on-disk size always 0 about badger HOT 6 CLOSED

I tried isolating the issue further by reducing my script to this:

package main

import (
	"encoding/binary"
	"fmt"
	"log"

	"github.com/dgraph-io/badger/badger"
)

func main() {

	// connection
	opt := badger.DefaultOptions
	opt.Dir = "/tmp/leveldb"
	opt.ValueDir = opt.Dir
	db, err := badger.NewKV(&opt)
	if err != nil {
		panic(err)
	}
	defer db.Close()

	// writes
	for i := 0; i < 10000; i++ {

		bytes := make([]byte, 8)
		binary.BigEndian.PutUint64(bytes, uint64(i))

		// write to db
		err = db.Set(bytes, bytes)
		if err != nil {
			log.Println("write error", err)
		}
	}

	// fetch one key
	keyOne := make([]byte, 8)
	binary.BigEndian.PutUint64(keyOne, uint64(1))

	// read from db
	var item badger.KVItem
	err = db.Get(keyOne, &item)
	if err != nil {
		log.Println("read error", err)
	}

	// debug
	data := item.Value()
	fmt.Println("val", data)
}

it seems like there are two issues:

• it is really slow, taking 11s to insert 10000 records, surely this can't be right?
• it doesn't flush the data to disk until the call to Close(), so it looks like it's not flushing when it actually is.

I think the issue for my original script it I got tired of waiting and cancelled the job, using leveldb it takes about 1.5s, I waited about 15s before giving it the 'ol cntl+c

from badger.

is it possible that I'm getting poor performance because I'm using an ext4 filesystem?

from badger.

from badger.

Let me know if there's something more I can help you with.

from badger.

hey @manishrjain thanks for your reply. I can re-jig my code to use batched writes instead of single writes, but the issue remains that comparing apples v. apples with leveldb, badger is much slower?

are you suggesting that the batch mode of badger is much faster than the batch mode of leveldb?

from badger.

I haven't tried running any benchmarks against leveldb. Also, serial writes in a single goroutine isn't something that we have optimized for. Most practical applications which care about performance would do batched writes, concurrently.

from badger.