Allocated a lot of memory in Go. How to fix? - go

Several hundred MB of memory is allocated for 50 requests of 5 MB. Memory is allocated and is no longer released.
How can I clear my memory? Why can this happen?
I've tried on Ubuntu on my home pc and on VPS
package main
import (
"fmt"
"io/ioutil"
"net/http"
"time"
)
func main() {
fmt.Println("start")
for i := 0; i < 50; i++ {
go func() {
DoRequest()
}()
time.Sleep(10 * time.Millisecond)
}
time.Sleep(10 * time.Minute)
}
func DoRequest() error {
requestUrl := "https://blockchain.info/rawblock/0000000000000000000eebedea046425bd54626e6c56eb032e66e714d0141ea6"
req, err := http.NewRequest("GET", requestUrl, nil)
if err != nil {
return err
}
req.Header.Set("user-agent", "free")
httpClient := &http.Client{
Timeout: time.Second * 10,
}
resp, err := httpClient.Do(req)
if resp != nil {
defer resp.Body.Close()
}
if err != nil {
return err
}
body, err := ioutil.ReadAll(resp.Body)
if err != nil {
return err
}
fmt.Println("bodylen", len(body))
return nil
}
Allocated somewhere 400MB

You are creating an http client for each go-routine.
Http client is designed to be create once & used many times. They are go-routine safe.
They allow for connection reuse & other efficiency savers.
Create the http client once in main (instead of in your go-routine) & then pass this single reference to all of your 50 go-routines.
Edit: Also, while it may not make a practical difference in your case, the order for a request is usually like so:
resp, err := httpClient.Do(req)
if err != nil {
return err // check error first
}
defer resp.Body.Close() // no error - so resp will *NOT* be nil - so this is safe
Edit 2: As #Adrian has mentioned: go's garbage collection is not instantaneous - nor should it be - as it is an expensive operation. If you no longer need a block of memory - simply don't reference it anymore. Let the GC do its job, so you can focus on yours!
If you're curious about the evolution of go's GC:
https://blog.golang.org/ismmkeynote (heavy on the technical side)
What kind of Garbage Collection does Go use?

for i := 0; i < 50; i++ {
go func() {
DoRequest()
}()
time.Sleep(10 * time.Millisecond)
}
Never create go-routines like this. Always make sure you create go-routines the way it not fill large ( all ) memory in any case ( including worst case )
Simple solution is control the count of go-routines can spawned ( or running ) at time.
You can pre-calculate memory to be occupied in worst case by multiplying max-number of go-routines you want to run at a time and max-memory can be used by one go-routine.
You can control instances of go-routines by using channles.
Refer first answer of this stackoverflow question
Always have x number of goroutines running at any time
Always use balanced solution between perforamce and required resources.
Update June 11,2019
Here is example go program
https://play.golang.org/p/HovNRgp6FxH

Related

How to optimise processing large data

The objective of my backend service is to process 90 milllion data and at least 10 million of data in 1 day.
My system config:
Ram 2000 Mb
CPU 2core(s)
what I am doing right now is something like this:
var wg sync.WaitGroup
//length of evs is 4455
for i, ev := range evs {
wg.Add(1)
go migrate(&wg)
}
wg.Wait()
func migrate(wg *sync.WaitGroup) {
defer wg.Done()
//processing
time.Sleep(time.Second)
}
Without knowing more detail about the type of work you need to do, your approach seems good. Some things to think about:
Re-using variables and or clients in your processing loop. For example reusing an HTTP client instead of recreating one.
Depending on how your use case calls to handle failures. It might be efficient to use erroGroup. It's a convenience wrapper that stops all the threads on error possibly saving you a lot of time.
In the migrate function be sure to be aware of the caveats regarding closure and goroutines.
func main() {
g := new(errgroup.Group)
var urls = []string{
"http://www.someasdfasdfstupidname.com/",
"ftp://www.golang.org/",
"http://www.google.com/",
}
for _, url := range urls {
url := url // https://golang.org/doc/faq#closures_and_goroutines
g.Go(func() error {
resp, err := http.Get(url)
if err == nil {
resp.Body.Close()
}
return err
})
}
fmt.Println("waiting")
if err := g.Wait(); err == nil {
fmt.Println("Successfully fetched all URLs.")
} else {
fmt.Println(err)
}
}
I have got the solution. to achieve this much huge processing what I have done is
a limited number of goroutine to 50 and increased the number of cores from 2 to 5.

