User Defined Functions (UDF) are an important and powerful extension point for database queries. Systems using incremental materialized views largely do not support UDFs because they cannot easily be incrementalized. In this work we design single-tuple UDF and User Defined Aggregates (UDA) interfaces for Noria, a state-of-the art dataflow system with incremental materialized views. We also add limited support for User Defined Table Functions (UDTF), by compiling them to query fragments. We show our UDTFs scale by implementing a motivational example used Friedman et al.

Large infrastructures of Internet companies, such as Facebook and Twitter, are composed of several layers of micro-services. While this modularity provides scalability to the system, the I/O associated with each service request strongly impacts its performance. In this context, writing concise programs which execute I/O efficiently is especially challenging. In this paper, we introduce Ÿauhau, a novel compile-time solution. Ÿauhau reduces the number of I/O calls through rewrites on a simple expression language. To execute I/O concurrently, it lowers the expression language to a dataflow representation. Our approach can be used alongside an existing programming language, permitting the use of legacy code. We describe an implementation in the JVM and use it to evaluate our approach. Experiments show that Ÿauhau can significantly improve I/O, both in terms of the number of I/O calls and concurrent execution. Ÿauhau outperforms state-of-the-art approaches with similar goals.