fix thread unsafety (#63)

Project.toml

@@ -8,8 +8,8 @@ StatsAPI = "82ae8749-77ed-4fe6-ae5f-f523153014b0"
 
 [compat]
 Distances = "0.8.1, 0.9, 0.10"
-julia = "1.3"
 StatsAPI = "1"
+julia = "1.3"
 
 [extras]
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"

src/StringDistances.jl

@@ -2,6 +2,7 @@ module StringDistances
 
 using Distances: Distances, SemiMetric, Metric, evaluate, result_type
 using StatsAPI: StatsAPI, pairwise, pairwise!
+
 # Distances API
 abstract type StringSemiMetric <: SemiMetric end
 abstract type StringMetric <: Metric end

src/find.jl

@@ -12,7 +12,7 @@ julia> compare("martha", "marhta", Levenshtein())
 """
 function compare(s1, s2, dist::Union{StringSemiMetric, StringMetric}; min_score = 0.0)
     1 - Normalized(dist)(s1, s2; max_dist = 1 - min_score)
-end 
+end
 
 """
     findnearest(s, itr, dist::Union{StringMetric, StringSemiMetric}) -> (x, index)
@@ -35,22 +35,34 @@ julia> findnearest(s, iter, Levenshtein(); min_score = 0.9)
 ```
 """
 function findnearest(s, itr, dist::Union{StringSemiMetric, StringMetric}; min_score = 0.0)
+    _citr = collect(itr)
+    isempty(_citr) && return (nothing, nothing)
+
+    _preprocessed_s = _preprocess(dist, s)
     min_score_atomic = Threads.Atomic{Float64}(min_score)
-    scores = [0.0 for _ in 1:Threads.nthreads()]
-    is = [0 for _ in 1:Threads.nthreads()]
-    s = _preprocess(dist, s)
-    # need collect since @threads requires a length method
-    Threads.@threads for i in collect(eachindex(itr))
-        score = compare(s, _preprocess(dist, itr[i]), dist; min_score = min_score_atomic[])
-        score_old = Threads.atomic_max!(min_score_atomic, score)
-        if score >= score_old
-            scores[Threads.threadid()] = score
-            is[Threads.threadid()] = i
+
+    chunk_size = max(1, length(_citr) ÷ (2 * Threads.nthreads()))
+    data_chunks = Iterators.partition(_citr, chunk_size)
+
+    chunk_score_tasks = map(data_chunks) do chunk
+        Threads.@spawn begin
+            map(chunk) do x
+                score = compare(_preprocessed_s, _preprocess(dist, x), dist; min_score = min_score)
+                Threads.atomic_max!(min_score_atomic, score)
+                score
+            end
         end
     end
-    imax = is[argmax(scores)]
-    imax == 0 ? (nothing, nothing) : (itr[imax], imax)
+
+    # retrieve return type of `compare` for type stability in task
+    _self_cmp = compare(_preprocessed_s, _preprocessed_s, dist; min_score = min_score)
+    chunk_scores = fetch.(chunk_score_tasks)::Vector{Vector{typeof(_self_cmp)}}
+    scores = reduce(vcat, fetch.(chunk_scores))
+
+    imax = argmax(scores)
+    iszero(scores) ? (nothing, nothing) : (_citr[imax], imax)
 end
+
 _preprocess(dist::AbstractQGramDistance, ::Missing) = missing
 _preprocess(dist::AbstractQGramDistance, s) = QGramSortedVector(s, dist.q)
 _preprocess(dist::Union{StringSemiMetric, StringMetric}, s) = s
@@ -83,14 +95,25 @@ julia> findall(s, iter, Levenshtein(); min_score = 0.9)
 ```
 """
 function Base.findall(s, itr, dist::Union{StringSemiMetric, StringMetric}; min_score = 0.8)
-    out = [Int[] for _ in 1:Threads.nthreads()]
-    s = _preprocess(dist, s)
-    # need collect since @threads requires a length method
-    Threads.@threads for i in collect(eachindex(itr))
-        score = compare(s, _preprocess(dist, itr[i]), dist; min_score = min_score)
-        if score >= min_score
-            push!(out[Threads.threadid()], i)
+    _citr = collect(itr)
+    _preprocessed_s = _preprocess(dist, s)
+
+    chunk_size = max(1, length(_citr) ÷ (2 * Threads.nthreads()))
+    data_chunks = Iterators.partition(itr, chunk_size)
+    isempty(data_chunks) && return empty(eachindex(_citr))
+
+    chunk_score_tasks = map(data_chunks) do chunk
+        Threads.@spawn begin
+            map(chunk) do x
+                compare(_preprocessed_s, _preprocess(dist, x), dist; min_score = min_score)
+            end
         end
     end
-    vcat(out...)
+
+    # retrieve return type of `compare` for type stability in task
+    _self_cmp = compare(_preprocessed_s, _preprocessed_s, dist; min_score = min_score)
+    chunk_scores::Vector{Vector{typeof(_self_cmp)}} = fetch.(chunk_score_tasks)
+
+    scores = reduce(vcat, fetch.(chunk_scores))
+    return findall(>=(min_score), scores)
 end