Tag: Spark
Episode 436: Apache Samza with Yi Pan
Yi Pan, lead maintainer of Apache Samza discusses the internals of the Samza project as well as the Stream Processing ecosystem. Host Adam Conrad spoke with Pan about the three core aspects of the Samza framework, how it compares to other streaming systems like Spark and Flink, as well as advice on how to handle […]
Episode 398: Apache Kudu with Adar Lieber-Dembo
Adar Lieber-Dembo from Cloudera discusses Apache Kudu, which is a columnar data storage system for fast analytics and fast ingestion of large datasets. Kudu takes its inspiration from systems in the Hadoop ecosystem, but it addresses many of their shortcomings. SE Radio’s Akshay Manchale spoke with Adar about motivations behind building Kudu, features available for […]
SE-Radio Episode 272: Frances Perry on Apache Beam
Jeff Meyerson talks with Frances Perry about Apache Beam, a unified batch and stream processing model. Topics include a history of batch and stream processing, from MapReduce to the Lambda Architecture to the more recent Dataflow model, originally defined in a Google paper. Dataflow overcomes the problem of event time skew by using watermarks and […]
SE-Radio Episode 260: Haoyuan Li on Alluxio
Jeff Meyerson talks to Haoyuan Li about Alluxio, a memory-centric distributed storage system. The cost of memory and disk capacity are both decreasing every year–but only the throughput of memory is increasing exponentially. This trend is driving opportunity in the space of big data processing. Alluxio is an open source, memory-centric, distributed, and reliable storage […]
SE-Radio Episode 235: Ben Hindman on Apache Mesos
Ben Hindman talks to Jeff Meyerson about Apache Mesos, a distributed systems kernel. Mesos abstracts away many of the hassles of managing a distributed system. Hindman starts with a high-level explanation of Mesos, explaining the problems he encountered trying to run multiple instances of Hadoop against a single data set. He then discusses how Twitter uses […]
