DB2 for I Frequently Asked Questions
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Query Optimization Techniques - Tips for Writing Efficient and Faster SQL Queries
INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 4, ISSUE 10, OCTOBER 2015 ISSN 2277-8616 Query Optimization Techniques - Tips For Writing Efficient And Faster SQL Queries Jean HABIMANA Abstract: SQL statements can be used to retrieve data from any database. If you've worked with databases for any amount of time retrieving information, it's practically given that you've run into slow running queries. Sometimes the reason for the slow response time is due to the load on the system, and other times it is because the query is not written to perform as efficiently as possible which is the much more common reason. For better performance we need to use best, faster and efficient queries. This paper covers how these SQL queries can be optimized for better performance. Query optimization subject is very wide but we will try to cover the most important points. In this paper I am not focusing on, in- depth analysis of database but simple query tuning tips & tricks which can be applied to gain immediate performance gain. ———————————————————— I. INTRODUCTION Query optimization is an important skill for SQL developers and database administrators (DBAs). In order to improve the performance of SQL queries, developers and DBAs need to understand the query optimizer and the techniques it uses to select an access path and prepare a query execution plan. Query tuning involves knowledge of techniques such as cost-based and heuristic-based optimizers, plus the tools an SQL platform provides for explaining a query execution plan.The best way to tune performance is to try to write your queries in a number of different ways and compare their reads and execution plans. -
PL/SQL 1 Database Management System
PL/SQL Database Management System – II Chapter – 1 Query optimization 1. What is query processing in detail: Query processing means set of activity that involves you to retrieve the database In other word we can say that it is process to breaking the high level language into low level language which machine understand and perform the requested action for user. Query processor in the DBMS performs this task. Query processing have three phase i. Parsing and transaction ii. Query optimization iii. Query evaluation Lets see the three phase in details : 1) Parsing and transaction : 1 PREPARED BY: RAHUL PATEL LECTURER IN COMPUTER DEPARTMENT (BSPP) PL/SQL . Check syntax and verify relations. Translate the query into an equivalent . relational algebra expression. 2) Query optimization : . Generate an optimal evaluation plan (with lowest cost) for the query plan. 3) Query evaluation : . The query-execution engine takes an (optimal) evaluation plan, executes that plan, and returns the answers to the query Let us discuss the whole process with an example. Let us consider the following two relations as the example tables for our discussion; Employee(Eno, Ename, Phone) Proj_Assigned(Eno, Proj_No, Role, DOP) where, Eno is Employee number, Ename is Employee name, Proj_No is Project Number in which an employee is assigned, Role is the role of an employee in a project, DOP is duration of the project in months. With this information, let us write a query to find the list of all employees who are working in a project which is more than 10 months old. SELECT Ename FROM Employee, Proj_Assigned WHERE Employee.Eno = Proj_Assigned.Eno AND DOP > 10; Input: . -
Database Systems Administrator FLSA: Exempt
CLOVIS UNIFIED SCHOOL DISTRICT POSITION DESCRIPTION Position: Database Systems Administrator FLSA: Exempt Department/Site: Technology Services Salary Grade: 127 Reports to/Evaluated by: Chief Technology Officer Salary Schedule: Classified Management SUMMARY Gathers requirements and provisions servers to meet the district’s need for database storage. Installs and configures SQL Server according to the specifications of outside software vendors and/or the development group. Designs and executes a security scheme to assure safety of confidential data. Implements and manages a backup and disaster recovery plan. Monitors the health and performance of database servers and database applications. Troubleshoots database application performance issues. Automates monitoring and maintenance tasks. Maintains service pack deployment and upgrades servers in consultation with the developer group and outside vendors. Deploys and schedules SQL Server Agent tasks. Implements and manages replication topologies. Designs and deploys datamarts under the supervision of the developer group. Deploys and manages cubes for SSAS implementations. DISTINGUISHING CAREER FEATURES The Database Systems Administrator is a senior level analyst position requiring specialized education and training in the field of study typically resulting in a degree. Advancement to this position would require competency in the design and administration of relational databases designated for business, enterprise, and student information. Advancement from this position is limited to supervisory management positions. ESSENTIAL DUTIES AND RESPONSIBILITIES Implements, maintains and administers all district supported versions of Microsoft SQL as well as other DBMS as needed. Responsible for database capacity planning and involvement in server capacity planning. Responsible for verification of backups and restoration of production and test databases. Designs, implements and maintains a disaster recovery plan for critical data resources. -
