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- Reduce initial time to productivity.
- Increase employee tenure.
- Plug-and-play into HR onboarding and career pathing programs.
- Customize for ad-hoc and cohort-based hiring approaches.
- Upskill For Tech Teams
- Upgrade and round out developer skills.
- Tailor to tech stack and specific project.
- Help teams, business units, centers of excellence and corporate tech universities.
- Reskill For Tech Teams
- Offer bootcamps to give employees a running start.
- Create immersive and cadenced learning journeys with guaranteed results.
- Supplement limited in-house L&D resources with all-inclusive programs to meet specific business goals.
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- Uplevel your existing tech learning framework.
- Extend HR efforts to provide growth opportunities within the organization.
- Prepare your team for an upcoming tech transformation.
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Course Summary
The Introduction to Hadoop for Developers training course teaches the fundamentals of setting up a Hadoop cluster, as well as the “soup” of related technologies like Hive, Pig and Oozie.
The course begins by teaching students how to access the Hadoop file system and write MapReduce jobs using Java, Pig, and Hive Oozie. Next, students will work with their own installation of a Hadoop 2, single node cluster in hands-on workshops. The course will then discuss examples of real world Map Reduce jobs and how Hadoop has solved real world data-intensive processing problems. The course concludes by exploring the different modes in which Hadoop can be run to support massive amounts of data, as well as students' MapReduce jobs during development.
Best of all, students will walk away with a fully configured virtual machine that can run under VirtualBox or VMWare with Hadoop and all related technologies installed, configured, and ready to run. The virtual machine will include the necessary development environment (using Eclipse), so students are immediately productive in growing their Hadoop knowledge by using a live environment, without the hassle of having to set one up from scratch.
Prerequisites: Basic Java knowledge
(experience with Eclipse is a plus); we recommend courses in our core Java catalog.
- Productivity Objectives:
- Discover the Hadoop Distributed File System (HDFS).
- Interpret general Hadoop Cluster/HDFS administration.
- Explain MapReduce.
- Define how to write a MapReduce job with Java, Pig, and Hive.
- Differentiate how the different Hadoop technologies inter-operate to provide a cohesive big data solution.
- Demonstrate basic management of a Hadoop cluster.
- Give examples of how to perform basic unit testing of MapReduce jobs.
- Distinguish how Message Passing Interface (MPI) and High Performance Computing (HPC) intersect with Hadoop.
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If you are not completely satisfied with your training class, we'll give you your money back.
about our training
-
Real-World Content
Project-focused demos and labs using your tool stack and environment, not some canned "training room" lab.
-
Expert Practitioners
Industry experts with 15+ years of industry experience that bring their battle scars into the classroom.
-
Experiential Learning
More coding than lecture, coupled with architectural and design discussions.
-
Fully Customized
One-size-fits-all doesn't apply to training teams. That's where we come in!
What You'll Learn
In the Introduction to Hadoop for Developers training course, you'll learn:
- Hadoop Overview
- Big Data Introduction
- History
- Comparison to Relational Databases
- Hadoop Ecosystem
- HDFS
- Architecture/Concepts
- Access
- Namenodes
- Filesystem Shell
- Accessing HDFS with Java
- Reading/Writing/Browsing File System
- Basic HDFS Admin
- HBASE
- Overview
- Architecture
- Data Model
- Installation and Shell
- Access via Java API
- Scan API
- Filters
- Storage Model
- Table Design
- Map Reduce on YARN
- Introduction
- Processing Model
- Command line tools
- MapReduce Framework
- Submitting MapReduce Jobs
- Writing MapReduce Jobs in Java
- MapReduce Theory
- Distributive Cache
- Speculative Execution
- YARN Components
- Counters
- Details of MapReduce Job Execution
- Hadoop Streaming
- Implementing a Streaming Job
- Counters in Streaming Jobs
- Contrast with Java Jobs
- MapReduce Workflows
- Problem Decomposition into MapReduce Jobs
- Coding Workflows
- Using the JobControl Class
- Oozie
- Installation
- Writing Oozie Workflows
- Deploying and Running Oozie Jobs
- Pig
- Installation
- Pig Latin
- Writing Pig Scripts
- User Defined functions
- Data Set Joins
- Hive
- Installation
- Table Creation and Deletion
- Partitioning
- Loading Data into Hive
- Joins
- Bucketing
Real-world content
Project-focused demos and labs using your tool stack and environment, not some canned "training room" lab.
Expert Practitioners
Industry experts that bring their battle scars into the classroom.
Experiential Learning
More coding than lecture, coupled with architectural and design discussions.
Fully Customized
One-size-fits-all doesn't apply to training teams. That's where we come in!
Elite Instructor Program
We recently launched our internal Elite Instructor Program. The community driven instructor program is designed to support instructors in transforming students’ lives by consistently showing a world-class level of engagement, ability, and teaching prowess. Reach out today to learn more about our instructors.
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