Building a near real-time analytical application with Kudu : solving bid data problems using the 'KIKS' Stack - Apache Kudu, Apache Impala, Apache Kafka, and Apache Spark /

"Building near real-time analytical applications that combine real-time data inserts, updates, and fast analytics is almost impossible with any single Hadoop storage technology. The introduction of Apache Kudu and the 'KIKS' stack breaks through this barrier, making it possible to bui...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Bosshart, Ryan (Orador)
Formato: Electrónico Video
Idioma:Inglés
Publicado: [Place of publication not identified] : O'Reilly Media, [2017]
Temas:
Apache Hadoop.
Big data.
Electronic data processing > Distributed processing.
Computer architecture.
Données volumineuses.
Traitement réparti.
Ordinateurs > Architecture.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

LEADER 00000cgm a2200000Ii 4500
001 OR_ocn981256450
003 OCoLC
005 20231017213018.0
006 m o c
007 cr cna||||||||
007 vz czazuu
008 170404s2017 xx 055 o vleng d
040 |a UMI  |b eng  |e rda  |e pn  |c UMI  |d TOH  |d OCLCF  |d UAB  |d OCLCO 
035 |a (OCoLC)981256450 
037 |a CL0500000844  |b Safari Books Online 
050 4 |a QA76.9.B45 
049 |a UAMI 
100 1 |a Bosshart, Ryan,  |e speaker. 
245 1 0 |a Building a near real-time analytical application with Kudu :  |b solving bid data problems using the 'KIKS' Stack - Apache Kudu, Apache Impala, Apache Kafka, and Apache Spark /  |c with Ryan Bosshart. 
264 1 |a [Place of publication not identified] :  |b O'Reilly Media,  |c [2017] 
300 |a 1 online resource (1 streaming video file (54 min., 19 sec.)) :  |b digital, sound, color 
336 |a two-dimensional moving image  |b tdi  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
337 |a video  |b v  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
511 0 |a Presenter, Ryan Bosshart. 
500 |a Title from title screen (viewed March 30, 2017). 
500 |a Date of publication from resource description page. 
520 |a "Building near real-time analytical applications that combine real-time data inserts, updates, and fast analytics is almost impossible with any single Hadoop storage technology. The introduction of Apache Kudu and the 'KIKS' stack breaks through this barrier, making it possible to build near real-time analytical applications that are simple, fast, and reliable. In this course, designed for developers, architects, and engineers with some experience working with common Hadoop components (Kafka, Hive, Spark, Impala, etc.), you'll use 'KIKS' to create an app that demonstrates the real-time ingestion, persistence, and visualization of time-series events. Kudu is at the center of this architecture. It combines real-time inserts, random lookups, and fast analytics into a single storage layer without the need for the complexities of the lambda architecture, making time-series and IOT use-cases much easier to conquer than with previous generation big data technologies. The app you'll build uses real-time financial data, but it also applies to use cases in IOT, retail, manufacturing, and other industries with real-time analytical needs."--Resource description page. 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
630 0 0 |a Apache Hadoop. 
630 0 7 |a Apache Hadoop.  |2 fast  |0 (OCoLC)fst01911570 
650 0 |a Big data. 
650 0 |a Electronic data processing  |x Distributed processing. 
650 0 |a Computer architecture. 
650 6 |a Données volumineuses. 
650 6 |a Traitement réparti. 
650 6 |a Ordinateurs  |x Architecture. 
650 7 |a Big data.  |2 fast  |0 (OCoLC)fst01892965 
650 7 |a Computer architecture.  |2 fast  |0 (OCoLC)fst00872026 
650 7 |a Electronic data processing  |x Distributed processing.  |2 fast  |0 (OCoLC)fst00906987 
856 4 0 |u https://learning.oreilly.com/videos/~/9781491985748/?ar  |z Texto completo (Requiere registro previo con correo institucional) 
994 |a 92  |b IZTAP 

Ejemplares similares