Big Data SMACK: A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka

3 valoración promedio
( 3 valoraciones por Goodreads )
 
9781484221747: Big Data SMACK: A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka
Ver todas las copias de esta edición ISBN.
 
 
Reseña del editor:

Learn how to integrate full-stack open source big data architecture and to choose the correct technology―Scala/Spark, Mesos, Akka, Cassandra, and Kafka―in every layer. 

Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases now, organizations need more than one paradigm to perform efficient analyses.

Big Data SMACK explains each of the full-stack technologies and, more importantly, how to best integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples in every situation. This book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by every technology. It covers the six main concepts of big data architecture and how integrate, replace, and reinforce every layer:

  • The language: Scala
  • The engine: Spark (SQL, MLib, Streaming, GraphX)
  • The container: Mesos, Docker
  • The view: Akka
  • The storage: Cassandra
  • The message broker: Kafka
  • What You Will Learn:

    • Make big data architecture without using complex Greek letter architectures
    • Build a cheap but effective cluster infrastructure
    • Make queries, reports, and graphs that business demands
    • Manage and exploit unstructured and No-SQL data sources
    • Use tools to monitor the performance of your architecture
    • Integrate all technologies and decide which ones replace and which ones reinforce

    Who This Book Is For:

    Developers, data architects, and data scientists looking to integrate the most successful big data open stack architecture and to choose the correct technology in every layer

    Contraportada:

    Integrate full-stack open-source fast data pipeline architecture and choose the correct technology―Spark, Mesos, Akka, Cassandra, and Kafka (SMACK)―in every layer. Fast data is becoming a requirement for many enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases organizations need more than one paradigm to perform efficient analyses.

    Big Data SMACK explains each technology and, more importantly, how to integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples. The book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by each technology. This book covers the five main concepts of data pipeline architecture and how to integrate, replace, and reinforce every layer:

    • The engine: Apache Spark
    • The container: Apache Mesos
    • The model: Akka<
    • The storage: Apache Cassandra
    • The broker: Apache Kafka

    "Sobre este título" puede pertenecer a otra edición de este libro.

    Comprar nuevo Ver libro

    Gastos de envío: GRATIS
    De Reino Unido a Estados Unidos de America

    Destinos, gastos y plazos de envío

    Añadir al carrito

    Los mejores resultados en AbeBooks

    1.

    Raul Estrada, Isaac Ruiz
    Publicado por aPress, United States (2016)
    ISBN 10: 1484221745 ISBN 13: 9781484221747
    Nuevo Paperback Original o primera edición Cantidad disponible: 1
    Librería
    The Book Depository
    (London, Reino Unido)
    Valoración
    [?]

    Descripción aPress, United States, 2016. Paperback. Condición: New. 1st ed.. Language: English . Brand New Book. Learn how to integrate full-stack open source big data architecture and to choose the correct technology-Scala/Spark, Mesos, Akka, Cassandra, and Kafka-in every layer. Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases now, organizations need more than one paradigm to perform efficient analyses. Big Data SMACK explains each of the full-stack technologies and, more importantly, how to best integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples in every situation. This book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by every technology. It covers the six main concepts of big data architecture and how integrate, replace, and reinforce every layer: The language: Scala The engine: Spark (SQL, MLib, Streaming, GraphX) The container: Mesos, Docker The view: Akka The storage: Cassandra The message broker: Kafka What You Will Learn: Make big data architecture without using complex Greek letter architectures Build a cheap but effective cluster infrastructure Make queries, reports, and graphs that business demands Manage and exploit unstructured and No-SQL data sources Use tools to monitor the performance of your architecture Integrate all technologies and decide which ones replace and which ones reinforce Who This Book Is For: Developers, data architects, and data scientists looking to integrate the most successful big data open stack architecture and to choose the correct technology in every layer. Nº de ref. del artículo: AAZ9781484221747

    Más información sobre este vendedor | Contactar al vendedor

    Comprar nuevo
    EUR 28,94
    Convertir moneda

    Añadir al carrito

    Gastos de envío: GRATIS
    De Reino Unido a Estados Unidos de America
    Destinos, gastos y plazos de envío

    2.

    Raul Estrada, Isaac Ruiz
    Publicado por aPress, United States (2016)
    ISBN 10: 1484221745 ISBN 13: 9781484221747
    Nuevo Paperback Original o primera edición Cantidad disponible: 1
    Librería
    Book Depository International
    (London, Reino Unido)
    Valoración
    [?]

