Search results
100% open source
- Apache Spark is 100% open source, hosted at the vendor-independent Apache Software Foundation. At Databricks, we are fully committed to maintaining this open development model.
www.databricks.com/spark/about
People also ask
Is Apache Spark open source?
What is Apache Spark?
What datastores does Spark SQL support?
What is Spark SQL?
What is spark & why should you use it?
Is Databricks open source?
Spark has a thriving open source community, with contributors from around the globe building features, documentation and assisting other users.
- Download
Spark docker images are available from Dockerhub under the...
- Libraries
Spark SQL is developed as part of Apache Spark. It thus gets...
- Documentation
Spark Connect is a new client-server architecture introduced...
- Examples
Apache Spark ™ examples. This page shows you how to use...
- Community
Apache Spark ™ community. Have questions? StackOverflow. For...
- Developers
Go to File -> Import Project, locate the spark source...
- Apache Software Foundation
"The most popular open source software is Apache…" DZone,...
- Spark Streaming
Spark Structured Streaming makes it easy to build streaming...
- Download
Apache Spark is an open-source unified analytics engine for large-scale data processing. Spark provides an interface for programming clusters with implicit data parallelism and fault tolerance.
Internet powerhouses such as Netflix, Yahoo, and eBay have deployed Spark at massive scale, collectively processing multiple petabytes of data on clusters of over 8,000 nodes. It has quickly become the largest open source community in big data, with over 1000 contributors from 250+ organizations.
- Resilient Distributed Dataset (RDD) Resilient Distributed Datasets (RDDs) are fault-tolerant collections of elements that can be distributed among multiple nodes in a cluster and worked on in parallel.
- Directed Acyclic Graph (DAG) As opposed to the two-stage execution process in MapReduce, Spark creates a Directed Acyclic Graph (DAG) to schedule tasks and the orchestration of worker nodes across the cluster.
- DataFrames and Datasets. In addition to RDDs, Spark handles two other data types: DataFrames and Datasets. DataFrames are the most common structured application programming interfaces (APIs) and represent a table of data with rows and columns.
- Spark Core. Spark Core is the base for all parallel data processing and handles scheduling, optimization, RDD, and data abstraction. Spark Core provides the functional foundation for the Spark libraries, Spark SQL, Spark Streaming, the MLlib machine learning library, and GraphX graph data processing.
Apr 3, 2024 · Apache Spark is a data processing framework that can quickly perform processing tasks on very large data sets, and can also distribute data processing tasks across multiple computers, either on...
- Ian Pointer
What Is Apache Spark? Apache Spark is an open source analytics engine used for big data workloads. It can handle both batches as well as real-time analytics and data processing workloads. Apache Spark started in 2009 as a research project at the University of California, Berkeley.
Jan 8, 2024 · Apache Spark is an open-source cluster-computing framework. It provides elegant development APIs for Scala, Java, Python, and R that allow developers to execute a variety of data-intensive workloads across diverse data sources including HDFS, Cassandra, HBase, S3 etc.