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August 29, 2015 14:01
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Python vs. Go performance ... reading a set of values from a file
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import time | |
def readFile(filename): | |
res = {} | |
for line in open(filename).read().split("\n"): | |
if line: | |
res[line] = True | |
return res | |
if __name__ == '__main__': | |
start_time = time.time() | |
res = readFile("hash.db") | |
duration = time.time() - start_time | |
print "reading %d entries in %f seconds" % (len(res), duration) |
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package main | |
import ( | |
"fmt" | |
"os" | |
"time" | |
"bytes" | |
) | |
type set map[string]bool | |
func readFile(filename string) set { | |
file, err := os.Open(filename) | |
if err != nil { | |
panic(err) | |
} | |
stat, err := file.Stat() | |
if err != nil { | |
panic(err) | |
} | |
buffer := make([]byte, stat.Size()) | |
_,err = file.Read(buffer) | |
if err != nil { | |
panic(err) | |
} | |
res := make(set) | |
for _,value := range bytes.Split(buffer, []byte("\n")) { | |
s := string(value) | |
if s != "" { | |
res[s] = true | |
} | |
} | |
return res | |
} | |
func main() { | |
start_time := time.Now() | |
res := readFile("hash.db") | |
duration := time.Now().Sub(start_time) | |
fmt.Printf("read %d entries in %s\n", len(res), duration) | |
} |
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import time | |
def readFile(filename): | |
res = set() | |
for line in open(filename).read().split("\n"): | |
if line: | |
res.add(line) | |
return res | |
if __name__ == '__main__': | |
start_time = time.time() | |
res = readFile("hash.db") | |
duration = time.time() - start_time | |
print "reading %d entries in %f seconds" % (len(res), duration) |
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import hashlib | |
def makeSet(size): | |
res = set() | |
for i in range(size): | |
value = hashlib.sha1(str(i)).hexdigest() | |
res.add(value) | |
return res | |
def makeFile(filename, size): | |
data = makeSet(size) | |
open(filename,"w").write("\n".join(data) + '\n') | |
if __name__ == '__main__': | |
makeFile("hash.db", 1000 * 1000) |
Ok ... the hint on the mailing list was give a size hint to make: So the cache-improved.go is doing this and is now on the same performance level as the Python implementation.
Go improved output: read 1000000 entries in 468.880726ms
package main
import (
"fmt"
"os"
"time"
"bytes"
)
type set map[string]struct{}
func readFile(filename string) set {
file, err := os.Open(filename)
if err != nil {
panic(err)
}
stat, err := file.Stat()
if err != nil {
panic(err)
}
buffer := make([]byte, stat.Size())
_,err = file.Read(buffer)
if err != nil {
panic(err)
}
splitBuffer := bytes.Split(buffer, []byte("\n"))
res := make(set, len(splitBuffer))
for _,value := range splitBuffer {
s := string(value)
if s != "" {
res[s] = struct{}{}
}
}
return res
}
func main() {
start_time := time.Now()
res := readFile("hash.db")
duration := time.Now().Sub(start_time)
fmt.Printf("read %d entries in %s\n", len(res), duration)
}
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A couple things you can try (not sure how much they will help):
map[string]struct{}
. For a large set, this should reduce the overall size noticeably.s
and usemap[string(value)]
, which is now free (no allocation).Also noting that most of the time is in the map assignment may be a red herring, unless you compare that directly to the amount of time that python spends in set assignment.