How to make concurrent GET requests from url pool

I completed the suggested go-tour, watched some tutorials and gopher-conferences on YouTube. And that's pretty much it.
I have a project which requires me to send get requests and store the results in files. But amount of URL's is around 80 million.
I'm testing with 1000 URLs only.
Problem: I think I couldn't managed to make it concurrent, although I've followed some guidelines. I don't know what's wrong. But maybe I'm wrong and it's concurrent, just did not seem fast to me, the speed felt like sequential requests.
Here is the code I've written:
package main
import (
"bufio"
"io/ioutil"
"log"
"net/http"
"os"
"sync"
"time"
)
var wg sync.WaitGroup // synchronization to wait for all the goroutines
func crawler(urlChannel <-chan string) {
defer wg.Done()
client := &http.Client{Timeout: 10 * time.Second} // single client is sufficient for multiple requests
for urlItem := range urlChannel {
req1, _ := http.NewRequest("GET", "http://"+urlItem, nil) // generating the request
req1.Header.Add("User-agent", "Mozilla/5.0 (X11; Linux i586; rv:31.0) Gecko/20100101 Firefox/74.0") // changing user-agent
resp1, respErr1 := client.Do(req1) // sending the prepared request and getting the response
if respErr1 != nil {
continue
}
defer resp1.Body.Close()
if resp1.StatusCode/100 == 2 { // means server responded with 2xx code
text1, readErr1 := ioutil.ReadAll(resp1.Body) // try to read the sourcecode of the website
if readErr1 != nil {
log.Fatal(readErr1)
}
f1, fileErr1 := os.Create("200/" + urlItem + ".txt") // creating the relative file
if fileErr1 != nil {
log.Fatal(fileErr1)
}
defer f1.Close()
_, writeErr1 := f1.Write(text1) // writing the sourcecode into our file
if writeErr1 != nil {
log.Fatal(writeErr1)
}
}
}
}
func main() {
file, err := os.Open("urls.txt") // the file containing the url's
if err != nil {
log.Fatal(err)
}
defer file.Close() // don't forget to close the file
urlChannel := make(chan string, 1000) // create a channel to store all the url's
scanner := bufio.NewScanner(file) // each line has another url
for scanner.Scan() {
urlChannel <- scanner.Text()
}
close(urlChannel)
_ = os.Mkdir("200", 0755) // if it's there, it will create an error, and we will simply ignore it
for i := 0; i < 10; i++ {
wg.Add(1)
go crawler(urlChannel)
}
wg.Wait()
}
My question is: why is this code not working concurrently? How can I solve the problem I've mentioned above. Is there something that I'm doing wrong for making concurrent GET requests?
Here's some code to get you thinking. I put the URLs in the code so it is self-sufficient, but you'd probably be piping them to stdin in practice. There's a few things I'm doing here that I think are improvements, or at least worth thinking about.
Before we get started, I'll point out that I put the complete url in the input stream. For one thing, this lets me support http and https both. I don't really see the logic behind hard coding the scheme in the code rather than leaving it in the data.
First, it can handle arbitrarily sized response bodies (your version reads the body into memory, so it is limited by some number of concurrent large requests filling memory). I do this with io.Copy().
[edited]
text1, readErr1 := ioutil.ReadAll(resp1.Body) reads the entire http body. If the body is large, it will take up lots of memory. io.Copy(f1,resp1.Body) would instead copy the data from the http response body directly to the file, without having to hold the whole thing in memory. It may be done in one Read/Write or many.
http.Response.Body is an io.ReadCloser because the HTTP protocol expects the body to be read progressively. http.Response does not yet have the entire body, until it is read. That's why it's not just a []byte. Writing it to the filesystem progressively while the data "streams" in from the tcp socket means that a finite amount of system resources can download an unlimited amount of data.
But there's even more benefit. io.Copy will call ReadFrom() on the file. If you look at the linux implementation (for example): https://golang.org/src/os/readfrom_linux.go , and dig a bit, you'll see it actually uses copy_file_range That system call is cool because
The copy_file_range() system call performs an in-kernel copy between two file descriptors without the additional cost of transferring data from the kernel to user space and then back into the kernel.
*os.File knows how to ask the kernel to deliver data directly from the tcp socket to the file without your program even having to touch it.
See https://golang.org/pkg/io/#Copy.
Second, I make sure to use all the url components in the filename. URLs with different query strings go to different files. The fragment probably doesn't differentiate response bodies, so including that in the path may be ill considered. There's no awesome heuristic for turning URLs into valid file paths - if this were a serious task, I'd probably store the data in files based on a shasum of the url or something - and create an index of results stored in a metadata file.
Third, I handle all errors. req1, _ := http.NewRequest(... might seem like a convenient shortcut, but what it really means is that you won't know the real cause of any errors - at best. I usually add some descriptive text to the errors when percolating up, to make sure I can easily tell which error I'm returning.
