Hadoop培训
Apache Hadoop培训
客户评论
你最喜欢什么训练？： 详细介绍每种工具。 琥珀Mehrotra NIIT有限公司 。
课程名称: Hadoop Administration
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你最喜欢什么训练？： 详细介绍每种工具。 琥珀Mehrotra NIIT有限公司 。
课程名称: Hadoop Administration
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实用部分。 Arkadi
Arkadiusz Iwaszko
课程名称: Big Data Hadoop Analyst Training
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1.一流的设备2.首次介绍Hadoop和技术的世界。
Przemysław Ćwik
课程名称: Big Data Hadoop Administration Training
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事实上所有的数据和软件都可以在一台已经准备好的虚拟机上使用，由教练在外部磁盘上提供。
vyzVoice
课程名称: Hadoop for Developers and Administrators
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培训师给予reallive例子。
Simon Hahn
课程名称: Administrator Training for Apache Hadoop
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培训师的强大能力。
Grzegorz Gorski
课程名称: Administrator Training for Apache Hadoop
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许多交流会
Jacek Pieczątka
课程名称: Administrator Training for Apache Hadoop
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愿意分享更多。
Balaram Chandra Paul
课程名称: A practical introduction to Data Analysis and Big Data
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非常喜欢互动的学习方式
Luigi Loiacono
课程名称: Data Analysis with Hive/HiveQL
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这是一个非常实用的训练，我喜欢练习练习。
Proximus
课程名称: Data Analysis with Hive/HiveQL
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良好的概述，理论和练习之间的良好平衡。
Proximus
课程名称: Data Analysis with Hive/HiveQL
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动态交互和“交付”主题，这要感谢虚拟机，非常刺激！
Philippe Job
课程名称: Data Analysis with Hive/HiveQL
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培训师的能力和知识。
Jonathan Puvilland
课程名称: Data Analysis with Hive/HiveQL
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它涵盖了广泛的信息
Continental AG / Abteilung: CF IT Finance
课程名称: A practical introduction to Data Analysis and Big Data
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技术介绍。
Continental AG / Abteilung: CF IT Finance
课程名称: A practical introduction to Data Analysis and Big Data
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总的来说内容很好
Sameer Rohadia
课程名称: A practical introduction to Data Analysis and Big Data
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涵盖了其他建议的其他主题。German Alonso Durango
German Alonso Durango Colmenares
课程名称: Capacitación de Administrador para Apache Hadoop
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这非常简单，我们花了一半时间在Cloudera / Hadoop中执行某些操作，运行不同的命令，检查系统等等。额外的材料（书籍，网站等）真的很感谢，我们将不得不继续学习。安装非常有趣，而且非常方便，从头开始的集群设置非常好。
Ericsson
课程名称: Administrator Training for Apache Hadoop
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其他课程类别
课程简介
| 代码 | 名字 | 时长 | 概览 |
|---|---|---|---|
| mdlmrah | Model MapReduce and Apache Hadoop | 14小时 | The course is intended for IT specialist that works with the distributed processing of large data sets across clusters of computers. |
| ApHadm1 | Apache Hadoop: Manipulation and Transformation of Data Performance | 21小时 | This course is intended for developers, architects, data scientists or any profile that requires access to data either intensively or on a regular basis. The major focus of the course is data manipulation and transformation. Among the tools in the Hadoop ecosystem this course includes the use of Pig and Hive both of which are heavily used for data transformation and manipulation. This training also addresses performance metrics and performance optimisation. The course is entirely hands on and is punctuated by presentations of the theoretical aspects. |
| apacheh | Administrator Training for Apache Hadoop | 35小时 | Audience: The course is intended for IT specialists looking for a solution to store and process large data sets in a distributed system environment Goal: Deep knowledge on Hadoop cluster administration. |
| hadoopforprojectmgrs | 面向项目经理的Hadoop | 14小时 | 随着越来越多的软件和IT项目从本地处理和数据管理转向分布式处理和大数据存储，项目经理们正在意识到需要升级他们的知识和技能，以掌握与大数据项目和机会相关的概念和实践。 本课程将向项目经理介绍当下最流行的大数据处理框架：Hadoop。 在这一由讲师引导的培训中，学员将学习Hadoop生态系统的核心组件，以及这些技术如何用于解决大规模问题。在学习这些基础的过程中，学员还将提高他们与这些系统的开发人员和实施人员以及许多IT项目涉及的数据科学家和分析师沟通的能力。 受众 希望将Hadoop应用到其现有开发或IT基础架构中的项目经理 需要与包括大数据工程师、数据科学家和业务分析师在内的跨职能团队进行沟通的项目经理 课程形式 部分讲座、部分讨论、练习和大量实操 |
| hadoopadm | Hadoop Administration | 21小时 | The course is dedicated to IT specialists that are looking for a solution to store and process large data sets in distributed system environment Course goal: Getting knowledge regarding Hadoop cluster administration |
