Relational Databases, Logic, and Complexity
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Optimizing Select-Project-Join Expressions
Optimizing select-project-join expressions Jan Van den Bussche Stijn Vansummeren 1 Introduction The expression that we obtain by translating a SQL query q into the re- lational algebra is called the logical query plan for q. The ultimate goal is to further translate this logical query plan into a physical query plan that contains all details on how the query is to be executed. First, however, we can apply some important optimizations directly on the logical query plan. These optimizations transform the logical query plan into an equivalent log- ical query plan that is more efficient to execute. In paragraph 16.3.3, the book discusses the simple (but very important) logical optimizations of \pushing" selections and projections; and recogniz- ing joins, based on the algebraic equalities from section 16.2. In addition, in these notes, we describe another important logical opti- mization: the removal of redundant joins. 2 Undecidability of the general problem In general, we could formulate the optimization problem of relational algebra expressions as follows: Input: A relational algebra expression e. Output: A relational algebra expression e0 such that: 1. e0 is equivalent to e (denoted as e0 ≡ e), in the sense that e(D) = e0(D) for every database D. Here, e(D) stands for the relation resulting from evaluating e on D. 2. e0 is optimal, in the sense that there is no expression e0 that is shorter than e0, yet still equivalent to e. Of course, we have to define what the length of a relational algebra expression is. A good way to do this is to count the number of times a relational algebra operator is applied in the expression. -
Database Concepts 7Th Edition
Database Concepts 7th Edition David M. Kroenke • David J. Auer Online Appendix E SQL Views, SQL/PSM and Importing Data Database Concepts SQL Views, SQL/PSM and Importing Data Appendix E All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America. Appendix E — 10 9 8 7 6 5 4 3 2 1 E-2 Database Concepts SQL Views, SQL/PSM and Importing Data Appendix E Appendix Objectives • To understand the reasons for using SQL views • To use SQL statements to create and query SQL views • To understand SQL/Persistent Stored Modules (SQL/PSM) • To create and use SQL user-defined functions • To import Microsoft Excel worksheet data into a database What is the Purpose of this Appendix? In Chapter 3, we discussed SQL in depth. We discussed two basic categories of SQL statements: data definition language (DDL) statements, which are used for creating tables, relationships, and other structures, and data manipulation language (DML) statements, which are used for querying and modifying data. In this appendix, which should be studied immediately after Chapter 3, we: • Describe and illustrate SQL views, which extend the DML capabilities of SQL. • Describe and illustrate SQL Persistent Stored Modules (SQL/PSM), and create user-defined functions. • Describe and use DBMS data import techniques to import Microsoft Excel worksheet data into a database. E-3 Database Concepts SQL Views, SQL/PSM and Importing Data Appendix E Creating SQL Views An SQL view is a virtual table that is constructed from other tables or views. -
Sql Create Table Variable from Select
Sql Create Table Variable From Select Do-nothing Dory resurrect, his incurvature distasting crows satanically. Sacrilegious and bushwhacking Jamey homologising, but Harcourt first-hand coiffures her muntjac. Intertarsal and crawlier Towney fanes tenfold and euhemerizing his assistance briskly and terrifyingly. How to clean starting value inside of data from select statements and where to use matlab compiler to store sql, and then a regular join You may not supported for that you are either hive temporary variable table. Before we examine the specific methods let's create an obscure procedure. INSERT INTO EXEC sql server exec into table. Now you can show insert update delete and invent all operations with building such as in pay following a write i like the Declare TempTable. When done use t or t or when to compact a table variable t. Procedure should create the temporary tables instead has regular tables. Lesson 4 Creating Tables SQLCourse. EXISTS tmp GO round TABLE tmp id int NULL SELECT empire FROM. SQL Server How small Create a Temp Table with Dynamic. When done look sir the Execution Plan save the SELECT Statement SQL Server is. Proc sql create whole health will select weight married from myliboutdata ORDER to weight ASC. How to add static value while INSERT INTO with cinnamon in a. Ssrs invalid object name temp table. Introduction to Table Variable Deferred Compilation SQL. How many pass the bash array in 'right IN' clause will select query. Creating a pope from public Query Vertica. Thus attitude is no performance cost for packaging a SELECT statement into an inline. -
Conjunctive Queries
