Hadoop Administrator Training
This four-day course provides the practical and theoretical knowledge necessary to operate a Hadoop cluster. We put great emphasis on practical hands-on exercises that aim to prepare participants to work as effective Hadoop administrators.
After the training, participants will be able to independently install and configure a secure and stable Hadoop cluster. They will understand the architecture, requirements and role of the individual components of core Hadoop. They will be also prepared to troubleshoot problems with Hadoop clusters and tune cluster performance.
A quick introduction to core Hadoop components
Hands-on Exercises: Installing the Hadoop cluster using a cluster manager - Connecting to machines in the public cloud
- Installing the cluster manager (Cloudera Manager or Apache Ambari)
- Installation of core components of a Hadoop cluster
Overview of HDFS
- Basic concepts e.g. writing/reading files, replication, metadata and blocks of data
- Daemons and cluster infrastructure e.g. NameNode, DataNodes
- Key properties and use-cases
- Hands-on Exercises: Verification of HDFS installation and running HDFS commands
Overview of YARN
- Motivation and basic concepts
- Daemons and cluster infrastructure e.g. ResourceManager, NodeManagers, containers
- Exercises: Verification of YARN installation and running YARN commands
Overview of projects from Hadoop Ecosystem
- Processing data in Hadoop cluster with Hive
- Interactive analysis with Spark
- Transferring data to HDFS with Sqoop
- Defining and submitting workflow with Oozie
- Hands-on Exercises: Using Hive, Sqoop, and Spark
Administrative aspects of HDFS
- NameNode internals e.g. metadata management, startup procedure, checkpointing with Secondary NameNode
- Important HDFS configuration settings
- Hands-on Exercises: Changing the Java heap size, restarting NameNode, checking checkpointing status, balancing HDFS
Administrative aspects of YARN
- Cluster resources e.g. container sizes, limits and best practices
- Important configuration settings
- Hands-on Exercises: Reviewing and tuning resource-related settings such as vcores and RAM.
Monitoring and alerting
- Monitoring and alerting capabilities
Hands-on Exercises: Creating custom charts, dashboards and receiving alerts
Hadoop Security, High Availability and Multi-tenancy
- Authentication with Kerberos
- Authorization for Hadoop (including Apache Sentry or Apache Ranger)
- Security-related features e.g. impersonation, encryption, auditing
High availability for Hadoop components
- HA design for HDFS, YARN, Hive, Oozie, HUE
- Hands-on Exercises: Enabling NameNode HA and verifying its correctness
- Bonus Hands-on Exercises: Migrating NameNode to a different host
- Bonus Hands-on Exercises: Enabling and verifying ResourceManager HA
- Overview of Fair/Capacity Scheduler
- Hands-on Exercises: Configuring queues and ACLs in the Scheduler
- Hands-on Exercises: Configuring multi-tenant queues and ACLs in the Scheduler
Popular Maintenance Tasks
Popular cluster maintenance tasks
- Hands-on Exercises: Expanding the cluster, balancing HDFS, decommissioning a node, troubleshooting Spark app
Backup and Disaster Recovery
- Build-in BDR features and components in Hadoop and other Hadoop-related projects
- Hands-on Exercises: Using Trash, HDFS snapshots and DistCp
BONUS: Advanced configuration settings for HDFS and YARN
BONUS: Hardware and software selection for Hadoop clusters
Completed in half the estimated time and with a fivefold improvement on data collection goals, the robust product has exponentially increased processing capabilities. GetInData’s in-depth engagement, reliability, and broad industry knowledge enabled seamless project execution and implementation.
GetInData had been supporting us in building production Big Data infrastructure and implementing real-time applications that process large streams of data. In light of our successful cooperation with GetInData, their unique experience and the quality of work delivered, we recommend the company as a Big Data vendor.
GetInData delivered a robust mechanism that met our requirements. Their involvement allowed us to add a feature to our product, despite not having the required developer capacity in-house.
Their consistent communication and responsiveness enabled GetInData to drive the project forward. They possess comprehensive knowledge of the relevant technologies and have an intuitive understanding of business needs and requirements. Customers can expect a partner that is open to feedback.
We sincerely recommend GetInData as a Big Data training provider! The trainer is a very experienced practitioner and he gave us a lot of tips regarding production deployments, possible issues as well as good practices that are invaluable for a Hadoop administrator.
The engineers and administrators at GetInData are world-class experts. They have proven experience in many open-source technologies such as Hadoop, Spark, Kafka and Flink for implementing batch and real-time pipelines.
Other Big Data Training
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Hadoop Developer TrainingThis four-day course gives software engineers a practical introduction to Big Data application development using popular projects from the Hadoop ecosystem and beyond.
Advanced Spark TrainingThis 2-day training is dedicated to Big Data engineers and data scientists who are already familiar with the basic concepts of Apache Spark and have hands-on experience implementing and running Spark applications.
Data Analyst TrainingThis four-day course teaches Data Analysts how to analyse massive amounts of data available in a Hadoop YARN cluster.
Real-Time Stream ProcessingThis two-day course teaches data engineers how to process unbounded streams of data in real-time using popular open-source frameworks.
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