| storm | Apache Storm | 28小时 | Apache Storm is a distributed, real-time computation engine used for enabling real-time business intelligence. It does so by enabling applications to reliably process unbounded streams of data (a.k.a. stream processing). "Storm is for real-time processing what Hadoop is for batch processing!" In this instructor-led live training, participants will learn how to install and configure Apache Storm, then develop and deploy an Apache Storm application for processing big data in real-time. Some of the topics included in this training include: Apache Storm in the context of Hadoop Working with unbounded data Continuous computation Real-time analytics Distributed RPC and ETL processing Request this course now! Audience Software and ETL developers Mainframe professionals Data scientists Big data analysts Hadoop professionals Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| hadoopmapr | Hadoop Administration on MapR | 28小时 | Audience: This course is intended to demystify big data/hadoop technology and to show it is not difficult to understand. |
| ambari | Apache Ambari: Efficiently manage Hadoop clusters | 21小时 | Apache Ambari is an open-source management platform for provisioning, managing, monitoring and securing Apache Hadoop clusters. In this instructor-led live training participants will learn the management tools and practices provided by Ambari to successfully manage Hadoop clusters. By the end of this training, participants will be able to: Set up a live Big Data cluster using Ambari Apply Ambari's advanced features and functionalities to various use cases Seamlessly add and remove nodes as needed Improve a Hadoop cluster's performance through tuning and tweaking Audience DevOps System Administrators DBAs Hadoop testing professionals Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| hadoopdeva | Advanced Hadoop for Developers | 21小时 | Apache Hadoop is one of the most popular frameworks for processing Big Data on clusters of servers. This course delves into data management in HDFS, advanced Pig, Hive, and HBase. These advanced programming techniques will be beneficial to experienced Hadoop developers. Audience: developers Duration: three days Format: lectures (50%) and hands-on labs (50%). |
| kylin | Apache Kylin: From classic OLAP to real-time data warehouse | 14小时 | Apache Kylin is an extreme, distributed analytics engine for big data. In this instructor-led live training, participants will learn how to use Apache Kylin to set up a real-time data warehouse. By the end of this training, participants will be able to: Consume real-time streaming data using Kylin Utilize Apache Kylin's powerful features, including snowflake schema support, a rich SQL interface, spark cubing and subsecond query latency Note We use the latest version of Kylin (as of this writing, Apache Kylin v2.0) Audience Big data engineers Big Data analysts Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| hadoopdev | Hadoop for Developers (4 days) | 28小时 | Apache Hadoop is the most popular framework for processing Big Data on clusters of servers. This course will introduce a developer to various components (HDFS, MapReduce, Pig, Hive and HBase) Hadoop ecosystem. |
| 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 |
| hadoopba | Hadoop for Business Analysts | 21小时 | Apache Hadoop is the most popular framework for processing Big Data. Hadoop provides rich and deep analytics capability, and it is making in-roads in to tradional BI analytics world. This course will introduce an analyst to the core components of Hadoop eco system and its analytics Audience Business Analysts Duration three days Format Lectures and hands on labs. |
| 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 |
| hadoopadm1 | Hadoop For Administrators | 21小时 | Apache Hadoop is the most popular framework for processing Big Data on clusters of servers. In this three (optionally, four) days course, attendees will learn about the business benefits and use cases for Hadoop and its ecosystem, how to plan cluster deployment and growth, how to install, maintain, monitor, troubleshoot and optimize Hadoop. They will also practice cluster bulk data load, get familiar with various Hadoop distributions, and practice installing and managing Hadoop ecosystem tools. The course finishes off with discussion of securing cluster with Kerberos. “…The materials were very well prepared and covered thoroughly. The Lab was very helpful and well organized” — Andrew Nguyen, Principal Integration DW Engineer, Microsoft Online Advertising Audience Hadoop administrators Format Lectures and hands-on labs, approximate balance 60% lectures, 40% labs. |
