Architecting a next-generation data platform
Using Entity 360 as an example, Jonathan Seidman, Ted Malaska, Mark Grover, and Gwen Shapira explain how to architect a modern, real-time big data platform leveraging recent advancements in the open source software world, using components like Kafka, Impala, Kudu, Spark Streaming, and Spark SQL with Hadoop to enable new forms of data processing and analytics.
| Talk Title | Architecting a next-generation data platform |
| Speakers | Jonathan Seidman (Cloudera), Ted Malaska (Capital One), Mark Grover (Lyft), Gwen Shapira (Confluent) |
| Conference | Strata + Hadoop World |
| Conf Tag | Big Data Expo |
| Location | San Jose, California |
| Date | March 14-16, 2017 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
Apache Hadoop is rapidly moving from its batch processing roots to a more flexible platform supporting both batch and streaming workloads. Rapid advancements in the Hadoop ecosystem are causing a dramatic evolution in both the storage and processing capabilities of the Hadoop platform. These advancements include projects like: While these advancements to the Hadoop platform are exciting, they also add a new array of tools that architects and developers need to understand when architecting solutions with Hadoop. Using Entity 360 as an example, Jonathan Seidman, Ted Malaska, Mark Grover, and Gwen Shapira explain how to architect a modern, real-time big data platform leveraging recent advancements in the open source software world, using components like Kafka, Impala, Kudu, Spark Streaming, and Spark SQL with Hadoop to enable new forms of data processing and analytics. Along the way, they discuss considerations and best practices for utilizing these components to implement solutions, cover common challenges and how to address them, and provide practical advice for building your own modern, real-time big data architectures. Topics include:
