DOCSLIB.ORG

How Does the Mysql Document Store Work? Architecture & Components

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
How Does the Mysql Document Store Work? Architecture & Components MySQL 8.0: Performance & Scalibility Bill Papp MySQL Solutions Architect 1 CopyrightCopyright © © 2016, 2017, Oracle Oracle and/or and/or its its affiliates. affiliates. All All rights rights reserved. reserved. | Safe Harbor Statement The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Improved UTF-8 Support Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Improved UTF-8 Support in MySQL 8.0 • Support for the latest Unicode 9.0 • utf8mb4 made default character set! –utf8mb4_0900_ai_ci default collation • Accent and case sensitive collations –Including 20+ language specific collations –Now also Japanese and Russian • Significantly improved performance Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 5 What Is in MySQL 5.7 and Earlier Versions? • Default charset is “latin1” and default collation is “latin1_swedish_ci” • utf8 = utf8mb3: support BMP Plane 0 only • utf8mb4 character set: –Only accent and case insensitive collations –Default collation is utf8mb4_general_ci, compares all characters beyond BMP, e.g. emojis, to be equal –20+ language specific collations –Recommend to use: utf8mb4_unicode_520_ci Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 6 New Default Character Set • No changes to existing tables • Only has effect on new tables/schemas where character set is not explicitly defined. • Separating character set/collation change from server upgrade – Upgrade first, change charset/collation afterwards • Recommend users to not mixing collations – Error “Illegal mix of collations” – Slower query because index can no longer be used Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 7 Transactional Data Dictionary Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Data Dictionary Definition • Metadata is information about data in the RDBMS – Column definitions, Index definitions, Foreign key definitions ... • Data Dictionary collects metadata for all things in RDBMS – User table structure, Stored program definitions ... Metadata ID NAME WEIGHT HEIGHT GENDER 3 Bob 80 185 M Data 5 Liz 55 165 F Copyright © 2018, Oracle and/or its affiliates. All rights reserved. MySQL Data Dictionary before MySQL 8.0 Data Dictionary Files File system FRM TRG OPT SQL System Tables (mysql.) MyISAM user events proc InnoDB System Tables InnoDB Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 10 MySQL Data Dictionary before MySQL 8.0 Problems • Performance of INFORMATION_SCHEMA • Inconsistencies between persistent storage in files and tables • Inconsistencies between InnoDB DD and Server DD • Showstopper for crash-safe / atomic DDL • Difficult for replication • Hard to extend Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 11 What do you get with the Transactional Data Dictionary? • All DD tables and system tables in a DD tablespace (mysql) • Atomic DDL (this is actually a big thing!!) – Especially important for replicated topologies – Crash situations will not end up in out-of-synch information sql-layer/SE-layer • Reliability and Redundancy – Serialized Dictionary Information • Better scaling INFORMATION_SCHEMA queries – Reimplemented with views over DD tables – Scaling both on database size and query load • Improved Upgrade Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 12 MySQL 8.0: Transactional Data Dictionary Atomic and crash-safe DDL Data Dictionary DD Table DDDD Table Table SQL InnoDB Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | 13 Transactional Data Dictionary in MySQL 8.0 Main features • All dictionary metadata stored in tables • Single repository of metadata for SEs and the MySQL server • Reliable, crash-safe InnoDB tables • INFORMATION_SCHEMA tables implemented as VIEWs over DD tables – Queries can be optimized by the optimizer – Improved performance – Simpler, uniform implementation, easier to maintain Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Transactional Data Dictionary in MySQL 8.0 Main features, cont’ed • Extensible –The data dictionary schema is based on the SQL standard definitions –The data dictionary is designed to be easily extended for new requirements –Designed to provide automated upgrade of dictionary data –Designed to allow plugins to add and extend system tables, I_S tables, Performance Schema tables Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Transactional Data Dictionary in MySQL 8.0 Overview INFORMATION SCHEMA Data Dictionary Optimizer InnoDB Views DD Table User Table Archive User Table CSV User Table Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 16 Transactional Data Dictionary API in MySQL 8.0 Design goals • The only way to deal with Data Dictionary – For the server core – For SEs – For other plugins • Less Error-prone • Internal API (non-stable) and external API (stable) • Provide a way to handle SE private data Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 17 Transactional Data Dictionary in MySQL 8.0 Architecture Query Executor Parser Optimizer Plugin Data Dictionary External API Data Dictionary Internal API Data Storage Dictionary Tablespace User Table Engine Tablespace InnoDB Internal SE Plugin Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 