Big Data

Descripción

Mapa Mental sobre Big Data, creado por s.rajeswari30 el 31/12/2013.
s.rajeswari30
Mapa Mental por s.rajeswari30, actualizado hace más de 1 año
s.rajeswari30
Creado por s.rajeswari30 hace casi 11 años
125
0

Resumen del Recurso

Big Data
  1. Definition

    Nota:

    • Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.
    1. Technologies

      Nota:

      • 1.Column-oriented database 2.Schema-less databases or No SQL databases. 3. MapReduce. 4,Hadoop 5.Hive 6.PIG 7. WibiData 8. PLATFORA 9.Storage Technologies 10.SkyTree
      1. Hadoop

        Nota:

        • Hadoop, formally called Apache Hadoop, is an Apache Software Foundationproject and open source software platform for scalable, distributed computing. Hadoop can provide fast and reliable analysis of both structured data and unstructured data. Given its capabilities to handle large data sets, it's often associated with the phrase big data.
        1. Example

          Nota:

          • 1.ebay 2.Facebook 3.Linked in 4.yahoo
          1. Architecture
            1. Hadoop Common

              Nota:

              •  The common utilities that support the other Hadoop subprojects.
              1. Hadoop Distributed File System

                Nota:

                • A distributed file system that provides high-throughput access to application data.
                1. Hadoop MapReduce

                  Nota:

                  •  A software framework for distributed processing of large data sets on compute clusters.
                  1. Hadoop YARN

                    Nota:

                    •  A framework for job scheduling and cluster resource management.
                  2. Scheduling

                    Nota:

                    • By default Hadoop uses FIFO, and optional 5 scheduling priorities to schedule jobs from a work queue. In version 0.19 the job scheduler was refactored out of the JobTracker, and added the ability to use an alternate scheduler 
                    1. Capacity scheduler

                      Nota:

                      • The capacity scheduler was developed by Yahoo.  The capacity scheduler supports several features that are similar to the fair scheduler. 1.Jobs are submitted into queues. 2.Queues are allocated a fraction of the total resource capacity. 3.Free resources are allocated to queues beyond their total capacity. 4.Within a queue a job with a high level of priority has access to the queue's resources. There is no preemption once a job is running.
                      1. Fair scheduler

                        Nota:

                        • The fair scheduler was developed by Facebook. The goal of the fair scheduler is to provide fast response times for small jobs and QoS for production jobs. 
                      2. History

                        Nota:

                        • Hadoop was created by Doug Cutting and Mike Cafarella in 2005. Cutting, who was working at Yahoo! at the time, named it after his son's toy elephant. It was originally developed to support distribution for the Nutch search engine project
                    2. Characteristic

                      Nota:

                      • 1.Volume 2.Variety 3. Velocity 4.Value
                      1. Government

                        Nota:

                        • In 2012, the Obama administration announced the Big Data Research and Development Initiative, which explored how big data could be used to address important problems faced by the government. The initiative was composed of 84 different big data programs spread across six departments.
                        • Big data analysis played a large role in Barack Obama's successful 2012 re-election campaign.
                        • The United States Federal Government owns six of the ten most powerful supercomputers in the world.
                        • The Utah Data Center is a data center currently being constructed by the United States National Security Agency. When finished, the facility will be able to handle a large amount of information collected by the NSA over the Internet. The exact amount of storage space is unknown, but more recent sources claim it will be on the order of a few Exabytes
                        1. Private

                          Nota:

                          • eBay.com uses two data warehouses at 7.5 petabytes and 40PB as well as a 40PB Hadoop cluster for search, consumer recommendations, and merchandising. Inside eBay’s 90PB data warehouse
                          • Amazon.com handles millions of back-end operations every day, as well as queries from more than half a million third-party sellers. The core technology that keeps Amazon running is Linux-based and as of 2005 they had the world’s three largest Linux databases, with capacities of 7.8 TB, 18.5 TB, and 24.7 TB.
                          • Walmart handles more than 1 million customer transactions every hour, which is imported into databases estimated to contain more than 2.5 petabytes (2560 terabytes) of data – the equivalent of 167 times the information contained in all the books in the US Library of Congress
                          • Facebook handles 50 billion photos from its user base.
                          • FICO Falcon Credit Card Fraud Detection System protects 2.1 billion active accounts world-wide.
                          • The volume of business data worldwide, across all companies, doubles every 1.2 years, according to estimates.
                          • Windermere Real Estate uses anonymous GPS signals from nearly 100 million drivers to help new home buyers determine their typical drive times to and from work throughout various times of the day.
                          1. Example

                            Nota:

                            • 1.IBM 2.Hp 3.Teradata 4.Oracle 5. SAP 6.Amazon 7.Google 8. Microsoft 9.10 gen 10. cloudera

                            Recursos multimedia adjuntos

                            Mostrar resumen completo Ocultar resumen completo

                            Similar

                            Managing Digital Data Review
                            Shannon Anderson-Rush
                            Big Data - Hadoop
                            Pedro J. Plasenc
                            SEGURIDAD DIGITAL
                            Ivonne Montes De Oca Ospina
                            QLIK Sense - Business Analyst
                            Abir Chowdhury
                            Top 5 Data Science Certifications In-demand By Fortune 500 Firms in 2022
                            Data science council of America
                            Top 5 Data Science Certifications In-demand By Fortune 500 Firms in 2022
                            Data science council of America
                            Big Data
                            Edgar Reverón
                            GLOSARIO EN FICHAS SOBRE CONCEPTOS RELACIONADOS CON LAS EMPRESAS EXPONENCIALES
                            Lisandro Perez
                            Conceptual Map: Big data
                            Jeffrey Bedoya
                            Data lake (warehouse)
                            Prohor Leykin