Cornell Systems Lunch

Abstract: The core data processing team at Google has longer than a decade experience in running stream processing systems that host many of Google’s revenue critical pipelines. Our systems provide strong correctness properties, such as exactly once semantics and globally consistent output, in the presence of various kinds of failures --- notably the failure of an entire data center. In this talk, I will present the set of design principles that have enabled us to run google-scale data pipelines with strict latency and completeness SLOs. I will also walk through two real production system architectures that incorporate these principles to support applications such as aggregation and streaming join at a really large scale.

Bio: Venugopalan “Rama” Ramasubramanian is a Senior Staff Software Engineer and Tech Lead Manager in the Core Data Processing team at Google. He is a lead architect, designer, and implementer of a large-scale stream processing service. His team is responsible for building and maintaining the infrastructure for some of Google’s most revenue-critical data pipelines. Prior to joining Google, he was a research scientist in Microsoft Research with a PhD in Computer Science from Cornell University.

New Oracle Autonomous Database provides automation of tasks that were typically performed by DBAs or experienced user. This includes Auto-Indexing, Auto-Materialized Views, Auto-Zonemaps, and Auto-Partitioning. These autonomous tasks eliminate the need for DBAs so users can concentrate on running their applications rather than on tuning them. In this talk we will elaborate on tools that were needed to automate the tasks, overview of the features including their main challenges, and usage of Machine Learning technology applied in some of their implementations in particular Auto-Materialized Views. In addition, we will elaborate on some challenging future Database areas where automation could be very beneficial. Areas will include automatic performance improvements of series of sql statements generated by typical multi-statements reports.

Bio: Andrew Witkowski is a Vice President in Oracle Corporation. He holds an M.S. in Electrical Engineering and a Ph.D. in computer science. He manages a top layer of Oracle query processing including Optimizer, Execution of SQL Statements, External Tables, Parallel Query, Oracle procedural language PL/SQL, Materialized Views and On-Line Redefinition. He has worked on many SQL extensions including Analytic Functions, SQL Spreadsheet, SQL Pattern Matching, Multi-Dimensional Zonemaps and External and Hybrid Partitioned Tables. He has published several papers in SIGMOD and VLDB conferences. He has 61 US patents including 8 pending ones. Previously he worked at Teradata and Jet Propulsion Laboratory.

Abstract: Upstart space companies are building massive constellations of low-flying satellites to provide Internet service. These developments comprise "one giant leap" in Internet infrastructure, promising global coverage and lower latency. However, fully exploiting the potential of such satellite constellations requires tackling their inherent challenges: thousands of low-Earth orbit satellites travel at high velocity relative to each other, and relative to terrestrial ground stations. The resulting highly-dynamic connectivity is at odds with the Internet design primitives, which assume a largely static core infrastructure. Virtually every aspect of Internet design --- physical interconnection, routing, congestion control, and application behavior --- will need substantial rethinking to integrate this new building block.

This talk will focus on one such problem, that of deciding which satellites should be connected to which others to form a performant network. I will draw out why traditional tools for network design are ill-suited here, and show how a simple, novel approach can improve network throughput by 2x compared to the standard method for interconnecting satellites. Lastly, I will highlight several open questions, and discuss our ongoing work on building tools to explore them.