Richard is very calm and methodical, with an analytical insight - exactly the qualities needed to present this sort of course
Kieran Mac Kenna - BAE Systems Applied Intelligence
Cursos de Apache Spark
Apache Spark - an engine for big data processing training
Client Testimonials
Programas de los Cursos de Apache Spark
| Código | Nombre | Duración | Información General |
|---|---|---|---|
| 68780 | Apache Spark | 14 horas | Why Spark? Problems with Traditional Large-Scale Systems Introducing Spark Spark Basics What is Apache Spark? Using the Spark Shell Resilient Distributed Datasets (RDDs) Functional Programming with Spark Working with RDDs RDD Operations Key-Value Pair RDDs MapReduce and Pair RDD Operations The Hadoop Distributed File System Why HDFS? HDFS Architecture Using HDFS Running Spark on a Cluster Overview A Spark Standalone Cluster The Spark Standalone Web UI Parallel Programming with Spark RDD Partitions and HDFS Data Locality Working With Partitions Executing Parallel Operations Caching and Persistence RDD Lineage Caching Overview Distributed Persistence Writing Spark Applications Spark Applications vs. Spark Shell Creating the SparkContext Configuring Spark Properties Building and Running a Spark Application Logging Spark, Hadoop, and the Enterprise Data Center Overview Spark and the Hadoop Ecosystem Spark and MapReduce Spark Streaming Spark Streaming Overview Example: Streaming Word Count Other Streaming Operations Sliding Window Operations Developing Spark Streaming Applications Common Spark Algorithms Iterative Algorithms Graph Analysis Machine Learning Improving Spark Performance Shared Variables: Broadcast Variables Shared Variables: Accumulators Common Performance Issues |
| sparkdev | Spark para Desarrolladores | 21 horas | This course will introduce Apache Spark. The students will learn how Spark fits into the Big Data ecosystem, and how to use Spark for data analysis. The course covers Spark shell for interactive data analysis, Spark internals, Spark APIs, Spark SQL, Spark streaming, and machine learning and graphX. AUDIENCIA: Desarrolladores / analistas de datos 1. Scala primer Una breve introducción a Scala Laboratorios: Conocimiento Scala 2. Spark Basics Antecedentes e historia Spark y Hadoop Spark conceptos y arquitectura Spark sistema ecológico (núcleo, spark sql, mlib, streaming) Labs: Instalación y funcionamiento de Spark 3. Primera mirada a la chispa Ejecutar Spark en modo local Interfaz web de Spark web Cáscara de chispa Análisis del conjunto de datos - parte 1 Inspección de RDDs Labs: Exploratio de la cáscara de la chispa 4. RDDs Conceptos de RDDs Particiones Operaciones / transformaciones RDD Tipos de RDD Par de valores clave y RDDs MapReduce en RDD Almacenamiento en caché y persistencia Labs: creación e inspección de RDDs; Caching de RDDs 5. Programación de Spark API Introducción al API Spark API / RDD Enviar el primer programa a Spark Depuración / registro Propiedades de configuración Labs: Programación en Spark API, Envío de trabajos Google Translate for Business:Translator ToolkitWebsite Translator 6. Spark SQL Soporte de SQL en Spark Dataframes Definición de tablas e importación de conjuntos de datos Consultar marcos de datos con SQL Formatos de almacenamiento: JSON / Parquet Labs: Creación y consulta de marcos de datos; Evaluación de formatos de datos 7. MLlib Introducción de MLlib Algoritmos MLlib Labs: Escritura de aplicaciones MLib 8. GraphX Descripción de la biblioteca GraphX API de GraphX Labs: Procesamiento de datos de gráficos utilizando Spark 9. Spark Streaming Descripción general de la transmisión Evaluación de plataformas de transmisión Operaciones de streaming Operaciones de ventana deslizante Labs: Escribir aplicaciones de chispa en streaming 10. Spark y Hadoop Hadoop Intro (HDFS / YARN) Arquitectura de Hadoop + Spark Ejecutar Spark en Hadoop YARN Procesamiento de archivos HDFS con Spark 11. Rendimiento y optimización de la chispa Variables de difusión Acumuladores Gestión de memoria y caché 12. Operaciones de chispa Implementación de Spark en producción Ejemplos de plantillas de implementación Configuraciones Supervisión Solución de problemas |
| hdp | Hortonworks Data Platform (HDP) for administrators | 21 horas | Hortonworks Data Platform is an open-source Apache Hadoop support platform that provides a stable foundation for developing big data solutions on the Apache Hadoop ecosystem. This instructor-led live training introduces Hortonworks and walks participants through the deployment of Spark + Hadoop solution. By the end of this training, participants will be able to: Use Hortonworks to reliably run Hadoop at a large scale Unify Hadoop's security, governance, and operations capabilities with Spark's agile analytic workflows. Use Hortonworks to investigate, validate, certify and support each of the components in a Spark project Process different types of data, including structured, unstructured, in-motion, and at-rest. Audience Hadoop administrators Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us. |
| magellan | Magellan: Geospatial Analytics with on Spark | 14 horas | Magellan is an open-source distributed execution engine for geospatial analytics on big data. Implemented on top of Apache Spark, it extends Spark SQL and provides a relational abstraction for geospatial analytics. This instructor-led, live training introduces the concepts and approaches for implementing geospacial analytics and walks participants through the creation of a predictive analysis application using Magellan on Spark. By the end of this training, participants will be able to: Efficiently query, parse and join geospatial datasets at scale Implement geospatial data in business intelligence and predictive analytics applications Use spatial context to extend the capabilities of mobile devices, sensors, logs, and wearables Audience Application developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us. |
| alluxio | Alluxio: Unifying disparate storage systems | 7 horas | Alexio is an open-source virtual distributed storage system that unifies disparate storage systems and enables applications to interact with data at memory speed. It is used by companies such as Intel, Baidu and Alibaba. In this instructor-led, live training, participants will learn how to use Alexio to bridge different computation frameworks with storage systems and efficiently manage multi-petabyte scale data as they step through the creation of an application with Alluxio. By the end of this training, participants will be able to: Develop an application with Alluxio Connect big data systems and applications while preserving one namespace Efficiently extract value from big data in any storage format Improve workload performance Deploy and manage Alluxio standalone or clustered Audience Data scientist Developer System administrator Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us. |
Próximos Cursos
| Curso | Fecha | Precio del Curso [A distancia / Presencial] |
|---|---|---|
| Spark for Developers - Granada Alahambra | Mié, 2017-11-08 09:30 | 5340EUR / 5990EUR |
| Apache Spark - Madrid, Chamartín business area | Jue, 2017-11-16 09:30 | 4080EUR / 4980EUR |
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Cursos de Fin de Semana de Apache Spark, Capacitación por la Tarde de Apache Spark, Apache Spark boot camp, Clases de Apache Spark
, Capacitación empresarial de Apache Spark, Talleres para empresas de Apache Spark, Cursos por la Tarde de Apache Spark, Capacitador de Apache Spark, Cursos Privados de Apache Spark, Apache Spark en sitio, Apache Spark con instructor, Programas de capacitación de Apache Spark, Apache Spark coaching, Clases Particulares de Apache Spark, Cursos en linea de Apache Spark,Capacitación de Fin de Semana de Apache Spark, Clases de Apache Spark
, Cursos de Formación de Apache Spark
