId, StudentTable)(_.id.?)
}

lazy val DocumentTable = TableQuery[DocumentTable]




case class Document(studentId: Option[Id[Student]],
                    name: String,
                    uuid: String,
                    id: Id[Document] = Id.none)
//...
//...

class DocumentTable(tag: Tag) extends Table[Document]
    (tag, "DOCUMENT") {
    def studentId = column[Option[Id[Student]]]("STUDENT_ID")
//...
//...
    def student = foreignKey("fk_document_student", 
        studentId, StudentTable)(_.id.?)
}




    DocumentTable
          .joinLeft(StudentTable).on(_.studentId === _.id)

    select x2."STUDENT_ID", ..., x3."ID", ... 

    from "DOCUMENT" x2 

    left outer join "STUDENT" x3 
        on x2."STUDENT_ID" = x3."ID"



        DocumentTable
          .joinLeft(StudentTable).on(_.studentId === _.id)
          .filter { case(doc, student) => 
                student.map(_.name) === "Tom" 
        }

    select x2."STUDENT_ID", ..., x3."ID", ... 

    from "DOCUMENT" x2 

    left outer join "STUDENT" x3 
        on x2."STUDENT_ID" = x3."ID"

     where x3."NAME" = 'Tom'

Slick 3.2 ?

https://github.com/slick/slick/issues/179

No nice monadic form for outer joins

Composition / Transactions

DBIO.transactionally

Click

db.run(
    (UniversityTable ++= Seq(
      University("Hogwart"),
      University("Scala University")
    )).transactionally
)

Transactions - example

OK, but how do we combine DB operations?

DBIO is a monad

db.run(
    (for {
        dbio1 <- insertUnis
        dbio2 <- ...
        dbio3 <- ...
        ...
        dbioN <- ...
    } yield {
        ...
    }).transactionally
)

def insertUnis: DBIO[Option[Int]] =
    UniversityTable ++= Seq(
      University("Hogwart"),
      University("Scala University")
    )

map / flatMap

seq

    val combined: DBIO[Unit] = DBIO.seq(
        produceDbOper1,    // DBIO[T]
        produceDbOper2,    // DBIO[R]
        produceDbOper3     // DBIO[M]
    )

sequence

    val combined: DBIO[Seq[T]] = DBIO.sequence(
        Seq(
            produceDbOper1, // DBIO[T]
            produceDbOper2, // DBIO[T]
            produceDbOper3  // DBIO[T]
        )
    )

  db.run( // Future[Seq[Seq[Course]]]
    for {
      students <- StudentTable.result
      courses <- DBIO.sequence(students.map(fetchMoreData))
    } yield {
      courses
    }
  )


...


  private def fetchMoreData(student: Student): 
    DBIO[Seq[Course]] = {
    (for {
      segment <- StudentCourseSegmentTable 
                if segment.studentId === student.id
      course <- segment.course
    } yield {
      course
    }).result
  }

unit

db.run(
    (for {
        student <- StudentTable
                    .filter(_.name === "Tim").result // DBIO
        smthNotDb <- calculateSomethingNotDb(student) // duh?!
        _ <- updateBasedOnCalculation(smthNotDb) // DBIO
    } yield (...)).transcationally
)

Wrong!

DBIO.successful

db.run(
    (for {
        student <- StudentTable
                    .filter(_.name === "Tim").result // DBIO
        smthNotDb <- DBIO.successful(
            calculateSomething(student)
        ) // Yeah!
        _ <- updateBasedOnCalculation(smthNotDb) // DBIO
    } yield (...)).transcationally
)





    def execTransact[T](dbio: DBIO[T]): Future[T] = 
        db.run(dbio.transactionally)

Combine operations & fire within transtion

Summary

Future / DBIO / Query

Slick is not ORM

DBIO composition

Think in terms of Collection API

Last but not least

Slick 3.1.1 and 3.2 are much better in terms of SQL generation

Questions?

@pdolega

Resources

Slick docs: http://slick.lightbend.com/docs/

Online workshop by Dave Gurnell: https://vimeo.com/148074461

Excelent book: http://underscore.io/books/essential-slick/

Bonus

    





    for {
          segment <- StudentCourseSegmentTable
          student <- segment.student if student.name === "Tim"
          course <- segment.course
          semester <- segment.semester
    } yield (segment, student, course, semester)


