Various research communities have independently arrived at stream processing as a programming model for high-performance and parallel computation, including digital signal processing, databases, operating systems, and complex event processing. Each of these communities has developed some of the same optimizations, but often with conflicting terminology and unstated assumptions. This paper presents a survey of optimizations for stream processing. It is aimed both at users who need to understand

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... nd guide the system's optimizer, and at implementers who need to make engineering trade-offs. To consolidate terminology, this paper is organized as a catalog, in a style similar to catalogs of design patterns or refactorings. To make assumptions explicit and help with trade-offs, each optimization is presented with its safety constraints (when does it preserve correctness?) and a profitability experiment (when does it improve performance?). We hope that this survey will help future optimization inventors to stand on the shoulders of giants from not just their own community.