The EXPLAIN statement is a very useful tool in SQL databases to help users better understand what's going on in queries and where to apply tweaks. For example, the output of EXPLAIN can help you decide where to add indexes and can quickly remedy slow queries by telling you the join type, the possible indexes to choose vs. the index actually chosen, the estimate of rows to be examined, etc.
Please see this exciting opportunity for interested faculty members below:
We are pleased to announce 2018 Sustainable Research Pathways (SRP) program is now accepting applications from faculty at US degree granting academic institutions. Come to Berkeley Lab to learn about summer research opportunities for you and/or your students at a Department of Energy National Laboratory
SRP Matching and Exploratory Workshop To facilitate the possible matching of faculty and/or their students with lab research opportunities, selected faculty will be invited to a...
Please see this exciting opportunity to learn Python remotely below:
The Center for High Performance Computing’s Summer 2018 Presentation Series continues tomorrow with part 1 of the hands-on introduction to python programming sessions presented by Brett Milash and Wim Cardoen:
Imagine conducting a randomized controlled trial with noncompliance (participants assigned to the treatment group can choose to avoid treatment, and participants assigned to the control group are able to seek out treatment). If the experimenter observes the ultimate treatment status for all participants, then she can use random assignment as an instrumental variable to measure the causal effect of treatment. Miguel...
Bob Freeman PhD, Director of Research Technology Operations at RCS, and a member of the Harvard Research Computing Council, will be giving a talk at the Harvard Technology ABCD meeting held on May 4th from 12pm - 2pm to discuss how research computing is changing at HBS, and examples of research that have benefited from RCS assistance. If you are interested in attending this meeting, please visit: https://www.abcd.harvard.edu/MeetingAnn.html
Dplyr is an R package used for data manipulation which provides much more concise, readable blocks of data manipulation code once you can understand its syntax. Dplyr is built around 5 verbs: Select, Filter, Arrange, Mutate, and Summarize.