| tigon | Tigon: Real-time streaming for the real world | 14小时 | Tigon is an open-source, real-time, low-latency, high-throughput, native YARN, stream processing framework that sits on top of HDFS and HBase for persistence. Tigon applications address use cases such as network intrusion detection and analytics, social media market analysis, location analytics, and real-time recommendations to users. This instructor-led, live training introduces Tigon's approach to blending real-time and batch processing as it walks participants through the creation a sample application. By the end of this training, participants will be able to: Create powerful, stream processing applications for handling large volumes of data Process stream sources such as Twitter and Webserver Logs Use Tigon for rapid joining, filtering, and aggregating of streams Audience Developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| hbasedev | HBase for Developers | 21小时 | This course introduces HBase – a NoSQL store on top of Hadoop. The course is intended for developers who will be using HBase to develop applications, and administrators who will manage HBase clusters. We will walk a developer through HBase architecture and data modelling and application development on HBase. It will also discuss using MapReduce with HBase, and some administration topics, related to performance optimization. The course is very hands-on with lots of lab exercises. Duration : 3 days Audience : Developers & Administrators |
| datameer | Datameer for Data Analysts | 14小时 | Datameer is a business intelligence and analytics platform built on Hadoop. It allows end-users to access, explore and correlate large-scale, structured, semi-structured and unstructured data in an easy-to-use fashion. In this instructor-led, live training, participants will learn how to use Datameer to overcome Hadoop's steep learning curve as they step through the setup and analysis of a series of big data sources. By the end of this training, participants will be able to: Create, curate, and interactively explore an enterprise data lake Access business intelligence data warehouses, transactional databases and other analytic stores Use a spreadsheet user-interface to design end-to-end data processing pipelines Access pre-built functions to explore complex data relationships Use drag-and-drop wizards to visualize data and create dashboards Use tables, charts, graphs, and maps to analyze query results Audience Data analysts Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| hivehiveql | Data Analysis with Hive/HiveQL | 7小时 | This course covers how to use Hive SQL language (AKA: Hive HQL, SQL on Hive, HiveQL) for people who extract data from Hive |
| nifi | Apache NiFi for Administrators | 21小时 | Apache NiFi (Hortonworks DataFlow) is a real-time integrated data logistics and simple event processing platform that enables the moving, tracking and automation of data between systems. It is written using flow-based programming and provides a web-based user interface to manage dataflows in real time. In this instructor-led, live training, participants will learn how to deploy and manage Apache NiFi in a live lab environment. By the end of this training, participants will be able to: Install and configure Apachi NiFi Source, transform and manage data from disparate, distributed data sources, including databases and big data lakes Automate dataflows Enable streaming analytics Apply various approaches for data ingestion Transform Big Data and into business insights Audience System administrators Data engineers Developers DevOps Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| 68736 | Hadoop for Developers (2 days) | 14小时 | |
| nifidev | Apache NiFi for Developers | 7小时 | Apache NiFi (Hortonworks DataFlow) is a real-time integrated data logistics and simple event processing platform that enables the moving, tracking and automation of data between systems. It is written using flow-based programming and provides a web-based user interface to manage dataflows in real time. In this instructor-led, live training, participants will learn the fundamentals of flow-based programming as they develop a number of demo extensions, components and processors using Apache NiFi. By the end of this training, participants will be able to: Understand NiFi's architecture and dataflow concepts Develop extensions using NiFi and third-party APIs Custom develop their own Apache Nifi processor Ingest and process real-time data from disparate and uncommon file formats and data sources Audience Developers Data engineers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| HadoopDevAd | Hadoop for Developers and Administrators | 21小时 | Hadoop is the most popular Big Data processing framework. |
