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Apache Spark is a powerful open-source, distributed processing system used for big data workloads. It leverages in-memory caching and optimized execution for fast analytical queries against data of any size. Spark supports a wide range of languages, including Java, Scala, Python, and R, making it accessible to diverse skillsets. It provides high-level APIs that enable developers to build sophisticated analytics applications with ease, covering data ingestion, transformation, machine learning, and real-time streaming.
Management and coordination of the Apache Spark project development and community.
N/A (Distributed Project - Relies on online collaboration tools and community events)
Open-source collaboration, meritocracy, community-driven development, emphasis on innovation and quality.
The ASF provides the infrastructure and governance to ensure the long-term viability and stability of Apache Spark.
Apache Spark has a massive global presence with users and developers in virtually every country. Its functions are supported globally through open-source contributions, community events, and widespread adoption in cloud platforms, enterprise data centers, and academic research.
N/A (Distributed Project)
N/A (Distributed Project)
N/A (Distributed Project)
N/A (Distributed Project)
Address: N/A (Distributed Project)
Supporting the global adoption and advancement of Apache Spark technology.
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As of April 2025, Apache Spark' leadership includes:
Apache Spark has been backed by several prominent investors over the years, including:
Because Apache Spark is an open-source project managed by the Apache Software Foundation (ASF), traditional executive hires and exits don't apply. Leadership changes occur within the ASF governance structure and are related to project management and committee roles. Identifying specific hires and exits comparable to a for-profit company is not possible.
Discover the tools Apache Spark uses. Highperformr reveals the technologies powering your target accounts — helping your sales, marketing, and GTM teams prioritize smarter and close faster.
As an open-source project, there isn't a standardized email format for the core Apache Spark team or contributors. Communication generally happens through mailing lists hosted by the Apache Software Foundation.
N/A (Contact via Apache mailing lists)
Format
N/A (Contact via Apache mailing lists)
Example
N/A%
Success rate
Apache Software Foundation • October 26, 2023
The Apache Software Foundation announces Apache Spark v3.5.0 - A milestone release with significant enhancements to SQL engine, Pandas API on Spark, Spark Connect and more....more
Datanami • November 15, 2023
Nvidia contributed Rapids Accelerator for Apache Spark, allowing for GPU acceleration of machine learning inference directly within Spark....more
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