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. Yuichi Iijima and . Yoshiharu Ishikawa. Nagoya University, Japan. Outline. Background and Problem Formulation. Related Work. Query Processing Strategies. Experimental Results. Conclusions. 1. 2. Imprecise. Abstract. With the wide deployment of public cloud computing infrastructures, using clouds to host data query services has become an appealing solution for the advantages on scalability and cost-saving. However, some data might be sensitive that the data owner does not want to move to the cloud unless the data confidentiality and query privacy are guaranteed.. Query Formulation. Ling573. NLP Systems and Applications. April 14, 2011. Roadmap. Motivation:. Retrieval gaps. Query F. ormulation:. Question Series. Query reformulation:. AskMSR. patterns. MULDER parse-based formulation. A query is stated using SQL or other languages, ideally natural languages. After query parsing, each query is essentially treated as a . relational algebra expression. Query optimizer . Enumerates . the possible plans to evaluate expression,. Dr. Bjarne Berg . 3. What We’ll Cover …. . Introduction. Performance Issues & Tips. MultiProviders and Partitioning. Aggregates. Query Design & Caching. Hardware & Servers. Designing for Performance. Adaptive Management. 2. Growth. Recruitment. Stock or. Biomass. Natural. Harvest. Risk. Assessment. Economics. Sociocultural. Political/Legal. Management. Objectives. Management. Actions. Stock. Assessment. Overview. . Adaptive. . Leadership Description. A Model of Adaptive Leadership. How Does Adaptive Leadership Work?. Strengths, Criticisms, Application. Peter G. Northouse, . Leadership: Theory and Practice. Database System Implementation CSE 507. Some slides . adapted from . S. ilberschatz. , . Korth. and . Sudarshan. Database System Concepts – 6. th. Edition.. And . Elamsri. and . Navathe. , Fundamentals of Database Systems – 6. A query is stated using SQL or other languages, ideally natural languages. After query parsing, each query is essentially treated as a . relational algebra expression. Query optimizer . Enumerates . the possible plans to evaluate expression,. 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: . on OpenCL-based FPGAs. Zeke Wang. , Johns Paul, Hui Yan Cheah . (. NTU,. . Singapore), . Bingsheng He (. NUS,. Singapore), . Wei Zhang (HKUST, Hong Kong). 1. Outline. Background and Problem. Challenges. Vagelis. . Hristidis. Eduardo Ruiz. 1. Collaborative Adaptive Data Sharing - FIU. Motivation. Many application domains where . users . collaborate and share domain-specific information. .. Disaster Management. Query optimization. :. The process of choosing a suitable execution strategy for processing a query.. Two internal representations of a query:. Query Tree. Query Graph. Introduction to Query Processing (2). Features of adaptive immunity:. Adaptive immunity is characterized by the following:. 1. Antigenic specificity: (. highly specific).. 2. Diversity : . ( each antigen there is specific T-cell and B-cell for it)..