An Overview of Query Optimization
An Overview of Query Optimization Why? Improving query processing time. Fast response is important in several db applications. Is it possible? Yes, but relative. A query can be evaluated in several ways. We can list all of them and then find the best among them. Sometime, we might not be able to do it because of the number of possible ways to evaluate the query is huge. We need to settle for a compromise: we try to find one that is reasonably good. Typical Query Evaluation Steps in DBMS. The DBMS has the following components for query evaluation: SQL parser, quey optimizer, cost estimator, query plan interpreter. The SQL parser accepts a SQL query and generates a relational algebra expression (sometime, the system catalog is considered in the generation of the expression). This expression is fed into the query optimizer, which works in conjunction with the cost estimator to generate a query execution plan (with hopefully a reasonably cost). This plan is then sent to the plan interpreter for execution. How? The query optimizer uses several heuristics to convert a relational algebra expression to an equivalent expres- sion which (hopefully!) can be computed efficiently. Different heuristics are (see explaination in textbook): (i) transformation between selection and projection; 1. Cascading of selection: σC1∧C2 (R) ≡ σC1 (σC2 (R)) 2. Commutativity of selection: σC1 (σC2 (R)) ≡ σC2 (σC1 (R)) 0 3. Cascading of projection: πAtts(R) = πAtts(πAtts0 (R)) if Atts ⊆ Atts 4. Commutativity of projection: πAtts(σC (R)) = σC (πAtts((R)) if Atts includes all attributes used in C. (ii) transformation between Cartesian product and join; 1. -
IBM Power Systems Solution Edition for Scale-Out Cloud
IBM Systems and Technology Solution Brief IBM Power Systems and Storage Solution Edition for Scale-Out Cloud Open source, Linux solution for scale-out data virtualization and cloud Cloud computing is no longer a question of “if” for IT organizations, but Highlights rather one of when, how and for which workloads. Cloud is widely understood to be an IT delivery model that can improve IT asset utilization, Allows open infrastructures to scale out intelligently, with less hardware, flexibility and responsiveness while reducing complexity and lowering power and cooling requirements costs. With these benefits come many complexities which need to be and better economics, using over considered as organizations define and implement a cloud delivery strategy. twice the bandwidth from previous Some technology options can hinder the efficiency and costs saving generations potential of the cloud by impeding interoperability, hampering workload Built-in data virtualization delivers performance, exposing security vulnerabilities and limiting scalability. seamless storage management from a single control point with no Building on the performance advantaged IBM POWER8™ architecture, the impact to applications Power Systems™ and Storage Solution Edition for Scale-Out Cloud Flexibility, agility and provides a superior cost effective platform with open source PowerKVM interoperability with open source, hypervisor, powerful data virtualized with IBM Storwize ® V7000, and community-driven virtualization and a single pane of glass for OpenStack-based cloud management for a single pane of glass cloud heterogeneous cloud management management. The Solution Edition reduces the timeframe for infrastructure deployments from months to days with integrated infrastructure and automated provisioning of virtualized resources. It ensures optimal cost effectiveness with Power scale out systems, automated Easy Tier® for flash and disk storage and Real-Time Compression™ that can store up to 5x as much data in the same physical space. -
The Relational Data Model and Relational Database Constraints
chapter 33 The Relational Data Model and Relational Database Constraints his chapter opens Part 2 of the book, which covers Trelational databases. The relational data model was first introduced by Ted Codd of IBM Research in 1970 in a classic paper (Codd 1970), and it attracted immediate attention due to its simplicity and mathematical foundation. The model uses the concept of a mathematical relation—which looks somewhat like a table of values—as its basic building block, and has its theoretical basis in set theory and first-order predicate logic. In this chapter we discuss the basic characteristics of the model and its constraints. The first commercial implementations of the relational model became available in the early 1980s, such as the SQL/DS system on the MVS operating system by IBM and the Oracle DBMS. Since then, the model has been implemented in a large num- ber of commercial systems. Current popular relational DBMSs (RDBMSs) include DB2 and Informix Dynamic Server (from IBM), Oracle and Rdb (from Oracle), Sybase DBMS (from Sybase) and SQLServer and Access (from Microsoft). In addi- tion, several open source systems, such as MySQL and PostgreSQL, are available. Because of the importance of the relational model, all of Part 2 is devoted to this model and some of the languages associated with it. In Chapters 4 and 5, we describe the SQL query language, which is the standard for commercial relational DBMSs. Chapter 6 covers the operations of the relational algebra and introduces the relational calculus—these are two formal languages associated with the relational model. -
