Apache Spark Training Courses

Apache Spark Training

Apache Spark - an engine for big data processing training

Testi...Client Testimonials

Spark for Developers

Richard is very calm and methodical, with an analytical insight - exactly the qualities needed to present this sort of course

Kieran Mac Kenna - BAE Systems Applied Intelligence

Spark for Developers

We know know a lot more about the whole environment

John Kidd - Cardano Risk Management

Spark for Developers

The trainer made the class interesting and entertaining which helps quite a bit with all day trainings

Ryan Speelman -

Spark for Developers

I think the trainer had an excellent style of combining humor and real life stories to make the subjects at hand very approachable. I would highly recommend this professor in the future.

Spark for Developers

I think the trainer had an excellent style of combining humor and real life stories to make the subjects at hand very approachable. I would highly recommend this professor in the future.

Spark for Developers

Ernesto did a great job explaining the high level concepts of using Spark and it's various modules.

Michael Nemerouf -

Apache Spark Course Outlines

Code Name Duration Overview
68780 Apache Spark 14 hours Why Spark? Problems with Traditional Large-Scale Systems Introducing Spark Spark Basics What is Apache Spark? Using the Spark Shell Resilient Distributed Datasets (RDDs) Functional Programming with Spark Working with RDDs RDD Operations Key-Value Pair RDDs MapReduce and Pair RDD Operations The Hadoop Distributed File System Why HDFS? HDFS Architecture Using HDFS Running Spark on a Cluster Overview A Spark Standalone Cluster The Spark Standalone Web UI Parallel Programming with Spark RDD Partitions and HDFS Data Locality Working With Partitions Executing Parallel Operations Caching and Persistence RDD Lineage Caching Overview Distributed Persistence Writing Spark Applications Spark Applications vs. Spark Shell Creating the SparkContext Configuring Spark Properties Building and Running a Spark Application Logging Spark, Hadoop, and the Enterprise Data Center Overview Spark and the Hadoop Ecosystem Spark and MapReduce Spark Streaming Spark Streaming Overview Example: Streaming Word Count Other Streaming Operations Sliding Window Operations Developing Spark Streaming Applications Common Spark Algorithms Iterative Algorithms Graph Analysis Machine Learning Improving Spark Performance Shared Variables: Broadcast Variables Shared Variables: Accumulators Common Performance Issues
sparkdev Spark for Developers 21 hours 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 Scala primer A quick introduction to Scala Labs : Getting know Scala Spark Basics Background and history Spark and Hadoop Spark concepts and architecture Spark eco system (core, spark sql, mlib, streaming) Labs : Installing and running Spark First Look at Spark Running Spark in local mode Spark web UI Spark shell Analyzing dataset – part 1 Inspecting RDDs Labs: Spark shell exploration RDDs RDDs concepts Partitions RDD Operations / transformations RDD types Key-Value pair RDDs MapReduce on RDD Caching and persistence Labs : creating & inspecting RDDs;   Caching RDDs Spark API programming Introduction to Spark API / RDD API Submitting the first program to Spark Debugging / logging Configuration properties Labs : Programming in Spark API, Submitting jobs Spark SQL SQL support in Spark Dataframes Defining tables and importing datasets Querying data frames using SQL Storage formats : JSON / Parquet Labs : Creating and querying data frames; evaluating data formats MLlib MLlib intro MLlib algorithms Labs : Writing MLib applications GraphX GraphX library overview GraphX APIs Labs : Processing graph data using Spark Spark Streaming Streaming overview Evaluating Streaming platforms Streaming operations Sliding window operations Labs : Writing spark streaming applications Spark and Hadoop Hadoop Intro (HDFS / YARN) Hadoop + Spark architecture Running Spark on Hadoop YARN Processing HDFS files using Spark Spark Performance and Tuning Broadcast variables Accumulators Memory management & caching Spark Operations Deploying Spark in production Sample deployment templates Configurations Monitoring Troubleshooting
hdp Hortonworks Data Platform (HDP) for administrators 21 hours 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 To request a customized course outline for this training, please contact us.  
alluxio Alluxio: Unifying disparate storage systems 7 hours 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 To request a customized course outline for this training, please contact us.  
magellan Magellan: Geospatial Analytics with on Spark 14 hours 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 geospatial 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 To request a customized course outline for this training, please contact us.  

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