_content/talks/2013/distsys.slide

Go, for Distributed Systems

Russ Cox
Google

* About the Talk

I gave variants of this talk three times in 2013, once at SOSP's Programming Languages and Operating Systems (PLOS) workshop, once at MIT Lincoln Lab's annual Software Engineering Symposium, and once at Twitter's Cambridge, Massachusetts office.

The talk assumes an audience familiar with the basic problems of building distributed systems. It presents Go's approach to solving some of those problems.

* Go

Go is an open source programming language that makes it easy to build simple, reliable, and efficient software.

* History

Design began in late 2007.

- Robert Griesemer, Rob Pike, Ken Thompson
- Ian Lance Taylor, Russ Cox

Became open source in November 2009.

Developed entirely in the open; very active community.
Language stable as of Go 1, early 2012.

* Motivation

Started as an answer to software problems at Google:

- multicore processors
- networked systems
- massive computation clusters
- scale: 10⁷ lines of code
- scale: 10³ programmers
- scale: 10⁶⁺ machines (design point)

* Go

A simple but powerful and fun language.

- start with C, remove complex parts
- add interfaces, concurrency
- also: garbage collection, closures, reflection, strings, ...

For more background on design:

- [[http://commandcenter.blogspot.com/2012/06/less-is-exponentially-more.html][Less is exponentially more]]
- [[/talks/2012/splash.article][Go at Google: Language Design in the Service of Software Engineering]]

* This Talk

Engineering

Interfaces

Concurrency

* Engineering

* Engineering: Imports

.play distsys/hello0.go

import "fmt" guaranteed to read exactly one file.

* Engineering: Imports

	$ go get github.com/golang/glog

.play distsys/hello1.go

Still guaranteed to read exactly one file.

Import name space is decentralized.

* Engineering: Program Rewrites

	$ gofmt -r 'glog.Infof -> glog.Errorf' hello1.go
	package main
	
	import (
		"flag"
		"github.com/golang/glog"
	)
	
	func main() {
		flag.Set("logtostderr", "true")
		glog.Errorf("hello, world")
	}
	$ 

* Engineering: Garbage Collection

In C and C++, too much programming _and_ API design is about memory management.

Go has garbage collection, only.

Fundamental for interfaces: memory management details do not bifurcate otherwise-similar APIs.

Fundamental for concurrency: too hard to track ownership otherwise.

Of course, adds cost, latency, complexity in run time system.

* Engineering: Garbage Collection

Experience with Java: Uncontrollable cost, too much tuning.

Go lets you limit allocation by controlling memory layout.

Examples:

	type Ring struct {
		R, W int
		Data [512]byte
	}

	type Point struct {
		X, Y int
	}
	
	type Rectangle struct {
		Min, Max Point
	}

* Engineering: Garbage Collection

Garbage collector implementation remains an active area of work and research.

Design decision: Interior pointers are allowed, as are foreign pointers.

- Cannot reuse Java GC algorithms directly.
- But gives _programmer_ more control over allocation.

Current design: parallel mark-and-sweep.
With care to use memory wisely, works well in production.

* Interfaces

* Interfaces

An interface defines a set of methods.

	package io
	
	type Writer interface {
		Write(data []byte) (n int, err error)
	}

* Interfaces

A type implements the interface by implementing the methods.

	package bytes
	
	type Buffer struct {
		...
	}
	
	func (b *Buffer) Write(data []byte) (n int, err error) {
		...
	}

* Interfaces

An implementation of an interface can be assigned to a variable of that interface type.

	package fmt
	
	func Fprintf(w io.Writer, format string, args ...interface{})

* Interfaces

.play distsys/writebuffer.go /^func.main/+1,/^}/-1

* Interfaces

Reader is the obvious counterpart.

	package io

	type Reader interface {
		Read(data []byte) (n int, err error)
	}

	func Copy(dst Writer, src Reader) (n int64, err error)

* Interfaces

.play distsys/writebuffer2.go /^func.main/+1,/^}/-1

* Interfaces

Reader and Writer turn out to be very useful.

Adapters

	package io
	
	func MultiWriter(writers ...Writer) Writer
	    MultiWriter creates a writer that duplicates its writes to all the
	    provided writers, similar to the Unix tee(1) command.

Chaining

	package gzip // compress/gzip
	
	func NewWriter(w io.Writer) *Writer

Also: buffered writers, encrypted writers, limited writers, HTTP responses.

