Used for
- Real-time data processingData ScienceMachine LearningData EngineeringSQL Analytics
Features
- High ScalabilityIntegration with popular frameworksBatch and streaming data processingMulti-language support (Python, SQL, Scala, Java, R)Advanced distributed SQL engineAdaptive Query ExecutionSupport for ANSI SQLScalable machine learningFault-tolerant cluster computingStructured and unstructured data handlingOpen source community supportBatch and real-time streaming data processingFast, distributed ANSI SQL queriesPetabyte-scale data analysisMachine learning at scaleIntegrates with popular frameworksFault-tolerant clustersOpen-source with extensive community support
What is Apache Spark™ used for?
Apache Spark™ is used for executing data engineering, data science, and machine learning on single-node machines or clusters.What languages does Apache Spark™ support?
Apache Spark™ supports multiple languages including Python, SQL, Scala, Java, and R.How does Apache Spark™ handle data processing?
Apache Spark™ handles data processing in both batch and real-time streaming modes.What makes Apache Spark™ fast?
Apache Spark™ executes fast, distributed ANSI SQL queries and has an advanced distributed SQL engine which contributes to its speed.Can Apache Spark™ handle large-scale data?
Yes, Apache Spark™ is designed to perform exploratory data analysis on petabyte-scale data.Does Apache Spark™ support machine learning?
Yes, Apache Spark™ supports machine learning and allows training algorithms on a laptop and scaling to clusters.What is Adaptive Query Execution in Apache Spark™?
Adaptive Query Execution in Apache Spark™ adapts the execution plan at runtime, such as automatically setting the number of reducers and join algorithms.Is Apache Spark™ open-source?
Yes, Apache Spark™ is open-source and supported by an extensive community.Who uses Apache Spark™?
Apache Spark™ is used by thousands of companies, including 80% of the Fortune 500.Does Apache Spark™ integrate with other frameworks?
Yes, Apache Spark™ integrates with popular frameworks, helping to scale them to thousands of machines.