DEBUG s.c.QueryCompilerBenchmark - ------------------- Phase: Time ---------
DEBUG s.c.QueryCompilerBenchmark -       assignUniqueSymbols:    0.446286 ms
DEBUG s.c.QueryCompilerBenchmark -                inferTypes:    0.239283 ms
DEBUG s.c.QueryCompilerBenchmark -              expandTables:    0.984031 ms
DEBUG s.c.QueryCompilerBenchmark -           forceOuterBinds:    1.048910 ms
DEBUG s.c.QueryCompilerBenchmark -         removeMappedTypes:    0.536035 ms
DEBUG s.c.QueryCompilerBenchmark -                expandSums:    0.016068 ms
DEBUG s.c.QueryCompilerBenchmark -         emulateOuterJoins:    0.108066 ms
DEBUG s.c.QueryCompilerBenchmark -             expandRecords:    0.421471 ms
DEBUG s.c.QueryCompilerBenchmark -        flattenProjections:    2.212847 ms
DEBUG s.c.QueryCompilerBenchmark -              rewriteJoins:    2.219579 ms
DEBUG s.c.QueryCompilerBenchmark -             verifySymbols:    0.204175 ms
DEBUG s.c.QueryCompilerBenchmark -             relabelUnions:    0.086386 ms
DEBUG s.c.QueryCompilerBenchmark -          createAggregates:    0.013349 ms
DEBUG s.c.QueryCompilerBenchmark -           resolveZipJoins:    0.126179 ms
DEBUG s.c.QueryCompilerBenchmark -          pruneProjections:    0.567347 ms
DEBUG s.c.QueryCompilerBenchmark -           rewriteDistinct:    0.018858 ms
DEBUG s.c.QueryCompilerBenchmark -    createResultSetMapping:    0.274411 ms
DEBUG s.c.QueryCompilerBenchmark -            hoistClientOps:    0.649790 ms
DEBUG s.c.QueryCompilerBenchmark -         reorderOperations:    0.643005 ms
DEBUG s.c.QueryCompilerBenchmark -     mergeToComprehensions:    4.482695 ms
DEBUG s.c.QueryCompilerBenchmark -            optimizeScalar:    0.179255 ms
DEBUG s.c.QueryCompilerBenchmark -          removeFieldNames:    1.145481 ms
DEBUG s.c.QueryCompilerBenchmark -                   codeGen:    3.783455 ms
DEBUG s.c.QueryCompilerBenchmark -                     TOTAL:   20.406962 ms

      
    val query = Compiled { name: Rep[String] =>
        for {
          segment <- StudentCourseSegmentTable
          student <- segment.student if student.name === name
          course <- segment.course
          semester <- segment.semester
        } yield (segment, student, course, semester)
    }
...
...
    db.run(query("Tim").result)

Precompilation

    Property age = Property.forName("age");
    List cats = sess.createCriteria(Cat.class)
    .add( Restrictions.disjunction()
        .add( age.isNull() )
        .add( age.eq( new Integer(0) ) )
        .add( age.eq( new Integer(1) ) )
        .add( age.eq( new Integer(2) ) )
    ) )
    .add( Property.forName("name").in( 
        new String[] { "Fritz", "Izi", "Pk" } ) 
    )
    .list();

Criteria API?

    StudentTable.filter(row: StudentTable => ...)

Criteria API?

  
  StudentTable.filter(myExtractedFilter)


  def myExtractedFilter(row: StudentTable): Rep[Boolean] = {
    row.name === "Tom" && row.nationality === "American"
  }




    StudentTable
        .map(s => (s.name, s.surname))
        .distinctOn(_._1)

    
    select "NAME", min("SURNAME") 

    from "STUDENT" 

    group by "NAME"

Introduction (101)

*Click*

Repository

Preso

pdole.ga

Who am I?

What is Slick?

Not an ORM

ORM problems

N+1 problem (lazy / eager fetching)

Session context scope

Execution under the cover (cache)

O-R impedance mismatch

False promise

Leaky abstraction

FRM

Reactive (™?)

Server handling 10 000 client connections may need not more than 10 connection

It's still viable

Async drivers?

The point being...

Description

vs

execution

Last but not least

Type-Safe

If you were to remember only one thing

Monadic Trio

The other thing worth to remember

It's (mostly) all about DBIO composition

And...

The best approach to write queries using Slick’s type-safe API is thinking in terms of Scala collections.

*Click*

Overview

Code samples:

Config

Tables

Code samples 2:

Poor version

Actions

Monadic Trio

Better version

DBIOAction / DBIO

DBIOAction[R, S, E]

R - type of result S - streaming / not streaming E - what kind of effect

DBIO[R] =

DBIOAction[R, NoStream, Effect.All]

R - type of result

Queries

Query

Query[M, U, C]

M - mixed type

U - unpacked type

C - collection type

Code samples:

Actual query

Actual query

Do you speak it?!

Queries

Wrong!

OK!

Joins

Wrong!

More complicated join

Applicative vs monadic

Sometimes one form is more elegant than the other

Outer joins

Slick 3.2 ?

No nice monadic form for outer joins

Composition / Transactions

DBIO.transactionally

*Click*

Transactions - example

OK, but how do we combine DB operations?

DBIO is a monad

map / flatMap

seq

sequence

unit

Wrong!

Click

Click

R - type of result
S - streaming / not streaming
E - what kind of effect

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