* Interfaces

Networking:

	package net

	type Conn interface {
		Read(b []byte) (n int, err error)
		Write(b []byte) (n int, err error)
		Close() error
	
		LocalAddr() Addr
		RemoteAddr() Addr
	
		SetDeadline(t time.Time) error
		SetReadDeadline(t time.Time) error
		SetWriteDeadline(t time.Time) error
	}

	func Dial(network, address string) (Conn, error)

* Interfaces

Networking example:

.play distsys/finger.go /^func.finger/+1,/^}/-1

* Interfaces

Networking client as adapter function:

	package smtp
	
	func NewClient(conn net.Conn, host string) (*Client, error)

Other implementations of net.Conn: testing, SSL, ...

* Interface Lessons

Key advantages:

- no dependence between interface and implementation
- expressive composition
- easy testing
- avoids overdesign, rigid hierarchy of inheritance-based OO

The source of all generality in the Go language.

* Concurrency

* Concurrency vs Parallelism

Concurrency is about dealing with lots of things at once.

Parallelism is about doing lots of things at once.

Concurrency is about structure, parallelism is about execution.

Concurrency provides a way to structure a solution to solve a problem that may be parallelizable (or not).

* Concurrency vs Parallelism

Concurrent: mouse, keyboard, display, and disk drivers in operating system.

Parallel: vector dot product, matrix multiply.

Concurrency can enable parallelism but is useful on its own: modern programs must deal with many things at once.

* Concurrency

Go provides two important concepts:

A goroutine is a thread of control within the program, with its own local variables and stack. Cheap, easy to create.

A channel carries typed messages between goroutines.

* Concurrency

.play distsys/hello.go

* Concurrency: CSP

Channels adopted from Hoare's Communicating Sequential Processes.

- Orthogonal to rest of language
- Can keep familiar model for computation
- Focus on _composition_ of regular code

Go _enables_ simple, safe concurrent programming.
It doesn't _forbid_ bad programming.

Caveat: not purely memory safe; sharing is legal.
Passing a pointer over a channel is idiomatic.

Experience shows this is practical.

* Concurrency

Sequential network address resolution, given a work list:

.play distsys/addr1.go /lookup/+1,/^}/-1

* Concurrency

Parallel network address resolution, given a work list:

.play distsys/addr2.go /lookup/+1,/^}/-1

* Concurrency

Aside: can abstract this pattern.

.play distsys/addr3.go /lookup/+1,/^}/-1

* Concurrency

Aside: can abstract this pattern further (hypothetical):

	var par ParallelDo

	for _, w := range worklist {
		w := w // copy iteration variable
		par.Do(func() {
			w.addrs, w.err = net.LookupHost(w.host)			
		})
	)

	par.Wait()

But it's still useful to be able to construct alternate patterns.

* Concurrency

Bounded parallelism:

.play distsys/addr4.go /lookup/+1,/^}/-1

* Concurrency

Bounded parallelism, 2:

.play distsys/addr5.go /lookup/+1,/^}/-1

* Concurrency:

Aside: can abstract (still hypothetical):

	par.Limit(10)

	for _, w := range work {
		w := w // copy iteration variable
		par.Do(func() {
			w.addrs, w.err = net.LookupHost(w.host)			
		})
	)

	par.Wait()

* Concurrency

Example: replicated storage with read and write quorums.

	const (
		F = 2
		N = 5 // >= 2F + 1
		ReadQuorum = F + 1
		WriteQuorum = N - F
	)

* Concurrency

Replicated write, returning after enough writes have succeeded.

.play distsys/replwrite.go /^func.Write/+2,/if.delay/-2/

* Concurrency

Replicated read, returning after enough reads have been gathered.

.play distsys/replread.go /^func.Read/+2,/if.delay/-2/

* Concurrency

Select allows choosing between multiple channel operations.

Example, chat program:

	for {
		select {
		case event := <-ui:
			// process user interface event
		case msg := <-server:
			// process server message
		case t := <-tick:
			// time has elapsed
		}
	}

* Concurrency Lessons

- Key feature for building distributed systems.
- Supported by closures and garbage collection.
- Message passing inside program, also outside program.

Most important:

- Do not communicate by sharing memory.
- Instead, share memory by communicating.

* Production Use

vitess/vtocc, MySQL query balancer

- serves all of YouTube's MySQL queries
- months of crash-free and leak-free operation

groupcache

- distributed in-memory immutable key-value cache
- used by (parts of) dl.google.com, Blogger, Google Code, Google Fiber, production monitoring systems

* More information and related talks

https://go.dev/

rsc@golang.org

Videos:

- Concurrency is not parallelism [[http://vimeo.com/49718712][video]]
- Go concurrency patterns [[http://www.youtube.com/watch?v=f6kdp27TYZs][video]]
- Advanced Go concurrency patterns [[http://www.youtube.com/watch?v=QDDwwePbDtw][video]]

Questions?