The document provides an overview of key concepts related to optimizing performance in MySQL databases, including storage engines, data types, normalization, indexing, and character sets and collations. It emphasizes choosing appropriate storage engines and data types based on application requirements, normalizing data to reduce redundancy while improving performance, and using indexes and EXPLAIN queries to optimize queries. Overall, understanding these foundational concepts can help developers design higher performing MySQL databases and applications.
MySQL: Know more about open Source DatabaseMahesh Salaria
- As a developer, it is important to understand MySQL's storage engines, data types, indexing, and normalization to build high-performing applications.
- MySQL has several storage engines that handle different table types differently in terms of transactions, locking, storage, and memory usage. Choosing the right engine depends on data usage.
- Properly normalizing data, using optimal data types, and adding indexes improves performance by reducing storage needs, memory usage, and speeding up queries.
Business Insight 2014 - Microsofts nye BI og database platform - Erling Skaal...Microsoft
This document discusses in-memory technologies in Microsoft SQL Server including:
1) In-memory columnstore indexes that can provide over 100x faster query speeds and significant data compression.
2) In-memory OLTP that provides up to 30x faster transaction processing.
3) Using memory technologies to provide faster insights, queries, and transactions for analytics and operational workloads.
IN-MEMORY DATABASE SYSTEMS FOR BIG DATA MANAGEMENT.SAP HANA DATABASE.George Joseph
SAP HANA is an in-memory database system that stores data in main memory rather than on disk for faster access. It uses a column-oriented approach to optimize analytical queries. SAP HANA can scale from small single-server installations to very large clusters and cloud deployments. Its massively parallel processing architecture and in-memory analytics capabilities enable real-time processing of large datasets.
This document provides a summary of Antonios Chatzipavlis's background and experience working with SQL Server. It details his career starting with SQL Server 6.0 in 1996 and earning his first Microsoft certification. It lists the various Microsoft certifications and roles he has held, including becoming an MVP for SQL Server. It also introduces his creation of SQL School Greece in 2012 to share his knowledge.
Mehdi Varse presented on high performance databases. The presentation outlined performance metrics to monitor in enterprise applications including business transactions, query performance, user and query conflicts, capacity, configuration, and NoSQL databases. It also discussed database tuning, in-memory databases, parallel and distributed database systems, and high-performance database requirements. Examples of databases used at Facebook like MySQL, Memcached, Haystack, and Cassandra were reviewed.
The document provides details about an SQL expert's background and certifications. It summarizes the expert's career starting in 1982 working with computers and 1988 starting in the computer industry. In 1996, they started working with SQL Server 6.0 and have since earned multiple Microsoft certifications. The expert now provides training and consultation services, and created an online school called SQL School Greece to teach SQL Server.
SQL Server 2017 Enhancements You Need To KnowQuest
In this session, database experts Pini Dibask and Jason Hall reveal the lesser-known features that’ll help you improve database performance in record time.
MySQL: Know more about open Source DatabaseMahesh Salaria
- As a developer, it is important to understand MySQL's storage engines, data types, indexing, and normalization to build high-performing applications.
- MySQL has several storage engines that handle different table types differently in terms of transactions, locking, storage, and memory usage. Choosing the right engine depends on data usage.
- Properly normalizing data, using optimal data types, and adding indexes improves performance by reducing storage needs, memory usage, and speeding up queries.
Business Insight 2014 - Microsofts nye BI og database platform - Erling Skaal...Microsoft
This document discusses in-memory technologies in Microsoft SQL Server including:
1) In-memory columnstore indexes that can provide over 100x faster query speeds and significant data compression.
2) In-memory OLTP that provides up to 30x faster transaction processing.
3) Using memory technologies to provide faster insights, queries, and transactions for analytics and operational workloads.
