[DB Seminar] Summer 2019 DB Group: Tianyu Li

Tianyu will present this paper in this meeting: Title: Cloud Programming Simplified: A Berkeley View on Serverless Computing Authors: Eric Jonas, Johann Schleier-Smith, Vikram Sreekanti, Chia-Che Tsai, Anurag Khandelwal, Qifan Pu, Vaishaal Shankar, Joao Carreira, Karl Krauth, Neeraja Yadwadkar, Joseph E. Gonzalez, Raluca Ada Popa, Ion Stoica, David A. Patterson Read More

[DB Seminar] Summer 2019 DB Group: Tianyu Li

Tianyu will give an introduction to the DI framework in this meeting. Tianyu potentially will also present this paper in this meeting: Title: Cloud Programming Simplified: A Berkeley View on Serverless Computing Authors: Eric Jonas, Johann Schleier-Smith, Vikram Sreekanti, Chia-Che Tsai, Anurag Khandelwal, Qifan Pu, Vaishaal Shankar, Joao Carreira, Karl Krauth, Neeraja Yadwadkar, Joseph E. Gonzalez, Raluca Ada Popa, Ion Stoica, David A. Patterson Read More

[DB Seminar] DB Group Meeting: Prashanth Menon

Prashanth will be presenting an overview of the new execution engine. Read More

[DB Seminar] Spring 2019 Reading Group: Lin Ma

In this meeting I'll do a practice talk for my presentation on Percona Live:https://www.percona.com/live/19/speaker/lin-ma Read More

[DB Seminar] Spring 2019 Reading Group: Laxman Dhulipala

Abstract:I will provide a broad overview of graph databases, from the earlydays of database research, to their adolescence and experimentationwith RDF, and finally to the current bloom of graph and multi-modelDBs available today. I will also try to defuse the hype around graphdatabases, and try to articulate scenarios where using such a databasecould be useful.Time permitting, I will provide a high-level overview of our recentwork on Aspen, a principled graph-streaming system that extends Ligrawith primitives for updating a graph. Read More

PDL Visit Day 2019: Luis Remis (Intel)

We introduce the Visual Data Management System (VDMS), which enables faster access to big-visual-data and adds support to visual analytics. This is achieved by searching for relevant visual data via metadata stored as a graph, and enabling faster access to visual data through new machine-friendly storage formats. VDMS differs from existing large scale photo serving, video streaming, and textual big-data management systems due to its primary focus on supporting machine learning and data analytics pipelines that use visual data (images, Read More

PDL Visit Day 2019: Pat Helland (SalesForce)

If you squint hard enough, many of the challenges of distributed computing appear similar to the work done by the great physicists. Dang, those fellows were smart! Here, I examine some of the most important physics breakthroughs and draw some whimsical parallels to phenomena in the world of computing... just for fun. Read More

PDL Visit Day 2019: Aurosish Mishra (Oracle)

Oracle Autonomous Database is the industry's first self-driving, self-securing and self-repairing cloud database. It combines decades of database automation techniques and database infrastructure development, with the power of machine learning to deliver a fully autonomous database that revolutionizes data management, enabling enterprises to evolve from the role of builders and managers of databases to users of autonomous database cloud services that offer self-driving capabilities - for any workload! In this talk, we will peek under the hood of the Oracle Read More

Master Thesis Talk: Supporting Hybrid Workloads for In-Memory Database Management Systems via a Universal Columnar Storage Format

The proliferation of modern data processing ecosystems has given rise to open-source columnar data formats. The key advantage of these formats is that they allow organizations to load data from database management systems (DBMSs) once instead of having to convert it to a new format for each usage. These formats, however, are read-only. This means that organizations must still use a heavy-weight transformation process to load data from their original format into the desired columnar format. We aim to reduce Read More

Master Thesis Talk: Non-blocking Lazy Schema Changes in Multi-version Database Management Systems

The relational schema of a table in a database management system (DBMS) describes its logical attribute information and constraints. Despite the aim of separation between logical schema and physical data storage, in practice, the schema often dictates how a DBMS organizes data on disk or in memory. This tight coupling is because the database's physical schema must match its logical schema. The problem with this is that applications that incur frequent schema changes (e.g., add a column, change column type) Read More