Transparent Autoscaling of Instance Storage
Big data workloads require access to disk space for a variety of operations, generally when intermediate results will not fit in memory. When the required disk space is not available, the jobs fail. To avoid job failures, data engineers and scientists typically waste time trying to estimate the necessary amount of disk via trial and...
Databricks Serverless: Next Generation Resource Management for Apache Spark
As the amount of data in an organization grows, more and more engineers, analysts and data scientists need to analyze this data using tools like Apache Spark. Today, IT teams constantly struggle to find a way to allocate big data infrastructure, budget among different users, and optimize performance. End-users like data scientists and analysts also...
