Sql Server to Aurora Postgresql Migration Playbook
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Perl DBI API Reference
H Perl DBI API Reference This appendix describes the Perl DBI application programming interface. The API consists of a set of methods and attributes for communicating with database servers and accessing databases from Perl scripts. The appendix also describes MySQL-specific extensions to DBI provided by DBD::mysql, the MySQL database driver. I assume here a minimum version of DBI 1.50, although most of the material applies to earlier versions as well. DBI 1.50 requires at least Perl 5.6.0 (with 5.6.1 preferred). As of DBI 1.611, the minimum Perl version is 5.8.1. I also assume a minimum version of DBD::mysql 4.00. To determine your versions of DBI and DBD::mysql (assuming that they are installed), run this program: #!/usr/bin/perl # dbi-version.pl - display DBI and DBD::mysql versions use DBI; print "DBI::VERSION: $DBI::VERSION\n"; use DBD::mysql; print "DBD::mysql::VERSION: $DBD::mysql::VERSION\n"; If you need to install the DBI software, see Appendix A , “Software Required to Use This Book.” Some DBI methods and attributes are not discussed here, either because they do not apply to MySQL or because they are experimental methods that may change as they are developed or may even be dropped. Some MySQL-specific DBD methods are not discussed because they are obsolete. For more information about new or obsolete methods, see the DBI or DBD::mysql documentation, available at http://dbi.perl.org or by running the following commands: % perldoc DBI % perldoc DBI::FAQ % perldoc DBD::mysql The examples in this appendix are only brief code fragments. -
Accessing DB from Programming Languages
Accessing DB from programming languages JDBCJDBC andand ODBCODBC • API (application-program interface) for a program to interact with a database server • Application makes calls to – Connect with the database server – Send SQL commands to the database server – Fetch tuples of result one-by-one into program variables • ODBC (Open Database Connectivity) works with C, C++, C#, and Visual Basic – Other API’s such as ADO.NET sit on top of ODBC • JDBC (Java Database Connectivity) works with Java JDBCJDBC • JDBC is a Java API for communicating with database systems supporting SQL. • JDBC supports a variety of features for querying and updating data, and for retrieving query results. • JDBC also supports metadata retrieval, such as querying about relations present in the database and the names and types of relation attributes. • Model for communicating with the database: – Open a connection – Create a “statement” object – Execute queries using the Statement object to send queries and fetch results – Exception mechanism to handle errors JDBCJDBC CodeCode public static void JDBCexample(String dbid, String userid, String passwd) { try { Class.forName ("oracle.jdbc.driver.OracleDriver"); Connection conn = DriverManager.getConnection( "jdbc:oracle:thin:@db.yale.edu:2000:univdb", userid, passwd); Statement stmt = conn.createStatement(); … Do Actual Work …. stmt.close(); conn.close(); } catch (SQLException sqle) { System.out.println("SQLException : " + sqle); } } JDBCJDBC CodeCode (Cont.)(Cont.) • Update to database try { stmt.executeUpdate( "insert -
Delivering Oracle Compatibility
DELIVERING ORACLE COMPATIBILITY A White Paper by EnterpriseDB www.EnterpriseDB.com TABLE OF CONTENTS Executive Summary 4 Introducing EnterpriseDB Advanced Server 6 SQL Compatibility 6 PL/SQL Compatibility 9 Data Dictionary Views 11 Programming Flexibility and Drivers 12 Transfer Tools 12 Database Replication 13 Enterprise-Class Reliability and Scalability 13 Oracle-Like Tools 14 Conclusion 15 Downloading EnterpriseDB 15 EnterpriseDB EXECUTIVE SUMMARY Enterprises running Oracle® are generally interested in alternative databases for at least three reasons. First, these enterprises are experiencing budget constraints and need to lower their database Total Cost of Ownership (TCO). Second, they are trying to gain greater licensing flexibility to become more agile within the company and in the larger market. Finally, they are actively pursuing vendors who will provide superior technical support and a richer customer experience. And, subsequently, enterprises are looking for a solution that will complement their existing infrastructure and skills. The traditional database vendors have been unable to provide the combination of all three benefits. While Microsoft SQL ServerTM and IBM DB2TM may provide the flexibility and rich customer experience, they cannot significantly reduce TCO. Open source databases, on the other hand, can provide the TCO benefits and the flexibility. However, these open source databases either lack the enterprise-class features that today’s mission critical applications require or they are not equipped to provide the enterprise-class support required by these organizations. Finally, none of the databases mentioned above provide the database compatibility and interoperability that complements their existing applications and staff. The fear of the costs of changing databases, including costs related to application re-coding and personnel re-training, outweigh the expected savings and, therefore, these enterprises remain paralyzed and locked into Oracle. -
