'Large data files' presentation slideshows

738 views • 59 slides

Finding your way through the woods with GrETEL

Finding your way through the woods with GrETEL. Liesbeth Augustinus Vincent Vandeghinste Ineke Schuurman Frank Van Eynde. TABU-dag - June 14, 2013. GrETEL. Gr eedy E xtraction of T rees for E mpirical L inguistics Query engine for treebanks

572 views • 46 slides

Overview of Bioconductor

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Perl R and SQL for the very beginners

347 views • 23 slides

LifeRaft: Data-Driven, Batch Processing for the Exploration of Scientific Databases

LifeRaft: Data-Driven, Batch Processing for the Exploration of Scientific Databases. BETTER LUCK NEXT TIME!. Problem. Q1. Q4. Q2. Q3. Goals. Eliminate redundant I/O to improve query throughput Batch queries with that exhibit data sharing Pre-process queries to identify data sharing

307 views • 20 slides

Developing LHCb Grid Software: Experiences and Advances

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MapReduce & Hadoo p

MapReduce & Hadoo p. IT332 Distributed Systems. Outline. MapReduce Hadoop Cloudera Hadoop Tutorial. MapReduce. MapReduce is a programming model for data processing The power of MapReduce lies in its ability to scale to 100s or 1000s of computers, each with several processor cores

388 views • 13 slides

Metadata Michael J. Watts mike.watts.nz

Metadata Michael J. Watts http://mike.watts.net.nz. Lecture Outline. What is metadata? The need for metadata XML Metadata and XML Problems with XML. What is metadata?. Data about data Documentation about data Describes a set of data Source Dimensions Variables. What is metadata?.

122 views • 12 slides

CSci 5707, Fall 2013

MapReduce vs. Parallel DBMS Hamid Safizadeh, Otelia Buffington. CSci 5707, Fall 2013. University of Minnesota. MapReduce Idea. Mapping map (k1, v1) ? list (k2, v2). Reducing reduce (k2, list(v2)) ? list (v2). Pseudo-code for counting the number of occurrences of each

191 views • 8 slides