    Descripción aPress, United States, 2016. Paperback. Condición: New. 1st ed.. Language: English . Brand New Book. Learn how to integrate full-stack open source big data architecture and to choose the correct technology-Scala/Spark, Mesos, Akka, Cassandra, and Kafka-in every layer. Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases now, organizations need more than one paradigm to perform efficient analyses. Big Data SMACK explains each of the full-stack technologies and, more importantly, how to best integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples in every situation. This book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by every technology. It covers the six main concepts of big data architecture and how integrate, replace, and reinforce every layer: The language: Scala The engine: Spark (SQL, MLib, Streaming, GraphX) The container: Mesos, Docker The view: Akka The storage: Cassandra The message broker: Kafka What You Will Learn: Make big data architecture without using complex Greek letter architectures Build a cheap but effective cluster infrastructure Make queries, reports, and graphs that business demands Manage and exploit unstructured and No-SQL data sources Use tools to monitor the performance of your architecture Integrate all technologies and decide which ones replace and which ones reinforce Who This Book Is For: Developers, data architects, and data scientists looking to integrate the most successful big data open stack architecture and to choose the correct technology in every layer. Nº de ref. del artículo: AAZ9781484221747

    Más información sobre este vendedor | Contactar al vendedor

    Comprar nuevo
    EUR 29,48
    Convertir moneda

    Añadir al carrito

    Gastos de envío: GRATIS
    De Reino Unido a Estados Unidos de America
    Destinos, gastos y plazos de envío

    3.

    Estrada, Raul, Ruiz, Isaac
    Publicado por Apress (2016)
    ISBN 10: 1484221745 ISBN 13: 9781484221747
    Nuevo Tapa blanda Original o primera edición Cantidad disponible: 2
    Librería
    Valoración
    [?]

    Descripción Apress, 2016. Condición: New. Num Pages: 264 pages, 22 black & white illustrations, 52 colour illustrations, biography. BIC Classification: UN. Category: (P) Professional & Vocational. Dimension: 180 x 332 x 18. Weight in Grams: 582. . 2016. 1st ed. Paperback. . . . . . Nº de ref. del artículo: V9781484221747

    Más información sobre este vendedor | Contactar al vendedor

    Comprar nuevo
    EUR 36,07
    Convertir moneda

    Añadir al carrito

    Gastos de envío: GRATIS
    De Irlanda a Estados Unidos de America
    Destinos, gastos y plazos de envío

    4.

    Raul Estrada (author), Isaac Ruiz (author)
    Publicado por Apress 2016-09-29, New York (2016)
    ISBN 10: 1484221745 ISBN 13: 9781484221747
    Nuevo paperback Cantidad disponible: > 20
    Librería
    Blackwell's
    (Oxford, OX, Reino Unido)
    Valoración
    [?]

    Descripción Apress 2016-09-29, New York, 2016. paperback. Condición: New. Nº de ref. del artículo: 9781484221747

    Más información sobre este vendedor | Contactar al vendedor

    Comprar nuevo
    EUR 31,63
    Convertir moneda

    Añadir al carrito

    Gastos de envío: EUR 6,83
    De Reino Unido a Estados Unidos de America
    Destinos, gastos y plazos de envío

    5.

    Estrada, Raul; Ruiz, Isaac
    Publicado por Apress
    ISBN 10: 1484221745 ISBN 13: 9781484221747
    Nuevo PAPERBACK Cantidad disponible: 4
    Librería
    WFL
    (Holtsville, NY, Estados Unidos de America)
    Valoración
    [?]

    Descripción Apress. PAPERBACK. Condición: New. 1484221745 Brand New ,Original Book , Direct from Source , Express 6-8 business days worldwide delivery. Nº de ref. del artículo: DG#IJ276285

    Más información sobre este vendedor | Contactar al vendedor

    Comprar nuevo
    EUR 34,37
    Convertir moneda

    Añadir al carrito

    Gastos de envío: EUR 4,23
    A Estados Unidos de America
    Destinos, gastos y plazos de envío

    6.

    Estrada, Raul, Ruiz, Isaac
    Publicado por Apress
    ISBN 10: 1484221745 ISBN 13: 9781484221747
    Nuevo Tapa blanda Cantidad disponible: 2
    Librería
    Kennys Bookstore
    (Olney, MD, Estados Unidos de America)
    Valoración
    [?]

    Descripción Apress. Condición: New. Num Pages: 264 pages, 22 black & white illustrations, 52 colour illustrations, biography. BIC Classification: UN. Category: (P) Professional & Vocational. Dimension: 180 x 332 x 18. Weight in Grams: 582. . 2016. 1st ed. Paperback. . . . . Books ship from the US and Ireland. Nº de ref. del artículo: V9781484221747

    Más información sobre este vendedor | Contactar al vendedor

    Comprar nuevo
    EUR 38,63
    Convertir moneda

    Añadir al carrito

    Gastos de envío: GRATIS
    A Estados Unidos de America
    Destinos, gastos y plazos de envío

    7.

    Raul Estrada
    Publicado por Apress (2016)
    ISBN 10: 1484221745 ISBN 13: 9781484221747
    Nuevo Tapa blanda Cantidad disponible: 4
    Librería
    Ria Christie Collections
    (Uxbridge, Reino Unido)
    Valoración
    [?]