Insert Query in Java Using Prepared Statement
Insert Query In Java Using Prepared Statement Overriding Ike reflates impartially while Barton always triturates his oftenness interpages faithfully, he mistrusts so boyishly. Piet remains circumfluous after Wade locate definably or decentralised any definition. Zacherie is aristocratically large-minded after scrubbier Stillman break-outs his sexes sketchily. By allowing the standard access to create a prepared statements quickly delete data is registered list of query in using insert java prepared statement affecting the stored procedure Stmt db-prepareINSERT INTO foo firstname lastname email VALUES. All these source stuff and easily switch to understand your name in cleanup after the insert statement is part of user row can add to above tutorial in. Previously he spares his picture might require that counted the using insert query in java statement can be grouped in statement and respond to. An interest in case of data expected by the member, we check the program to advancing racial equity for using insert query that does it. To teach good coding world through this clause if it behave in prepared insert query statement in java using a later filled with technological advances. Java PreparedStatement javatpoint. When people prepare the statement Cassandra parses the folder string caches the result. To distress an INSERT statement against multiple rows the normal method is to commend a. Java JDBC Tutorial Inserting Data with User Input luv2code. Update PostgreSQL Record using Prepared Statement in Java. To insert a service in school table using PreparedStatement in Java you need not use below syntax to. The typical workflow of using a prepared statement is as follows. -
Automated Fix Generator for SQL Injection Attacks
Automated Fix Generator for SQL Injection Attacks Fred Dysart and Mark Sherriff Department of Computer Science, University of Virginia, Charlottesville, VA 22903 {ftd4q, sherriff}@virginia.edu Abstract Thomas’s solution, any variable that defines a prepared A critical problem facing today’s internet community statement’s structure must be within the same scope as is the increasing number of attacks exploiting flaws the execution of that statement. Our solution does not found in Web applications. This paper specifically incur this limitation because the generation of the targets input validation vulnerabilities found in SQL prepared statement fix is not dependant on the actual queries that may lead to SQL Injection Attacks statement declaration in the code. (SQLIAs). We introduce a tool that automatically detects and suggests fixes to SQL queries that are found 3. SecurePHP to contain SQL Injection Vulnerabilities (SQLIVs). Our solution is called SecurePHP. It was written in Testing was performed against phpBB v2.0, an open C# and utilized the .NET framework. There were two source forum package, to determine the accuracy and main design decisions that guided us through efficacy of our software. development. First, we wanted the tool to be easy to use. While all applications should be simple for a user 1. Introduction to interact with, the reasoning behind our decision was According to the National Institute of Standards and that the increasing amount of SQLIVs present in Technology, SQL Injection Vulnerabilities (SQLIVs) software might be from legacy software that is not amounted 14% of the total Web application maintained by a developer with experience fixing vulnerabilities in 2006 [3]. -
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 -
A First Attempt to Computing Generic Set Partitions: Delegation to an SQL Query Engine Frédéric Dumonceaux, Guillaume Raschia, Marc Gelgon
A First Attempt to Computing Generic Set Partitions: Delegation to an SQL Query Engine Frédéric Dumonceaux, Guillaume Raschia, Marc Gelgon To cite this version: Frédéric Dumonceaux, Guillaume Raschia, Marc Gelgon. A First Attempt to Computing Generic Set Partitions: Delegation to an SQL Query Engine. DEXA’2014 (Database and Expert System Applications), Sep 2014, Munich, Germany. pp.433-440. hal-00993260 HAL Id: hal-00993260 https://hal.archives-ouvertes.fr/hal-00993260 Submitted on 28 Oct 2014 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. A First Attempt to Computing Generic Set Partitions: Delegation to an SQL Query Engine Fr´ed´ericDumonceaux, Guillaume Raschia, and Marc Gelgon LINA (UMR CNRS 6241), Universit´ede Nantes, France [email protected] Abstract. Partitions are a very common and useful way of organiz- ing data, in data engineering and data mining. However, partitions cur- rently lack efficient and generic data management functionalities. This paper proposes advances in the understanding of this problem, as well as elements for solving it. We formulate the task as efficient process- ing, evaluating and optimizing queries over set partitions, in the setting of relational databases. -
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 -
Lecture 3: Advanced SQL
