# Shared Arrangements: practical inter-query sharing for streaming dataflows

## TL;DR

Shared arrangements enable multiple concurrent streaming queries to efficiently share maintained state, reducing redundancy and improving response times and resource usage across various high-throughput data processing domains.

## Contribution

The paper introduces shared arrangements, a novel approach for inter-query sharing of maintained state in streaming dataflows, enhancing efficiency without sacrificing scalability.

## Key findings

- Order-of-magnitude improvements in query response time.
- Significant reductions in resource consumption.
- Enhanced performance across multiple domains.

## Abstract

Current systems for data-parallel, incremental processing and view maintenance over high-rate streams isolate the execution of independent queries. This creates unwanted redundancy and overhead in the presence of concurrent incrementally maintained queries: each query must independently maintain the same indexed state over the same input streams, and new queries must build this state from scratch before they can begin to emit their first results. This paper introduces shared arrangements: indexed views of maintained state that allow concurrent queries to reuse the same in-memory state without compromising data-parallel performance and scaling. We implement shared arrangements in a modern stream processor and show order-of-magnitude improvements in query response time and resource consumption for interactive queries against high-throughput streams, while also significantly improving performance in other domains including business analytics, graph processing, and program analysis.