This program is supposed to read a file consisting of pairs of ints (one pair per line) and remove duplicate pairs. While it works on small files, it throws a runtime error on huge files (say a file of 1.5 GB). Initially, I thought that it is the map data structure which is causing this, but even after commenting it out, it still runs out of memory. Any ideas why this is happening? How to rectify it? Here's a data file on which it runs out of memory: http://snap.stanford.edu/data/com-Orkut.html
该程序应该读取包含一对ints(每行一对)和删除重复对的文件。当它在小文件上运行时,它会在巨大的文件上抛出一个运行时错误(比如一个1.5 GB的文件)。最初,我认为是地图数据结构导致了这一点,但即使在注释掉它之后,它仍然没有内存。有什么想法吗?如何纠正它吗?这是一个内存不足的数据文件:http://snap.stanford.edu/data/com-Orkut.html。
package main
import (
"fmt"
"bufio"
"os"
"strings"
"strconv"
)
func main() {
file, err := os.Open(os.Args[1])
if err != nil {
panic(err.Error())
}
defer file.Close()
type Edge struct {
u, v int
}
//seen := make(map[Edge]bool)
edges := []Edge{}
scanner := bufio.NewScanner(file)
for i, _ := strconv.Atoi(os.Args[2]); i > 0; i-- {
scanner.Scan()
}
for scanner.Scan() {
str := scanner.Text()
edge := strings.Split(str, ",")
u, _ := strconv.Atoi(edge[0])
v, _ := strconv.Atoi(edge[1])
var key Edge
if u < v {
key = Edge{u,v}
} else {
key = Edge{v,u}
}
//if seen[key] {
// continue
//}
//seen[key] = true
edges = append(edges, key)
}
for _, e := range edges {
s := strconv.Itoa(e.u) + "," + strconv.Itoa(e.v)
fmt.Println(s)
}
}
A sample input is given below. The program can be run as follows (where the last input says how many lines to skip). go run undup.go a.txt 1
下面给出了一个示例输入。这个程序可以运行如下(最后一个输入说要跳过多少行)。去undup运行。去一个。txt 1
# 3072441,117185083
1,2
1,3
1,4
1,5
1,6
1,7
1,8
2 个解决方案
#1
5
I looked at this file: com-orkut.ungraph.txt
and it contains 117,185,082 lines. The way your data is structured, that's at least 16 bytes per line. (Edge is two 64bit ints) That alone is 1.7GB. I have had this problem in the past, and it can be a tricky one. Are you trying to solve this for a specific use case (the file in question) or the general case?
我查看了这个文件:com-orkut.ungraph。txt和它包含117,185082行。数据结构的方式,每一行至少有16个字节。(Edge是两个64位的ints),只有1.7GB。过去我曾遇到过这个问题,但它可能是一个棘手的问题。您是否正在尝试为特定的用例(问题中的文件)或一般情况解决这个问题?
In the specific case there are a few things about the data you could leverage: (1) the keys are sorted and (2) it looks it stores every connection twice, (3) the numbers don't seem huge. Here are a couple ideas:
在特定的情况下,可以利用的数据有几处:(1)键是有序的,(2)它会将每个连接存储两次,(3)这些数字看起来并不大。这里有一些想法:
-
If you use a smaller type for the key you will use less memory. Try a
uint32
.如果您使用较小类型的键,您将使用较少的内存。试一试uint32。
-
You could stream (without using a map) the keys to another file by simply seeing if the 2nd column is greater than the first:
您可以通过简单地查看第二列是否大于第一列来流(不使用映射)到另一个文件的键:
if u < v { // write the key to another file } else { // skip it because v will eventually show v -> u }
For the general case there are a couple strategies you could use:
对于一般情况,你可以使用以下几种策略:
-
If the order of the resulting list doesn't matter: Use an on-disk hash table to store the map. There are a bunch of these: leveldb, sqlite, tokyo tyrant, ... A really nice one for go is bolt.
如果结果列表的顺序无关紧要:使用on-disk哈希表来存储映射。有很多这样的例子:leveldb, sqlite,东京暴君,……真是个不错的选择。
In your for loop you would just check to see if a bucket contains the given key. (You can convert the ints into byte slices using encoding/binary) If it does, just skip it and continue. You will need to move the second for loop processing step into the first for loop so that you don't have to store all the keys.
