Apache Spark

Apache Spark has gained popularity for its ability to handle diverse data processing workloads, including batch processing, real-time data streaming, machine learning, and graph processing.

Its flexibility, performance, and rich set of libraries make it a versatile choice for building data-intensive applications and performing complex analytics on large-scale datasets.

This introduction course covers the main concepts in Apache Spark:

• the core (architecture, RDDs/Dataframes/Datasets, transformations & actions, DAG)

• the SQL engine

• the streaming engine

• machine learning libraries

It also highlights the possible usage of Spark in different use cases like: ETL, Analytics and Machine Learning.

During the course, we will build an end-to-end case with Spark, from data input, data cleaning, data storage, and machine learning. We will work in a cloud environment and we will use Apache Zeppelin for all the Spark coding/exercises (Scala).

This course is taught in Romanian, with course materials available in either English, or Romanian. The course can be customized - on request.