High Performance Systems in Go - GopherCon 2014

of 38 /38
High Performance Systems in Go Derek Collison April 24, 2014 GopherCon

description

Short presentation on some techniques to gain performance of the NATS messaging system as it was rewritten in Go.

Transcript of High Performance Systems in Go - GopherCon 2014

Page 1: High Performance Systems in Go - GopherCon 2014

High Performance Systems in Go

Derek Collison April 24, 2014 GopherCon

Page 2: High Performance Systems in Go - GopherCon 2014

About

Architected/Built TIBCO Rendezvous and EMS Messaging SystemsDesigned and Built CloudFoundry at VMwareCo-founded AJAX APIs group at GoogleDistributed SystemsFounder of Apcera, Inc. in San Francisco, CA@[email protected]

Derek Collison

Page 3: High Performance Systems in Go - GopherCon 2014

Why Go?• Simple Compiled Language

• Good Standard Library

• Concurrency

• Synchronous Programming Model

• Garbage Collection

• STACKS!

Page 4: High Performance Systems in Go - GopherCon 2014

Why Go?

• Not C/C++

• Not Java (or any JVM based language)

• Not Ruby/Python/Node.js

Page 5: High Performance Systems in Go - GopherCon 2014
Page 6: High Performance Systems in Go - GopherCon 2014

What about High Performance?

Page 7: High Performance Systems in Go - GopherCon 2014

NATS

Page 8: High Performance Systems in Go - GopherCon 2014
Page 9: High Performance Systems in Go - GopherCon 2014

NATS Messaging 101• Subject-Based

• Publish-Subscribe

• Distributing Queueing

• TCP/IP Overlay

• Clustered Servers

• Multiple Clients (Go, Node.js, Java, Ruby)

Page 10: High Performance Systems in Go - GopherCon 2014
Page 11: High Performance Systems in Go - GopherCon 2014
Page 12: High Performance Systems in Go - GopherCon 2014

NATS• Originally written to support CloudFoundry

• In use by CloudFoundry, Baidu, Apcera and others

• Written first in Ruby -> 150k msgs/sec

• Rewritten at Apcera in Go (Client and Server)

• First pass -> 500k msgs/sec

• Current Performance -> 5-6m msgs/sec

Page 13: High Performance Systems in Go - GopherCon 2014

Tuning NATS (gnatsd)

or how to get from 500k to 6m

Page 14: High Performance Systems in Go - GopherCon 2014
Page 15: High Performance Systems in Go - GopherCon 2014

Target Areas

• Shuffling Data

• Protocol Parsing

• Subject/Routing

Page 16: High Performance Systems in Go - GopherCon 2014

Target Areas

• Shuffling Data

• Protocol Parsing!

• Subject/Routing

Page 17: High Performance Systems in Go - GopherCon 2014

Protocol Parsing• NATS is a text based protocol

• PUB foo.bar 2\r\nok\r\n

• SUB foo.> 2\r\n

• Ruby version based on RegEx

• First Go version was port of RegEx

• Current is zero allocation byte parser

Page 18: High Performance Systems in Go - GopherCon 2014
Page 19: High Performance Systems in Go - GopherCon 2014
Page 20: High Performance Systems in Go - GopherCon 2014
Page 21: High Performance Systems in Go - GopherCon 2014

Some Tidbits

• Early on, defer was costly

• Text based proto needs conversion from ascii to int

• This was also slow due to allocations in strconv.ParseInt

Page 22: High Performance Systems in Go - GopherCon 2014

defer

Page 23: High Performance Systems in Go - GopherCon 2014

defer Results

golang1.3 looks promising

Page 24: High Performance Systems in Go - GopherCon 2014

parseSize

Page 25: High Performance Systems in Go - GopherCon 2014

parseSize vs

strconv.ParseInt

Page 26: High Performance Systems in Go - GopherCon 2014

Target Areas

• Shuffling Data

• Protocol Parsing

• Subject/Routing

Page 27: High Performance Systems in Go - GopherCon 2014

Subject Router

• Matches subjects to subscribers

• Utilizes a trie of nodes and hashmaps

• Has a frontend dynamic eviction cache

• Uses []byte as keys (Go’s builtin does not)

Page 28: High Performance Systems in Go - GopherCon 2014

Subject Router

• Tried to avoid []byte -> string conversions

• Go’s builtin hashmap was slow pre 1.0

• Built using hashing algorithms on []byte

• Built on hashmaps with []byte keys

Page 29: High Performance Systems in Go - GopherCon 2014

Hashing Algorithms

Page 30: High Performance Systems in Go - GopherCon 2014

Hashing Algorithms

Page 31: High Performance Systems in Go - GopherCon 2014

Jesteress

Page 32: High Performance Systems in Go - GopherCon 2014

HashMap Comparisons

Page 33: High Performance Systems in Go - GopherCon 2014

Some Lessons Learned• Use go tool pprof (linux)

• Avoid short lived objects on the heap

• Use the stack or make long lived objects

• Benchmark standard library builtins (strconv)

• Benchmark builtins (defer, hashmap)

• Don’t use channels in performance critical path

Page 34: High Performance Systems in Go - GopherCon 2014

Big Lesson Learned?

Page 35: High Performance Systems in Go - GopherCon 2014

Go is a good choice for performance based

systems

Page 36: High Performance Systems in Go - GopherCon 2014

Go is getting better faster than the others

Page 37: High Performance Systems in Go - GopherCon 2014

Thanks

Page 38: High Performance Systems in Go - GopherCon 2014

Resources

• https://github.com/apcera/gnatsd

• https://github.com/apcera/nats

• https://github.com/derekcollison/nats