Over the past decade, developers, researchers, and the community at large have successfully built tens of thousands of data applications using Apache Spark™. Since then, use cases and requirements of data applications have evolved. Today, every application, from web services that run in application servers, interactive environments such as notebooks and IDEs, to phones and edge devices such as smart home devices, want to leverage the power of data. However, Spark's driver architecture is monolithic, running client applications on top of a scheduler, optimizer and analyzer. This architecture makes it hard to address these new requirements as there is no built-in capability to remotely connect to a Spark cluster from languages other than SQL.

Spark Connect introduces a decoupled client-server architecture for Apache Spark that allows remote connectivity to Spark clusters using the DataFrame API and unresolved logical plans as the protocol. The separation between client and server allows Spark and its open ecosystem to be leveraged from everywhere. It can be embedded in modern data applications, in IDEs, notebooks and programming languages. This session highlights how simple it is to connect to Spark using Spark Connect from any data applications or IDEs. We will do a deep dive into the architecture of Spark Connect and provide an outlook on how the community can participate in the extension of Spark Connect for new programming languages and frameworks bringing the power of Spark everywhere.

Talk by: Martin Grund and Stefania Leone

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

Have some great questions about Apache Spark™ and Lakehouses?  Well, come by and ask the experts your questions!

Talk by: Martin Grund, Hyukjin Kwon, and Wenchen Fan

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

Spark developers want to develop and debug their code using their tools of choice and development best practices while ensuring high-production fidelity on the target remote cluster. However, Spark's driver architecture is monolithic, with no built-in capability to directly connect to a remote Spark cluster from languages other than SQL. This makes it hard to enable such interactive developer experiences from a user’s local IDE of choice. Spark Connect’s decoupled client-server architecture introduces remote connectivity to Spark clusters and with that, enables interactive development experience - Spark and its open ecosystem can be leveraged from everywhere.

In this session, we show how we leverage Spark Connect to build a completely redesigned version of Databricks Connect, a first-class IDE-based developer experience that offers interactive debugging from any IDE. We show how developers can easily ensure consistency between their local and remote environments. We walk the audience through real-live examples of how to locally debug code running on Databrick. We also show how Databricks Connect integrates into the Databricks Visual Studio Code extension for an even better developer experience.

Talk by: Martin Grund and Stefania Leone

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

Over the past decade, developers, researchers, and the community have successfully built tens of thousands of data applications using Spark. Since then, use cases and requirements of data applications have evolved: Today, every application, from web services that run in application servers, interactive environments such as notebooks and IDEs, to phones and edge devices such as smart home devices, want to leverage the power of data.

However, Spark's driver architecture is monolithic, running client applications on top of a scheduler, optimizer and analyzer. This architecture makes it hard to address these new requirements: there is no built-in capability to remotely connect to a Spark cluster from languages other than SQL.

Spark Connect introduces a decoupled client-server architecture for Apache Spark that allows remote connectivity to Spark clusters using the DataFrame API and unresolved logical plans as the protocol. The separation between client and server allows Spark and its open ecosystem to be leveraged from everywhere. It can be embedded in modern data applications, in IDEs, Notebooks and programming languages.

This talk highlights how simple it is to connect to Spark using Spark Connect from any data applications or IDEs. We will do a deep dive into the architecture of Spark Connect and give an outlook of how the community can participate in the extension of Spark Connect for new programming languages and frameworks - to bring the power of Spark everywhere.