High Performance Systems in Go - GopherCon 2014
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The document discusses the advantages of using Go for high-performance systems, particularly in the context of messaging systems like NATS, originally designed for Cloud Foundry. It outlines the performance improvements achieved by rewriting NATS in Go, highlighting key areas for tuning performance, such as protocol parsing and subject routing. The document also shares lessons learned in performance optimization with Go, emphasizing its effectiveness for performance-critical applications.
![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)](https://image.slidesharecdn.com/gophercon2014-140424122115-phpapp01/85/High-Performance-Systems-in-Go-GopherCon-2014-27-320.jpg)
![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](https://image.slidesharecdn.com/gophercon2014-140424122115-phpapp01/85/High-Performance-Systems-in-Go-GopherCon-2014-28-320.jpg)
High Performance Systems in Go - GopherCon 2014
- 1. High Performance Systems in Go Derek Collison April 24, 2014 GopherCon
- 2. About Architected/Built TIBCO Rendezvous and EMS Messaging Systems Designed and Built CloudFoundry at VMware Co-founded AJAX APIs group at Google Distributed Systems Founder of Apcera, Inc. in San Francisco, CA @derekcollison [email protected] Derek Collison
- 3. Why Go? • Simple Compiled Language • Good Standard Library • Concurrency • Synchronous Programming Model • Garbage Collection • STACKS!
- 4. Why Go? • Not C/C++ • Not Java (or any JVM based language) • Not Ruby/Python/Node.js
- 7. NATS
- 9. NATS Messaging 101 • Subject-Based • Publish-Subscribe • Distributing Queueing • TCP/IP Overlay • Clustered Servers • Multiple Clients (Go, Node.js, Java, Ruby)
- 12. 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
- 13. Tuning NATS (gnatsd) or how to get from 500k to 6m
- 15. Target Areas • Shuffling Data • Protocol Parsing • Subject/Routing
- 16. Target Areas • Shuffling Data • Protocol Parsing! • Subject/Routing
- 17. Protocol Parsing • NATS is a text based protocol • PUB foo.bar 2rnokrn • SUB foo.> 2rn • Ruby version based on RegEx • First Go version was port of RegEx • Current is zero allocation byte parser
- 21. 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
- 22. defer
- 23. defer Results golang1.3 looks promising
- 24. parseSize
- 26. Target Areas • Shuffling Data • Protocol Parsing • Subject/Routing
- 27. 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)
- 28. 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
- 31. Jesteress
- 33. 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
- 35. Go is a good choice for performance based systems
- 36. Go is getting better faster than the others
- 37. Thanks
- 38. Resources • https://github.com/apcera/gnatsd • https://github.com/apcera/nats • https://github.com/derekcollison/nats