IBM Power® Systems for SAS® Empowers Advanced Analytics Harry Seifert, Laurent Montaron, IBM Corporation
Paper 4695-2020 IBM Power® Systems for SAS® Empowers Advanced Analytics Harry Seifert, Laurent Montaron, IBM Corporation ABSTRACT For over 40+ years of partnership between IBM and SAS®, clients have been benefiting from the added value brought by IBM’s infrastructure platforms to deploy SAS analytics, and now SAS Viya’s evolution of modern analytics. IBM Power® Systems and IBM Storage empower SAS environments with infrastructure that does not make tradeoffs among performance, cost, and reliability. The unified solution stack, comprising server, storage, and services, reduces the compute time, controls costs, and maximizes resilience of SAS environment with ultra-high bandwidth and highest availability. INTRODUCTION We will explore how to deploy SAS on IBM Power Systems platforms and unleash the full potential of the infrastructure, to reduce deployment risk, maximize flexibility and accelerate insights. We will start by reviewing IBM and SAS’s technology relationship and the current state of SAS products on IBM Power Systems. Then we will look at some of the infrastructure options to deploy SAS 9.4 on IBM Power Systems and IBM Storage, while maximizing resiliency & throughput by leveraging best practices. Next, we will look at SAS Viya, which introduces changes to the underlying infrastructure requirements while remaining able to be deployed alongside a traditional SAS 9.4 operation. We’ll explore the various deployment modes available. Finally, we’ll look at tuning practices and reference materials available for a deeper dive in deploying SAS on IBM platforms. SAS: 40 YEARS OF PARTNERSHIP WITH IBM IBM and SAS have been partners since the founding of SAS. -
POWER® Processor-Based Systems
IBM® Power® Systems RAS Introduction to IBM® Power® Reliability, Availability, and Serviceability for POWER9® processor-based systems using IBM PowerVM™ With Updates covering the latest 4+ Socket Power10 processor-based systems IBM Systems Group Daniel Henderson, Irving Baysah Trademarks, Copyrights, Notices and Acknowledgements Trademarks IBM, the IBM logo, and ibm.com are trademarks or registered trademarks of International Business Machines Corporation in the United States, other countries, or both. These and other IBM trademarked terms are marked on their first occurrence in this information with the appropriate symbol (® or ™), indicating US registered or common law trademarks owned by IBM at the time this information was published. Such trademarks may also be registered or common law trademarks in other countries. A current list of IBM trademarks is available on the Web at http://www.ibm.com/legal/copytrade.shtml The following terms are trademarks of the International Business Machines Corporation in the United States, other countries, or both: Active AIX® POWER® POWER Power Power Systems Memory™ Hypervisor™ Systems™ Software™ Power® POWER POWER7 POWER8™ POWER® PowerLinux™ 7® +™ POWER® PowerHA® POWER6 ® PowerVM System System PowerVC™ POWER Power Architecture™ ® x® z® Hypervisor™ Additional Trademarks may be identified in the body of this document. Other company, product, or service names may be trademarks or service marks of others. Notices The last page of this document contains copyright information, important notices, and other information. Acknowledgements While this whitepaper has two principal authors/editors it is the culmination of the work of a number of different subject matter experts within IBM who contributed ideas, detailed technical information, and the occasional photograph and section of description. -
IBM Power Systems Solution for Mariadb
IBM Power Systems solution for MariaDB Performance overview of MariaDB Enterprise on Linux on Power featuring the new IBM POWER8 technology Axel Schwenke MariaDB Corporation Hari Reddy IBM Systems and Technology Group ISV Enablement Basu Vaidyanathan IBM Systems and Technology Group Performance Analysis October 2014 © Copyright IBM Corporation, 2014 Table of contents Abstract........................................................................................................................................1 Introduction .................................................................................................................................1 Advantages of MariaDB on Power Systems.............................................................................1 MariaDB architecture ..................................................................................................................2 Sysbench OLTP benchmark.................................................................................................................... 3 MariaDB performance.............................................................................................................................. 3 Relative performance of IBM Power S822L and IBM System x3650 M4 ................................................ 3 Power Systems built with the POWER8 technology................................................................6 Tested configuration details ......................................................................................................7 -