18 Reliability and Redundancy Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Transactional Data Dictionary in MySQL 8.0 Reliability and Redundancy SDI: Serialized Dictionary Information - Used for data migration and is a redundant write-only copy in normal operation The InnoDB Data Dictionary tablespace ”mysql” is the metadata storage InnoDB User Tablespaces InnoDB Data Dictionary tablespace mysql.tables User Table ID Name 1 User Table 1 SDI 2 User Table 2 Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 20 Example - DROP SCHEMA at high level MySQL 5.7 MySQL 8.0 • Delete tables • Delete tables – Metadata, TRN/TRG/FRM files – Metadata, rows in InnoDB – Data, InnoDB tables – Data, InnoDB tables • Delete stored programs Delete stored programs – Metadata, rows in MyISAM (non- • transactional) – Metadata, rows in InnoDB • Delete schema • Delete schema – Metadata, DB.OPT file – Metadata, rows in InnoDB Mix of filesystem, non- Updates to transactional storage, transactional/transactional one commit storage and multiple commits Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 21 Reliability – Disaster Recovery Use case – IMPORT using Serialized Dictionary Information • All data stored in InnoDB (transactional SE) – Metadata stored in an SDI embedded in .ibd – Data stored in .ibd • InnoDB logging DDL operations as «Dictionary Storage Engine» – After restart and recovery, the DDL operation will be complete or rolled back Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 22 Reliability – Automated Dictionary Upgrade Use case – Upgrade • The Data Dictionary definition will have a version attached • The MySQL Server executable will support upgrading dictionary tables Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 23 Reliability – Protecting Dictionary Tables • Data Dictionary tables are protected against user DML – This means there will be no possibility for corruption from user DML on these tables – All information in the dictionary tables will be available through INFORMATION_SCHEMA Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 24 Data Dictionary CREATE TABLE customers( CREATE PROCEDURE p1(v INT) id INT AUTO_INCREMENT SQL SECURITY INVOKER ... BEGIN PRIMARY KEY (id), ... INDEX ... END FOREIGN KEY ... ) Data Dictionary Table Definitions SP Definitions ACL View Definitions Plugins Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Hot Row Contention Improvements Copyright © 2018, Oracle and/or its affiliates. All rights reserved. SELECT ... FOR UPDATE SKIP LOCKED • Common problem: – Hot row contention, multiple worker threads accessing the same rows • Solution 1: – Only read rows that are not locked – InnoDB skips a locked row, and the next one goes to the result set • Example: – Booking system: Skip orders that are pending START TRANSACTION; SELECT * FROM seats WHERE seat_no BETWEEN 2 AND 3 AND booked = 'NO' FOR UPDATE SKIP LOCKED; Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 27 SELECT… FOR UPDATE NOWAIT • Common problem: – Hot row contention, multiple worker threads accessing the same rows • Solution 2: – If any of the rows are already locked, the statement should fail immediately – Without NOWAIT, have to wait for innodb_lock_wait_timeout (default: 50 sec) while trying to acquire lock • Usage: START TRANSACTION; SELECT * FROM seats WHERE seat_no BETWEEN 2 AND 3 AND booked = 'NO' FOR UPDATE NOWAIT; ERROR 3572 (HY000): Statement aborted because lock(s) could not be acquired … Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 28 Index Extensions Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Invisible Index • Index is maintained
Load more

Recommended publications
  • Mysql Workbench Mysql Workbench
    MySQL Workbench MySQL Workbench Abstract This manual documents the MySQL Workbench SE version 5.2 and the MySQL Workbench OSS version 5.2. If you have not yet installed MySQL Workbench OSS please download your free copy from the download site. MySQL Workbench OSS is available for Windows, Mac OS X, and Linux. Document generated on: 2012-05-01 (revision: 30311) For legal information, see the Legal Notice. Table of Contents Preface and Legal Notice ................................................................................................................. vii 1. MySQL Workbench Introduction ..................................................................................................... 1 2. MySQL Workbench Editions ........................................................................................................... 3 3. Installing and Launching MySQL Workbench ................................................................................... 5 Hardware Requirements ............................................................................................................. 5 Software Requirements .............................................................................................................. 5 Starting MySQL Workbench ....................................................................................................... 6 Installing MySQL Workbench on Windows .......................................................................... 7 Launching MySQL Workbench on Windows .......................................................................
