Today, Hadoop is deployed on-premises and in the public cloud, with public cloud becoming increasingly more prevalent. The cloud provides some unique abilities, including on-demand infrastructure, cluster elasticity, persisted globally available object storage, and pay-for-use pricing, which enables even more flexible and cost-efficient deployment options for BI and SQL analytic users of Impala but brings in new challenges that need to be carefully considered to achieve optimal outcome.
Henry Robinson and Alex Gutow explain how to best take advantage of the flexibility and cost-effectiveness of the cloud with your BI and SQL analytic workloads using Apache Hadoop and Apache Impala (incubating) to provide the same great functionality, partner ecosystem, and flexibility of on-premises deployments. Henry and Alex cover the architectural considerations, best practices, tuning, and functionality available when deploying or migrating BI and SQL analytic workloads to the cloud.
Henry Robinson is a software engineer at Cloudera. For the past few years, he has worked on Apache Impala, an SQL query engine for data stored in Apache Hadoop, and leads the scalability effort to bring Impala to clusters of thousands of nodes. Henry’s main interest is in distributed systems. He is a PMC member for the Apache ZooKeeper, Apache Flume, and Apache Impala open source projects.
Alex Gutow is senior product marketing manager at Cloudera, where she focuses on the analytic database platform solution and technologies. Previously, she managed technical marketing and PR for Basho Technologies and managed consumer and enterprise marketing for Truaxis, a Mastercard company. Alex holds a BS in marketing and a BA in psychology from Carnegie Mellon University.
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