codegravity.com Report : Visit Site


  • Ranking Alexa Global: # 738,206,Alexa Ranking in India is # 77,530

    Server:nginx/1.4.6 (Ubuntu)...
    X-Powered-By:PHP/5.5.9-1ubuntu4.25

    The main IP address: 188.166.117.100,Your server Netherlands,Amsterdam ISP:Digital Ocean Inc.  TLD:com CountryCode:NL

    The description :work on open freelance projects. submit a project request for free! choose from one of 2000 freelance developers to complete a freelance project for you...

    This report updates in 01-Jul-2018

Created Date:2003-07-18
Changed Date:2018-06-18

Technical data of the codegravity.com


Geo IP provides you such as latitude, longitude and ISP (Internet Service Provider) etc. informations. Our GeoIP service found where is host codegravity.com. Currently, hosted in Netherlands and its service provider is Digital Ocean Inc. .

Latitude: 52.374031066895
Longitude: 4.8896899223328
Country: Netherlands (NL)
City: Amsterdam
Region: Noord-Holland
ISP: Digital Ocean Inc.

the related websites

HTTP Header Analysis


HTTP Header information is a part of HTTP protocol that a user's browser sends to called nginx/1.4.6 (Ubuntu) containing the details of what the browser wants and will accept back from the web server.

X-Powered-By:PHP/5.5.9-1ubuntu4.25
Transfer-Encoding:chunked
Set-Cookie:20c6361822d2ca024ac00327c7944810=enhl4bli2br0uvls89p6enb1s4; path=/, lang=deleted; expires=Thu, 01-Jan-1970 00:00:01 GMT; Max-Age=0; path=/, jfcookie=deleted; expires=Thu, 01-Jan-1970 00:00:01 GMT; Max-Age=0; path=/, jfcookie[lang]=en-GB; expires=Mon, 02-Jul-2018 02:26:06 GMT; Max-Age=86400; path=/
Expires:Mon, 1 Jan 2001 00:00:00 GMT
Server:nginx/1.4.6 (Ubuntu)
Last-Modified:Sun, 01 Jul 2018 02:26:06 GMT
Connection:keep-alive
Pragma:no-cache
Cache-Control:post-check=0, pre-check=0
Date:Sun, 01 Jul 2018 02:26:06 GMT
P3P:CP="NOI ADM DEV PSAi COM NAV OUR OTRo STP IND DEM"
Content-Type:text/html; charset=utf-8
X-Frame-Options:DENY
Content-Encoding:gzip

DNS

soa:ns.forpsi.net. admin.forpsi.com. 2018042701 3600 1800 2592000 3600
txt:"v=spf1 a mx ip4:104.236.247.125 ip4:108.166.43.98 mx:mx1.emailsrvr.com mx:mx2.emailsrvr.com mx:codegravity.com mx:www.codegravity.com mx:smtp122.ord1d.emailsrvr.com a:smtp83.iad3a.emailsrvr.com a:smtp105.iad3a.emailsrvr.com -all"
ns:ns.forpsi.cz.
ns.forpsi.it.
ns.forpsi.us.
ns.forpsi.net.
ipv4:IP:188.166.117.100
ASN:14061
OWNER:DIGITALOCEAN-ASN - DigitalOcean, LLC, US
Country:NL
mx:MX preference = 10, mail exchanger = mx1.emailsrvr.com.
MX preference = 20, mail exchanger = mx2.emailsrvr.com.

