Authors
Bart Samwel, John Cieslewicz, Ben Handy, Jason Govig, Petros Venetis, Chanjun Yang, Keith Peters, Jeff Shute, Daniel Tenedorio, Himani Apte, Felix Weigel, David Wilhite, Jiacheng Yang, Jun Xu, Jiexing Li, Zhan Yuan, Craig Chasseur, Qiang Zeng, Ian Rae, Anurag Biyani, Andrew Harn, Yang Xia, Andrey Gubichev, Amr El-Helw, Orri Erling, Zhepeng Yan, Mohan Yang, Yiqun Wei, Thanh Do, Colin Zheng, Goetz Graefe, Somayeh Sardashti, Ahmed M Aly, Divy Agrawal, Ashish Gupta, Shiv Venkataraman
Publication date
2018/8/1
Journal
Proceedings of the VLDB Endowment
Volume
11
Issue
12
Pages
1835-1848
Publisher
VLDB Endowment
Description
F1 Query is a stand-alone, federated query processing platform that executes SQL queries against data stored in different file-based formats as well as different storage systems at Google (e.g., Bigtable, Spanner, Google Spreadsheets, etc.). F1 Query eliminates the need to maintain the traditional distinction between different types of data processing workloads by simultaneously supporting: (i) OLTP-style point queries that affect only a few records; (ii) low-latency OLAP querying of large amounts of data; and (iii) large ETL pipelines. F1 Query has also significantly reduced the need for developing hard-coded data processing pipelines by enabling declarative queries integrated with custom business logic. F1 Query satisfies key requirements that are highly desirable within Google: (i) it provides a unified view over data that is fragmented and distributed over multiple data sources; (ii) it leverages datacenter resources …
Scholar articles
B Samwel, J Cieslewicz, B Handy, J Govig, P Venetis… - Proceedings of the VLDB Endowment, 2018