在for循环中,您将检查一个bucket是否包含给定的键。(您可以使用编码/二进制将ints转换成字节片),如果有的话,跳过它继续。您需要将第二个for循环处理步骤插入到第一个for循环中,这样就不必存储所有的键。
-
If the order of the resulting list does matter (and you can't guarantee the input is in order): You can also use an on-disk hash table, but it needs to be sorted. Bolt is sorted so that will work. Add all the keys to it, then traverse it in the second loop.
如果结果列表的顺序很重要(并且您不能保证输入是有序的):您也可以使用on-disk哈希表,但是需要对其进行排序。螺栓被排好,这样就可以工作了。添加所有的键,然后在第二个循环中遍历它。
Here is an example: (this program will take a while to run with 100 million records)
这里有一个例子:(这个程序需要一段时间才能运行1亿条记录)
package main
import (
"bufio"
"encoding/binary"
"fmt"
"github.com/boltdb/bolt"
"os"
"strconv"
"strings"
)
type Edge struct {
u, v int
}
func FromKey(bs []byte) Edge {
return Edge{int(binary.BigEndian.Uint64(bs[:8])), int(binary.BigEndian.Uint64(bs[8:]))}
}
func (e Edge) Key() [16]byte {
var k [16]byte
binary.BigEndian.PutUint64(k[:8], uint64(e.u))
binary.BigEndian.PutUint64(k[8:], uint64(e.v))
return k
}
func main() {
file, err := os.Open(os.Args[1])
if err != nil {
panic(err.Error())
}
defer file.Close()
scanner := bufio.NewScanner(file)
for i, _ := strconv.Atoi(os.Args[2]); i > 0; i-- {
scanner.Scan()
}
db, _ := bolt.Open("ex.db", 0777, nil)
defer db.Close()
bucketName := []byte("edges")
db.Update(func(tx *bolt.Tx) error {
tx.CreateBucketIfNotExists(bucketName)
return nil
})
batchSize := 10000
total := 0
batch := make([]Edge, 0, batchSize)
writeBatch := func() {
total += len(batch)
fmt.Println("write batch. total:", total)
db.Update(func(tx *bolt.Tx) error {
bucket := tx.Bucket(bucketName)
for _, edge := range batch {
key := edge.Key()
bucket.Put(key[:], nil)
}
return nil
})
}
for scanner.Scan() {
str := scanner.Text()
edge := strings.Split(str, "\t")
u, _ := strconv.Atoi(edge[0])
v, _ := strconv.Atoi(edge[1])
var key Edge
if u < v {
key = Edge{u, v}
} else {
key = Edge{v, u}
}
batch = append(batch, key)
if len(batch) == batchSize {
writeBatch()
// reset the batch length to 0
batch = batch[:0]
}
}
// write anything leftover
writeBatch()
db.View(func(tx *bolt.Tx) error {
tx.Bucket(bucketName).ForEach(func(k, v []byte) error {
edge := FromKey(k)
fmt.Println(edge)
return nil
})
return nil
})
}
#2
2
You are squandering memory. Here's how to rectify it.
你是浪费内存。以下是如何矫正它的方法。
You give the sample input a.txt
, 48 bytes.
你给出样本输入a。三、48字节。
# 3072441,117185083
1,2
1,3
1,4
1,5
On http://snap.stanford.edu/data/com-Orkut.html, I found http://snap.stanford.edu/data/bigdata/communities/com-orkut.ungraph.txt.gz, 1.8 GB uncompressed, 117,185,083 edges.
在http://snap.stanford.edu/data/com-Orkut.html中,我找到了http://snap.stanford.edu/data/bigdata/ties/com-orku .ungraph.txt.gz, 1.8 GB未压缩,117,185,083条边。
# Undirected graph: ../../data/output/orkut.txt
# Orkut
# Nodes: 3072441 Edges: 117185083
# FromNodeId ToNodeId
1 2
1 3
1 4
1 5
On http://socialnetworks.mpi-sws.org/data-imc2007.html, I found http://socialnetworks.mpi-sws.mpg.de/data/orkut-links.txt.gz, 3.4 GB uncompressed, 223,534,301 edges.