Advanced SQL Lecture 3: Advanced SQL 1 / 64 Advanced SQL Relational Language Relational Language • User only needs to specify the answer that they want, not how to compute it. • The DBMS is responsible for efficient evaluation of the query. I Query optimizer: re-orders operations and generates query plan 2 / 64 Advanced SQL Relational Language SQL History • Originally “SEQUEL" from IBM’s System R prototype. I Structured English Query Language I Adopted by Oracle in the 1970s. I IBM releases DB2 in 1983. I ANSI Standard in 1986. ISO in 1987 I Structured Query Language 3 / 64 Advanced SQL Relational Language SQL History • Current standard is SQL:2016 I SQL:2016 −! JSON, Polymorphic tables I SQL:2011 −! Temporal DBs, Pipelined DML I SQL:2008 −! TRUNCATE, Fancy sorting I SQL:2003 −! XML, windows, sequences, auto-gen IDs. I SQL:1999 −! Regex, triggers, OO • Most DBMSs at least support SQL-92 • Comparison of different SQL implementations 4 / 64 Advanced SQL Relational Language Relational Language • Data Manipulation Language (DML) • Data Definition Language (DDL) • Data Control Language (DCL) • Also includes: I View definition I Integrity & Referential Constraints I Transactions • Important: SQL is based on bag semantics (duplicates) not set semantics (no duplicates). 5 / 64 Advanced SQL Relational Language Today’s Agenda • Aggregations + Group By • String / Date / Time Operations • Output Control + Redirection • Nested Queries • Join • Common Table Expressions • Window Functions 6 / 64 Advanced SQL Relational Language Example Database SQL Fiddle: Link sid name login age gpa sid cid grade 1 Maria maria@cs 19 3.8 1 1 B students 2 Rahul rahul@cs 22 3.5 enrolled 1 2 A 3 Shiyi shiyi@cs 26 3.7 2 3 B 4 Peter peter@ece 35 3.8 4 2 C cid name 1 Computer Architecture courses 2 Machine Learning 3 Database Systems 4 Programming Languages 7 / 64 Advanced SQL Aggregates Aggregates • Functions that return a single value from a bag of tuples: I AVG(col)−! Return the average col value. -
SQL Version Analysis
Rory McGann SQL Version Analysis Structured Query Language, or SQL, is a powerful tool for interacting with and utilizing databases through the use of relational algebra and calculus, allowing for efficient and effective manipulation and analysis of data within databases. There have been many revisions of SQL, some minor and others major, since its standardization by ANSI in 1986, and in this paper I will discuss several of the changes that led to improved usefulness of the language. In 1970, Dr. E. F. Codd published a paper in the Association of Computer Machinery titled A Relational Model of Data for Large shared Data Banks, which detailed a model for Relational database Management systems (RDBMS) [1]. In order to make use of this model, a language was needed to manage the data stored in these RDBMSs. In the early 1970’s SQL was developed by Donald Chamberlin and Raymond Boyce at IBM, accomplishing this goal. In 1986 SQL was standardized by the American National Standards Institute as SQL-86 and also by The International Organization for Standardization in 1987. The structure of SQL-86 was largely similar to SQL as we know it today with functionality being implemented though Data Manipulation Language (DML), which defines verbs such as select, insert into, update, and delete that are used to query or change the contents of a database. SQL-86 defined two ways to process a DML, direct processing where actual SQL commands are used, and embedded SQL where SQL statements are embedded within programs written in other languages. SQL-86 supported Cobol, Fortran, Pascal and PL/1. -
Modèle Bull 2009 Blanc Fr
CNAF PostgreSQL project Philippe BEAUDOIN, Project leader [email protected] 2010, Dec 7 CNAF - Caisse Nationale des Allocations Familiales - Key organization of the French social security system - Distributes benefits to help - Families - Poor people - 123 CAF (local organizations) all over France - 11 million families and 30 million people - 69 billion € in benefits distributed (2008) 2 ©Bull, 2010 CNAF PostgreSQL project The project … in a few clicks GCOS 8 GCOS 8 CRISTAL SDP CRISTAL SDP (Cobol) (Cobol) (Cobol) (Cobol) DBSP RFM-II RHEL-LINUX PostgreSQL Bull - NovaScale 9000 servers (mainframes) 3 ©Bull, 2010 CNAF PostgreSQL project DBSP GCOS 8 CRISTAL SDP (Cobol) (Cobol) InfiniBand link LINUX S.C. S.C. (c+SQL) (c+SQL) PostgreSQL S.C. = Surrogate Client 4 ©Bull, 2010 CNAF PostgreSQL project CNAF I.S. - CRISTAL + SDP : heart of the Information System - Same application running on Bull (GCOS 8) and IBM (z/OS+DB2) mainframes - Also J2E servers, under AIX, … and a lot of peripheral applications - 6 to 8 CRISTAL versions per year ! 5 ©Bull, 2010 CNAF PostgreSQL project Migration to PostgreSQL project plan - A lot of teams all over France (developers, testers, production,...) - 3 domains - CRISTAL application, SDP application - Infrastructure and production - National project leading CRISTAL Developmt Tests 1 CAF C. Deployment C. PRODUCTION Preparation 1 Depl S SDP Develpmt Tests 9/08 1/09 5/09 9/09 12/09 3/10 6 ©Bull, 2010 CNAF PostgreSQL project How BULL participated to the project - Assistance to project leading - Technical expertise