This two-day workshop is designed to teach developers how to implement data analytics using Apache Spark for Reactive applications. In this workshop, developers will use hands-on exercises to learn the principles of Apache Spark programming and idioms for specific problems, such as event stream processing, SQL-based analysis on structured data in files, integration with Reactive frameworks like Akka, as well as Hadoop and related tools, and advanced analytics such as machine learning and graph algorithms.
- Understand how to use the Spark Scala APIs to implement various data analytics algorithms for offline (batchmode) and eventstreaming applications
- Understand Spark internals
- Understand Spark performance considerations
- Understand how to test and deploy Spark applications
- Understand the basics of integrating Spark with Mesos, Hadoop, and Akka
- Experience with Scala, such as completion of Fast Track to Scala course
- Experience with SQL, machine learning, and other Big Data tools will be helpful, but not required.
- Developers with basic knowledge of Scala, as covered in “Lightbend Scala Language - Professional”
- Developers with an interest in data science looking to put theory into high-scale practice
- Managers who want to understand how to field applications powered by fast data analytics
Financing in France
- May be financed through OPCA (if financing covers all of the cost of the training)
- Cannot be financed through the CPF