Primula: A practical shuffle/sort operator for serverless computing
Proceedings of the 21st International Middleware Conference Industrial Track, 2020•dl.acm.org
Serverless computing has recently gained much attention as a feasible alternative to always-
on IaaS for data processing. However, existing severless frameworks are not (yet) usable
enough to reach out to a large number of users. To wit, they still require developers to
specify the number of serverless functions for a simple sort job. We report our experience in
designing Primula, a serverless sort operator that abstracts away users from the
complexities of resource provisioning, skewed data and stragglers, yielding the most …
on IaaS for data processing. However, existing severless frameworks are not (yet) usable
enough to reach out to a large number of users. To wit, they still require developers to
specify the number of serverless functions for a simple sort job. We report our experience in
designing Primula, a serverless sort operator that abstracts away users from the
complexities of resource provisioning, skewed data and stragglers, yielding the most …
Serverless computing has recently gained much attention as a feasible alternative to always-on IaaS for data processing. However, existing severless frameworks are not (yet) usable enough to reach out to a large number of users. To wit, they still require developers to specify the number of serverless functions for a simple sort job. We report our experience in designing Primula, a serverless sort operator that abstracts away users from the complexities of resource provisioning, skewed data and stragglers, yielding the most accessible sort primitive to date. Our evaluation on the IBM Cloud platform demonstrates the usability of Primula without abandoning performance (e.g., 3x faster than a serverless Spark backend and 62% slower than a hybrid serverless/IaaS solution).
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