reactive slick at scala user group vienna may 20 2015

Reactive Slick The principles behind Slick 3

Lutz Hühnken (@lutzhuehnken)

JDBC

   try {      // make the connection      Class.forName(driver)      connection = DriverManager.getConnection(url, username, password)       // create the statement, and run the select query      val statement = connection.createStatement()      val resultSet = statement.executeQuery("SELECT host, user FROM user")      while ( resultSet.next() ) {        val host = resultSet.getString("host")        val user = resultSet.getString("user")        println("host, user = " + host + ", " + user)      }    } catch {      case e => e.printStackTrace    }    connection.close()  }

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Reactive Slick

JDBC

The problem with that code • well there are probably many, style etc.

But the problem:

• Synchronous I/O • Will block the thread it’s running on. • This is true not only for JDBC, but any DB lib running on top of

JDBC, Slick included.

We like to avoid that. Why?

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Reactive Slick

Digression: Concurrency model

Java EE: Threads. Servlet API: Thread per Request

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Note: This is a snapshot at one point in time, not a sequence of events.

Reactive Slick

Problems with Threads

• Context Switching is expensive • Memory overhead per thread •  Lock contention when communicating between threads (if

you have shared mutable state, which is likely..)

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Reactive Slick

Digression: Concurrency model

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Source: John Rose, Java VM Architect, JFokus, Stockholm, February 2015

Reactive Slick

Task level concurrency

This does not mean: „no threads“.

It means: Threads should not be the finest level of concurrency. Not be the level the application developer works on.

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Reactive Slick

Digression: Concurrency model

Reactive: Sub-Thread. Play: n threads per m requests

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Note: This is a snapshot at one point in time, not a sequence of events.

Reactive Slick

Solution: Use Future / blocking combo

• Put blocking database calls in Future(blocking( ... ))

• Contention for Connections (but may be limited by the ExecutionContext)

• A saturated thread pool blocks everything.

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Reactive Slick

Better solution: Isolation

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Note: This is a snapshot at one point in time, not a sequence of events.

Reactive Slick

New Question: Size

Idea: number of threads <= number of connections in pool, so getConnection never blocks.

Given you want to handle 10.000 concurrent clients.. what size should your connection pool be?

• 10

• 100

• 1.000

• 10.000

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Reactive Slick

It was a trick question…

A formula which has held up pretty well across a lot of benchmarks for years is that for optimal throughput the number of active connections should be somewhere near ((core_count * 2) + effective_spindle_count). Core count should not include HT threads, even if hyperthreading is enabled. Effective spindle count is zero if the active data set is fully cached, and approaches the actual number of spindles as the cache hit rate falls. ... There hasn't been any analysis so far regarding how well the formula works with SSDs.

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(From PostgreSQL)

Reactive Slick

Example: Quad-core server

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Image by Stefan Zeiger

Reactive Slick

The difference

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Image by Stefan Zeiger

Reactive Slick

Slick

Every Database contains an AsyncExecutor that manages the thread pool for asynchronous execution of Database I/O Actions.

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mydb = { dataSourceClass = "org.postgresql.ds.PGSimpleDataSource" properties = { databaseName = "mydb" user = "myuser" password = "secret" } numThreads = 10 }

Switch to code

Reactive Slick

JDBC (again, it’s the same slide)

   try {      // make the connection      Class.forName(driver)      connection = DriverManager.getConnection(url, username, password)       // create the statement, and run the select query      val statement = connection.createStatement()      val resultSet = statement.executeQuery("SELECT host, user FROM user")      while ( resultSet.next() ) {        val host = resultSet.getString("host")        val user = resultSet.getString("user")        println("host, user = " + host + ", " + user)      }    } catch {      case e => e.printStackTrace    }    connection.close()  }

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Reactive Streams

Reactive Slick

Reactive Streams Overview

• How do we: • Handle potentially infinite streams of data? • Handle data in a reactive manner? • Achieve asynchronous non-blocking data flow? • Avoid out of memory errors?

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Reactive Slick

Supply and Demand

• Data Items Flow Downstream

• Demand Flows Upstream

• Data Items flow only when there is demand.

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Reactive Slick

Reactive Streams Specification

• Interface Specification • Java interfaces for implementations

• TCK • Test Harness to validate implementations

• Specification Website • http://www.reactive-streams.org/

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Reactive Slick

Publisher

package org.reactivestreams;

public interface Publisher<T> { public void subscribe<T>( Subscriber<T> subscriber);}

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Reactive Slick

Subscriber

public interface Subscriber<T> { public void onSubscribe( Subscription subscription); public void onNext(T element); public void onComplete(); public void onError(Throwable cause);}

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Reactive Slick

Subscription

public interface Subscription { public void cancel(); public void request(long elements);}

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Reactive Slick

Dynamic Push-Pull

• “Push” behavior when consumer is faster

• “Pull” behavior when producer is faster

• Switches automatically between these

• Batching demand allows batching data

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Reactive Slick

Linear Transformations

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Demand

Source Sinkmap …

Reactive Slick

Linear Transformations

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Source

DemanSink

drop

map

Reactive Slick

Linear Stream Transformations

• Deterministic (like for collections) • map, filter, collect, grouped, drop, take, groupBy, ...

• Time-Based • takeWithin, dropWithin, groupedWithin, ...

• Rate-Detached • expand, conflate, buffer, ...

• asynchronous • mapAsync, mapAsyncUnordered, ...

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Reactive Slick

Non-linear Stream Transformations

• Fan-In • merge, concat, zip

• Fan-Out • broadcast, route, unzip

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Reactive Slick

Fan In

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Reactive Slick

Fan Out

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Reactive Slick

Materialization

• Akka Streams separate the what from the how • declarative Source/Flow/Sink DSL to create blueprint • FlowMaterializer turns this into running Actors

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Switch to code

Reactive Slick

Try it yourself!

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Reactive Slick

Thank You

Further information: http://slick.typesafe.com

Contact: lutz.huehnken@typesafe.com

Twitter: @lutzhuehnken

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