Finally, I return successfully processed URLs so that I can see the final results. When scanning millions of URLS, you'd probably also want a list of which failed, but a count of successful is a good start at sending final data back for summary.
package main
import (
"bufio"
"bytes"
"fmt"
"io"
"log"
"net/http"
"net/url"
"os"
"path/filepath"
"time"
)
const urls_text = `http://danf.us/
https://farrellit.net/?3=2&#1
`
func crawler(urls <-chan *url.URL, done chan<- int) {
var processed int = 0
defer func() { done <- processed }()
client := http.Client{Timeout: 10 * time.Second}
for u := range urls {
if req, err := http.NewRequest("GET", u.String(), nil); err != nil {
log.Printf("Couldn't create new request for %s: %s", u.String(), err.Error())
} else {
req.Header.Add("User-agent", "Mozilla/5.0 (X11; Linux i586; rv:31.0) Gecko/20100101 Firefox/74.0") // changing user-agent
if res, err := client.Do(req); err != nil {
log.Printf("Failed to get %s: %s", u.String(), err.Error())
} else {
filename := filepath.Base(u.EscapedPath())
if filename == "/" || filename == "" {
filename = "response"
} else {
log.Printf("URL Filename is '%s'", filename)
}
destpath := filepath.Join(
res.Status, u.Scheme, u.Hostname(), u.EscapedPath(),
fmt.Sprintf("?%s",u.RawQuery), fmt.Sprintf("#%s",u.Fragment), filename,
)
if err := os.MkdirAll(filepath.Dir(destpath), 0755); err != nil {
log.Printf("Couldn't create directory %s: %s", filepath.Dir(destpath), err.Error())
} else if f, err := os.OpenFile(destpath, os.O_WRONLY|os.O_CREATE|os.O_TRUNC, 0644); err != nil {
log.Printf("Couldn't open destination file %s: %s", destpath, err.Error())
} else {
if b, err := io.Copy(f, res.Body); err != nil {
log.Printf("Could not copy %s body to %s: %s", u.String(), destpath, err.Error())
} else {
log.Printf("Copied %d bytes from body of %s to %s", b, u.String(), destpath)
processed++
}
f.Close()
}
res.Body.Close()
}
}
}
}
const workers = 3
func main() {
urls := make(chan *url.URL)
done := make(chan int)
var submitted int = 0
var inputted int = 0
var successful int = 0
for i := 0; i < workers; i++ {
go crawler(urls, done)
}
sc := bufio.NewScanner(bytes.NewBufferString(urls_text))
for sc.Scan() {
inputted++
if u, err := url.Parse(sc.Text()); err != nil {
log.Printf("Could not parse %s as url: %w", sc.Text(), err)
} else {
submitted++
urls <- u
}
}
close(urls)
for i := 0; i < workers; i++ {
successful += <-done
}
log.Printf("%d urls input, %d could not be parsed. %d/%d valid URLs successful (%.0f%%)",
inputted, inputted-submitted,
successful, submitted,
float64(successful)/float64(submitted)*100.0,
)
}
When setting up a concurrent pipeline, a good guideline to follow is to always first set up and instantiate the listeners that will execute concurrently (in your case, crawlers), and then start feeding them data through the pipeline (in your case, the urlChannel).
In your example, the only thing preventing a deadlock is the fact that you've instantiated a buffered channel with the same number of rows that your test file has (1000 rows). What the code does is it puts URLs inside the urlChannel. Since there are 1000 rows inside your file, the urlChannel can take all of them without blocking. If you put more URLs inside the file, the execution will block after filling up the urlChannel.
Here is the version of the code that should work:
package main
import (
"bufio"
"io/ioutil"
"log"
"net/http"
"os"
"sync"
"time"
)
func crawler(wg *sync.WaitGroup, urlChannel <-chan string) {
defer wg.Done()
client := &http.Client{Timeout: 10 * time.Second} // single client is sufficient for multiple requests
for urlItem := range urlChannel {
req1, _ := http.NewRequest("GET", "http://"+urlItem, nil) // generating the request
req1.Header.Add("User-agent", "Mozilla/5.0 (X11; Linux i586; rv:31.0) Gecko/20100101 Firefox/74.0") // changing user-agent
resp1, respErr1 := client.Do(req1) // sending the prepared request and getting the response
if respErr1 != nil {
continue
}
if resp1.StatusCode/100 == 2 { // means server responded with 2xx code
text1, readErr1 := ioutil.ReadAll(resp1.Body) // try to read the sourcecode of the website
if readErr1 != nil {
log.Fatal(readErr1)
}
resp1.Body.Close()
f1, fileErr1 := os.Create("200/" + urlItem + ".txt") // creating the relative file
if fileErr1 != nil {
log.Fatal(fileErr1)
}
_, writeErr1 := f1.Write(text1) // writing the sourcecode into our file
if writeErr1 != nil {
log.Fatal(writeErr1)
}
f1.Close()
}
}
}
func main() {
var wg sync.WaitGroup
file, err := os.Open("urls.txt") // the file containing the url's
if err != nil {
log.Fatal(err)
}
defer file.Close() // don't forget to close the file
urlChannel := make(chan string)
_ = os.Mkdir("200", 0755) // if it's there, it will create an error, and we will simply ignore it
// first, initialize crawlers
wg.Add(10)
for i := 0; i < 10; i++ {
go crawler(&wg, urlChannel)
}
//after crawlers are initialized, start feeding them data through the channel
scanner := bufio.NewScanner(file) // each line has another url
for scanner.Scan() {
urlChannel <- scanner.Text()
}
close(urlChannel)
wg.Wait()
}

