Search for SNS by Friendster, LinkedIn, Orkut, and liring
Author: hhqTime: 09:48:01Original load: www.hhq.pim.cn
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SNS research ColumnSince Friendster launched the social network service (SNS), it has set off a boom in Social Network Services (SNS) around the world. The Social Network Service (SNS) site wants to change the Internet through the record of Interpersonal Network relationships. Traditional portal websites have
CODE:#!/usr/bin/python #-*-Coding:utf-8-*-"' Created on 2014-8-16@author:guaguastd@name:login.py ' ' # Twitter Logind EF Linkedin_login (): From LinkedIn import linkedin consumer_key = ' Consumer_secret = ' User_token = ' ' User_secret = ' return_url = ' #developer does not need this # instantiate the developer Authenticatio N class auth =
From: http://blog.sina.com.cn/s/blog_6c9b83990101bbzq.html
1. About databus
LinkedIn opened up its low-Latency Change Data Capture System databus in February 26. This system can capture data on MySQL and Oracle Data sources. Currently, LinkedIn only opens up the connector on Oracle. Databus, as a consistency assurance component in the LinkedIn ecosystem, remain
In Thursday, Salesforce called on EU regulators to conduct a full investigation into Microsoft's deal to buy LinkedIn for $26 billion, foreign media reported. Microsoft is expected to seek EU antitrust approvals for the deal in the next few weeks. It's the biggest deal in Microsoft's history.650) this.width=650; "alt=" mutual pinch, salesforce calls on the EU to investigate Microsoft's acquisition of the LinkedIn
SNS websites are not popular on the Internet outside China. Every name is well-known: Facebook, Twitter, YouTube, MySpace, Flickr and LinkedIn.
Recently, I have been engaged in the development of overseas mobile phone apps for these websites, including Facebook, Twitter, and YouTube. I was looking for some domestic materials, but I really couldn't. There were few (possible reasons for being banned ). This is because
kafka[Is LinkedIn (a company) for log processing of distributed Message Queuing, LinkedIn's log data capacity is large, but the reliability requirements are not high, its log data mainly includes user behavior (login, browse, click, Share, like) and system running log (CPU, memory, disk, network, System and process status).Many of the current Message Queuing services provide reliable delivery guarantees, and the default is instant consumption (not sui
LinkedIn Director Vicente Silveira told his blog that the website password has indeed been leaked.
The full text of the statement is as follows:
This morning, some reports reported that the password was stolen and we hope to provide some up-to-date information. We have confirmed that some LinkedIn accounts and passwords have been stolen. We are investigating. The following measures are taken against the s
it is. However, I noticed that the above csrtfToken parameter has different results for each request. Remember one thing: cookie.
Then, use firebug to analyze what cookies have written.
To ensure security, linkedin checks whether the cookie on the client is the same as that of the original client for each request. If it denies the request, it is considered unsafe, we have to put the request link (https://api.linkedin.com/uas/oauth/authorize? Oauth_t
Last week, LinkedIn CEO Jeff Weiner interviewed Pando daily in San Francisco. In medium, Li Jiang, an investor and writer, summarized three important courses he learned. There are suggestions that can be heard frequently in Silicon Valley, and some ideas that are hardly mentioned by anyone. I would like to share them with you here.
1. Focus
Focus. Yes, you must have heard of this before. "Focus" is almost the mantra of Silicon Valley people. To start
are multiple synchronized methods within a class, be careful about the deadlock problem. It is best to avoid sleeping in the synchronized method. If you can, use synchronized block instead.In addition to this, some LinkedIn design on the process of deploying services are observed. Although most technology companies may be like this, but for my little white, it is an eye-opener. First, before the code churn is formally generated, a test is conducted,
· LinkedIn Cubert Installation Guide · Understanding Cubert Concepts (i) partitioned blocks Understanding Cubert Concepts (ii) co-partitioned Blocks
Original articles, reproduced please specify:
Reprinted from: Oopsoutofmemory Shengli's blog, oopsoutofmemory
This article link address: http://blog.csdn.net/oopsoom/article/details/46707733
Note: This document is based on the attribution-NonCommercial use-prohibition of the deduction of the
. "minute Files") to the consumer.
Most of them use a "push" model in which the broker forwards data to consumers. at LinkedIn, we find the "pull" model more suitable for our applications since each consumer can retrieve the messages at the maximum rate it can sustain andAvoid being floodedBy messages pushed faster than it can handle.
Why should we use pull instead of push? consumer's hunger is only known by consumer, so it is reasonable for the br
so simple that anyone can easily implement it, but it's also powerful enough that you can do anything with it.Because all of the UNIX tools implement the same interface, we call it a unified interface. This is why you can not hesitate to pipe the gunzip data out of the WC, even if the author of the two tools may never have communicated. It's like Lego bricks, they all use the same pattern to achieve nodes and slots, allowing you to pile up Lego bricks as you wish, regardless of their shape, siz
I. Overall Architecture
Zoie is a real-time search engine system implemented by linkedin Based on Lucene. Its official wiki is described as follows:
Http://snaprojects.jira.com/wiki/display/ZOIE/Overview
Zoie is a realtime indexing and search system, and as such needs to have relatively close coupling between the logically distinct Indexing and Searching subsystems: as soon as a document made available to be indexed, it must be immediately searchable.
CODE:#!/usr/bin/python #-*-Coding:utf-8-*-"Created on 2014-8-19@author:guaguastd@name:company_suffix_normalize.py" # import Jsonimport Osimport csvfrom collections Import counterfrom operator import itemgetterfrom prettytable import Pret tytable# Specify CSV directorycsv_file = Os.path.join (r "E:", "\ \", "Eclipse", "LinkedIn", "Dfile", "My_connections.csv") # define a set of transforms that converts the first item# to the second itemtransforms = [('
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