Apache Spark培训

Apache Spark培训

Apache Spark培训

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Apache Spark大纲

代码 名字 时长 概览
sparkdev Spark for Developers 21小时 OBJECTIVE: 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. AUDIENCE : Developers / Data Analysts
hdp Hortonworks Data Platform (HDP) for administrators 21小时 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
magellan Magellan: Geospatial Analytics with on Spark 14小时 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
alluxio Alluxio: Unifying disparate storage systems 7小时 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
graphcomputing Introduction to Graph Computing 28小时 A large number of real world problems can be described in terms of graphs. For example, the Web graph, the social network graph, the train network graph and the language graph. These graphs tend to be extremely large; processing them requires a specialized set of tools and mindset referred to as graph computing. In this instructor-led, live training, participants will learn about the various technology offerings and implementations for processing graph data. The aim is to identify real-world objects, their characteristics and relationships, then model these relationships and process them as data using graph computing approaches. We start with a broad overview and narrow in on specific tools as we step through a series of case studies, hands-on exercises and live deployments. By the end of this training, participants will be able to: Understand how graph data is persisted and traversed Select the best framework for a given task (from graph databases to batch processing frameworks) Implement Hadoop, Spark, GraphX and Pregel to carry out graph computing across many machines in parallel View real-world big data problems in terms of graphs, processes and traversals Audience Developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
sparkpython 用Spark和Python通过PySpark处理大数据 21小时 Spark是一个用于查询、分析和转换大数据的数据处理引擎。Python是一种高级编程语言,因其清晰的语法和代码可读性而闻名。PySpark允许用户将Spark与Python连接。 在这一由讲师引导的现场培训中,学员将通过实践练习学习如何使用Python和Spark一起分析大数据。 在本次培训结束后,学员将能够: 了解如何使用Spark和Python一起分析大数据 开展模拟真实世界环境的练习 用不同的工具和技术通过PySpark进行大数据分析 受众 开发人员 IT专业人士 数据科学家 课程形式 部分讲座、部分讨论、练习和大量实操
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这些图表往往非常大,处理它们需要一套专门的工具和思维方式,称为图计算。 在这个由教师领导的现场培训中,学员将学习处理图形数据的各种技术产品和实现。 通过本次培训的结束,参与者将能够:了解图形数据如何被持久化和遍历为特定任务选择最佳框架(从图形数据库到批处理框架)实施Hadoop,Spark,GraphX和Pregel来执行图形在多台机器上并行计算查看图形,进程和遍历方面的真实世界大数据问题读者开发人员课程形式部分讲座,部分讨论,练习和重要的动手练习本课程主要介绍大数据的分布式处理原理。 这次由讲师引导的现场培训介绍了Hortonworks,并通过部署Spark + Hadoop解决方案向参与者进行了讲解。 交付模式在这个过程中,代表们将会看到大多数开源技术的实例。