Apache Spark and it's Components
Explore Apache Spark and its key components including Spark Core, Spark SQL, Streaming, MLlib, and GraphX. Understand how Spark's driver and Resilient Distributed Datasets accelerate big data processing for batch and real-time analytics.
Apache Spark
Apache Spark was developed in 2009 at the University of California, Berkeley. Apache Spark is an open-source distributed processing system used for processing big data. It offers many advantages over Hadoop, one of which is its speed. It can utilize in-memory caching and optimized query execution to retrieve query results quickly. It is well-suited for machine learning, graph analytics, batch processing, and real-time processing. It also provides APIs for popular programming languages such as Java, Scala, Python, and R.
Apache Spark workloads
The Apache Spark framework ...