Descripción:
Spark es una de las más importantes tecnologías Big Data. La cantidad de datos generados por los dispositivos de hoy en día, las aplicaciones y los usuarios se está disparando. Por lo tanto, existe una necesidad crítica de herramientas que puedan analizar datos a gran escala y percibir el valor de los mismos. Spark es una poderosa tecnología que satisface esa necesidad. Hay una escasez crítica de personas con experiencia en el análisis de grandes volúmenes de datos, por lo que las empresas están dispuestas a pagar mucho por las personas con habilidades en áreas como Spark y Scala. Luego de la absorción de sus principios mediante este curso, proporcionará un gran impulso a su carrera.
Objetivo:
Este Curso de Big Data Analytics con Spark es una guía para el aprendizaje de Spark para el análisis de datos a gran escala. Usted aprenderá cómo usar Spark para diferentes tipos de grandes proyectos de análisis de datos, incluyendo lotes, interactivo, grafos, y el análisis de flujo de datos, así como el aprendizaje automático.
Temario:
Parte 1: El panorama de la tecnología Big Data
Hadoop | Serialización de datos | Almacenamiento Columnar | Sistemas de mensajería | NoSQL | Motor de consultas Distribuidas SQL
Parte 2: Programando en Scala
Programación Funcional | Fundamentos de Scala | Una aplicación en Scala
Parte 3: El núcleo de Spark
Arquitectura de alto nivel | Ejecución de aplicación | Fuentes de Datos | El API de Spark | Lazi Operations | Cacheo | Variables Compartidas
Parte 4: Análisis de Datos interactivo con Spark Shell
Primeros pasos | Comandos REPL | Uso del Shell de Spark como un Shell de Scala | Análisis numérico | Análisis de Logs
Parte 5: Escribiendo aplicaciones en Spark
Compilando y ejecutando aplicación | Monitoreo de aplicación | Depuración de aplicación | Spark Streaming
Parte 6: Spark SQL
Introducción a Spark SQL | Performance | Aplicaciones | El API de Spark SQL | Funciones incorporadas | UDFs y UDAFs | Ejemplo de Análisis Interactivo | Análisis Interactivo con Spark SQL y JDBC Server
Parte 7: Machine Learning con Spark
Introducción a Machine Learning | Librerías en Spark de Machine Learning | El API de MLib | Spark ML
Parte 8: Procesamiento de Grafos con Spark
Introducción a Grafos | Introducción a GraphX | El API de GraphX
Parte 9: Gestores de Clústers y Monitoreo
Gestión de un Clúster independiente | Apache Mesos | YARN | Monitoreo de un Clúster independiente | Monitoreo de una Aplicación Spark
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