    [Show full text]
  • Beyond Relational Databases
    EXPERT ANALYSIS BY MARCOS ALBE, SUPPORT ENGINEER, PERCONA Beyond Relational Databases: A Focus on Redis, MongoDB, and ClickHouse Many of us use and love relational databases… until we try and use them for purposes which aren’t their strong point. Queues, caches, catalogs, unstructured data, counters, and many other use cases, can be solved with relational databases, but are better served by alternative options. In this expert analysis, we examine the goals, pros and cons, and the good and bad use cases of the most popular alternatives on the market, and look into some modern open source implementations. Beyond Relational Databases Developers frequently choose the backend store for the applications they produce. Amidst dozens of options, buzzwords, industry preferences, and vendor offers, it’s not always easy to make the right choice… Even with a map! !# O# d# "# a# `# @R*7-# @94FA6)6 =F(*I-76#A4+)74/*2(:# ( JA$:+49>)# &-)6+16F-# (M#@E61>-#W6e6# &6EH#;)7-6<+# &6EH# J(7)(:X(78+# !"#$%&'( S-76I6)6#'4+)-:-7# A((E-N# ##@E61>-#;E678# ;)762(# .01.%2%+'.('.$%,3( @E61>-#;(F7# D((9F-#=F(*I## =(:c*-:)U@E61>-#W6e6# @F2+16F-# G*/(F-# @Q;# $%&## @R*7-## A6)6S(77-:)U@E61>-#@E-N# K4E-F4:-A%# A6)6E7(1# %49$:+49>)+# @E61>-#'*1-:-# @E61>-#;6<R6# L&H# A6)6#'68-# $%&#@:6F521+#M(7#@E61>-#;E678# .761F-#;)7-6<#LNEF(7-7# S-76I6)6#=F(*I# A6)6/7418+# @ !"#$%&'( ;H=JO# ;(\X67-#@D# M(7#J6I((E# .761F-#%49#A6)6#=F(*I# @ )*&+',"-.%/( S$%=.#;)7-6<%6+-# =F(*I-76# LF6+21+-671># ;G';)7-6<# LF6+21#[(*:I# @E61>-#;"# @E61>-#;)(7<# H618+E61-# *&'+,"#$%&'$#( .761F-#%49#A6)6#@EEF46:1-#
    [Show full text]
  • SQL Server Column Store Indexes Per-Åke Larson, Cipri Clinciu, Eric N
    SQL Server Column Store Indexes Per-Åke Larson, Cipri Clinciu, Eric N. Hanson, Artem Oks, Susan L. Price, Srikumar Rangarajan, Aleksandras Surna, Qingqing Zhou Microsoft {palarson, ciprianc, ehans, artemoks, susanpr, srikumar, asurna, qizhou}@microsoft.com ABSTRACT SQL Server column store indexes are “pure” column stores, not a The SQL Server 11 release (code named “Denali”) introduces a hybrid, because they store all data for different columns on new data warehouse query acceleration feature based on a new separate pages. This improves I/O scan performance and makes index type called a column store index. The new index type more efficient use of memory. SQL Server is the first major combined with new query operators processing batches of rows database product to support a pure column store index. Others greatly improves data warehouse query performance: in some have claimed that it is impossible to fully incorporate pure column cases by hundreds of times and routinely a tenfold speedup for a store technology into an established database product with a broad broad range of decision support queries. Column store indexes are market. We’re happy to prove them wrong! fully integrated with the rest of the system, including query To improve performance of typical data warehousing queries, all a processing and optimization. This paper gives an overview of the user needs to do is build a column store index on the fact tables in design and implementation of column store indexes including the data warehouse. It may also be beneficial to build column enhancements to query processing and query optimization to take store indexes on extremely large dimension tables (say more than full advantage of the new indexes.