IN-MEMORY DATABASE SYSTEMS FOR BIG DATA MANAGEMENT.SAP HANA DATABASE.George Joseph
SAP HANA is an in-memory database system that stores data in main memory rather than on disk for faster access. It uses a column-oriented approach to optimize analytical queries. SAP HANA can scale from small single-server installations to very large clusters and cloud deployments. Its massively parallel processing architecture and in-memory analytics capabilities enable real-time processing of large datasets.
This document provides a summary of Antonios Chatzipavlis's background and experience working with SQL Server. It details his career starting with SQL Server 6.0 in 1996 and earning his first Microsoft certification. It lists the various Microsoft certifications and roles he has held, including becoming an MVP for SQL Server. It also introduces his creation of SQL School Greece in 2012 to share his knowledge.
Mehdi Varse presented on high performance databases. The presentation outlined performance metrics to monitor in enterprise applications including business transactions, query performance, user and query conflicts, capacity, configuration, and NoSQL databases. It also discussed database tuning, in-memory databases, parallel and distributed database systems, and high-performance database requirements. Examples of databases used at Facebook like MySQL, Memcached, Haystack, and Cassandra were reviewed.
The document provides details about an SQL expert's background and certifications. It summarizes the expert's career starting in 1982 working with computers and 1988 starting in the computer industry. In 1996, they started working with SQL Server 6.0 and have since earned multiple Microsoft certifications. The expert now provides training and consultation services, and created an online school called SQL School Greece to teach SQL Server.
SQL Server 2017 Enhancements You Need To KnowQuest
In this session, database experts Pini Dibask and Jason Hall reveal the lesser-known features that’ll help you improve database performance in record time.
SQL Server 2016 introduces new editions that provide varying levels of capabilities for different workloads. The key editions are Express, Standard, and Enterprise. Express is free and ideal for small applications. Standard provides core data management and business intelligence. Enterprise delivers comprehensive datacenter capabilities for mission critical workloads and advanced analytics. All editions now support new security features and hybrid cloud capabilities like stretch database.
Optimization SQL Server for Dynamics AX 2012 R3Juan Fabian
This document provides guidance on sizing and configuring SQL Server, the Application Object Server (AOS), Enterprise Portal, and other components for a Microsoft Dynamics AX implementation. It includes recommendations for hardware sizing based on transaction volumes and user counts. It also describes best practices for SQL Server configuration settings, indexing, statistics maintenance, and other tasks to ensure optimal performance of the Dynamics AX database and system.
SQL Server 2016 introduces new capabilities to help improve performance, security, and analytics:
- Operational analytics allows running analytics queries concurrently with OLTP workloads using the same schema. This provides minimal impact on OLTP and best performance.
- In-Memory OLTP enhancements include greater Transact-SQL coverage, improved scaling, and tooling improvements.
- The new Query Store feature acts as a "flight data recorder" for databases, enabling quick performance issue identification and resolution.
This document summarizes new features in SQL Server 2016 for SQL Server Integration Services (SSIS), Master Data Services (MDS), Data Quality Services (DQS), Analysis Services (SSAS), and Reporting Services (SSRS). For SSIS, new features include auto-adjusting buffer size, an Azure feature pack, and incremental package deployment. For MDS, improvements include longer attribute names, composite indexes, and entity synchronization. For SSAS, enhancements focus on performance, consistency, and new DAX functions. For SSRS, additions center around treemap/sunburst charts, custom parameters, and HTML5 rendering.
SQL Server 2016 New Features and EnhancementsJohn Martin
SQL Server 2016 new features session that I delivered at SQL Relay 2015 at; Reading, London, Cardiff and Birmingham.
Looking at some of the new features currently slated for inclusion in the next version of Microsoft SQL Server 2016.
Demo Code can be found at: http://1drv.ms/1PC5smY
This document discusses optimizing data warehouse star schemas with MySQL. It provides tips for database design including using a star schema approach with dimension and fact tables. It recommends MySQL 5.x, optimizing the MySQL configuration file, designing tables and indexes effectively, using the correct data loading architecture, analyzing tables, writing efficient query styles, and examining explain plans. Optimizing these areas can help ensure fast query performance from large data warehouses built with MySQL.