IBM Power System E850 the Most Agile 4-Socket System in the Marketplace, Optimized for Performance, Reliability and Expansion
IBM Systems Data Sheet IBM Power System E850 The most agile 4-socket system in the marketplace, optimized for performance, reliability and expansion Businesses today are demanding faster insights that analyze more data in Highlights new ways. They need to implement applications in days versus months, and they need to achieve all these goals while reducing IT costs. This is ●● ●●Designed for data and analytics, delivers creating new demands on IT infrastructures, requiring new levels of per- secure, reliable performance in a compact, 4-socket system formance and the flexibility to respond to new business opportunities, all at an affordable price. ●● ●●Can flexibly scale to rapidly respond to changing business needs The IBM® Power® System E850 server offers a unique blend of ●● ●●Can reduce IT costs through application enterprise-class capabilities in a space-efficient, 4-socket system with consolidation, higher availability and excellent price performance. With up to 48 IBM POWER8™ processor virtualization to yield over 70 percent utilization cores, advanced IBM PowerVM® virtualization that can yield over 70 percent system utilization and Capacity on Demand (CoD), no other 4-socket system in the industry delivers this combination of performance, efficiency and business agility. These capabilities make the Power E850 server an ideal platform for medium-size businesses and as a departmental server or data center building block for large enterprises. Designed for the demands of big data and analytics Businesses are amassing a wealth of data and IBM Power Systems™, built with innovation to support today’s data demands, can store it, secure it and, most important, extract actionable insight from it. -
Introduction to Query Processing and Optimization
Introduction to Query Processing and Optimization Michael L. Rupley, Jr. Indiana University at South Bend [email protected] owned_by 10 No ABSTRACT All database systems must be able to respond to The drivers relation: requests for information from the user—i.e. process Attribute Length Key? queries. Obtaining the desired information from a driver_id 10 Yes database system in a predictable and reliable fashion is first_name 20 No the scientific art of Query Processing. Getting these last_name 20 No results back in a timely manner deals with the age 2 No technique of Query Optimization. This paper will introduce the reader to the basic concepts of query processing and query optimization in the relational The car_driver relation: database domain. How a database processes a query as Attribute Length Key? well as some of the algorithms and rule-sets utilized to cd_car_name 15 Yes* produce more efficient queries will also be presented. cd_driver_id 10 Yes* In the last section, I will discuss the implementation plan to extend the capabilities of my Mini-Database Engine program to include some of the query 2. WHAT IS A QUERY? optimization techniques and algorithms covered in this A database query is the vehicle for instructing a DBMS paper. to update or retrieve specific data to/from the physically stored medium. The actual updating and 1. INTRODUCTION retrieval of data is performed through various “low-level” operations. Examples of such operations Query processing and optimization is a fundamental, if for a relational DBMS can be relational algebra not critical, part of any DBMS. To be utilized operations such as project, join, select, Cartesian effectively, the results of queries must be available in product, etc. -
SQL Vs Nosql: a Performance Comparison
SQL vs NoSQL: A Performance Comparison Ruihan Wang Zongyan Yang University of Rochester University of Rochester [email protected] [email protected] Abstract 2. ACID Properties and CAP Theorem We always hear some statements like ‘SQL is outdated’, 2.1. ACID Properties ‘This is the world of NoSQL’, ‘SQL is still used a lot by We need to refer the ACID properties[12]: most of companies.’ Which one is accurate? Has NoSQL completely replace SQL? Or is NoSQL just a hype? SQL Atomicity (Structured Query Language) is a standard query language A transaction is an atomic unit of processing; it should for relational database management system. The most popu- either be performed in its entirety or not performed at lar types of RDBMS(Relational Database Management Sys- all. tems) like Oracle, MySQL, SQL Server, uses SQL as their Consistency preservation standard database query language.[3] NoSQL means Not A transaction should be consistency preserving, meaning Only SQL, which is a collection of non-relational data stor- that if it is completely executed from beginning to end age systems. The important character of NoSQL is that it re- without interference from other transactions, it should laxes one or more of the ACID properties for a better perfor- take the database from one consistent state to another. mance in desired fields. Some of the NOSQL databases most Isolation companies using are Cassandra, CouchDB, Hadoop Hbase, A transaction should appear as though it is being exe- MongoDB. In this paper, we’ll outline the general differences cuted in iso- lation from other transactions, even though between the SQL and NoSQL, discuss if Relational Database many transactions are execut- ing concurrently.