Flock：FaaS 平台上的低成本流式查询引擎
Flock: A Low-Cost Streaming Query Engine on FaaS Platforms
AI总结：
Flock 是一种基于 FaaS 平台的云原生流式查询引擎，利用函数调用负载进行数据交换，无需外部存储和集中协调器，支持 SQL 和 DataFrame API，相比 Apache Flink 成本降低 10-20 倍且性能相当。
摘要：
现有的无服务器数据分析系统依赖外部存储服务（如 S3）进行云函数之间的数据混洗和通信。虽然这种方法提供了无服务器计算的弹性优势，但它带来了额外的延迟和成本开销。我们提出了 Flock，一种新颖的云原生流式查询引擎，利用 FaaS 平台的按需可扩展性进行实时数据分析。Flock 利用函数调用负载进行高效的数据交换，无需外部存储。这不仅降低了延迟和成本，还通过移除集中式协调器的需求简化了架构。Flock 采用基于模板的方法为每个查询阶段动态创建云函数，并采用函数组机制来处理数据聚合和混洗。它同时支持 SQL 和 DataFrame API，易于使用。我们的评估表明，与现有的无服务器和有服务器流式系统相比，Flock 提供了显著的性能提升和成本节省。它在成本上比 Apache Flink 优越 10-20 倍，同时实现了相似的延迟和吞吐量。
英文摘要：
Existing serverless data analytics systems rely on external storage services like S3 for data shuffling and communication between cloud functions. While this approach provides the elasticity benefits of serverless computing, it incurs additional latency and cost overheads. We present Flock, a novel cloud-native streaming query engine that leverages the on-demand scalability of FaaS platforms for real-time data analytics. Flock utilizes function invocation payloads for efficient data exchange, eliminating the need for external storage. This not only reduces latency and cost but also simplifies the architecture by removing the requirement for a centralized coordinator. Flock employs a template-based approach to dynamically create cloud functions for each query stage and a function group mechanism for handling data aggregation and shuffling. It supports both SQL and DataFrame APIs, making it easy to use. Our evaluation shows that Flock provides significant performance gains and cost savings compared to existing serverless and serverful streaming systems. It outperforms Apache Flink by 10-20x in cost while achieving similar latency and throughput.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