    [Show full text]
  • When Relational-Based Applications Go to Nosql Databases: a Survey
    information Article When Relational-Based Applications Go to NoSQL Databases: A Survey Geomar A. Schreiner 1,* , Denio Duarte 2 and Ronaldo dos Santos Mello 1 1 Departamento de Informática e Estatística, Federal University of Santa Catarina, 88040-900 Florianópolis - SC, Brazil 2 Campus Chapecó, Federal University of Fronteira Sul, 89815-899 Chapecó - SC, Brazil * Correspondence: [email protected] Received: 22 May 2019; Accepted: 12 July 2019; Published: 16 July 2019 Abstract: Several data-centric applications today produce and manipulate a large volume of data, the so-called Big Data. Traditional databases, in particular, relational databases, are not suitable for Big Data management. As a consequence, some approaches that allow the definition and manipulation of large relational data sets stored in NoSQL databases through an SQL interface have been proposed, focusing on scalability and availability. This paper presents a comparative analysis of these approaches based on an architectural classification that organizes them according to their system architectures. Our motivation is that wrapping is a relevant strategy for relational-based applications that intend to move relational data to NoSQL databases (usually maintained in the cloud). We also claim that this research area has some open issues, given that most approaches deal with only a subset of SQL operations or give support to specific target NoSQL databases. Our intention with this survey is, therefore, to contribute to the state-of-art in this research area and also provide a basis for choosing or even designing a relational-to-NoSQL data wrapping solution. Keywords: big data; data interoperability; NoSQL databases; relational-to-NoSQL mapping 1.
    [Show full text]
  • Data Dictionary a Data Dictionary Is a File That Helps to Define The
    Cleveland | v. 216.369.2220 • Columbus | v. 614.291.8456 Data Dictionary A data dictionary is a file that helps to define the organization of a particular database. The data dictionary acts as a description of the data objects or items in a model and is used for the benefit of the programmer or other people who may need to access it. A data dictionary does not contain the actual data from the database; it contains only information for how to describe/manage the data; this is called metadata*. Building a data dictionary provides the ability to know the kind of field, where it is located in a database, what it means, etc. It typically consists of a table with multiple columns that describe relationships as well as labels for data. A data dictionary often contains the following information about fields: • Default values • Constraint information • Definitions (example: functions, sequence, etc.) • The amount of space allocated for the object/field • Auditing information What is the data dictionary used for? 1. It can also be used as a read-only reference in order to obtain information about the database 2. A data dictionary can be of use when developing programs that use a data model 3. The data dictionary acts as a way to describe data in “real-world” terms Why is a data dictionary needed? One of the main reasons a data dictionary is necessary is to provide better accuracy, organization, and reliability in regards to data management and user/administrator understanding and training. Benefits of using a data dictionary: 1.
