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Nov 13, 2015
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Add benchmarks from R's data.table benchmarks #36

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86 changes: 86 additions & 0 deletions test/data.table.timings.jl
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# Julia benchmarks from R's data.table
# https://github.com/Rdatatable/data.table/wiki/Benchmarks-:-Grouping

using DataFrames, DataFramesMeta
using NullableArrays

N=10_000_000; K=100
srand(1)

# Array version

DA = DataFrame(
id1 = P(rand([symbol(string("id", i)) for i=1:K], N)), # large groups (char)
id2 = P(rand([symbol(string("id", i)) for i=1:K], N)), # large groups (char)
id3 = P(rand([symbol(string("id", i)) for i=1:Int(N/K)], N)), # small groups (char)
id4 = P(rand(1:K, N)), # large groups (int)
id5 = P(rand(1:K, N)), # large groups (int)
id6 = P(rand(1:Int(N/K), N)), # small groups (int)
v1 = P(rand(1:5, N)), # int in range [1,5]
v2 = P(rand(1:5, N)), # int in range [1,5]
v3 = P(rand(N)) # numeric e.g. 23.5749
);

# PooledDataArray version

DPDA = DataFrame(
id1 = PooledDataArray(rand([symbol(string("id", i)) for i=1:K], N)), # large groups (char)
id2 = PooledDataArray(rand([symbol(string("id", i)) for i=1:K], N)), # large groups (char)
id3 = PooledDataArray(rand([symbol(string("id", i)) for i=1:Int(N/K)], N)), # small groups (char)
id4 = PooledDataArray(rand(1:K, N)), # large groups (int)
id5 = PooledDataArray(rand(1:K, N)), # large groups (int)
id6 = PooledDataArray(rand(1:Int(N/K), N)), # small groups (int)
v1 = P(rand(1:5, N)), # int in range [1,5]
v2 = P(rand(1:5, N)), # int in range [1,5]
v3 = P(rand(N)) # numeric e.g. 23.5749
);

# DataArray version

DDA = DataFrame(
id1 = (rand([symbol(string("id", i)) for i=1:K], N)), # large groups (char)
id2 = (rand([symbol(string("id", i)) for i=1:K], N)), # large groups (char)
id3 = (rand([symbol(string("id", i)) for i=1:Int(N/K)], N)), # small groups (char)
id4 = (rand(1:K, N)), # large groups (int)
id5 = (rand(1:K, N)), # large groups (int)
id6 = (rand(1:Int(N/K), N)), # small groups (int)
v1 = (rand(1:5, N)), # int in range [1,5]
v2 = (rand(1:5, N)), # int in range [1,5]
v3 = (rand(N)) # numeric e.g. 23.5749
);

# NullableArray version

DNA = DataFrame(
id1 = P(NullableArray(rand([symbol(string("id", i)) for i=1:K], N))), # large groups (char)
id2 = P(NullableArray(rand([symbol(string("id", i)) for i=1:K], N))), # large groups (char)
id3 = P(NullableArray(rand([symbol(string("id", i)) for i=1:Int(N/K)], N))), # small groups (char)
id4 = P(NullableArray(rand(1:K, N))), # large groups (int)
id5 = P(NullableArray(rand(1:K, N))), # large groups (int)
id6 = P(NullableArray(rand(1:Int(N/K), N))), # small groups (int)
v1 = P(NullableArray(rand(1:5, N))), # int in range [1,5]
v2 = P(NullableArray(rand(1:5, N))), # int in range [1,5]
v3 = P(NullableArray(rand(N))) # numeric e.g. 23.5749
);


function dt_timings(D)
@time @by(D, :id1, sv =sum(:v1));
@time @by(D, :id1, sv =sum(:v1));
@time @by(D, [:id1, :id2], sv =sum(:v1));
@time @by(D, [:id1, :id2], sv =sum(:v1));
@time @by(D, :id3, sv = sum(:v1), mv3 = mean(:v3));
@time @by(D, :id3, sv = sum(:v1), mv3 = mean(:v3));
@time aggregate(D[[4,7:9;]], :id4, mean);
@time aggregate(D[[4,7:9;]], :id4, mean);
@time aggregate(D[[6,7:9;]], :id6, sum);
@time aggregate(D[[6,7:9;]], :id6, sum);
return
end

dt_timings(DA)
dt_timings(DPDA)
dt_timings(DNA)
dt_timings(DDA)

@profile @by(D, :id1, sv =sum(:v1));