Ontology and Database Systems: Foundations of Database Systems Part 3: Conjunctive Queries Werner Nutt Faculty of Computer Science Master of Science in Computer Science A.Y. 2013/2014 Foundations of Database Systems Part 3: Conjunctive Queries Looking Back . We have reviewed three formalisms for expressing queries Relational Algebra Relational Calculus (with its domain-independent fragment) Nice SQL and seen that they have the same expressivity However, crucial properties ((un)satisfiability, equivalence, containment) are undecidable Hence, automatic analysis of such queries is impossible Can we do some analysis if queries are simpler? unibz.it W. Nutt ODBS-FDBs 2013/2014 (1/43) Foundations of Database Systems Part 3: Conjunctive Queries Many Natural Queries Can Be Expressed . in SQL using only a single SELECT-FROM-WHERE block and conjunctions of atomic conditions in the WHERE clause; we call these the CSQL queries. in Relational Algebra using only the operators selection σC (E), projection πC (E), join E1 1C E2, renaming (ρA B(E)); we call these the SPJR queries (= select-project-join-renaming queries) . in Relational Calculus using only the logical symbols \^" and 9 such that every variable occurs in a relational atom; we call these the conjunctive queries unibz.it W. Nutt ODBS-FDBs 2013/2014 (2/43) Foundations of Database Systems Part 3: Conjunctive Queries Conjunctive Queries Theorem The classes of CSQL queries, SPJR queries, and conjunctive queries have all the same expressivity. Queries can be equivalently translated from one formalism to the other in polynomial time. Proof. By specifying translations. Intuition: By a conjunctive query we define a pattern of what the things we are interested in look like. -
Support Aggregate Analytic Window Function Over Large Data by Spilling
Support Aggregate Analytic Window Function over Large Data by Spilling Xing Shi and Chao Wang Guangdong University of Technology, Guangzhou, Guangdong 510006, China North China University of Technology, Beijing 100144, China Abstract. Analytic function, also called window function, is to query the aggregation of data over a sliding window. For example, a simple query over the online stock platform is to return the average price of a stock of the last three days. These functions are commonly used features in SQL databases. They are supported in most of the commercial databases. With the increasing usage of cloud data infra and machine learning technology, the frequency of queries with analytic window functions rises. Some analytic functions only require const space in memory to store the state, such as SUM, AVG, while others require linear space, such as MIN, MAX. When the window is extremely large, the memory space to store the state may be too large. In this case, we need to spill the state to disk, which is a heavy operation. In this paper, we proposed an algorithm to manipulate the state data in the disk to reduce the disk I/O to make spill available and efficiency. We analyze the complexity of the algorithm with different data distribution. 1. Introducion In this paper, we develop novel spill techniques for analytic window function in SQL databases. And discuss different various types of aggregate queries, e.g., COUNT, AVG, SUM, MAX, MIN, etc., over a relational table. Aggregate analytic function, also called aggregate window function, is to query the aggregation of data over a sliding window. -
SQL Standards Update 1
2017-10-20 SQL Standards Update 1 SQL STANDARDS UPDATE Keith W. Hare SC32 WG3 Convenor JCC Consulting, Inc. October 20, 2017 2017-10-20 SQL Standards Update 2 Introduction • What is SQL? • Who Develops the SQL Standards • A brief history • SQL 2016 Published • SQL Technical Reports • What's next? • SQL/MDA • Streaming SQL • Property Graphs • Summary 2017-10-20 SQL Standards Update 3 Who am I? • Senior Consultant with JCC Consulting, Inc. since 1985 • High performance database systems • Replicating data between database systems • SQL Standards committees since 1988 • Convenor, ISO/IEC JTC1 SC32 WG3 since 2005 • Vice Chair, ANSI INCITS DM32.2 since 2003 • Vice Chair, INCITS Big Data Technical Committee since 2015 • Education • Muskingum College, 1980, BS in Biology and Computer Science • Ohio State, 1985, Masters in Computer & Information Science 2017-10-20 SQL Standards Update 4 What is SQL? • SQL is a language for defining databases and manipulating the data in those databases • SQL Standard uses SQL as a name, not an acronym • Might stand for SQL Query Language • SQL queries are independent of how the data is actually stored – specify what data you want, not how to get it 2017-10-20 SQL Standards Update 5 Who Develops the SQL Standards? In the international arena, the SQL Standard is developed by ISO/ IEC JTC1 SC32 WG3. • Officers: • Convenor – Keith W. Hare – USA • Editor – Jim Melton – USA • Active participants are: • Canada – Standards Council of Canada • China – Chinese Electronics Standardization Institute • Germany – DIN Deutsches -
Chapter 1 Logic and Set Theory