    [Show full text]
  • XAMPP Web Development Stack
    XAMPP Web Development Stack Overview @author R.L. Martinez, Ph.D. The steps below outline the processes for installing the XAMPP stack on a local machine. The XAMPP (pronounced Zamp) stack includes the following: Apache HTTP Server, MariaDB (essentially MySQL), Database Server, Perl, and the PHP Interpreter. The “X” in XAMPP is used to signify the cross-platform compatibility of the stack. The Apache HTTP Server and PHP are required to run phpMyAdmin which is a PHP application that is used for database administration tasks such as creating databases and tables, adding users, etc. Alternative to XAMPP If you have experience with MySQL Workbench, you may prefer to install MySQL Server and MySQL Workbench via the MySQL Installer. MySQL Workbench performs the same functions as phpMyAdmin. However, unlike phpMyAdmin which is a web-based application, MySQL Workbench is a locally installed application and therefore does not require an HTTP Server (e.g. Apache) to run. Installing XAMPP Many of the steps listed have several alternatives (such as changing MySQL passwords via a command line) and students are welcomed and encouraged to explore alternatives. 1. Download XAMPP from the URL below and place the installer (.exe) in the location where you want to install XAMPP. Placing the installer (.exe) in the same location as the intended installation is not required but preferred. http://www.apachefriends.org/download.html Page 1 of 17 XAMPP Web Development Stack 2. See the warning which recommends not installing to C:\Program Files (x86) which can be restricted by UAC (User Account Control). In the steps below XAMPP is installed to a USB flash drive for portability.
    [Show full text]
  • Mariadb Presentation
    THE VALUE OF OPEN SOURCE MICHAEL ”MONTY” WIDENIUS Entrepreneur, MariaDB Hacker, MariaDB CTO MariaDB Corporation AB 2019-09-25 Seoul 11 Reasons Open Source is Better than Closed Source ● Using open standards (no lock in into proprietary standards) ● Resource friendly; OSS software tend to work on old hardware ● Lower cost; Usually 1/10 of closed source software ● No cost for testing the full software ● Better documentation and more troubleshooting resources ● Better support, in many cases directly from the developers ● Better security, auditability (no trap doors and more eye balls) ● Better quality; Developed together with users ● Better customizability; You can also participate in development ● No vendor lock in; More than one vendor can give support ● When using open source, you take charge of your own future Note that using open source does not mean that you have to become a software producer! OPEN SOURCE, THE GOOD AND THE BAD ● Open source is a better way to develop software ● More developers ● More spread ● Better code (in many cases) ● Works good for projects that can freely used by a lot of companies in their production or products. ● It's very hard to create a profitable company developing an open source project. ● Not enough money to pay developers. ● Hard to get money and investors for most projects (except for infrastructure projects like libraries or daemon services). OPEN SOURCE IS NATURAL OR WHY OPEN SOURCE WORKS ● You use open source because it's less expensive (and re-usable) ● You solve your own problems and get free help and development efforts from others while doing it.
    [Show full text]
  • High Performance Mysql Other Microsoft .NET Resources from O’Reilly
    High Performance MySQL Other Microsoft .NET resources from O’Reilly Related titles Managing and Using MySQL PHP Cookbook™ MySQL Cookbook™ Practical PostgreSQL MySQL Pocket Reference Programming PHP MySQL Reference Manual SQL Tuning Learning PHP Web Database Applications PHP 5 Essentials with PHP and MySQL .NET Books dotnet.oreilly.com is a complete catalog of O’Reilly’s books on Resource Center .NET and related technologies, including sample chapters and code examples. ONDotnet.com provides independent coverage of fundamental, interoperable, and emerging Microsoft .NET programming and web services technologies. Conferences O’Reilly Media bring diverse innovators together to nurture the ideas that spark revolutionary industries. We specialize in docu- menting the latest tools and systems, translating the innovator’s knowledge into useful skills for those in the trenches. Visit con- ferences.oreilly.com for our upcoming events. Safari Bookshelf (safari.oreilly.com) is the premier online refer- ence library for programmers and IT professionals. Conduct searches across more than 1,000 books. Subscribers can zero in on answers to time-critical questions in a matter of seconds. Read the books on your Bookshelf from cover to cover or sim- ply flip to the page you need. Try it today for free. SECOND EDITION High Performance MySQL Baron Schwartz, Peter Zaitsev, Vadim Tkachenko, Jeremy D. Zawodny, Arjen Lentz, and Derek J. Balling Beijing • Cambridge • Farnham • Köln • Sebastopol • Taipei • Tokyo High Performance MySQL, Second Edition by Baron Schwartz, Peter Zaitsev, Vadim Tkachenko, Jeremy D. Zawodny, Arjen Lentz, and Derek J. Balling Copyright © 2008 O’Reilly Media, Inc. All rights reserved. Printed in the United States of America.
