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// +build darwin linux
// run
// Copyright 2013 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
// Test that maps don't go quadratic for NaNs and other values.
package main
import (
"fmt"
"math"
"time"
)
// checkLinear asserts that the running time of f(n) is in O(n).
// tries is the initial number of iterations.
func checkLinear(typ string, tries int, f func(n int)) {
// Depending on the machine and OS, this test might be too fast
// to measure with accurate enough granularity. On failure,
// make it run longer, hoping that the timing granularity
// is eventually sufficient.
timeF := func(n int) time.Duration {
t1 := time.Now()
f(n)
return time.Since(t1)
}
t0 := time.Now()
n := tries
fails := 0
for {
t1 := timeF(n)
t2 := timeF(2 * n)
// should be 2x (linear); allow up to 3x
if t2 < 3*t1 {
if false {
fmt.Println(typ, "\t", time.Since(t0))
}
return
}
// If n ops run in under a second and the ratio
// doesn't work out, make n bigger, trying to reduce
// the effect that a constant amount of overhead has
// on the computed ratio.
if t1 < 1*time.Second {
n *= 2
continue
}
// Once the test runs long enough for n ops,
// try to get the right ratio at least once.
// If five in a row all fail, give up.
if fails++; fails >= 5 {
panic(fmt.Sprintf("%s: too slow: %d inserts: %v; %d inserts: %v\n",
typ, n, t1, 2*n, t2))
}
}
}
type I interface {
f()
}
type C int
func (C) f() {}
func main() {
// NaNs. ~31ms on a 1.6GHz Zeon.
checkLinear("NaN", 30000, func(n int) {
m := map[float64]int{}
nan := math.NaN()
for i := 0; i < n; i++ {
m[nan] = 1
}
if len(m) != n {
panic("wrong size map after nan insertion")
}
})
// ~6ms on a 1.6GHz Zeon.
checkLinear("eface", 10000, func(n int) {
m := map[interface{}]int{}
for i := 0; i < n; i++ {
m[i] = 1
}
})
// ~7ms on a 1.6GHz Zeon.
// Regression test for CL 119360043.
checkLinear("iface", 10000, func(n int) {
m := map[I]int{}
for i := 0; i < n; i++ {
m[C(i)] = 1
}
})
// ~6ms on a 1.6GHz Zeon.
checkLinear("int", 10000, func(n int) {
m := map[int]int{}
for i := 0; i < n; i++ {
m[i] = 1
}
})
// ~18ms on a 1.6GHz Zeon.
checkLinear("string", 10000, func(n int) {
m := map[string]int{}
for i := 0; i < n; i++ {
m[fmt.Sprint(i)] = 1
}
})
// ~6ms on a 1.6GHz Zeon.
checkLinear("float32", 10000, func(n int) {
m := map[float32]int{}
for i := 0; i < n; i++ {
m[float32(i)] = 1
}
})
// ~6ms on a 1.6GHz Zeon.
checkLinear("float64", 10000, func(n int) {
m := map[float64]int{}
for i := 0; i < n; i++ {
m[float64(i)] = 1
}
})
// ~22ms on a 1.6GHz Zeon.
checkLinear("complex64", 10000, func(n int) {
m := map[complex64]int{}
for i := 0; i < n; i++ {
m[complex(float32(i), float32(i))] = 1
}
})
// ~32ms on a 1.6GHz Zeon.
checkLinear("complex128", 10000, func(n int) {
m := map[complex128]int{}
for i := 0; i < n; i++ {
m[complex(float64(i), float64(i))] = 1
}
})
// ~70ms on a 1.6GHz Zeon.
// The iterate/delete idiom currently takes expected
// O(n lg n) time. Fortunately, the checkLinear test
// leaves enough wiggle room to include n lg n time
// (it actually tests for O(n^log_2(3)).
// To prevent false positives, average away variation
// by doing multiple rounds within a single run.
checkLinear("iterdelete", 2500, func(n int) {
for round := 0; round < 4; round++ {
m := map[int]int{}
for i := 0; i < n; i++ {
m[i] = i
}
for i := 0; i < n; i++ {
for k := range m {
delete(m, k)
break
}
}
}
})
}
|
