Kai Yu

Kai_Yu_ACED

Kai Yu

Distinguished Engineer

Dell Technologies, Inc

Biography

Kai Yu is a Distinguished Engineer in Dell EMC Solutions Engineering and a member of Dell Technical Leadership Community. Kai has 26 years’ experience of architecting and implementing various IT solutions by specializing in Oracle RAC database, Oracle BI and Oracle EBS, Virtualization/Cloud. Kai has been a frequent speaker at various IT/Oracle conferences with over 180 presentations in more than 20 countries. He also authored 35 articles in technical journals such as IEEE Transactions on Big Data, IOUG Select and Dell Power Solutions and co-authored Apress book “Expert Oracle RAC12c”. Kai has taken some leadership positions in IOUG such as IOUG conference committee member, IOUG RAC SIG president and IOUG Cloud SIG co-founder and the current vice president. Kai has been an Oracle ACE Director since 2010 and was featured as Oracle ACE Spotlight by OTN. He also received the 2011 OAUG Innovator of Year award the 2012 Oracle Excellence Award: Technologist of the Year: Cloud Architect by Oracle Magazine. Kai has shared all his technical articles and conference presentations on his Oracle blog: https://kyuoracleblog.wordpress.com/.

Papers

Boosting Database Performance in Oracle 21c Database with Persistent Memory.

Event: Connect 2021
Stream: Architecture, Cloud Database & Technology

The Latest Persistent Memory such as Intel Optane Persistent Memory (PMEM) combines near-DRAM performance with the data persistence of storage. It can be configured in memory mode or application direct mode. When the memory mode is used, PMEMs can be considered as volatile and can be used as main memory and DRAM is treated as a write-back cache. PMEMs can also be configured in application direct mode to store database files and redo logs. This presentation will discuss the use cases of PMEM:1) In memory mode use PMEMs for Oracle In-Memory store;2) in Application direct mode to store the database files, namely persistent Memory Database in Oracle 21c. We will discuss the significant performance benefits that can be achieved from either of these two modes. We will discuss the Persistent Memory Database feature that includes directly mapped buffer cache and Persistent Memory Filestore (PMEM Filestore) in Oracle 21c. We will also discuss how PMEMs are used in Oracle Exadata X8M.

In-database Machine Learning with Oracle Database and/or Oracle Autonomous Database

Event: Connect 2021
Stream: Architecture, Cloud Database & Technology

Many Machine Learning tasks need to access a lot of data set, which in many cases are stored in a database such as Oracle Database. It makes a more scalable solution to do the machine learning task in the database, which is called in-database machine learning. Oracle Autonomous Database comes with a library of Oracle machine learning algorithms and a set of building tools such as SQL notebooks for machine learning. This allows Data scientists to run Machine Learning projects in Oracle Database without moving data. This session will examine Oracle Machine Learning as part of the Oracle database as well as Oracle Autonomous Database. We will discuss the process of machine learning: analyze and prepare data set; build and evaluate and apply machine learning model. We also will discuss the Oracle machine learning features in Oracle 21c such as AutoML for In-Database Machine Learning and newly added in-database machine learning algorithms for anomaly detection, regression, and deep learning analysis.