erikig

Schachte

import java.util.*;

class LongestSubstringKDistinct {
  public static int findLength(String str, int k) {
    int windowStart = 0, maxLength = 0;
    Map<Character, Integer> charFrequencyMap = new HashMap<>();
    for (int windowEnd = 0; windowEnd < str.length(); windowEnd++) {
      char rightChar = str.charAt(windowEnd);
      charFrequencyMap.put(rightChar, charFrequencyMap.getOrDefault(rightChar, 0) + 1);

djspiewak

Quick Tips for Fast Code on the JVM

I was talking to a coworker recently about general techniques that almost always form the core of any effort to write very fast, down-to-the-metal hot path code on the JVM, and they pointed out that there really isn't a particularly good place to go for this information. It occurred to me that, really, I had more or less picked up all of it by word of mouth and experience, and there just aren't any good reference sources on the topic. So… here's my word of mouth.

This is by no means a comprehensive gist. It's also important to understand that the techniques that I outline in here are not 100% absolute either. Performance on the JVM is an incredibly complicated subject, and while there are rules that almost always hold true, the "almost" remains very salient. Also, for many or even most applications, there will be other techniques that I'm not mentioning which will have a greater impact. JMH, Java Flight Recorder, and a good profiler are your very best friend! Mea

Rich-Harris

Edit — February 2019

This gist had a far larger impact than I imagined it would, and apparently people are still finding it, so a quick update:

• TC39 is currently moving forward with a slightly different version of TLA, referred to as 'variant B', in which a module with TLA doesn't block sibling execution. This vastly reduces the danger of parallelizable work happening in serial and thereby delaying startup, which was the concern that motivated me to write this gist
• In the wild, we're seeing (async main(){...}()) as a substitute for TLA. This completely eliminates the blocking problem (yay!) but it's less powerful, and harder to statically analyse (boo). In other words the lack of TLA is causing real problems
• Therefore, a version of TLA that solves the original issue is a valuable addition to the language, and I'm in full support of the current proposal, which you can read here.

I'll leave the rest of this document unedited, for archaeological

IgorMinar

/**
 * ==================  angular-ios9-uiwebview.patch.js v1.1.1 ==================
 *
 * This patch works around iOS9 UIWebView regression that causes infinite digest
 * errors in Angular.
 *
 * The patch can be applied to Angular 1.2.0 – 1.4.5. Newer versions of Angular
 * have the workaround baked in.
 *
 * To apply this patch load/bundle this file with your application and add a

ktmud

var BatchStream = require('batch-stream2')
var gulp = require('gulp')
var coffee = require('gulp-coffee')
var uglify = require('gulp-uglify')
var cssmin = require('gulp-minify-css')
var bower = require('gulp-bower-files')
var stylus = require('gulp-stylus')
var livereload = require('gulp-livereload')
var include = require('gulp-include')
var concat = require('gulp-concat')

coffeemug

Querying by multiple keys

The previous releases of RethinkDB allowed querying indexes as follows:

// Three ways to get the user with primary key 5
r.table('users').get(5)
r.table('users').getAll(5)
r.table('users').getAll(5, {index: 'id'})

FredrikWendt

package se.wendt.statoil.mastercard;

import java.util.ArrayList;
import java.util.concurrent.CountDownLatch;

import redis.clients.jedis.Jedis;
import redis.clients.jedis.JedisPubSub;

public class JedisTest {

jboner

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD

oodavid

Backup MySQL to Amazon S3

This is a simple way to backup your MySQL tables to Amazon S3 for a nightly backup - this is all to be done on your server :-)

Sister Document - Restore MySQL from Amazon S3 - read that next

1 - Install s3cmd

this is for Centos 5.6, see http://s3tools.org/repositories for other systems like ubuntu etc