| hadooppython | Hadoop with Python | 28小时 | Hadoop is a popular Big Data processing framework. Python is a high-level programming language famous for its clear syntax and code readibility. In this instructor-led, live training, participants will learn how to work with Hadoop, MapReduce, Pig, and Spark using Python as they step through multiple examples and use cases. By the end of this training, participants will be able to: Understand the basic concepts behind Hadoop, MapReduce, Pig, and Spark Use Python with Hadoop Distributed File System (HDFS), MapReduce, Pig, and Spark Use Snakebite to programmatically access HDFS within Python Use mrjob to write MapReduce jobs in Python Write Spark programs with Python Extend the functionality of pig using Python UDFs Manage MapReduce jobs and Pig scripts using Luigi Audience Developers IT Professionals Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| IntroToAvro | Apache Avro: Data serialization for distributed applications | 14小时 | This course is intended for Developers Format of the course Lectures, hands-on practice, small tests along the way to gauge understanding |
| apachedrill | Apache Drill用于飞速分析多种大数据格式 | 21小时 | Apache Drill是一种无模式、分布式、内存列式SQL查询引擎，用于Hadoop、NoSQL及其他云和文件存储系统。Apache Drill的强大之处在于它能够使用单个查询连接来自多个数据存储的数据。Apache Drill支持许多NoSQL数据库和文件系统，包括HBase、MongoDB、MapR-DB、HDFS、MapR-FS、Amazon S3、Azure Blob Storage、Google Cloud Storage、Swift、NAS和本地文件。 在这一由讲师引导的现场培训中，学员将学习Apache Drill的基础知识，然后利用SQL的强大功能和便利性在无需编写代码的情况下交互式查询大数据。学员还将学习如何优化分布式SQL执行的Drill查询。 在本次培训结束后，学员将能够： 对Hadoop上的结构化和半结构化数据进行“自助式”探索 使用SQL查询来查询已知以及未知数据 了解Apache Drills如何接收和执行查询 编写SQL查询来分析不同类型的数据，包括Hive中的结构化数据，HBase或MapR-DB表中的半结构化数据，以及Parquet和JSON文件中保存的数据。 使用Apache Drill执行即时模式发现，绕过对复杂ETL和模式操作的需求 将Apache Drill与BI（商业智能）工具（如Tableau、Qlikview、MicroStrategy、Excel）集成在一起 受众 数据分析师 数据科学家 SQL程序员 课程形式 部分讲座、部分讨论、练习和大量实操 |
| druid | Druid: Build a fast, real-time data analysis system | 21小时 | Druid is an open-source, column-oriented, distributed data store written in Java. It was designed to quickly ingest massive quantities of event data and execute low-latency OLAP queries on that data. Druid is commonly used in business intelligence applications to analyze high volumes of real-time and historical data. It is also well suited for powering fast, interactive, analytic dashboards for end-users. Druid is used by companies such as Alibaba, Airbnb, Cisco, eBay, Netflix, Paypal, and Yahoo. In this course we explore some of the limitations of data warehouse solutions and discuss how Druid can compliment those technologies to form a flexible and scalable streaming analytics stack. We walk through many examples, offering participants the chance to implement and test Druid-based solutions in a lab environment. Audience Application developers Software engineers Technical consultants DevOps professionals Architecture engineers Format of the course Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding |
| bigdataanahealth | Big Data Analytics in Health | 21小时 | Big data analytics involves the process of examining large amounts of varied data sets in order to uncover correlations, hidden patterns, and other useful insights. The health industry has massive amounts of complex heterogeneous medical and clinical data. Applying big data analytics on health data presents huge potential in deriving insights for improving delivery of healthcare. However, the enormity of these datasets poses great challenges in analyses and practical applications to a clinical environment. In this instructor-led, live training (remote), participants will learn how to perform big data analytics in health as they step through a series of hands-on live-lab exercises. By the end of this training, participants will be able to: Install and configure big data analytics tools such as Hadoop MapReduce and Spark Understand the characteristics of medical data Apply big data techniques to deal with medical data Study big data systems and algorithms in the context of health applications Audience Developers Data Scientists Format of the Course Part lecture, part discussion, exercises and heavy hands-on practice. Note To request a customized training for this course, please contact us to arrange. |
| voldemort | Voldemort: Setting up a key-value distributed data store | 14小时 | Voldemort is an open-source distributed data store that is designed as a key-value store. It is used at LinkedIn by numerous critical services powering a large portion of the site. This course will introduce the architecture and capabilities of Voldomort and walk participants through the setup and application of a key-value distributed data store. Audience Software developers System administrators DevOps engineers Format of the course Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding |
| BigData_ | 数据分析和大数据的实用介绍 | 35小时 | 参与者完成此次培训后，将会对大数据及其相关技术、方法、工具有一个实际和真实的理解。 参与者将有机会通过动手练习将这些知识付诸实践。小组互动和讲师反馈是课堂的重要组成部分。 本课程首先介绍大数据的基本概念，然后讲解用于执行数据分析的编程语言和方法，最后我们会讨论可启用大数据存储、分布式处理及可扩展性的工具和基础架构。 受众 开发人员/程序员 IT顾问 课程形式 部分讲座、部分讨论、实操、偶尔测评进度 |