Is there a way to optimize that code? TCP-server in Go

coders. Here is the basic tcp-server, that accepts connection, reads the incoming data and writes back.
package main
import (
"bufio"
"io"
"log"
"net"
)
func main() {
li, err := net.Listen("tcp", ":8080")
if err != nil {
log.Fatalln(err)
}
defer li.Close()
for {
conn, err := li.Accept()
if err != nil {
log.Fatalln(err)
}
scanner := bufio.NewScanner(conn)
for scanner.Scan() {
ln := scanner.Text()
io.WriteString(conn, ln+"\n")
}
conn.Close()
}
}
However, there is a nested loop for scanner and declaring new scanner on each iteration of external loop. I heard, that nested loops lead to extra complexety and maybe declaring new scanner on each iteration of infinite loop leads to some memory leaks. Actually, I don't know how to do it in another way and I'm just want to ask 2 things:
Is it possible to do the same in another way?
Do we actually need more optimization on such low-level server
abstraction?
The outer loop is waiting for new connections, the inner loop is parsing the input data, so from that point of view it's fine. Not all nested loops are evil. However, while you're handling that single connection, the server is not accepting them any more (you can test that by trying to connect to the server from multiple clients). To fix that, handle the connection in a goroutine:
for {
conn, err := li.Accept()
if err != nil {
log.Fatalln(err)
}
go func() {
defer conn.Close()
scanner := bufio.NewScanner(conn)
for scanner.Scan() {
ln := scanner.Text()
io.WriteString(conn, ln+"\n")
}
}()
}