在http://socialnetworks.mpi-sws.org/data-imc2007.html中,我找到了http://socialnetworks.mpi-sws.mpg.de/data/orkut-links.txt.gz, 3.4 GB未压缩,223,534,301条边。
1 2
1 3
1 4
1 5
Since they are similar, one program can handle all formats.
因为它们是相似的,一个程序可以处理所有的格式。
Your Edge
type is
你的边缘类型是
type Edge struct {
u, v int
}
which is 16 bytes on a 64-bit architecture.
它在64位体系结构上是16个字节。
Use
使用
type Edge struct {
U, V uint32
}
which is 8 bytes, it is adequate.
这是8个字节,足够了。
If the capacity of a slice is not large enough to fit the additional values, append
allocates a new, sufficiently large underlying array that fits both the existing slice elements and the additional values. Otherwise, append
re-uses the underlying array. For a large slice, the new array is 1.25 times the size of the old array. While the old array is being copied to the new array, 1 + 1.25 = 2.25 times the memory for the old array is required. Therefore, allocate the underlying array so that all values fit.
如果slice的容量不足以满足附加的值,append就会分配一个新的、足够大的底层数组,它既符合现有的片元素,也符合附加的值。否则,append将重新使用底层数组。对于较大的部分,新数组的大小是旧数组的1.25倍。当旧数组被复制到新数组时,1 + 1.25 = 2.25倍的旧数组的内存是必需的。因此,分配底层数组以使所有值都适合。
make(T, n)
initializes map of type T with initial space for n elements. Provide a value for n to limit the cost of reorganization and fragmentation as elements are added. Hashing functions are often imperfect which leads to wasted space. Eliminate the map as it's unneccesary. To eliminate duplicates, sort the slice in place and move the unique elements down.
make(T, n)初始化T类型的map,初始空间为n个元素。为n提供一个值,以便在添加元素时限制重组和碎片化的成本。散列函数常常是不完美的,从而导致浪费空间。把地图去掉,因为它是不存在的。为了消除重复,将切片进行排序,并将独特的元素移到下面。
A string
is immutable, therefore a new string
is allocated for scanner.Text()
to convert from a byte
slice buffer. To parse numbers we use strconv
. To minimize temporary allocations, use scanner.Bytes()
and adapt strconv.ParseUint
to accept a byte array argument (bytconv
).
字符串是不可变的,因此为scanner.Text()分配了一个新的字符串,用于从字节片缓冲区转换。为了解析数字,我们使用strconv。为了最小化临时分配,可以使用scanner.Bytes()和adapt strconv。ParseUint接受字节数组参数(bytconv)。
For example,
例如,
orkut.go
orkut.go
package main
import (
"bufio"
"bytes"
"errors"
"fmt"
"os"
"runtime"
"sort"
"strconv"
)
type Edge struct {
U, V uint32
}
func (e Edge) String() string {
return fmt.Sprintf("%d,%d", e.U, e.V)
}
type ByKey []Edge
func (a ByKey) Len() int { return len(a) }
func (a ByKey) Swap(i, j int) { a[i], a[j] = a[j], a[i] }
func (a ByKey) Less(i, j int) bool {
if a[i].U < a[j].U {
return true
}
if a[i].U == a[j].U && a[i].V < a[j].V {
return true
}
return false
}
func countEdges(scanner *bufio.Scanner) int {
var nNodes, nEdges int
for scanner.Scan() {
line := scanner.Bytes()
if !(len(line) > 0 && line[0] == '#') {
nEdges++
continue
}
n, err := fmt.Sscanf(string(line), "# Nodes: %d Edges: %d", &nNodes, &nEdges)
if err != nil || n != 2 {
n, err = fmt.Sscanf(string(line), "# %d,%d", &nNodes, &nEdges)
if err != nil || n != 2 {
continue
}
}
fmt.Println(string(line))
break
}
if err := scanner.Err(); err != nil {
panic(err.Error())
}
fmt.Println(nEdges)
return nEdges
}
func loadEdges(filename string) []Edge {
file, err := os.Open(filename)
if err != nil {
panic(err.Error())
}
defer file.Close()
scanner := bufio.NewScanner(file)
nEdges := countEdges(scanner)
edges := make([]Edge, 0, nEdges)
offset, err := file.Seek(0, os.SEEK_SET)
if err != nil || offset != 0 {
panic(err.Error())
}