HtmlToText

news products extrawatch™ freelance all freelancers register submit project open projects java developer projects visitors blog top 15+ free wordpress theme providers of 2017 free joomla extensions recommended by the experts free wordpress plugins recommended by the experts joomla 3.5 and php 7 13 must-have wordpress seo plugins in 2016 emerging trend of java ee microservices login codegravity ® check our new blog.codegravity.com simple single sign-on server on linux and tomcat i spent nearly one hour trying to find a solution how to setup a single sign-on server (sso) on ubuntu and tomcat. what i found is this tutorial and it uses jasig cas server on tomcat 7: https://sonnguyen.ws/install-jasig-cas-ubuntu-14-04/ you can have your own hosted ubuntu on digital ocean for as little as $5/month which is an incredible price for all possibilities it gives you! add new comment hadoop tutorial first, before beginning this hadoop tutorial , let's explain some terms. what is big data? big data is the reality of to do business for most organizations. big data is a collection of large data sets which can not be processed using routine data processing techniques . big data is no longer a given, it became a complete subject which involves various tools, techniques and frameworks. big data involves data produced by applications and devices. some areas that are under the big data roof some examples of big data social media data such as facebook and twitter capture information and views displayed by millions of people worldwide . currency exchange data contains information on the "buy" decisions and "sell" on the one hand made from different companies by clients. power grid data contains information used by a particular node with respect to a base station. transport data includes model, capacity, availability and distance of a vehicle. search engine data recover much data from different databases. big data types the data will be of three types: - structured data is relational data. - semi-structured data are xml data. - unstructured data are documents like word, pdf, text, media newspapers technologies used in big data there are various technologies in the market from different vendors, including amazon, ibm, microsoft , etc. to manage large volumes of data. in this article we will examine the two following classes of technologies: operational big data it includes a system like mongodb operational capabilities that provide real-time, interactive workloads where data is mainly captured and stores. nosql big data systems are designed to take advantage of new architectures of cloud, it makes operational workloads of large data much more manageable, cheaper and faster to implement. big data analytics it includes systems such as massively parallel processing (mpp) systems and database mapreduce analytic capabilities that provide complex analysis to show which can affect most or all of the data. mapreduce provide a new method of data analysis that is corresponding to the capabilities of sql and mapreduce-based system that can be scaled from single servers to thousands of high-end devices and low. difficulties encountered by big data the main challenges related to large volumes of data are: • data capture • conservation • storage • research • share • transfer • analysis • presentation hadoop big data solution old traditional approach in traditional business old approach will have a computer to store and process large data . in these data will be stored in an rdbms such as oracle database, ms sql server or db2 and complicated software can be written to interact with the database process the required data and present users for purposes of analysis. limitation of the traditional approach we use this approach where we have less volume of data that can be accommodated by the database servers or standard data to the processor limit that is currently processing the data. but when it comes to trade with h uge amounts of data traditional approach is really a tedious task to process the data via a traditional database server . the google solution mapreduce algorithm is google's solution for this problem. in this algorithm, we split the task into smaller parts and assign the parts to many computers on the network and collect the results to form the final result dataset . where the apache hadoop fits in? let's first begin in this hadoop tutorial what the apache hadoop actually is. hadoop is basically an open framework of software that can store data and process data through hardware clusters. hadoop is designed to grow from a single server to thousands of machines offering to each local storage and computer. hadoop gives a massive storage for any data type with enormous processing power and the ability to handle tasks or virtually unlimited parallel jobs . hadoop big data solution and history doug cutting , mike cafarella and his team took the solution provided by google and started an open source project called hadoop . hadoop in 2005 is a trademark of the apache software foundation. apache hadoop is an open source framework written in java that allows processing of large data sets on distributed computer clusters using simple programming models . hadoop runs applications using the mapreduce algorithm, where the data are processed in parallel on various processor nodes. hadoop framework is capable enough to develop applications that run on computer clusters and they could do a full statistical analysis to huge amounts of data . hadoop architecture framework hadoop framework consists of four modules: 1) common hadoop 2) hadoop yarn 3) hadoop distributed file system 4) hadoop mapreduce discussing in detail the four hadoop modules 1) common hadoop is java libraries and utilities required by other hadoop modules. these libraries provide files and os level abstractions system to contain the java files and scripts needed to start hadoop. 2) yarn hadoop is a framework for task scheduling and managing cluster resources. 3) hadoop distributed file system that provides broadband access to the application data. 4) hadoop mapreduce is yarn based system for parallel processing of large data sets. working of hadoop there are 3 steps in hadoop can discuss in detail in this hadoop tutorial: 1st step : the user submits a job / application to hadoop for the necessary process by specifying the following: 1. define the locations of the input and output files in the distributed file system. 2. define the java classes as a jar file containing the implementation of the plan and reduce functions. 3. definition of the configuration of the job by defining different parameters specific to the job. 2nd step: hadoop (a hadoop job client) then submits the job (jar / executable etc.) and configuring the job tracker which then assumes responsibility for distributing the software / configuration to the slaves, scheduling tasks and monitoring of granting status as diagnosis information to the job client. 3rd step: task trackers on different nodes perform the task by the implementation and output of the function to reduce mapreduce is stored in the output files on the file system. benefits of hadoop top reasons to choose hadoop is its ability to store and process huge amount of data quickly . other benefits of hadoop are: • computing power - hadoop distributed computing data module quickly process any amount of data. the increase in processing power using several computing nodes. • flexibility - information you should pretreatment before storing. you can store as much information as you require and choose how to use it later. • fault tolerance - information and handling of the application are insured against hardware failures. incase a node goes down task are automatically redirected to other nodes to ensure that distributed computing is not lacking. hadoop automatically store multiple copies of data. • low cost - hadoop is open source hadoop software framework is free & used good material to store large amount o

