PgQuery::Node: Add inner and inner= helpers to modify inner object

[lfittl]

Because of how oneof messages work in protobuf, its a bit tedious to make modifications to a Node object, in particular when changing the type of the inner object held within the Node in a generic code path (i.e. with a dynamic inner type), which required first knowing the name of the new inner object type, and then using public_send to set the new value.

To help, introduce the new "inner" and "inner=" methods for PgQuery::Node, that get/set the inner object directly, avoiding the use of public_send.

This will be of particular help for anyone utilizing the walk! API to make modifications to the query tree. To illustrate, an example is added to the treewalker spec showing how to utilize this.

---

Additionally, this makes utilizing the walk! treewalker easier for the common use case of working with the node directly (without using the parent or location information).

[olleolleolle]

https://bugs.ruby-lang.org/issues/15143
Can we use to_h with a block here? That was merged in 2018.

[lfittl]

Good point - looks like that was added in Ruby 2.6 (see commit), so we could use it.

[lfittl]

Per request (in a different channel), I've run a quick benchmark showing that this doesn't impact the time the treewalker takes negatively, which it does not:

Before (6 longest SQL statements in fingerprint test file):

Benchmarking time for parse+walk...
                       user     system      total        real
4a6db94fbada8341  52.937340   0.678991  53.616331 ( 53.624522)
b7dbf54ce62af0ca   0.241984   0.002727   0.244711 (  0.244712)
18e71bc17baea13b   0.006921   0.000028   0.006949 (  0.006943)
3a5494404465d0f9   0.014623   0.000034   0.014657 (  0.014658)
1cca3f304295181c   0.009612   0.000013   0.009625 (  0.009623)
f936eab75b8c1b90   0.000537   0.000001   0.000538 (  0.000538)

Benchmarking memory for parse+walk...
Calculating -------------------------------------
    4a6db94fbada8341    13.806B memsize (     0.000  retained)
                        49.838M objects (     0.000  retained)
                        50.000  strings (     0.000  retained)
    b7dbf54ce62af0ca    76.937M memsize (     0.000  retained)
                        88.861k objects (     0.000  retained)
                        50.000  strings (     0.000  retained)
    18e71bc17baea13b     2.268M memsize (     0.000  retained)
                        10.540k objects (     0.000  retained)
                        50.000  strings (     0.000  retained)
    3a5494404465d0f9     4.793M memsize (     0.000  retained)
                        17.635k objects (     0.000  retained)
                        50.000  strings (     0.000  retained)
    1cca3f304295181c     3.159M memsize (     0.000  retained)
                        12.182k objects (     0.000  retained)
                        50.000  strings (     0.000  retained)
    f936eab75b8c1b90   158.198k memsize (     0.000  retained)
                       926.000  objects (     0.000  retained)
                        50.000  strings (     0.000  retained)

After (6 longest SQL statements in fingerprint test file):

Benchmarking time for parse+walk...
                       user     system      total        real
4a6db94fbada8341  50.811444   0.857045  51.668489 ( 51.743262)
b7dbf54ce62af0ca   0.241765   0.002221   0.243986 (  0.244304)
18e71bc17baea13b   0.006827   0.000019   0.006846 (  0.006843)
3a5494404465d0f9   0.014364   0.000009   0.014373 (  0.014371)
1cca3f304295181c   0.009489   0.000013   0.009502 (  0.009501)
f936eab75b8c1b90   0.000513   0.000004   0.000517 (  0.000515)

Benchmarking memory for parse+walk...
    4a6db94fbada8341    13.806B memsize (     0.000  retained)
                        49.838M objects (     0.000  retained)
                        50.000  strings (     0.000  retained)
    b7dbf54ce62af0ca    76.937M memsize (     0.000  retained)
                        88.862k objects (     0.000  retained)
                        50.000  strings (     0.000  retained)
    18e71bc17baea13b     2.268M memsize (     0.000  retained)
                        10.541k objects (     0.000  retained)
                        50.000  strings (     0.000  retained)
    3a5494404465d0f9     4.793M memsize (     0.000  retained)
                        17.636k objects (     0.000  retained)
                        50.000  strings (     0.000  retained)
    1cca3f304295181c     3.159M memsize (     0.000  retained)
                        12.183k objects (     0.000  retained)
                        50.000  strings (     0.000  retained)
    f936eab75b8c1b90   158.278k memsize (     0.000  retained)
                       927.000  objects (     0.000  retained)
                        50.000  strings (     0.000  retained)

Benchmark script:

# spec/benchmark.rb
#
# Needs "s.add_development_dependency 'benchmark-memory', '~> 0'" in the gemspec

require 'pg_query'
require 'json'
require 'benchmark'
require 'benchmark/memory'

def fingerprint_defs
  # Sort input SQL by size (largest first), since those would be most interesting usually
  @fingerprint_defs ||= JSON.parse(File.read(File.join(__dir__, 'files/fingerprint.json'))).sort_by { |d| -d['input'].size }
end

puts 'Benchmarking time for parse+walk...'

Benchmark.bmbm do |x|
  fingerprint_defs.each do |testdef|
    x.report(testdef['expectedHash']) { PgQuery.parse(testdef['input']).walk! { |_, _, _, _| } }
  end
end

puts 'Benchmarking memory for parse+walk...'

Benchmark.memory do |x|
  fingerprint_defs.each do |testdef|
    x.report(testdef['expectedHash']) { PgQuery.parse(testdef['input']).walk! { |_, _, _, _| } }
  end
end