var sep byte = '\t'
scanner = bufio.NewScanner(file)
for scanner.Scan() {
line := scanner.Bytes()
if len(line) > 0 && line[0] == '#' {
continue
}
i := bytes.IndexByte(line, sep)
if i < 0 || i+1 >= len(line) {
sep = ','
i = bytes.IndexByte(line, sep)
if i < 0 || i+1 >= len(line) {
err := errors.New("Invalid line format: " + string(line))
panic(err.Error())
}
}
u, err := ParseUint(line[:i], 10, 32)
if err != nil {
panic(err.Error())
}
v, err := ParseUint(line[i+1:], 10, 32)
if err != nil {
panic(err.Error())
}
if u > v {
u, v = v, u
}
edges = append(edges, Edge{uint32(u), uint32(v)})
}
if err := scanner.Err(); err != nil {
panic(err.Error())
}
if len(edges) <= 1 {
return edges
}
sort.Sort(ByKey(edges))
j := 0
i := j + 1
for ; i < len(edges); i, j = i+1, j+1 {
if edges[i] == edges[j] {
break
}
}
for ; i < len(edges); i++ {
if edges[i] != edges[j] {
j++
edges[j] = edges[i]
}
}
edges = edges[:j+1]
return edges
}
func main() {
if len(os.Args) <= 1 {
err := errors.New("Missing file name")
panic(err.Error())
}
filename := os.Args[1]
fmt.Println(filename)
edges := loadEdges(filename)
var ms runtime.MemStats
runtime.ReadMemStats(&ms)
fmt.Println(ms.Alloc, ms.TotalAlloc, ms.Sys, ms.Mallocs, ms.Frees)
fmt.Println(len(edges), cap(edges))
for i, e := range edges {
fmt.Println(e)
if i >= 10 {
break
}
}
}
// bytconv from strconv
// Return the first number n such that n*base >= 1<<64.
func cutoff64(base int) uint64 {
if base < 2 {
return 0
}
return (1<<64-1)/uint64(base) + 1
}
// ParseUint is like ParseInt but for unsigned numbers.
func ParseUint(s []byte, base int, bitSize int) (n uint64, err error) {
var cutoff, maxVal uint64
if bitSize == 0 {
bitSize = int(strconv.IntSize)
}
s0 := s
switch {
case len(s) < 1:
err = strconv.ErrSyntax
goto Error
case 2 <= base && base <= 36:
// valid base; nothing to do
case base == 0:
// Look for octal, hex prefix.
switch {
case s[0] == '0' && len(s) > 1 && (s[1] == 'x' || s[1] == 'X'):
base = 16
s = s[2:]
if len(s) < 1 {
err = strconv.ErrSyntax
goto Error
}
case s[0] == '0':
base = 8
default:
base = 10
}
default:
err = errors.New("invalid base " + strconv.Itoa(base))
goto Error
}
n = 0
cutoff = cutoff64(base)
maxVal = 1<<uint(bitSize) - 1
for i := 0; i < len(s); i++ {
var v byte
d := s[i]
switch {
case '0' <= d && d <= '9':
v = d - '0'
case 'a' <= d && d <= 'z':
v = d - 'a' + 10
case 'A' <= d && d <= 'Z':
v = d - 'A' + 10
default:
n = 0
err = strconv.ErrSyntax
goto Error
}
if int(v) >= base {
n = 0
err = strconv.ErrSyntax
goto Error
}
if n >= cutoff {
// n*base overflows
n = 1<<64 - 1
err = strconv.ErrRange
goto Error
}
n *= uint64(base)
n1 := n + uint64(v)
if n1 < n || n1 > maxVal {
// n+v overflows
n = 1<<64 - 1
err = strconv.ErrRange
goto Error
}
n = n1
}
return n, nil
Error:
return n, &strconv.NumError{"ParseUint", string(s0), err}
}
Output:
输出:
$ go build orkut.go
$ time ./orkut ~/release-orkut-links.txt
/home/peter/release-orkut-links.txt
223534301
1788305680 1788327856 1904683256 135 50
117185083 223534301
1,2
1,3
1,4
1,5
1,6
1,7
1,8
1,9
1,10
1,11
1,12
real 2m53.203s
user 2m51.584s
sys 0m1.628s
$
The orkut.go
program with the release-orkut-links.txt
file (3,372,855,860 (3.4 GB) bytes with 223,534,301 edges) uses about 1.8 GiB of memory. After eliminating duplicates, 117,185,083 unique edges remain. This matches the 117,185,083 unique edge com-orkut.ungraph.txt
file.
