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Apache Spark overview

Industry
Technology
Revenue
Headquarters
Employees
375
Founded in
Website
Organization type
Private
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Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Apache Spark is a medium technology company with 375 employees and an annual revenue of $25.0M that is headquartered in Berkeley, CA.

Apache Spark's mission statement

To create a new framework, optimized for fast iterative processing like machine learning, and interactive data analysis, while retaining the scalability, and fault tolerance of Hadoop MapReduce.

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The team at Apache Spark

  • The founders of Apache Spark is Ali Ghodsi.
  • The key people at Apache Spark is Ali Ghodsi.
Key people
Ali Ghodsi

Apache Spark rankings

Apache Spark is ranked #8 on the Best Technology companies to work for in Berkeley, CA list. Zippia's Best Places to Work lists provide unbiased, data-based evaluations of companies. Rankings are based on government and proprietary data on salaries, company financial health, and employee diversity.

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Apache Spark financial performance

8.9
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Zippia gives an in-depth look into the details of Apache Spark, including salaries, political affiliations, employee data, and more, in order to inform job seekers about Apache Spark. The employee data is based on information from people who have self-reported their past or current employments at Apache Spark. The data on this page is also based on data sources collected from public and open data sources on the Internet and other locations, as well as proprietary data we licensed from other companies. Sources of data may include, but are not limited to, the BLS, company filings, estimates based on those filings, H1B filings, and other public and private datasets. While we have made attempts to ensure that the information displayed are correct, Zippia is not responsible for any errors or omissions or for the results obtained from the use of this information. None of the information on this page has been provided or approved by Apache Spark. The data presented on this page does not represent the view of Apache Spark and its employees or that of Zippia.

Apache Spark may also be known as or be related to Apache Spark.