We Rubyists love our hashes.  But hashes have a few well known flaws. As Richard pointed out in Hashie Considered Harmful, they can be TOO flexible at times - a quick typo and you can assign and reference keys that you never intended.

a = { type: "F150" }
a[:typo] # nil

Some Common Hash Alternatives

If you're using hashes to store actual structured data, you may decide that you don't really need flexibility. That it's only going to get you into trouble.

There are a few alternatives. Imagine that you need to store a pair of XY coordinates. One approach might be to define a class, whose only job is to hold a pair of XY coordinates.

class PointClass # I don't recommend ending class names with Class :) 
  attr_accessor :x, :y
  def initialize(args)
    @x = args.fetch(:x)
    @y = args.fetch(:y)
  end
end

point_class = PointClass.new(x: 1, y: 2)
point_class.x # 1

Since in this case we only need to encapsulate data, a more concise choice might be to use a Struct. Here's what that looks like:

PointStruct = Struct.new(:x, :y)

point_struct = PointStruct.new(1, 2)
point_struct.x # 1

A third option might be to use OpenStruct. OpenStruct looks kind of like a struct, but lets you set arbitrary values like a hash. Here's an example:

point_os = OpenStruct.new(x: 1, y: 2)

point_os.x # 1

Performance Implications

[UPDATE 7/10/2015: It appears that my benchmarking script was unfair to hashes. As Patrick Helm pointed out, I was using an inefficient method of initializing them. So please disregard the results for hashes. Though my main point about openstruct being super slow is still valid. You can see his changes to my benchmark script here]

Looking at these four options, I began to wonder what the performance implications were. It's pretty obvious that any of these options is fast enough if you're only dealing with a little bit of data. But if you have thousands or millions of items to process, then the performance impact of a hash vs OpenStruct vs struct vs class could begin to matter.

At Honeybadger, we have thousands of exceptions being reported to our API each second, so understanding performance implications like this is always on our minds.

So, I wrote a simple benchmark script. I like to use the benchmark-ips gem for experiments like this because it automatically figures out a good sample size, and reports standard deviation.

Initialization

When I benchmarked initialization times for PointClass, PointStruct, Hash, and OpenStruct I found that PointClass and PointStruct were the clear winners. They were about 10x faster than OpenStruct, and about 2x faster than the hash.

initialization_benchmark_chart

PointClass and PointStruct were nearly 10x faster than OpenStruct PointClass and PointStruct were nearly 10x faster than OpenStruct

These results make sense. Structs are the simplest, so they're fastest. OpenStruct is the most complex (it's a wrapper for Hash) so it's the slowest. However the magnitude of the difference in speed is kind of surprising.

After running this experiment, I'd be really hesitant to use OpenStruct in any code where speed is a concern. And I'll be casting a wary eye at any hashes that I see in performance-critical code.

Read / Write

Unlike initialization, all four options are roughly the same when it comes to setting and accessing values.

rw_bench

Reading and writing benchmarks show no huge difference between Struct, class, hash and OpenStruct Reading and writing benchmarks show no huge difference between Struct, class, hash and OpenStruct

The Benchmarking Script

If you'd like to run the benchmark on your own system, you can use the script below. I ran it on MRI 2.1 on OSX. If you're curious about performance on other ruby interpreters, Michael Cohen has created an awesome gist with results for MRI 2.2, JRuby and others.

require 'benchmark/ips'
require 'ostruct'

data = { x: 100, y: 200 }

PointStruct = Struct.new(:x, :y)

class PointClass
  attr_accessor :x, :y
  def initialize(args)
    @x = args.fetch(:x)
    @y = args.fetch(:y)
  end
end

puts "\n\nINITIALIZATION =========="

Benchmark.ips do |x|
  x.report("PointStruct") { PointStruct.new(100, 200) }
  x.report("PointClass") { PointClass.new(data) }
  x.report("Hash") { Hash.new.merge(data) }
  x.report("OpenStruct") { OpenStruct.new(data) }
end

puts "\n\nREAD =========="

point_struct = PointStruct.new(100, 200)
point_class = PointClass.new(data)
point_hash = Hash.new.merge(data)
point_open_struct = OpenStruct.new(data)

Benchmark.ips do |x|
  x.report("PointStruct") { point_struct.x }
  x.report("PointClass") {  point_class.x }
  x.report("Hash") { point_hash.fetch(:x) }
  x.report("OpenStruct") {  point_open_struct.x }
end


puts "\n\nWRITE =========="

Benchmark.ips do |x|
  x.report("PointStruct") { point_struct.x = 1 }
  x.report("PointClass") {  point_class.x = 1 }
  x.report("Hash") { point_hash[:x] = 1 }
  x.report("OpenStruct") {  point_open_struct.x = 1 }
end

Get the Honeybadger newsletter

Each month we share news, best practices, and stories from the DevOps & monitoring community—exclusively for developers like you.
    author photo
    Starr Horne

    Starr Horne is a Rubyist and Chief JavaScripter at Honeybadger.io. When she's not neck-deep in other people's bugs, she enjoys making furniture with traditional hand-tools, reading history and brewing beer in her garage in Seattle.

    More articles by Starr Horne
    An advertisement for Honeybadger that reads 'Turn your logs into events.'

    "Splunk-like querying without having to sell my kidneys? nice"

    That’s a direct quote from someone who just saw Honeybadger Insights. It’s a bit like Papertrail or DataDog—but with just the good parts and a reasonable price tag.

    Best of all, Insights logging is available on our free tier as part of a comprehensive monitoring suite including error tracking, uptime monitoring, status pages, and more.

    Start logging for FREE
    Simple 5-minute setup — No credit card required