This document summarizes new features in SQL Server 2016. It discusses improvements to columnstore indexes, in-memory OLTP, the query store, temporal tables, always encrypted, stretch database, live query statistics, row level security, and dynamic data masking. It provides links to documentation and demos for these features. It also suggests what may be included in future CTP releases and lists resources for learning more about SQL Server 2016.
SQL Server 2016 is now in review! The newest version promises to deliver new real-time, built-in advanced analytics, advanced security technology, hybrid cloud scenarios as well as amazing rich visualizations on mobile devices.
There are many great reasons to move to SQL 2016, however if you are still working on SQL Server 2005 you may have another good motivator - the end-of-life clock of SQL 2005 is ticking down and support is about to end April 12, 2016.
In this deck we review the significant licensing changes introduced with SQL 2012. If our experience as Microsoft's Gold Certified Member has taught us anything - it is one thing. During migrations many of our clients get outright lost when trying to figure out the number of licenses they have or need. This often leads to under-deployment, and subsequently serious compliance issues with Microsoft. And yes, in some cases over-deployment means big savings back to your department.
The document provides an overview and summary of new features in Microsoft SQL Server 2016. It discusses enhancements to the database engine, in-memory OLTP, columnstore indexes, R services, high availability, security, and Reporting Services. Key highlights include support for up to 2TB of durable memory-optimized tables, increased index key size limits, temporal data support, row-level security, and improved integration with Azure and Power BI capabilities. The presentation aims to help users understand and leverage the new and improved features in SQL Server 2016.
CSQL is open source main memory database management system and cache. It encourages student contribution and provides help to students by providing guidance through forums and chat.
SQL Server 2016 introduces several new features for In-Memory OLTP including support for up to 2 TB of user data in memory, system-versioned tables, row-level security, and Transparent Data Encryption. The in-memory processing has also been updated to support more T-SQL functionality such as foreign keys, LOB data types, outer joins, and subqueries. The garbage collection process for removing unused memory has also been improved.
Nesta segunda parte do tema Redshift, mostramos o case da Movile, líder em mobile commerce com 50 milhões de usuários, e analisamos tópicos avançados como compressão, macros SQL embutidas e índices multidimensionais para grandes bases de dados.
This document provides an introduction and overview of Azure Data Lake. It describes Azure Data Lake as a single store of all data ranging from raw to processed that can be used for reporting, analytics and machine learning. It discusses key Azure Data Lake components like Data Lake Store, Data Lake Analytics, HDInsight and the U-SQL language. It compares Data Lakes to data warehouses and explains how Azure Data Lake Store, Analytics and U-SQL process and transform data at scale.
- Distributed Replay allows replaying a captured workload from multiple client computers to better simulate production loads.
- A controller coordinates the replay across clients to reproduce the original query rates or run in stress test mode faster than original rates.
- It improves on SQL Server Profiler for application compatibility testing, performance debugging, capacity planning, and benchmarking.
- Events are replayed in synchronization mode to match original order, or unsynchronized to stress test without timing constraints.
SQL Server 2016 includes several new features such as columnstore indexes, in-memory OLTP, live query statistics, temporal tables, and row-level security. It also features improved manage backup functionality, support for multiple tempdb files, and new ways to format and encrypt query results. Advanced capabilities like PolyBase and Stretch Database further enhance analytics and management of historical data.
This document summarizes common T-SQL anti-patterns that can negatively impact query performance, including using SELECT *, functions in predicates, OR operators, implicit conversions, unnecessary sorts, correlated subqueries, and dynamic SQL execution. The presentation provides explanations of why each anti-pattern hurts performance and recommendations for more optimized alternatives such as using indexes, temporary tables, parameterization, and execution plan analysis.