orkut。go程序与发布-orkut链接。txt文件(3372,855,860 (3.4 GB)字节与223,534,301条边)使用约1.8 GiB的内存。消除重复后,保留了117,185,083个独特的边。这与117,185,083独特的edge com-orku .ungraph相匹配。txt文件。
With 8 GB of memory on your machine, you can load much larger files.
在您的机器上有8 GB的内存,您可以加载更大的文件。
#1
5
I looked at this file: com-orkut.ungraph.txt
and it contains 117,185,082 lines. The way your data is structured, that's at least 16 bytes per line. (Edge is two 64bit ints) That alone is 1.7GB. I have had this problem in the past, and it can be a tricky one. Are you trying to solve this for a specific use case (the file in question) or the general case?
我查看了这个文件:com-orkut.ungraph。txt和它包含117,185082行。数据结构的方式,每一行至少有16个字节。(Edge是两个64位的ints),只有1.7GB。过去我曾遇到过这个问题,但它可能是一个棘手的问题。您是否正在尝试为特定的用例(问题中的文件)或一般情况解决这个问题?
In the specific case there are a few things about the data you could leverage: (1) the keys are sorted and (2) it looks it stores every connection twice, (3) the numbers don't seem huge. Here are a couple ideas:
在特定的情况下,可以利用的数据有几处:(1)键是有序的,(2)它会将每个连接存储两次,(3)这些数字看起来并不大。这里有一些想法:
-
If you use a smaller type for the key you will use less memory. Try a
uint32
.如果您使用较小类型的键,您将使用较少的内存。试一试uint32。
-
You could stream (without using a map) the keys to another file by simply seeing if the 2nd column is greater than the first:
您可以通过简单地查看第二列是否大于第一列来流(不使用映射)到另一个文件的键:
if u < v { // write the key to another file } else { // skip it because v will eventually show v -> u }
For the general case there are a couple strategies you could use:
对于一般情况,你可以使用以下几种策略:
-
If the order of the resulting list doesn't matter: Use an on-disk hash table to store the map. There are a bunch of these: leveldb, sqlite, tokyo tyrant, ... A really nice one for go is bolt.
如果结果列表的顺序无关紧要:使用on-disk哈希表来存储映射。有很多这样的例子:leveldb, sqlite,东京暴君,……真是个不错的选择。
In your for loop you would just check to see if a bucket contains the given key. (You can convert the ints into byte slices using encoding/binary) If it does, just skip it and continue. You will need to move the second for loop processing step into the first for loop so that you don't have to store all the keys.
在for循环中,您将检查一个bucket是否包含给定的键。(您可以使用编码/二进制将ints转换成字节片),如果有的话,跳过它继续。您需要将第二个for循环处理步骤插入到第一个for循环中,这样就不必存储所有的键。
-
If the order of the resulting list does matter (and you can't guarantee the input is in order): You can also use an on-disk hash table, but it needs to be sorted. Bolt is sorted so that will work. Add all the keys to it, then traverse it in the second loop.
