Lazin

vimdiff cheat sheet

##git mergetool

In the middle file (future merged file), you can navigate between conflicts with ]c and [c.

Choose which version you want to keep with :diffget //2 or :diffget //3 (the //2 and //3 are unique identifiers for the target/master copy and the merge/branch copy file names).

:diffupdate (to remove leftover spacing issues)

:only (once you’re done reviewing all conflicts, this shows only the middle/merged file)

Lazin

I've just test std::unordered_map against robin hood hash - https://gist.github.com/Lazin/e033fb1e0641332e28ca (based on this code - https://gist.github.com/ssylvan/5538011).

Insertion:
std::unordered_map:
-------avg 0.00170812
----median 0.00168089
----stddev 4.17363e-09
-------min 0.00166761
-------max 0.00255526
robin-hood hashing:

Lazin

#include <iostream>
#include <deque>
#include <vector>
#include <unordered_map>
#include <algorithm>

namespace perf {
    class Timer
    {
    public:

Lazin

Main Talks:
-----------
Please, no More Minutes, Milliseconds, Monoliths... or Monitoring Tools!
Adrian Cockcroft
http://vimeo.com/95064249
http://www.slideshare.net/adriancockcroft/monitorama-please-no-more

Computers are a Sadness, I am the Cure
James Mickens
http://vimeo.com/95066828

Lazin

  void do_read()
  {
    auto self(shared_from_this());
    socket_.async_read_some(boost::asio::buffer(data_, max_length),
        [this, self](boost::system::error_code ec, std::size_t length)
        {
          if (!ec)
          {
            do_write(length);
          }

Lazin

1. General Background and Overview

• 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.
• Models and Issues in Data Stream Systems
• 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
• Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
• [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep

Lazin

___ Begin jemalloc statistics ___
Version: 3.5.1-0-g7709a64c59daf0b1f938be49472fcc499e1bd136
Assertions disabled
Run-time option settings:
opt.abort: false
opt.lg_chunk: 22
opt.dss: "secondary"
opt.narenas: 32
opt.lg_dirty_mult: 3
opt.stats_print: false

Lazin

#include <iostream>
#include <vector>
#include <boost/pool/pool.hpp>
#include <boost/timer.hpp>
#include <jemalloc/jemalloc.h>

using namespace std;

const size_t COUNT = 1000000;
const size_t SMALL_OBJ_SIZE = sizeof(int);

Lazin

class RWLock {
    pthread_rwlock_t rwlock_;
public:
    RWLock()
        : rwlock_ PTHREAD_RWLOCK_INITIALIZER
    {
    }
    ...
};

Lazin

#include <iostream>
#include <tuple>
#include <vector>
#include <algorithm>
#include <boost/timer.hpp>
#include <boost/range/iterator_range.hpp>
#include <boost/heap/skew_heap.hpp>
#include <google/profiler.h>

using namespace std;