    [Show full text]
  • USER GUIDE Optum Clinformatics™ Data Mart Database
    USER GUIDE Optum Clinformatics Data Mart Database 1 | P a g e TABLE OF CONTENTS TOPIC PAGE # 1. REQUESTING DATA 3 Eligibility 3 Forms 3 Contact Us 4 2. WHAT YOU WILL NEED 4 SAS Software 4 VPN 5 3. ABSTRACTS, MANUSCRIPTS, THESES, AND DISSERTATIONS 5 Referencing Optum Data 5 Optum Review 5 4. DATA USER SET-UP AND ACCESS INFORMATION 6 Server Log-In After Initial Set-Up 6 Server Access 6 Establishing a Connection to Enterprise Guide 7 Instructions to Add SAS EG to the Cleared Firewall List 8 How to Proceed After Connection 8 5. BEST PRACTICES FOR DATA USE 9 Saving Programs and Back-Up Procedures 9 Recommended Coding Practices 9 6. APPENDIX 11 Version Date: 27-Feb-17 2 | P a g e Optum® ClinformaticsTM Data Mart Database The Optum® ClinformaticsTM Data Mart is an administrative health claims database from a large national insurer made available by the University of Rhode Island College of Pharmacy. The statistically de-identified data includes medical and pharmacy claims, as well as laboratory results, from 2010 through 2013 with over 22 million commercial enrollees. 1. REQUESTING DATA The following is a brief outline of the process for gaining access to the data. Eligibility Must be an employee or student at the University of Rhode Island conducting unfunded or URI internally funded projects. Data will be made available to the following users: 1. Faculty and their research team for projects with IRB approval. 2. Students a. With a thesis/dissertation proposal approved by IRB and the Graduate School (access request form, see link below, must be signed by Major Professor).
    [Show full text]
  • Mysql Database Administrator
    MySQL Database Administrator Author: Kacper Wysocki Contact: [email protected] Date: December 2010 License: Creative Commons: CC BY-SA Oslo, December 2010, CC BY-SA Contents Introduction 5 Introductions everybody 5 About this course 5 Course outline 6 Course schedule 6 How to do excersies 6 MySQL: history and future 6 MySQL: the present 7 MySQL: the future 7 MySQL compared to other DBs 7 MySQL language support 8 Embedding MySQL 8 Getting help with MySQL 8 MySQL architecture 9 Modular architecture 9 The MySQL modules 9 Client/server architecture 10 Installing MySQL 10 Installation process 10 Distribution packages 11 MySQL official binaries 11 Deploying sandboxes 12 Installing from source 13 Server Startup and Shutdown 14 MySQL relevant files 15 Excersises: Installation 15 Upgrading MySQL 16 Clients: the mysql* suite 16 Client: mysql 16 Excersise: Client mysql 16 Excersise: mysql CLI 17 Further CLI fun 17 Digression: some SQL 18 Client: mysqladmin 18 Excersises: Client: mysql 18 Clients: applications and libraries 18 Oslo, December 2010, CC BY-SA migration 19 Importing data: timezones 19 Importing data 19 Excersises: importing data 20 Excersises: time zones 20 Exporting data 20 Excersises: Exporting data 21 Configuration 21 More configuration 21 Run-time Variables 22 MySQL Architecture 23 Storage Engines 23 Storage Engines 23 Storage Engines types 23 MyISAM 24 MYISAM_MRG 24 InnoDB 24 Excersises: InnoDB 24 FEDERATED 25 CSV 25 ARCHIVE 25 MEMORY 25 BLACKHOLE 25 So... which engine? 26 Engine Excersises 26 Implementing Security 26