如果结果列表的顺序很重要(并且您不能保证输入是有序的):您也可以使用on-disk哈希表,但是需要对其进行排序。螺栓被排好,这样就可以工作了。添加所有的键,然后在第二个循环中遍历它。
Here is an example: (this program will take a while to run with 100 million records)
这里有一个例子:(这个程序需要一段时间才能运行1亿条记录)
package main
import (
"bufio"
"encoding/binary"
"fmt"
"github.com/boltdb/bolt"
"os"
"strconv"
"strings"
)
type Edge struct {
u, v int
}
func FromKey(bs []byte) Edge {
return Edge{int(binary.BigEndian.Uint64(bs[:8])), int(binary.BigEndian.Uint64(bs[8:]))}
}
func (e Edge) Key() [16]byte {
var k [16]byte
binary.BigEndian.PutUint64(k[:8], uint64(e.u))
binary.BigEndian.PutUint64(k[8:], uint64(e.v))
return k
}
func main() {
file, err := os.Open(os.Args[1])
if err != nil {
panic(err.Error())
}
defer file.Close()
scanner := bufio.NewScanner(file)
for i, _ := strconv.Atoi(os.Args[2]); i > 0; i-- {
scanner.Scan()
}
db, _ := bolt.Open("ex.db", 0777, nil)
defer db.Close()
bucketName := []byte("edges")
db.Update(func(tx *bolt.Tx) error {
tx.CreateBucketIfNotExists(bucketName)
return nil
})
batchSize := 10000
total := 0
batch := make([]Edge, 0, batchSize)
writeBatch := func() {
total += len(batch)
fmt.Println("write batch. total:", total)
db.Update(func(tx *bolt.Tx) error {
bucket := tx.Bucket(bucketName)
for _, edge := range batch {
key := edge.Key()
bucket.Put(key[:], nil)
}
return nil
})
}
for scanner.Scan() {
str := scanner.Text()
edge := strings.Split(str, "\t")
u, _ := strconv.Atoi(edge[0])
v, _ := strconv.Atoi(edge[1])
var key Edge
if u < v {
key = Edge{u, v}
} else {
key = Edge{v, u}
}
batch = append(batch, key)
if len(batch) == batchSize {
writeBatch()
// reset the batch length to 0
batch = batch[:0]
}
}
// write anything leftover
writeBatch()
db.View(func(tx *bolt.Tx) error {
tx.Bucket(bucketName).ForEach(func(k, v []byte) error {
edge := FromKey(k)
fmt.Println(edge)
return nil
})
return nil
})
}
#2
2
You are squandering memory. Here's how to rectify it.
你是浪费内存。以下是如何矫正它的方法。
You give the sample input a.txt
, 48 bytes.
你给出样本输入a。三、48字节。
# 3072441,117185083
1,2
1,3
1,4
1,5
On http://snap.stanford.edu/data/com-Orkut.html, I found http://snap.stanford.edu/data/bigdata/communities/com-orkut.ungraph.txt.gz, 1.8 GB uncompressed, 117,185,083 edges.
在http://snap.stanford.edu/data/com-Orkut.html中,我找到了http://snap.stanford.edu/data/bigdata/ties/com-orku .ungraph.txt.gz, 1.8 GB未压缩,117,185,083条边。
# Undirected graph: ../../data/output/orkut.txt
# Orkut
# Nodes: 3072441 Edges: 117185083
# FromNodeId ToNodeId
1 2
1 3
1 4
1 5
On http://socialnetworks.mpi-sws.org/data-imc2007.html, I found http://socialnetworks.mpi-sws.mpg.de/data/orkut-links.txt.gz, 3.4 GB uncompressed, 223,534,301 edges.
在http://socialnetworks.mpi-sws.org/data-imc2007.html中,我找到了http://socialnetworks.mpi-sws.mpg.de/data/orkut-links.txt.gz, 3.4 GB未压缩,223,534,301条边。
1 2
1 3
1 4
1 5
Since they are similar, one program can handle all formats.
因为它们是相似的,一个程序可以处理所有的格式。
Your Edge
type is
你的边缘类型是
type Edge struct {
u, v int
}
which is 16 bytes on a 64-bit architecture.
它在64位体系结构上是16个字节。
Use
使用
type Edge struct {
U, V uint32
}
which is 8 bytes, it is adequate.
这是8个字节,足够了。
If the capacity of a slice is not large enough to fit the additional values, append
allocates a new, sufficiently large underlying array that fits both the existing slice elements and the additional values. Otherwise, append
re-uses the underlying array. For a large slice, the new array is 1.25 times the size of the old array. While the old array is being copied to the new array, 1 + 1.25 = 2.25 times the memory for the old array is required. Therefore, allocate the underlying array so that all values fit.
