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Course Summary
The Introduction to Administering Hadoop Clusters training course is designed to demonstrate the key aspects of installing and maintaining a Hadoop cluster in various forms.
The course begins by examining how to operate the Hadoop Distributed File System (HDFS) file system and MapReduce I/O framework as complementary technologies. Next, it explores how to configure and monitor processes to manage storage and job tasks. The course concludes with an analysis of supplementing clusters with enhanced storage features and client tools.
- Java - Big Data Training - Hadoop - Apache
- Productivity Objectives:
- Describe the HDFS file system and MapReduce I/O frameworks
- Configure and monitor storage management processes and tasks
- Add network topology awareness to a cluster
- Configure a highly-available storage system
- Supplement clusters with enhanced storage features and client tools
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about our training
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Real-World Content
Project-focused demos and labs using your tool stack and environment, not some canned "training room" lab.
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Expert Practitioners
Industry experts with 15+ years of industry experience that bring their battle scars into the classroom.
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Experiential Learning
More coding than lecture, coupled with architectural and design discussions.
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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 Administering Hadoop Clusters training course, you'll learn:
- Hadoop Concepts
- Operate on large data sets
- Parallelize to improve performance
- Use large block sizes
- Distribute and replicate data
- Assign code to data
- Compensate for Node failures and recoveries
- Add Nodes for better performance
- Utilize virtualization for rapid deployment
- Installing a Hadoop Cluster
- Understand the NameNode
- Understand the secondary NameNode
- Understand the Data Node
- Understand the JobTracker
- Understand the TaskTracker
- Understanding the MapReduce Flow
- Map data
- Shuffle and sorting
- Reduce data
- Utilize the “Write Once, Read Many” approach
- Reviewing Job Performance
- Interpret console output
- Navigate the JobTracker UI
- Use TaskTracker logs
- Configuring Nodes
- Understand Hadoop property management
- Manage core properties
- Manage HDFS properties
- Manage MapReduce properties
- Manage worker properties
- Restrict job property changes
- Supporting Federated & HA File Systems
- Restore NameNode services
- Protect NameNode metadata
- Use Federated NameNodes
- Understand the NameNode HA model
- Configure a Federated HDFS system
- Create defensive copies of NameNode metadata
- Controlling Jobs and Resources
- Schedule jobs
- Understand the FairScheduler
- Orchestrate Workflows
- Importing Legacy and Continuous Data
- Utilize Sqoop
- Use Flume
- Understand Hive, Impala, and HBase
- Maintaining HDFS
- Check block integrity
- Balance data across nodes
- Use HDFS Safe Mode
- Address other HDFS systems
- Restrict Node additions
- Installing Ecosystem Packages
- Install Pig
- Install Hive
- Review HBase requirements
- Improving Hadoop Security
- Review authentication & authorization
- Analyze Hadoop’s authorization model
- Understand kerberos architecture
- Review Kerberos implementation options
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!

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