started with datatable

perf/Rdatatable.jl

@@ -0,0 +1,96 @@
+
+
+
+
+module QueryPerf
+
+using Query, DataFrames, StatsBase, RCall
+
+    function R_bench(N,K)
+
+        R"""
+        library(data.table)
+        N <- $N
+        K <- $K
+        # copied from https://github.com/Rdatatable/data.table/wiki/Benchmarks-%3A-Grouping
+        set.seed(1)
+        DT <- data.table(
+          id1 = sample(sprintf("id%03d",1:K), N, TRUE),      # large groups (char)
+          id2 = sample(sprintf("id%03d",1:K), N, TRUE),      # large groups (char)
+          id3 = sample(sprintf("id%010d",1:(N/K)), N, TRUE), # small groups (char)
+          id4 = sample(K, N, TRUE),                          # large groups (int)
+          id5 = sample(K, N, TRUE),                          # large groups (int)
+          id6 = sample(N/K, N, TRUE),                        # small groups (int)
+          v1 =  sample(5, N, TRUE),                          # int in range [1,5]
+          v2 =  sample(5, N, TRUE),                          # int in range [1,5]
+          v3 =  sample(round(runif(100,max=100),4), N, TRUE) # numeric e.g. 23.5749
+        )
+
+        timings <- list()
+
+        timings$sum1 <- system.time( DT[, sum(v1), keyby=id1] )[3]
+        timings$sum2 <- system.time( DT[, sum(v1), keyby=id1] )[3]
+        timings$sum3 <- system.time( DT[, sum(v1), keyby="id1,id2"] )[3]
+        timings$sum4 <- system.time( DT[, sum(v1), keyby="id1,id2"] )[3]
+        timings$sum_mean1 <- system.time( DT[, list(sum(v1),mean(v3)), keyby=id3] )[3]
+        timings$sum_mean2 <- system.time( DT[, list(sum(v1),mean(v3)), keyby=id3] )[3]
+        timings$mean7_9_by_id4_1 <- system.time( DT[, lapply(.SD, mean), keyby=id4, .SDcols=7:9] )[3]
+        timings$mean7_9_by_id4_2 <- system.time( DT[, lapply(.SD, mean), keyby=id4, .SDcols=7:9] )[3]
+        timings$sum7_9_by_id6_2 <- system.time( DT[, lapply(.SD, sum), keyby=id6, .SDcols=7:9] )[3]
+        timings$sum7_9_by_id6_2 <- system.time( DT[, lapply(.SD, sum), keyby=id6, .SDcols=7:9] )[3]
+        """
+        @rget timings
+        return timings
+    end
+
+    function createData(N::Int,K::Int)
+
+        N = 1_000
+        K = 100
+
+        df = DataFrame(id1 = sample(["id$x" for x in 1:K],N),
+                       id2 = sample(["id$x" for x in 1:K],N),
+                       id3 = sample(["id$x" for x in 1:(N/K)],N*K),
+                       id4 = sample(1:K,N),
+                       id5 = sample(1:K,N),
+                       id6 = sample(1:(N/K),N*K),
+                       v1 = sample(1:5,N),
+                       v2 = sample(1:5,N),
+                       v3 = sample(round(rand(100),4),N))
+
+        return df
+    end
+
+    function bench1(df::DataFrame)
+
+        t1 = @from i in df begin
+                 @group i by i.id1 into g
+                 @select r=sum(g..v1)
+                 @collect DataFrame 
+            end
+        return nothing
+    end
+
+    function run_benches(N=1_000,K=100)
+        # get small data for JIT warmup
+        d_ = createData(10,3)
+        # warm up
+        bench1(d_)
+
+        # get real data
+        d = createData(N,K)
+        # measure
+        t1 = @elapsed bench1(d)
+
+    end
+
+
+end # module
+
+
+
+
+
+
+
+