MichaelScofield

package test;

public class Main {

    private final Object MONITOR = new Object();

    private class PrintNum extends Thread {

        volatile int num = 1;

MichaelScofield

public class ClhSpinLock {
    private final ThreadLocal<Node> pred;
    private final ThreadLocal<Node> node;
    private final AtomicReference<Node> tail = new AtomicReference<Node>(new Node());

    public ClhSpinLock() {
        node = new ThreadLocal<Node>() {
            protected Node initialValue() {
                return new Node();
            }

MichaelScofield

var sum int

func convertBST(root *TreeNode) *TreeNode {
    if root == nil {
        return nil
    }

    sum = 0
    traverse(root)

MichaelScofield

import org.apache.commons.lang3.tuple.Pair;

import java.util.Arrays;

public class Main {
    public static void main(String[] args) {
        //noinspection unchecked
        Pair<String, Boolean>[] testCases = new Pair[]{
                Pair.of("ex 1", true),
                Pair.of("px 1", true),

MichaelScofield

from telnetlib import Telnet

class RedisLiteClient:
  """
  Super lightweight no-frills blocking Redis client that doesn't require any additional dependencies.

  This is a microlibrary, designed for easy copy'n'paste into a project, where you don't want to
  rely on pip/easy_install/etc.

  Usage:

MichaelScofield

High Performance Redis

In response to this brief blog entry, @antirez tweeted for some documentation on high-performance techniques for Redis. What I present here are general high-performance computing (HPC) techniques. The examples are oriented to Redis. but they work well for any program designed to be single- or worker-threaded and asynchronous (e.g. uses epoll).

The motivation for using these techniques is to maximize performance of our system and services. By isolating work, controlling memory, and other tuning, you can achieve significant reduction in latency and increase in throughput.

My perspective comes from the microcosm of my own bare-metal (vs VM), on-premises deployment. It might not be suitable for all scenarios, especially cloud deployments, as I have little experience with HPC there. After some discussion, maybe this can be adapted as [redis.io documentation](https://redis.io/do