    Descripción Apress, 2016. Condición: New. book. Nº de ref. del artículo: ria9781484221747_rkm

    Más información sobre este vendedor | Contactar al vendedor

    Comprar nuevo
    EUR 34,43
    Convertir moneda

    Añadir al carrito

    Gastos de envío: EUR 4,40
    De Reino Unido a Estados Unidos de America
    Destinos, gastos y plazos de envío

    8.

    Estrada, Raul / Ruiz, Isaac
    ISBN 10: 1484221745 ISBN 13: 9781484221747
    Nuevo Cantidad disponible: 1
    Librería
    Valoración
    [?]

    Descripción Condición: New. Publisher/Verlag: Springer, Berlin | A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka | Learn how to integrate full-stack open source big data architecture and to choose the correct technology-Scala/Spark, Mesos, Akka, Cassandra, and Kafka-in every layer.Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases now, organizations need more than one paradigm to perform efficient analyses.Big Data SMACK explains each of the full-stack technologies and, more importantly, how to best integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples in every situation. This book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by every technology. It covers the six main concepts of big data architecture and how integrate, replace, and reinforce every layer:The language: ScalaThe engine: Spark (SQL, MLib, Streaming, GraphX)The container: Mesos, DockerThe view: AkkaThe storage: CassandraThe message broker: KafkaWhat You Will Learn:Make big data architecture without using complex Greek letter architecturesBuild a cheap but effective cluster infrastructureMake queries, reports, and graphs that business demandsManage and exploit unstructured and No-SQL data sourcesUse tools to monitor the performance of your architectureIntegrate all technologies and decide which ones replace and which ones reinforceWho This Book Is For:Developers, data architects, and data scientists looking to integrate the most successful big data open stack architecture and to choose the correct technology in every layer | Part I: Introduction.- Chapter 1-Big Data, Big Problems.- Chapter 2-Big Data, Big Solutions.- Part II: Playing SMACK.- Chapter 3-The Language.- Chapter 4-The Engine.- Chapter 5-The Container.- Chapter 6-The View.- Chapter 7-The Storage.- Chapter 8-The Message Broker.- Part III: Improving SMACK.- Chapter 9-Enterprise Integration Patterns.- Chapter 10-Big Data Pipelines.- Chapter 11-Summary. Part 1. IntroductionChapter 1. Big Data, Big ProblemsChapter 2. Big Data, Big SolutionsPart 2. Playing SMACKChapter 3. The Language: ScalaChapter 4. The Model: AkkaChapter 5. Storage. Apache CassandraChapter 6. The ViewChapter 7. The Manager: Apache MesosChapter 8. The Broker: Apache KafkaPart 3. Improving SMACKChapter 9. Fast Data PatternsChapter 10. Big Data PipelinesChapter 11. Glossary. | Format: Paperback | Language/Sprache: english | 566 gr | 257x178x14 mm | 264 pp. Nº de ref. del artículo: K9781484221747

    Más información sobre este vendedor | Contactar al vendedor

    Comprar nuevo
    EUR 36,70
    Convertir moneda

    Añadir al carrito

    Gastos de envío: EUR 2,99
    De Alemania a Estados Unidos de America
    Destinos, gastos y plazos de envío

    9.

    Estrada, Raul
    Publicado por APress (2016)
    ISBN 10: 1484221745 ISBN 13: 9781484221747
    Nuevo Cantidad disponible: > 20
    Impresión bajo demanda
    Librería
    Pbshop
    (Wood Dale, IL, Estados Unidos de America)
    Valoración
    [?]

    Descripción APress, 2016. PAP. Condición: New. New Book. Shipped from US within 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: IQ-9781484221747

    Más información sobre este vendedor | Contactar al vendedor

    Comprar nuevo
    EUR 36,64
    Convertir moneda

    Añadir al carrito

    Gastos de envío: EUR 3,45
    A Estados Unidos de America
    Destinos, gastos y plazos de envío

    10.

    Raul Estrada
    Publicado por APress (2016)
    ISBN 10: 1484221745 ISBN 13: 9781484221747
    Nuevo Cantidad disponible: 4
    Librería
    Books2Anywhere
    (Fairford, GLOS, Reino Unido)
    Valoración
    [?]

    Descripción APress, 2016. PAP. Condición: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Nº de ref. del artículo: GB-9781484221747

    Más información sobre este vendedor | Contactar al vendedor

    Comprar nuevo
    EUR 29,89
    Convertir moneda

    Añadir al carrito

    Gastos de envío: EUR 10,24
    De Reino Unido a Estados Unidos de America
    Destinos, gastos y plazos de envío

    Existen otras copia(s) de este libro

    Ver todos los resultados de su búsqueda