amyangfei

package main

import "testing"

var allowList = []string{
	"create",
	"cancel",
	"update",
}

amyangfei

package main
        
import (
	"testing"
	"strconv"
	"sync"
)
        
func BenchmarkCreateGoroutine(b *testing.B) {
	nums := []int {

amyangfei

package main

import (
	"context"
	"fmt"
	_ "net/http/pprof"
	"time"

	"github.com/pingcap/log"
	"go.etcd.io/etcd/clientv3"

amyangfei

sysbench insert

• run sysbench insert for at least 12 hours
• status: ✅

sysbench insert with multiple regions Pass

• pre split regions

amyangfei

#!/bin/bash

# This script prints out all of your Redis keys and their size in a human readable format
# Inspired by https://gist.github.com/epicserve/5699837
# Copyright 2015 amyangfei
# License: http://www.apache.org/licenses/LICENSE-2.0

human_size() {
    awk -v sum="$1" ' BEGIN {hum[1024^3]="Gb"; hum[1024^2]="Mb"; hum[1024]="Kb"; for (x=1024^3; x>=1024; x/=1024) { if (sum>=x) { printf "%.2f %s\n",sum/x,hum[x]; break; } } if (sum<1024) print sum,"bytes"; } '
}

amyangfei

/* Dictionary reuse scheme to save calls to malloc, free, and memset */
// Dict对象缓冲池
#ifndef PyDict_MAXFREELIST
#define PyDict_MAXFREELIST 80
#endif
static PyDictObject *free_list[PyDict_MAXFREELIST];
static int numfree = 0;

PyObject *
PyDict_New(void)

amyangfei

from wsgiref.simple_server import make_server

class AppClass:

    def __call__(self,environ, start_response):
        status = '200 OK'
        response_headers = [('Content-type', 'text/plain')]
        start_response(status, response_headers)
    return ["hello world!"]

amyangfei

import io, cStringIO, StringIO
import time
import functools
from memory_profiler import memory_usage

def data_gen():
    return 'datadata' * 100

times = 1000000
dflt_interval = 0.5

amyangfei

#!/usr/bin/env python
# coding: utf-8

import json
import sys
import re
from tornado.httputil import url_concat
from tornado.httpclient import AsyncHTTPClient
from tornado.ioloop import IOLoop

amyangfei

#!/usr/bin/env python
# coding: utf-8

import hashlib
import time
import functools
from memory_profiler import memory_usage


def print_timing(func):