Incorrect data re-transmisson

I need my program to be in the middle of the connection and transfer data correctly in both directions. I wrote this code, but it does not work properly
package main
import (
"fmt"
"net"
)
func main() {
listener, err := net.Listen("tcp", ":8120")
if err != nil {
fmt.Println(err)
return
}
defer listener.Close()
fmt.Println("Server is listening...")
for {
var conn1, conn2 net.Conn
var err error
conn1, err = listener.Accept()
if err != nil {
fmt.Println(err)
conn1.Close()
continue
}
conn2, err = net.Dial("tcp", "185.151.245.51:80")
if err != nil {
fmt.Println(err)
conn2.Close()
continue
}
go handleConnection(conn1, conn2)
go handleConnection(conn2, conn1)
}
}
func handleConnection(conn1, conn2 net.Conn) {
defer conn1.Close()
for {
input := make([]byte, 1024)
n, err := conn1.Read(input)
if n == 0 || err != nil {
break
}
conn2.Write([]byte(input))
}
}
The problem is that the data is corrupted,
for example.
Left one is original, right one is what i got.
End of the final gotten file is unreadable.
But at the beginnig everything is ok.
I tried to change input slice size. If size > 0 and < 8, everything is fine, but slow. If i set input size very large, corruption of data become more awful.
What I'm doing wrong?
In handleConnection, you always write 1024 bytes, no matter what conn1.Read returns.
You want to write the data like this:
conn2.Write(input[:n])
You should also check your top-level for loop. Are you sure you're not accepting multiple connections and smushing them all together? I'd sprinkle in some log statements so you can see when connections are made and closed.
Another (probably inconsequential) mistake, is that you treat n==0 as a termination condition. In the documentation of io.Reader it's recommended that you ignore n==0, err==nil. Without checking the code I can't be sure, but I expect that conn.Read never returns n==0, err==nil, so it's unlikely that this is causing you trouble.
Although it doesn't affect correctness, you could also lift the definition of input out of the loop so that it's reused on each iteration; it's likely to reduce the amount of work the garbage collector has to do.

