Best practices for streaming applications
Date: This event took place live on June 21 2016
Duration: Approximately 60 minutes.
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Mark Grover and Ted Malaska offer an overview of projects that can be used for streaming applications, including Kafka, Flume, and Spark Streaming, and discuss the various architectural schemas available, such as Lambda and Kappa Architectures. Mark and Ted compare and contrast each of these options and outline best practices and recommendations based on real-world use cases.
About Mark Grover
Mark Grover is a software engineer at Cloudera working on Apache Spark, as well as a committer on Apache Bigtop and a committer and PMC member on Apache Sentry. Mark has contributed to a number of open source projects including Apache Hadoop, Apache Hive, Apache Sqoop, and Apache Flume. He is a coauthor of O'Reilly Media's Hadoop Application Architectures and wrote a section of Programming Hive. Mark is a sought-after speaker at various national and international conference on topics related to big data. He occasionally blogs about technology.
About Ted Malaska
Ted Malaska is a solutions architect at Cloudera. Ted has 18 years of professional experience working for startups, the US government, some of the world's largest banks, commercial firms, bio firms, retail firms, hardware appliance firms, and the largest nonprofit financial regulator in the US and has worked on close to one hundred clusters for over two dozen clients with over hundreds of use cases. He has architecture experience across topics including Hadoop, Web 2.0, mobile, SOA (ESB, BPM), and big data. Ted is a regular contributor to the Hadoop, HBase, and Spark projects, a regular committer to Flume, Avro, Pig, and YARN, and the coauthor of O'Reilly Media's Hadoop Application Architectures.