Chapter 1 Logic and Set Theory To criticize mathematics for its abstraction is to miss the point entirely. Abstraction is what makes mathematics work. If you concentrate too closely on too limited an application of a mathematical idea, you rob the mathematician of his most important tools: analogy, generality, and simplicity. – Ian Stewart Does God play dice? The mathematics of chaos In mathematics, a proof is a demonstration that, assuming certain axioms, some statement is necessarily true. That is, a proof is a logical argument, not an empir- ical one. One must demonstrate that a proposition is true in all cases before it is considered a theorem of mathematics. An unproven proposition for which there is some sort of empirical evidence is known as a conjecture. Mathematical logic is the framework upon which rigorous proofs are built. It is the study of the principles and criteria of valid inference and demonstrations. Logicians have analyzed set theory in great details, formulating a collection of axioms that affords a broad enough and strong enough foundation to mathematical reasoning. The standard form of axiomatic set theory is denoted ZFC and it consists of the Zermelo-Fraenkel (ZF) axioms combined with the axiom of choice (C). Each of the axioms included in this theory expresses a property of sets that is widely accepted by mathematicians. It is unfortunately true that careless use of set theory can lead to contradictions. Avoiding such contradictions was one of the original motivations for the axiomatization of set theory. 1 2 CHAPTER 1. LOGIC AND SET THEORY A rigorous analysis of set theory belongs to the foundations of mathematics and mathematical logic. -
Multiple Condition Where Clause Sql
Multiple Condition Where Clause Sql Superlunar or departed, Fazeel never trichinised any interferon! Vegetative and Czechoslovak Hendrick instructs tearfully and bellyings his tupelo dispensatorily and unrecognizably. Diachronic Gaston tote her endgame so vaporously that Benny rejuvenize very dauntingly. Codeigniter provide set class function for each mysql function like where clause, join etc. The condition into some tests to write multiple conditions that clause to combine two conditions how would you occasionally, you separate privacy: as many times. Sometimes, you may not remember exactly the data that you want to search. OR conditions allow you to test multiple conditions. All conditions where condition is considered a row. Issue date vary each bottle of drawing numbers. How sql multiple conditions in clause condition for column for your needs work now query you take on clauses within a static list. The challenge join combination for joining the tables is found herself trying all possibilities. TOP function, if that gives you no idea. New replies are writing longer allowed. Thank you for your feedback! Then try the examples in your own database! Here, we have to provide filters or conditions. The conditions like clause to make more content is used then will identify problems, model and arrangement of operators. Thanks for your help. Thanks for war help. Multiple conditions on the friendly column up the discount clause. This sql where clause, you have to define multiple values you, we have to basic syntax. But your suggestion is more readable and straight each way out implement. Use parenthesis to set of explicit groups of contents open source code. -
Relational Algebra
Relational Algebra Instructor: Shel Finkelstein Reference: A First Course in Database Systems, 3rd edition, Chapter 2.4 – 2.6, plus Query Execution Plans Important Notices • Midterm with Answers has been posted on Piazza. – Midterm will be/was reviewed briefly in class on Wednesday, Nov 8. – Grades were posted on Canvas on Monday, Nov 13. • Median was 83; no curve. – Exam will be returned in class on Nov 13 and Nov 15. • Please send email if you want “cheat sheet” back. • Lab3 assignment was posted on Sunday, Nov 5, and is due by Sunday, Nov 19, 11:59pm. – Lab3 has lots of parts (some hard), and is worth 13 points. – Please attend Labs to get help with Lab3. What is a Data Model? • A data model is a mathematical formalism that consists of three parts: 1. A notation for describing and representing data (structure of the data) 2. A set of operations for manipulating data. 3. A set of constraints on the data. • What is the associated query language for the relational data model? Two Query Languages • Codd proposed two different query languages for the relational data model. – Relational Algebra • Queries are expressed as a sequence of operations on relations. • Procedural language. – Relational Calculus • Queries are expressed as formulas of first-order logic. • Declarative language. • Codd’s Theorem: The Relational Algebra query language has the same expressive power as the Relational Calculus query language. Procedural vs. Declarative Languages • Procedural program – The program is specified as a sequence of operations to obtain the desired the outcome. I.e., how the outcome is to be obtained. -
