Apache Spark Description

Apache Spark™ serves as a comprehensive analytics platform designed for large-scale data processing. It delivers exceptional performance for both batch and streaming data by employing an advanced Directed Acyclic Graph (DAG) scheduler, a sophisticated query optimizer, and a robust execution engine. With over 80 high-level operators available, Spark simplifies the development of parallel applications. Additionally, it supports interactive use through various shells including Scala, Python, R, and SQL. Spark supports a rich ecosystem of libraries such as SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming, allowing for seamless integration within a single application. It is compatible with various environments, including Hadoop, Apache Mesos, Kubernetes, and standalone setups, as well as cloud deployments. Furthermore, Spark can connect to a multitude of data sources, enabling access to data stored in systems like HDFS, Alluxio, Apache Cassandra, Apache HBase, and Apache Hive, among many others. This versatility makes Spark an invaluable tool for organizations looking to harness the power of large-scale data analytics.

Pricing

Free Version:
Yes

Integrations

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Company Details

Company:
Apache Software Foundation
Year Founded:
1999
Headquarters:
United States
Website:
spark.apache.org

Media

Apache Spark Screenshot 1
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Product Details

Platforms
Web-Based
Types of Training
Training Docs

Apache Spark Features and Options

Streaming Analytics Platform

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation

Apache Spark Lists

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