This document discusses test driven development (TDD) and automation for PHP projects. It covers what TDD is, why it should be done, where tests should run, who should adopt TDD, and why unit testing, code coverage, code sniffing and Selenium are important. It also discusses tools for PHP TDD like Xdebug, PHPUnit, PHP_CodeSniffer and IDEs. The document provides examples of writing test cases with the red-green-refactor process and integrating TDD into a build system with automated testing on every code change.
The document summarizes Drupal 8's render pipeline. It begins with the kernel.request event which determines the route and controller. The controller returns either a response object or render array. If a render array, the main content renderer handles rendering the format like HTML, AJAX, etc. It also describes placeholder strategies like BigPipe which can improve front-end performance. BigPipe first sends initial chunks and then streams content to replace placeholders.
SQL Server 2016 introduces new editions that provide varying levels of capabilities for different workloads. The key editions are Express, Standard, and Enterprise. Express is free and ideal for small applications. Standard provides core data management and business intelligence. Enterprise delivers comprehensive datacenter capabilities for mission critical workloads and advanced analytics. All editions now support new security features and hybrid cloud capabilities like stretch database.
Optimization SQL Server for Dynamics AX 2012 R3Juan Fabian
This document provides guidance on sizing and configuring SQL Server, the Application Object Server (AOS), Enterprise Portal, and other components for a Microsoft Dynamics AX implementation. It includes recommendations for hardware sizing based on transaction volumes and user counts. It also describes best practices for SQL Server configuration settings, indexing, statistics maintenance, and other tasks to ensure optimal performance of the Dynamics AX database and system.
SQL Server 2016 introduces new capabilities to help improve performance, security, and analytics:
- Operational analytics allows running analytics queries concurrently with OLTP workloads using the same schema. This provides minimal impact on OLTP and best performance.
- In-Memory OLTP enhancements include greater Transact-SQL coverage, improved scaling, and tooling improvements.
- The new Query Store feature acts as a "flight data recorder" for databases, enabling quick performance issue identification and resolution.
This document summarizes new features in SQL Server 2016 for SQL Server Integration Services (SSIS), Master Data Services (MDS), Data Quality Services (DQS), Analysis Services (SSAS), and Reporting Services (SSRS). For SSIS, new features include auto-adjusting buffer size, an Azure feature pack, and incremental package deployment. For MDS, improvements include longer attribute names, composite indexes, and entity synchronization. For SSAS, enhancements focus on performance, consistency, and new DAX functions. For SSRS, additions center around treemap/sunburst charts, custom parameters, and HTML5 rendering.
SQL Server 2016 New Features and EnhancementsJohn Martin
SQL Server 2016 new features session that I delivered at SQL Relay 2015 at; Reading, London, Cardiff and Birmingham.
Looking at some of the new features currently slated for inclusion in the next version of Microsoft SQL Server 2016.
Demo Code can be found at: http://1drv.ms/1PC5smY
This document discusses optimizing data warehouse star schemas with MySQL. It provides tips for database design including using a star schema approach with dimension and fact tables. It recommends MySQL 5.x, optimizing the MySQL configuration file, designing tables and indexes effectively, using the correct data loading architecture, analyzing tables, writing efficient query styles, and examining explain plans. Optimizing these areas can help ensure fast query performance from large data warehouses built with MySQL.
This document summarizes new features in SQL Server 2016. It discusses improvements to columnstore indexes, in-memory OLTP, the query store, temporal tables, always encrypted, stretch database, live query statistics, row level security, and dynamic data masking. It provides links to documentation and demos for these features. It also suggests what may be included in future CTP releases and lists resources for learning more about SQL Server 2016.
SQL Server 2016 is now in review! The newest version promises to deliver new real-time, built-in advanced analytics, advanced security technology, hybrid cloud scenarios as well as amazing rich visualizations on mobile devices.
There are many great reasons to move to SQL 2016, however if you are still working on SQL Server 2005 you may have another good motivator - the end-of-life clock of SQL 2005 is ticking down and support is about to end April 12, 2016.
