Gelbpunkt

Filesystem benchmarks

I've added a file /vendor/random.data with 4GB of random data from /dev/urandom. We are comparing block sizes 2K, 4K, 8K and 16K for ext4 and erofs.

For erofs, we are also using BOARD_EROFS_PCLUSTER_SIZE := 262144 according to the Google documentation. We will compare lz4hc, lz4 and disabling compression.

I did mount /vendor -o remount,cache_strategy=disabled for erofs to make sure nothing gets cached. The 5.10 kernel on cupid does not seem to support dax=always or the legacy dax flags, neither does it support deduplicating blocks. That may result in more accurate and/or better results, but the numbers difference is huge as is.

Also, ext4 has quite stable read numbers, while erofs with compression fluctuates by ~5-10% on subsequent runs.

Gelbpunkt

import asyncio
from asyncio.subprocess import PIPE, STDOUT

class Result:

    def __init__(self, status, stdout, stderr):
        self.status = status
        self._stdout = stdout or ""
        self._stderr = stderr or ""
        if stdout is not None:

Gelbpunkt

import aiopg

#attach the pool to the bot
async def create_pool():
    connstring = 'dbname=databasename user=databaseuser password=databasepassword host=databasehost'
    pool = await aiopg.create_pool(connstring)
    return pool

async def start_bot():
    pool = await create_pool()