URL analysis for codegravity.com


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http://www.codegravity.com/blog/android-l-vs-android-m
http://www.codegravity.com/blog/hadoop-tutorial#comments
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Whois Information


Whois is a protocol that is access to registering information. You can reach when the website was registered, when it will be expire, what is contact details of the site with the following informations. In a nutshell, it includes these informations;

Domain Name: CODEGRAVITY.COM
Registry Domain ID: 100720331_DOMAIN_COM-VRSN
Registrar WHOIS Server: whois.tucows.com
Registrar URL: http://www.tucowsdomains.com
Updated Date: 2018-06-18T09:52:09Z
Creation Date: 2003-07-18T12:41:38Z
Registry Expiry Date: 2020-07-18T12:41:38Z
Registrar: Tucows Domains Inc.
Registrar IANA ID: 69
Registrar Abuse Contact Email:
Registrar Abuse Contact Phone:
Domain Status: clientTransferProhibited https://icann.org/epp#clientTransferProhibited
Domain Status: clientUpdateProhibited https://icann.org/epp#clientUpdateProhibited
Name Server: NS.FORPSI.CZ
Name Server: NS.FORPSI.IT
Name Server: NS.FORPSI.NET
Name Server: NS.FORPSI.US
DNSSEC: unsigned
URL of the ICANN Whois Inaccuracy Complaint Form: https://www.icann.org/wicf/
>>> Last update of whois database: 2018-07-01T02:26:31Z <<<

For more information on Whois status codes, please visit https://icann.org/epp

NOTICE: The expiration date displayed in this record is the date the
registrar's sponsorship of the domain name registration in the registry is
currently set to expire. This date does not necessarily reflect the expiration
date of the domain name registrant's agreement with the sponsoring
registrar. Users may consult the sponsoring registrar's Whois database to
view the registrar's reported date of expiration for this registration.

TERMS OF USE: You are not authorized to access or query our Whois
database through the use of electronic processes that are high-volume and
automated except as reasonably necessary to register domain names or
modify existing registrations; the Data in VeriSign Global Registry
Services' ("VeriSign") Whois database is provided by VeriSign for
information purposes only, and to assist persons in obtaining information
about or related to a domain name registration record. VeriSign does not
guarantee its accuracy. By submitting a Whois query, you agree to abide
by the following terms of use: You agree that you may use this Data only
for lawful purposes and that under no circumstances will you use this Data
to: (1) allow, enable, or otherwise support the transmission of mass
unsolicited, commercial advertising or solicitations via e-mail, telephone,
or facsimile; or (2) enable high volume, automated, electronic processes
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repackaging, dissemination or other use of this Data is expressly
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use electronic processes that are automated and high-volume to access or
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to restrict your access to the Whois database in its sole discretion to ensure
operational stability. VeriSign may restrict or terminate your access to the
Whois database for failure to abide by these terms of use. VeriSign
reserves the right to modify these terms at any time.

The Registry database contains ONLY .COM, .NET, .EDU domains and
Registrars.

  REGISTRAR Tucows Domains Inc.

SERVERS

  SERVER com.whois-servers.net

  ARGS domain =codegravity.com

  PORT 43

  TYPE domain

DOMAIN

  NAME codegravity.com

  CHANGED 2018-06-18

  CREATED 2003-07-18

STATUS
clientTransferProhibited https://icann.org/epp#clientTransferProhibited
clientUpdateProhibited https://icann.org/epp#clientUpdateProhibited

NSERVER

  NS.FORPSI.CZ 81.2.209.185

  NS.FORPSI.IT 95.110.254.165

  NS.FORPSI.NET 81.2.194.130

  NS.FORPSI.US 95.110.254.165

  REGISTERED yes

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The following list shows you to spelling mistakes possible of the internet users for the website searched .

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