hugo53

#########################
# .gitignore file for Xcode4 / OS X Source projects
#
# Version 2.0
#    For latest version, see: http://stackoverflow.com/questions/49478/git-ignore-file-for-xcode-projects
#
# 2013 updates:
#    - fixed the broken "save personal Schemes"
#
# NB: if you are storing "built" products, this WILL NOT WORK,

hugo53

from scrapy.spider import BaseSpider
from scrapy.http import FormRequest, Request
from scrapy.selector import HtmlXPathSelector

class DjangoSpider(BaseSpider):
    domain_name = "django.local"
    start_urls = ["http://localhost:8000/admin/"]
    extra_domain_names = ["localhost"]

    def parse(self, response):

hugo53

//
//  UIDeviceHardware.h
//
//  Used to determine EXACT version of device software is running on.

#import <Foundation/Foundation.h>

@interface UIDeviceHardware : NSObject 

- (NSString *) platform;

hugo53

5 entertaining things you can find with the GitHub Search API

Let's have some command-line fun with curl, [jq][1], and the [new GitHub Search API][2].

Today we're looking for:

• The hottest repositories created in the last week.
• The oldest user accounts with zero followers. (So sad.)
• Issue trends by language.
• Clojure projects defying convention.

hugo53

The Case For Go

• Iron.io: How We Went from 30 Servers to 2 with Go
• Go at Google: Language Design in the Service of Software Engineering
• Behind the Scenes: Big Data at Torbit
• pool.ntp.org DNS server in Go
• Juju at Canonical
• Go at bitly
• NSQ: realtime distributed message processing at scale

hugo53

Not for everyone. Each programmer has their own appreciation of what is good coding music.

For when I need to think deep, debug something, or design

(From most influential to least)

• David Helpling & Jon Jenkins (sample)
• Patrick O'Hearn (sample)
• Ólafur Arnalds (sample)
• Michael Hedges (sample)
• Alex de Grassi (sample)

hugo53

If you want, I can try and help with pointers as to how to improve the indexing speed you get. Its quite easy to really increase it by using some simple guidelines, for example:

- Use create in the index API (assuming you can).
- Relax the real time aspect from 1 second to something a bit higher (index.engine.robin.refresh_interval).
- Increase the indexing buffer size (indices.memory.index_buffer_size), it defaults to the value 10% which is 10% of the heap.
- Increase the number of dirty operations that trigger automatic flush (so the translog won't get really big, even though its FS based) by setting index.translog.flush_threshold (defaults to 5000).
- Increase the memory allocated to elasticsearch node. By default its 1g.
- Start with a lower replica count (even 0), and then once the bulk loading is done, increate it to the value you want it to be using the update_settings API. This will improve things as possibly less shards will be allocated to each machine.
- Increase the number of machines you have so

hugo53

Node 1

IP: 192.168.33.10

cluster_name: dinhhoanglong91
node.name: node-vagrant-1
node.master: true
network.host: 192.168.33.10
discovery.zen.ping.unicast.hosts: ["192.168.33.10", "192.168.33.20"]

hugo53

import java.io.FileDescriptor;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.OutputStream;
import java.io.PrintStream;

public class HelloWorld{
	private static HelloWorld instance;
    public static void main(String[] args){
        instantiateHelloWorldMainClassAndRun();

hugo53

-Xmx10g
m2.xlarge (4 virtual cores)

Both Jetty and Netty execute the same code--generate 8k of random bits and compute a sha1, returning it over the wire.

INTERNAL (Benchmark tool runs on same machine)
--------

Jetty: