Fred Reiss’s research while affiliated with University of California, Berkeley and other places

What is this page?


This page lists works of an author who doesn't have a ResearchGate profile or hasn't added the works to their profile yet. It is automatically generated from public (personal) data to further our legitimate goal of comprehensive and accurate scientific recordkeeping. If you are this author and want this page removed, please let us know.

Publications (2)


TelegraphCQ
  • Conference Paper

June 2003

·

23 Reads

·

91 Citations

Sirish Chandrasekaran

·

Mehul A. Shah

·

Owen Cooper

·

[...]

·

Fred Reiss

TelegraphCQ: Continuous Dataflow Processing for an
  • Article
  • Full-text available

December 2002

·

371 Reads

·

83 Citations

Increasingly pervasive networks are leading towards a world where data is constantly in motion. In such a world, conventional techniques for query processing, which were developed under the assumption of a far more static and predictable computational environment, will not be sufficient. Instead, query processors based on adaptive dataflow will be necessary. The Telegraph project has developed a suite of novel technologies for continuously adaptive query processing. The next generation Telegraph system, called TelegraphCQ, is focused on meeting the challenges that arise in handling large streams of continuous queries over high-volume, highly-variable data streams. In this paper, we describe the system architecture and its underlying technology, and report on our ongoing implementation effort, which leverages the PostgreSQL open source code base. We also discuss open issues and our research agenda.

Download

Citations (1)


... Some systems such as Millwheel [27] and Dataflow [28] choose to separate state from the application logic. They have the state centralized in a remote storage [22,32,33] (e.g., a database management system, HDFS or GFS) shared among applications, periodically checkpointing it for fault tolerance. Using external storage can scale well to large distributed states, but it significantly increases latency in the critical path of stream processing. ...

Reference:

SR3: Customizable Recovery for Stateful Stream Processing Systems
TelegraphCQ: Continuous Dataflow Processing for an