Performance improvements (krynju#17)

Author: krynju

README.md

@@ -16,13 +16,16 @@ An overview of performance is shown below. Times are shown for an average of 100
 
 ### Table
 
-| N    | insert [us]    | delete [us] | lookup [us] |
-| :------------- | :------------- | :-------| :---- |
-| 10<sup>3</sup>     |    86.039  |   67.768 |   67.433    |
-|10<sup>4</sup>  | 152.533 | 87.305 |   89.556 |
-|   10<sup>5</sup>  |  260.794 | 107.378 |  114.014 |
-|  10<sup>6</sup>  | 424.0  | 123.648 |  124.587 |
-| 10<sup>7</sup>  | 659.088  |  135.373 | 134.609 |
+```julia
+ Row │ n         insert[us]   delete[us]    search[us]
+     │ Any       Float64?     Float64?      Float64?  
+─────┼────────────────────────────────────────────────
+   1 │ 1000          152.67        32.02    0.00222892
+   2 │ 10000         174.1         63.86    0.00227912
+   3 │ 100000        299.6        165.86    0.00235597
+   4 │ 1000000       629.11       524.92    0.00304124
+   5 │ 10000000      964.76       912.39    0.025
+```
 
 ### Plot
 

benchmark/benchmark.jl

@@ -28,7 +28,7 @@ search_vec = []
 
 
 d = DataFrame((op=[], time=[], n=[]))
-x = [1_000, 10_000, 100_000]
+x = [1_000, 10_000, 100_000, 1_000_000, 10_000_000]
 
 function prepare_t(t)
     _t = deepcopy(t)
@@ -49,9 +49,9 @@ for attempt in 1:1
             insert!(t, i, i)
         end
 
-        insertion = @benchmark batch_insert!(_t, nums_test) setup=(_t =deepcopy(t)) samples=1 evals=1
-        search = @benchmark batch_find(t, nums_test) setup=(_t = prepare_t(t)) samples=1 evals=1
-        deletion = @benchmark batch_delete!(t, nums_test) setup=(_t = prepare_t(t)) samples=1 evals=1
+        insertion = @benchmark batch_insert!(_t, nums_test) setup=(_t =deepcopy(t))
+        search = @benchmark batch_find(t, nums_test) setup=(_t = prepare_t(t))
+        deletion = @benchmark batch_delete!(t, nums_test) setup=(_t = prepare_t(t))
 
         push!(d, ("insert", minimum(insertion).time, N))
         push!(d, ("delete", minimum(deletion).time,N))
@@ -71,16 +71,17 @@ c = combine(groupby(d, [:op,:n]), :time => minimum)
 
 plot(
     x,
-    [c[(c.op.=="insert"),:].time_minimum./10000,c[(c.op.=="delete"),:].time_minimum./10000, c[(c.op.=="search"),:].time_minimum./10000],
+    [c[(c.op.=="insert"),:].time_minimum,c[(c.op.=="delete"),:].time_minimum, c[(c.op.=="search"),:].time_minimum],
     xscale = :log10,
     ylabel = "operation time [us]",
     xlabel = "N",
+    xticks = [1e3, 1e4, 1e5, 1e6, 1e7],
     markershape =[:diamond :utriangle :dtriangle],
     labels= ["insert" "delete" "lookup"],
     legend=:topleft,
 )
 
-savefig("result_master.svg")
-savefig("result_master.png")
+savefig("branch_results_new2.svg")
+savefig("result_new2.png")
 using CSV
-CSV.write("branch_results_master.csv", c)
+CSV.write("branch_results_new2.csv", c)

benchmark/result.svg

@@ -0,0 +1,16 @@
+op,n,time_minimum
+insert,1000,1.5267e6
+delete,1000,320200.0
+search,1000,22.289156626506024
+insert,10000,1.741e6
+delete,10000,638600.0
+search,10000,22.79116465863454
+insert,100000,2.996e6
+delete,100000,1.6586e6
+search,100000,23.559670781893004
+insert,1000000,6.2911e6
+delete,1000000,5.2492e6
+search,1000000,30.412371134020617
+insert,10000000,9.6476e6
+delete,10000000,9.1239e6
+search,10000000,250.0

benchmark/results.csv

@@ -16,17 +16,17 @@ function AVLSet(x::K) where {K <: AbstractVector}
 end
 
 Base.eltype(::Type{AVLSet{K}}) where {K} = K
-Base.length(set::AVLSet) = length(set.tree) 
-Base.in(x::K, set::AVLSet{K}) where {K} = !isnothing(find_node(set.tree, x)) 
+Base.length(set::AVLSet) = length(set.tree)
+Base.in(x::K, set::AVLSet{K}) where {K} = x in set.tree
 
 function iterate(set::AVLSet{K}) where {K}
     ret = iterate(set.tree)
-    if isnothing(ret) return nothing else return (ret[1][1], ret[2])  end
+    if ret === nothing return nothing else return (ret[1][1], ret[2])  end
 end
 
 function iterate(set::AVLSet{K}, node::Node{K,Nothing}) where {K}
     ret = iterate(set.tree, node)
-    if isnothing(ret) return nothing else return (ret[1][1], ret[2])  end
+    if ret === nothing return nothing else return (ret[1][1], ret[2])  end
 end
 
 Base.push!(set::AVLSet{K}, item::K) where {K} = insert!(set.tree, item, nothing)