如果slice的容量不足以满足附加的值,append就会分配一个新的、足够大的底层数组,它既符合现有的片元素,也符合附加的值。否则,append将重新使用底层数组。对于较大的部分,新数组的大小是旧数组的1.25倍。当旧数组被复制到新数组时,1 + 1.25 = 2.25倍的旧数组的内存是必需的。因此,分配底层数组以使所有值都适合。
make(T, n)
initializes map of type T with initial space for n elements. Provide a value for n to limit the cost of reorganization and fragmentation as elements are added. Hashing functions are often imperfect which leads to wasted space. Eliminate the map as it's unneccesary. To eliminate duplicates, sort the slice in place and move the unique elements down.
make(T, n)初始化T类型的map,初始空间为n个元素。为n提供一个值,以便在添加元素时限制重组和碎片化的成本。散列函数常常是不完美的,从而导致浪费空间。把地图去掉,因为它是不存在的。为了消除重复,将切片进行排序,并将独特的元素移到下面。
A string
is immutable, therefore a new string
is allocated for scanner.Text()
to convert from a byte
slice buffer. To parse numbers we use strconv
. To minimize temporary allocations, use scanner.Bytes()
and adapt strconv.ParseUint
to accept a byte array argument (bytconv
).
字符串是不可变的,因此为scanner.Text()分配了一个新的字符串,用于从字节片缓冲区转换。为了解析数字,我们使用strconv。为了最小化临时分配,可以使用scanner.Bytes()和adapt strconv。ParseUint接受字节数组参数(bytconv)。
For example,
例如,
orkut.go
orkut.go
package main
import (
"bufio"
"bytes"
"errors"
"fmt"
"os"
"runtime"
"sort"
"strconv"
)
type Edge struct {
U, V uint32
}
func (e Edge) String() string {
return fmt.Sprintf("%d,%d", e.U, e.V)
}
type ByKey []Edge
func (a ByKey) Len() int { return len(a) }
func (a ByKey) Swap(i, j int) { a[i], a[j] = a[j], a[i] }
func (a ByKey) Less(i, j int) bool {
if a[i].U < a[j].U {
return true
}
if a[i].U == a[j].U && a[i].V < a[j].V {
return true
}
return false
}
func countEdges(scanner *bufio.Scanner) int {
var nNodes, nEdges int
for scanner.Scan() {
line := scanner.Bytes()
if !(len(line) > 0 && line[0] == '#') {
nEdges++
continue
}
n, err := fmt.Sscanf(string(line), "# Nodes: %d Edges: %d", &nNodes, &nEdges)
if err != nil || n != 2 {
n, err = fmt.Sscanf(string(line), "# %d,%d", &nNodes, &nEdges)
if err != nil || n != 2 {
continue
}
}
fmt.Println(string(line))
break
}
if err := scanner.Err(); err != nil {
panic(err.Error())
}
fmt.Println(nEdges)
return nEdges
}
func loadEdges(filename string) []Edge {
file, err := os.Open(filename)
if err != nil {
panic(err.Error())
}
defer file.Close()
scanner := bufio.NewScanner(file)
nEdges := countEdges(scanner)
edges := make([]Edge, 0, nEdges)
offset, err := file.Seek(0, os.SEEK_SET)
if err != nil || offset != 0 {
panic(err.Error())
}
var sep byte = '\t'
scanner = bufio.NewScanner(file)
for scanner.Scan() {
line := scanner.Bytes()
if len(line) > 0 && line[0] == '#' {
continue
}
i := bytes.IndexByte(line, sep)
if i < 0 || i+1 >= len(line) {
sep = ','
i = bytes.IndexByte(line, sep)
if i < 0 || i+1 >= len(line) {
err := errors.New("Invalid line format: " + string(line))
panic(err.Error())
}
}
u, err := ParseUint(line[:i], 10, 32)
if err != nil {
panic(err.Error())
}
v, err := ParseUint(line[i+1:], 10, 32)
if err != nil {
panic(err.Error())
}
if u > v {
u, v = v, u
}
edges = append(edges, Edge{uint32(u), uint32(v)})
}
if err := scanner.Err(); err != nil {
panic(err.Error())
}
if len(edges) <= 1 {
return edges
}
sort.Sort(ByKey(edges))
j := 0
i := j + 1
for ; i < len(edges); i, j = i+1, j+1 {
if edges[i] == edges[j] {
break
}
}
for ; i < len(edges); i++ {
if edges[i] != edges[j] {
j++
edges[j] = edges[i]
}
}
edges = edges[:j+1]
return edges
}
func main() {
if len(os.Args) <= 1 {
err := errors.New("Missing file name")
panic(err.Error())
}
filename := os.Args[1]
fmt.Println(filename)
edges := loadEdges(filename)
var ms runtime.MemStats
runtime.ReadMemStats(&ms)
fmt.Println(ms.Alloc, ms.TotalAlloc, ms.Sys, ms.Mallocs, ms.Frees)
fmt.Println(len(edges), cap(edges))
for i, e := range edges {
fmt.Println(e)
if i >= 10 {
break
}
}
}
// bytconv from strconv
// Return the first number n such that n*base >= 1<<64.
