Apache Spark is the next generation successor to MapReduce. Spark is a powerful, open-source processing engine for data in the Hadoop cluster, optimized for speed, ease of use, and sophisticated analytics. The Spark framework supports streaming data processing and complex, iterative algorithms, enabling applications to run up to 100x faster than traditional Hadoop MapReduce programs.
The 2 day Spark course is aimed at developers who are encountering Spark for the first time and want to understand how to build Big Data Products with Spark. The course would enable participants to build complete, unified Big Data applications combining batch, streaming, and interactive analytics on all their data.
Developers would be able to write sophisticated parallel applications to execute faster decisions, better decisions, and real-time actions, applied to a wide variety of use cases, architectures, and industries.
The course has a practical focus, mixing presentation with in-depth hands-on labs and exercises.
To benefit from this course you should have programming experience with Scala or with Python. The language of instruction is Scala. Basic Linux knowledge is expected.
Big Data Why and What?
Introduction to Spark.
Programming with Spark.
Jobs, Stages, Task
Building and running.
Resilient Distributed Datasets.
Key value pair.
Partitions and Data Locality.
Executing parallel operations.
Sliding window operations.
Tunning Spark Application
Using HDFS with Spark.
Spark and MapReduce.
Maximum Class Size of 15
Access to Course Materials
Certificate of Completion
Access to a Private Channel with Trainers in the Academy Slack
A Q&A session one week post-course
A pre-and-post meeting with our trainers