Farm out work to a slice but limit number of workers

I'm trying to improve the performance of an app.
One part of its code uploads a file to a server in chunks.
The original version simply does this in a sequential loop. However, it's slow and during the sequence it also needs to talk to another server before uploading each chunk.
The upload of chunks could simply be placed in a goroutine. It works, but is not a good solution because if the source file is extremely large it ends up using a large amount of memory.
So, I try to limit the number of active goroutines by using a buffered channel. Here is some code that shows my attempt. I've stripped it down to show the concept and you can run it to test for yourself.
package main
import (
"fmt"
"io"
"os"
"time"
)
const defaultChunkSize = 1 * 1024 * 1024
// Lets have 4 workers
var c = make(chan int, 4)
func UploadFile(f *os.File) error {
fi, err := f.Stat()
if err != nil {
return fmt.Errorf("err: %s", err)
}
size := fi.Size()
total := (int)(size/defaultChunkSize + 1)
// Upload parts
buf := make([]byte, defaultChunkSize)
for partno := 1; partno <= total; partno++ {
readChunk := func(offset int, buf []byte) (int, error) {
fmt.Println("readChunk", partno, offset)
n, err := f.ReadAt(buf, int64(offset))
if err != nil {
return n, err
}
return n, nil
}
// This will block if there are not enough worker slots available
c <- partno
// The actual worker.
go func() {
offset := (partno - 1) * defaultChunkSize
n, err := readChunk(offset, buf)
if err != nil && err != io.EOF {
return
}
err = uploadPart(partno, buf[:n])
if err != nil {
fmt.Println("Uploadpart failed:", err)
}
<-c
}()
}
return nil
}
func uploadPart(partno int, buf []byte) error {
fmt.Printf("Uploading partno: %d, buflen=%d\n", partno, len(buf))
// Actually upload the part. Lets test it by instead writing each
// buffer to another file. We can then use diff to compare the
// source and dest files.
// Open file. Seek to (partno - 1) * defaultChunkSize, write buffer
f, err := os.OpenFile("/home/matthewh/Downloads/out.tar.gz", os.O_CREATE|os.O_WRONLY, 0755)
if err != nil {
fmt.Printf("err: %s\n", err)
}
n, err := f.WriteAt(buf, int64((partno-1)*defaultChunkSize))
if err != nil {
fmt.Printf("err=%s\n", err)
}
fmt.Printf("%d bytes written\n", n)
defer f.Close()
return nil
}
func main() {
filename := "/home/matthewh/Downloads/largefile.tar.gz"
fmt.Printf("Opening file: %s\n", filename)
f, err := os.Open(filename)
if err != nil {
panic(err)
}
UploadFile(f)
}
It almost works. But there are several problems.
1) The final partno 22 is occuring 3 times. The correct length is actually 612545 as the file length isn't a multiple of 1MB.
// Sample output
...
readChunk 21 20971520
readChunk 22 22020096
Uploading partno: 22, buflen=1048576
Uploading partno: 22, buflen=612545
Uploading partno: 22, buflen=1048576
Another problem, the upload could fail and I am not familiar enough with go and how best to solve failure of the goroutine.
Finally, I want to ordinarily return some data from the uploadPart when it succeeds. Specifically, it'll be a string (an HTTP ETag header value). These etag values need to be collected by the main function.
What is a better way to structure this code in this instance? I've not yet found a good golang design pattern that correctly fulfills my needs here.
Skipping for the moment the question of how better to structure this code, I see a bug in your code which may be causing the problem you're seeing. Since the function you're running in the goroutine uses the variable partno, which changes with each iteration of the loop, your goroutine isn't necessarily seeing the value of partno at the time you invoked the goroutine. A common way of fixing this is to create a local copy of that variable inside the loop:
for partno := 1; partno <= total; partno++ {
partno := partno
// ...
}
Data race #1
Multiple goroutines are using the same buffer concurrently. Note that one gorouting may be filling it with a new chunk while another is still reading an old chunk from it. Instead, each goroutine should have it's own buffer.
Data race #2
As Andy Schweig has pointed, the value in partno is updated by the loop before the goroutine created in that iteration has a chance to read it. This is why the final partno 22 occurs multiple times. To fix it, you can pass partno as a argument to the anonymous function. That will ensure each goroutine has it's own part number.
Also, you can use a channel to pass the results from the workers. Maybe a struct type with the part number and error. That way, you will be able to observe the progress and retry failed uploads.
For an example of a good pattern check out this example from the GOPL book.
Suggested changes
As noted by dev.bmax buf moved into go routine, as noted by Andy Schweig partno is param to anon function, also added WaitGroup since UploadFile was exiting before uploads were complete. Also defer f.Close() file, good habit.
package main
import (
"fmt"
"io"
"os"
"sync"
"time"
)
const defaultChunkSize = 1 * 1024 * 1024
// wg for uploads to complete
var wg sync.WaitGroup
// Lets have 4 workers
var c = make(chan int, 4)
func UploadFile(f *os.File) error {
// wait for all the uploads to complete before function exit
defer wg.Wait()
fi, err := f.Stat()
if err != nil {
return fmt.Errorf("err: %s", err)
}
size := fi.Size()
fmt.Printf("file size: %v\n", size)
total := int(size/defaultChunkSize + 1)
// Upload parts
for partno := 1; partno <= total; partno++ {
readChunk := func(offset int, buf []byte, partno int) (int, error) {
fmt.Println("readChunk", partno, offset)
n, err := f.ReadAt(buf, int64(offset))
if err != nil {
return n, err
}
return n, nil
}
// This will block if there are not enough worker slots available
c <- partno
// The actual worker.
go func(partno int) {
// wait for me to be done
wg.Add(1)
defer wg.Done()
buf := make([]byte, defaultChunkSize)
offset := (partno - 1) * defaultChunkSize
n, err := readChunk(offset, buf, partno)
if err != nil && err != io.EOF {
return
}
err = uploadPart(partno, buf[:n])
if err != nil {
fmt.Println("Uploadpart failed:", err)
}
<-c
}(partno)
}
return nil
}
func uploadPart(partno int, buf []byte) error {
fmt.Printf("Uploading partno: %d, buflen=%d\n", partno, len(buf))
// Actually do the upload. Simulate long running task with a sleep
time.Sleep(time.Second)
return nil
}
func main() {
filename := "/home/matthewh/Downloads/largefile.tar.gz"
fmt.Printf("Opening file: %s\n", filename)
f, err := os.Open(filename)
if err != nil {
panic(err)
}
defer f.Close()
UploadFile(f)
}
I'm sure you can deal a little smarter with the buf situation. I'm just letting go deal with the garbage. Since you are limiting your workers to specific number 4 you really need only 4 x defaultChunkSize buffers. Please do share if you come up with something simple and shareworth.
Have fun!

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