jarek-przygodzki

 yum --enablerepo=base-debuginfo install -y kernel-debuginfo-$(uname -r)

shkhln

import com.sun.btrace.AnyType;
import com.sun.btrace.annotations.*;

import static com.sun.btrace.BTraceUtils.*;

@BTrace
public class ChannelTrace {

  @TLS static boolean subscribed = false;

schleumer

import slick.model.Model
import slick.driver.PostgresDriver
import Config._
import scala.concurrent._
import scala.concurrent.duration._
import scala.concurrent.ExecutionContext.Implicits.global
import slick.codegen.SourceCodeGenerator
import slick.jdbc.meta.MTable
import slick.model.Column

tuxfight3r

Bash Shortcuts

Moving

command	description
ctrl + a	Goto BEGINNING of command line

markgoodyear

/*!
 * gulp
 * $ npm install gulp-ruby-sass gulp-autoprefixer gulp-cssnano gulp-jshint gulp-concat gulp-uglify gulp-imagemin gulp-notify gulp-rename gulp-livereload gulp-cache del --save-dev
 */

// Load plugins
var gulp = require('gulp'),
    sass = require('gulp-ruby-sass'),
    autoprefixer = require('gulp-autoprefixer'),
    cssnano = require('gulp-cssnano'),

denji

Moved to git repository: https://github.com/denji/nginx-tuning

NGINX Tuning For Best Performance

For this configuration you can use web server you like, i decided, because i work mostly with it to use nginx.

Generally, properly configured nginx can handle up to 400K to 500K requests per second (clustered), most what i saw is 50K to 80K (non-clustered) requests per second and 30% CPU load, course, this was 2 x Intel Xeon with HyperThreading enabled, but it can work without problem on slower machines.

You must understand that this config is used in testing environment and not in production so you will need to find a way to implement most of those features best possible for your servers.

debasishg

General Background and Overview

1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
2. Models and Issues in Data Stream Systems
3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

rednaxelafx

import java.io.*;
import java.util.*;
import sun.jvm.hotspot.memory.*;
import sun.jvm.hotspot.oops.*;
import sun.jvm.hotspot.debugger.*;
import sun.jvm.hotspot.runtime.*;
import sun.jvm.hotspot.tools.*;
import sun.jvm.hotspot.utilities.*;

public class DirectMemorySize extends Tool {

rednaxelafx

$ export SAPATH=/home/sajia/taobao-jdk-repo/hotspot/make/linux/linux_amd64_compiler2/generated/
$ java -classpath .:$SAPATH/sa-jdi.jar sun.jvm.hotspot.tools.JMap -histo `pgrep java` > jmap_output.log
Attaching to process ID 1587, please wait...
WARNING: Hotspot VM version 20.5-b03 does not match with SA version 20.0-b12-internal. You may see unexpected results. 
Debugger attached successfully.
Server compiler detected.
JVM version is 20.5-b03
Iterating over heap. This may take a while...
Heap traversal took 3.577 seconds.
$ java -version

rednaxelafx

$ pgrep java
3464
$ clhsdb
hsdb> attach 3464
Attaching to process 3464, please wait...
hsdb> jsload objtree.js
hsdb> objtree 0xc99f6378
Oop for java/util/HashSet @ 0x00000000c99f6378 (size of 16)
  _mark: 5
  map: Oop for java/util/HashMap @ 0x00000000c99f6388 (size of 48)