PPT-Adaptive Query Processing

CSE 8330 Conventional Query Processing Statistics generation Query optimization Query execution Unreliable cardinality e stimates Complex queries Changes in the runtime environment Query interactivity. Dr. Bjarne Berg . 3. What We’ll Cover …. . Introduction. Performance Issues & Tips. MultiProviders and Partitioning. Aggregates. Query Design & Caching. Hardware & Servers. Designing for Performance. Formulation & Expansion. Ling573. NLP Systems and Applications. May 2, 2013. Deeper Processing for Query Formulation. MULDER (Kwok, . Etzioni. , & Weld). Converts question to multiple search queries. Slow Money Maine. July 23, 2015. Adaptive Agriculture LLC ~ contact: . mark@adaptive.ag; . geoff@adaptive.ag ~ all content . proprietary. and . confidential. Adaptive Ag. adapt. . –. . become adjusted to new conditions . Dr. Bjarne Berg . 3. What We’ll Cover …. . Introduction. Performance Issues & Tips. MultiProviders and Partitioning. Aggregates. Query Design & Caching. Hardware & Servers. Designing for Performance. Joseph J. Glavan. glavan.3@wright.edu . Joseph W. . Houpt. Wright State University. How are stimuli processed?. Multiple sources of information:. Color . and shape. Facial features. Curved and straight text features. Formulation & Expansion. Ling573. NLP Systems and Applications. May 2, 2013. Deeper Processing for Query Formulation. MULDER (Kwok, . Etzioni. , & Weld). Converts question to multiple search queries. IDOL Under . the . Hood. Techniques and algorithms. #. SeizeTheData. Read the presenter notes before presenting.. Most of the content of this presentation is contained therein.. IDOL knowledge flow. Acquisition. SpatialHadoop. Type: Research Paper (Experimental evaluation). Authors: Ahmed . Eldawy. , . Louai. . Alarabi. , Mohamed F. . Mokbel. Presented by: Siddhant Kulkarni. Term: Fall 2015. Motivation. John . Sirmon. Senior Escalation Engineer – Microsoft Corporation. Microsoft CSS at PASS 2009. Session Objectives And Takeaways. Processing issues . When good cubes go bad. Troubleshooting processing simplified . of Massive Trajectory Data based on MapReduce. Qiang. Ma, Bin Yang (. Fudan. University). Weining. . Qian. , . Aoying. Zhou (ECNU). Presented By: . Xin. Cao (Aalborg University). Outline. Introduction . Deliverable #2. Jonggun Park . Haotian. He. Maria . Antoniak. Ron Lockwood. System architecture. Two modules:. Indexing. Querying . query processing. p. assage retrieval. answer processing/ranking. Processing Systems Using Markov Decision. Processes. 1. Georgia . Institute of . Technology, USA. 2. University . of Maryland. , . USA. 3. Tampere . University of Technology, Finland. With contributions from: . adjusts its coefficients . to adapt input signal . via an adaptive algorithm. .. Applications:. Signal enhancement. Active noise control. Noise cancellation. Telephone echo cancellation. 1. Text: Digital Signal Processing by Li Tan, Chapter 10. Query Processing. Document-at-a-time. Calculates complete scores for documents by processing all term lists, one document at a time. Term-at-a-time. Accumulates scores for documents by processing term lists one at a time.