Yu Xu

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26 patents (9 pending & 17 issued); 60 internal Invention Disclosures; 6 papers from work published at top database conferences. Many of the ideas I have come up with for optimizing parallel computing apply both to parallel DBMS and to Hadoop. Responsible for Teradata's MapReduce Roadmap and advanced R&D work to answer new marketing challenges and cutting-edge customer requirements. Project highlights Hadoop MapReduce I initiated the Hadoop/MapReduce research, prototyping, experiments in Teradata in early 2008 well before Teradata had any customer interests. My work was used to answer customer inquiries and provide marketing materials. Part of my work went to Teradata Developer articles and highlighted in Teradata's Partner's conference as a major part of Teradata's MapReduce strategy in 2009. In 2010, I made the Hadoop MapReduce part of the largest government benchmark project in Teradata possible by helping the benchmark group with Hadoop installation/tuning, and fixing Hadoop out of memory and data skew issues. I initiated the TeradataInputFormat approach to allow MapReduce programs direct parallel access to Teradata which formed the foundation for Teradata and Cloudera's partnership. created a Tweets/Retweets social analysis demo for Teradata Partners Conference 2011 using Twitter Streaming API lead and demonstrated two Teradata Hadoop demos at the 2010 Teradata Partners Conference. Data skew handling data skew has been a fundamental problem since the beginning of parallel DBMS because a node doing too much work slows down the whole system. Despite more than 30 years of extensive academia research and industry efforts, no effective skew handling mechanism had been implemented by any major parallel DBMS. I invented the PRPD algorithm (published in SIGMOD 2008), the first industrial-strength and cost-efficient data skew solution. Patents filed and papers published. The new PRPD join plan is available in production Teradata 14.