func cutoff64(base int) uint64 {
if base < 2 {
return 0
}
return (1<<64-1)/uint64(base) + 1
}
// ParseUint is like ParseInt but for unsigned numbers.
func ParseUint(s []byte, base int, bitSize int) (n uint64, err error) {
var cutoff, maxVal uint64
if bitSize == 0 {
bitSize = int(strconv.IntSize)
}
s0 := s
switch {
case len(s) < 1:
err = strconv.ErrSyntax
goto Error
case 2 <= base && base <= 36:
// valid base; nothing to do
case base == 0:
// Look for octal, hex prefix.
switch {
case s[0] == '0' && len(s) > 1 && (s[1] == 'x' || s[1] == 'X'):
base = 16
s = s[2:]
if len(s) < 1 {
err = strconv.ErrSyntax
goto Error
}
case s[0] == '0':
base = 8
default:
base = 10
}
default:
err = errors.New("invalid base " + strconv.Itoa(base))
goto Error
}
n = 0
cutoff = cutoff64(base)
maxVal = 1<<uint(bitSize) - 1
for i := 0; i < len(s); i++ {
var v byte
d := s[i]
switch {
case '0' <= d && d <= '9':
v = d - '0'
case 'a' <= d && d <= 'z':
v = d - 'a' + 10
case 'A' <= d && d <= 'Z':
v = d - 'A' + 10
default:
n = 0
err = strconv.ErrSyntax
goto Error
}
if int(v) >= base {
n = 0
err = strconv.ErrSyntax
goto Error
}
if n >= cutoff {
// n*base overflows
n = 1<<64 - 1
err = strconv.ErrRange
goto Error
}
n *= uint64(base)
n1 := n + uint64(v)
if n1 < n || n1 > maxVal {
// n+v overflows
n = 1<<64 - 1
err = strconv.ErrRange
goto Error
}
n = n1
}
return n, nil
Error:
return n, &strconv.NumError{"ParseUint", string(s0), err}
}
Output:
输出:
$ go build orkut.go
$ time ./orkut ~/release-orkut-links.txt
/home/peter/release-orkut-links.txt
223534301
1788305680 1788327856 1904683256 135 50
117185083 223534301
1,2
1,3
1,4
1,5
1,6
1,7
1,8
1,9
1,10
1,11
1,12
real 2m53.203s
user 2m51.584s
sys 0m1.628s
$
The orkut.go
program with the release-orkut-links.txt
file (3,372,855,860 (3.4 GB) bytes with 223,534,301 edges) uses about 1.8 GiB of memory. After eliminating duplicates, 117,185,083 unique edges remain. This matches the 117,185,083 unique edge com-orkut.ungraph.txt
file.
orkut。go程序与发布-orkut链接。txt文件(3372,855,860 (3.4 GB)字节与223,534,301条边)使用约1.8 GiB的内存。消除重复后,保留了117,185,083个独特的边。这与117,185,083独特的edge com-orku .ungraph相匹配。txt文件。
With 8 GB of memory on your machine, you can load much larger files.
在您的机器上有8 GB的内存,您可以加载更大的文件。