Look out the Window Functions and Free Your SQL
Concepts Syntax Other Look Out The Window Functions and free your SQL Gianni Ciolli 2ndQuadrant Italia PostgreSQL Conference Europe 2011 October 18-21, Amsterdam Look Out The Window Functions Gianni Ciolli Concepts Syntax Other Outline 1 Concepts Aggregates Different aggregations Partitions Window frames 2 Syntax Frames from 9.0 Frames in 8.4 3 Other A larger example Question time Look Out The Window Functions Gianni Ciolli Concepts Syntax Other Aggregates Aggregates 1 Example of an aggregate Problem 1 How many rows there are in table a? Solution SELECT count(*) FROM a; • Here count is an aggregate function (SQL keyword AGGREGATE). Look Out The Window Functions Gianni Ciolli Concepts Syntax Other Aggregates Aggregates 2 Functions and Aggregates • FUNCTIONs: • input: one row • output: either one row or a set of rows: • AGGREGATEs: • input: a set of rows • output: one row Look Out The Window Functions Gianni Ciolli Concepts Syntax Other Different aggregations Different aggregations 1 Without window functions, and with them GROUP BY col1, . , coln window functions any supported only PostgreSQL PostgreSQL version version 8.4+ compute aggregates compute aggregates via by creating groups partitions and window frames output is one row output is one row for each group for each input row Look Out The Window Functions Gianni Ciolli Concepts Syntax Other Different aggregations Different aggregations 2 Without window functions, and with them GROUP BY col1, . , coln window functions only one way of aggregating different rows in the same for each group -
John P. Burgess Department of Philosophy Princeton University Princeton, NJ 08544-1006, USA [email protected]
John P. Burgess Department of Philosophy Princeton University Princeton, NJ 08544-1006, USA [email protected] LOGIC & PHILOSOPHICAL METHODOLOGY Introduction For present purposes “logic” will be understood to mean the subject whose development is described in Kneale & Kneale [1961] and of which a concise history is given in Scholz [1961]. As the terminological discussion at the beginning of the latter reference makes clear, this subject has at different times been known by different names, “analytics” and “organon” and “dialectic”, while inversely the name “logic” has at different times been applied much more broadly and loosely than it will be here. At certain times and in certain places — perhaps especially in Germany from the days of Kant through the days of Hegel — the label has come to be used so very broadly and loosely as to threaten to take in nearly the whole of metaphysics and epistemology. Logic in our sense has often been distinguished from “logic” in other, sometimes unmanageably broad and loose, senses by adding the adjectives “formal” or “deductive”. The scope of the art and science of logic, once one gets beyond elementary logic of the kind covered in introductory textbooks, is indicated by two other standard references, the Handbooks of mathematical and philosophical logic, Barwise [1977] and Gabbay & Guenthner [1983-89], though the latter includes also parts that are identified as applications of logic rather than logic proper. The term “philosophical logic” as currently used, for instance, in the Journal of Philosophical Logic, is a near-synonym for “nonclassical logic”. There is an older use of the term as a near-synonym for “philosophy of language”. -
SQL DELETE Table in SQL, DELETE Statement Is Used to Delete Rows from a Table
SQL is a standard language for storing, manipulating and retrieving data in databases. What is SQL? SQL stands for Structured Query Language SQL lets you access and manipulate databases SQL became a standard of the American National Standards Institute (ANSI) in 1986, and of the International Organization for Standardization (ISO) in 1987 What Can SQL do? SQL can execute queries against a database SQL can retrieve data from a database SQL can insert records in a database SQL can update records in a database SQL can delete records from a database SQL can create new databases SQL can create new tables in a database SQL can create stored procedures in a database SQL can create views in a database SQL can set permissions on tables, procedures, and views Using SQL in Your Web Site To build a web site that shows data from a database, you will need: An RDBMS database program (i.e. MS Access, SQL Server, MySQL) To use a server-side scripting language, like PHP or ASP To use SQL to get the data you want To use HTML / CSS to style the page RDBMS RDBMS stands for Relational Database Management System. RDBMS is the basis for SQL, and for all modern database systems such as MS SQL Server, IBM DB2, Oracle, MySQL, and Microsoft Access. The data in RDBMS is stored in database objects called tables. A table is a collection of related data entries and it consists of columns and rows. SQL Table SQL Table is a collection of data which is organized in terms of rows and columns.