    [Show full text]
  • Activant Prophet 21
    Activant Prophet 21 Understanding Prophet 21 Databases This class is designed for… Prophet 21 users that are responsible for report writing System Administrators Operations Managers Helpful to be familiar with SQL Query Analyzer and how to write basic SQL statements Objectives Explain the difference between databases, tables and columns Extract data from different areas of the system Discuss basic SQL statements using Query Analyzer Use Prophet 21 to gather SQL Information Utilize Data Dictionary This course will NOT cover… Basic Prophet 21 functionality Seagate’s Crystal Reports Definitions Columns Contains a single piece of information (fields) Record (rows) One complete set of columns Table A collection of rows View Virtual table created for easier data extraction Database Collection of information organized for easy selection of data SQL Query A graphical user interface used to extract Analyzer data SQL Query Analyzer Accessed through Microsoft SQL Server SQL Server Tools Enterprise Manager Perform administrative functions such as backing up and restoring databases and maintaining SQL Logins Profiler Run traces of activity in your system Basic SQL Commands sp_help sp_help <table_name> select * from <table_name> Select <field_name> from <table_name> Most Common Reporting Areas Address and Contact tables Order Processing Inventory Purchasing Accounts Receivable Accounts Payable Production Orders Address and Contact tables Used in conjunction with other tables These tables hold every address/contact in the
    [Show full text]
  • Navicat Premium Romania V12
    Table of Contents Chapter 1 - Introduction 8 About Navicat 8 Installation 10 End-User License Agreement 12 Chapter 2 - User Interface 18 Main Window 18 Navigation Pane 19 Object Pane 20 Information Pane 21 Chapter 3 - Navicat Cloud 23 About Navicat Cloud 23 Manage Navicat Cloud 24 Chapter 4 - Connection 27 About Connection 27 General Settings 28 RDBMS 28 MongoDB 30 SSL Settings 31 SSH Settings 33 HTTP Settings 34 Advanced Settings 34 Databases / Attached Databases Settings 37 Chapter 5 - Server Objects 38 About Server Objects 38 MySQL / MariaDB 38 Databases 38 Tables 38 Views 39 Procedures / Functions 40 Events 41 Maintain Objects 41 Oracle 41 Schemas 41 Tables 42 Views 42 Materialized Views 43 Procedures / Functions 44 Packages 45 Recycle Bin 46 Other Objects 47 1 Maintain Objects 47 PostgreSQL 49 Databases & Schemas 49 Tables 50 Views 51 Materialized Views 51 Functions 52 Types 53 Foreign Servers 53 Other Objects 54 Maintain Objects 54 SQL Server 54 Databases & Schemas 54 Tables 55 Views 56 Procedures / Functions 56 Other Objects 57 Maintain Objects 58 SQLite 59 Databases 59 Tables 59 Views 60 Other Objects 60 Maintain Objects 61 MongoDB 61 Databases 61 Collections 61 Views 62 Functions 62 Indexes 63 MapReduce 63 GridFS 63 Maintain Objects 64 Chapter 6 - Data Viewer 66 About Data Viewer 66 RDBMS 66 RDBMS Data Viewer 66 Use Navigation Bar 66 Edit Records 67 Sort / Find / Replace Records 73 Filter Records 75 Manipulate Raw Data 75 2 Format Data View 76 MongoDB 77 MongoDB Data Viewer 77 Use Navigation Bar 78 Grid View 79 Tree View 85 JSON
    [Show full text]