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Apache Spark

Apache Spark

Apache Spark is an open and fast framework for distributed data processing and analytics at scale.

Used at
spark.apache.org github.com github.com

About Apache Spark

Apache Spark is a powerful engine for processing large datasets in both batch and real time, with first-class support for Scala, Java, Python and R. By moving much work into memory and leveraging a cluster environment, Spark can be significantly faster than traditional disk-based Hadoop MapReduce.

What makes Spark especially compelling is that it is more than simple data transformation - it provides a unified ecosystem: run SQL queries with Spark SQL, analyze streaming data, run machine learning workloads with MLlib and perform graph processing with GraphX.

The community around Spark is active: it’s an Apache Software Foundation project with source on GitHub and a large ecosystem of third-party packages and resources for building diverse data workflows.

If you work with data engineering or large-scale analytics, Apache Spark is a strong choice - it scales from a handful of nodes to thousands, and its versatility lets you use the same framework for ETL jobs, real-time analytics and ML pipelines.

Apache Spark is often used together with

Java
Python

Apache Spark is included as part of

MARQS
SMACK

Apache Spark is used at

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