evanjones.ca
Farewell to MIT (evanjones.ca)
http://www.evanjones.ca/farewell-mit.html
I'll just say that I don't personally find writing papers to be very fulfilling, and I'd rather make things that people will actually use. I'm trying to do that now. I also learned how to do academic research. While my publication record is not stellar, it is also not terrible. Many people have written better. Than I could, so I won't try. However, there is one important piece of advice I wish I could give to my past self, when I started my PhD:. I didn't have time for dumb meetings.
orczhou.com
初识PostgreSQL - 一个故事@MySQL DBA
http://www.orczhou.com/index.php/2014/10/first-sight-postgresql
Amazon RDS for PostgreSQL. 1970年,在Codd发表了关系型数据库的论文,1973年,IBM的System R研究小组也发表了关于实现的系列论文之后, Michael Stonebraker. 开始和学生一起做关系型数据相关的研究并成立了项目Ingres, Interactive Graphics and Retrieval System. 在当时,Ingres相比System R是一个运行在低端机器的( low end ,相对于大型机 "big iron" IBM mainframes)产品。 到后来,80年代初期, 低端机器 的性能和容量已经开始威胁到 大型机。 和一些fellow成立了Ingres Corporation,公司随后出售给 Computer Associates。 POSTGRES在设计的时候,就考虑加上复杂的数据类型、并尝试提供终端用户的性能,还对扩展性做了很多改进,使得对很多环节的修改和改进变得更容易(参考 The design of POSTGRES. 版本号从60开始,之后一直由社区贡献者更新到当前的最新版本9.4 编年概要( 参考. 26412;...
oracle.readthedocs.io
SQL — Oracle SQL & PL/SQL Optimization for Developers 2.1.1 documentation
http://oracle.readthedocs.io/en/latest/sql/index.html
Oracle SQL and PL/SQL Optimization for Developers. Oracle SQL and PL/SQL Optimization for Developers. Before Edgar F. Codd formulated the relational model [Codd69]. For database management in 1969/1970 we had the Dark Ages of databases. Applications that required some form of stored data used a database unique to the application. Therefore, each development project had to reinvent the wheel again. Honestly, who gives a hoot! In-memory databases (IMDB) like SAP’s HANA. Instead; in SQL Server there is.
database.cs.brown.edu
Projects - Brown University Data Management Research Group
http://database.cs.brown.edu/projects
Data Management Research Group. December 12th, 2015. 20/20: Human-in-the-Loop Data Exploration. QUDE: Quantifying Uncertainty in Data Exploration. Tupleware: Redefining Modern Analytics. S-Store: A streaming OLTP system for big velocity applications. SciDB: Data Management System for Scientific Applications. MLbase: Distributed machine learning made easy. H-Store: A Next Generation OLTP DBMS. Longview: Querying the Future Now. Automatic Design for Next-Generation Database Systems.
database.cs.brown.edu
Big Data Internship - Brown University Data Management Research Group
http://database.cs.brown.edu/big-data-internship
Data Management Research Group. November 22nd, 2015. Big Data Summer Internship Program, Summer 2013/14. Data Management Group @ Brown Computer Science. Is a data management service that is designed to assist naive users in exploring large data sets. DBNav aims to provide interactive, real-time performance for human-in-the-loop analysis and exploration, while assisting users with easy navigation through the data space by leveraging models of user interests and application semantics. Current work ...Longv...