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Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWHosted SparkAll>Hosted SparkTry Databricks for freeGet StartedWhat is Hosted Spark?Apache Spark is a fast and general cluster computing system for Big Data built around speed, ease of use, and advanced analytics that was originally built in 2009 at UC Berkeley. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. In addition, it also supports several other tools such as Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for stream processing.Spark Provides Two Modes for Data Exploration:InteractiveBatch For a simplified end-user interaction, Spark is also provided to organizations in a unified hosted data platform. In the absence of direct access to Spark resources by remote applications, the user had to face a longer route to production. In order to overcome this obstacle, there have been created services that enable remote apps to efficiently connect to a Spark cluster over a REST API from anywhere. These interfaces support the execution of snippets of code or programs in a Spark context that runs locally or in Apache Hadoop YARN. Hosted Spark interfaces proved to be turnkey solutions as they facilitate the interaction between Spark and application servers, streamlining the architecture required by interactive web and mobile apps.Hosted Spark Services Provide These Features:Interactive Scala, Python, and R coveringsBatch submissions in Scala, Java, PythonMultiple users are able to share the same serverAllows users to submit jobs from anywhere through RESTNo code change is required do be done to your programsOrganizations can now easily overcome the existing bottlenecks that impede their ability to operationalize Spark, and instead, focus on capturing the value promised by big data.  Additional ResourcesAbout Apache SparkAzure Databricks—Apache Spark as a ServiceLearning Apache Spark 2nd Edition eBookBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers
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