In this deck we review the significant licensing changes introduced with SQL 2012. If our experience as Microsoft's Gold Certified Member has taught us anything - it is one thing. During migrations many of our clients get outright lost when trying to figure out the number of licenses they have or need. This often leads to under-deployment, and subsequently serious compliance issues with Microsoft. And yes, in some cases over-deployment means big savings back to your department.
The document provides an overview and summary of new features in Microsoft SQL Server 2016. It discusses enhancements to the database engine, in-memory OLTP, columnstore indexes, R services, high availability, security, and Reporting Services. Key highlights include support for up to 2TB of durable memory-optimized tables, increased index key size limits, temporal data support, row-level security, and improved integration with Azure and Power BI capabilities. The presentation aims to help users understand and leverage the new and improved features in SQL Server 2016.
CSQL is open source main memory database management system and cache. It encourages student contribution and provides help to students by providing guidance through forums and chat.
SQL Server 2016 introduces several new features for In-Memory OLTP including support for up to 2 TB of user data in memory, system-versioned tables, row-level security, and Transparent Data Encryption. The in-memory processing has also been updated to support more T-SQL functionality such as foreign keys, LOB data types, outer joins, and subqueries. The garbage collection process for removing unused memory has also been improved.
Nesta segunda parte do tema Redshift, mostramos o case da Movile, líder em mobile commerce com 50 milhões de usuários, e analisamos tópicos avançados como compressão, macros SQL embutidas e índices multidimensionais para grandes bases de dados.
This document provides an introduction and overview of Azure Data Lake. It describes Azure Data Lake as a single store of all data ranging from raw to processed that can be used for reporting, analytics and machine learning. It discusses key Azure Data Lake components like Data Lake Store, Data Lake Analytics, HDInsight and the U-SQL language. It compares Data Lakes to data warehouses and explains how Azure Data Lake Store, Analytics and U-SQL process and transform data at scale.
- Distributed Replay allows replaying a captured workload from multiple client computers to better simulate production loads.
- A controller coordinates the replay across clients to reproduce the original query rates or run in stress test mode faster than original rates.
- It improves on SQL Server Profiler for application compatibility testing, performance debugging, capacity planning, and benchmarking.
- Events are replayed in synchronization mode to match original order, or unsynchronized to stress test without timing constraints.
SQL Server 2016 includes several new features such as columnstore indexes, in-memory OLTP, live query statistics, temporal tables, and row-level security. It also features improved manage backup functionality, support for multiple tempdb files, and new ways to format and encrypt query results. Advanced capabilities like PolyBase and Stretch Database further enhance analytics and management of historical data.
This document summarizes common T-SQL anti-patterns that can negatively impact query performance, including using SELECT *, functions in predicates, OR operators, implicit conversions, unnecessary sorts, correlated subqueries, and dynamic SQL execution. The presentation provides explanations of why each anti-pattern hurts performance and recommendations for more optimized alternatives such as using indexes, temporary tables, parameterization, and execution plan analysis.
This document discusses test driven development (TDD) and automation for PHP projects. It covers what TDD is, why it should be done, where tests should run, who should adopt TDD, and why unit testing, code coverage, code sniffing and Selenium are important. It also discusses tools for PHP TDD like Xdebug, PHPUnit, PHP_CodeSniffer and IDEs. The document provides examples of writing test cases with the red-green-refactor process and integrating TDD into a build system with automated testing on every code change.
The document summarizes Drupal 8's render pipeline. It begins with the kernel.request event which determines the route and controller. The controller returns either a response object or render array. If a render array, the main content renderer handles rendering the format like HTML, AJAX, etc. It also describes placeholder strategies like BigPipe which can improve front-end performance. BigPipe first sends initial chunks and then streams content to replace placeholders.
This document discusses test-driven development (TDD) and unit testing. It begins with an introduction to TDD and examples using PHPUnit. It then explores the TDD cycle, common excuses for not using TDD, and pros and cons of TDD. Next, it distinguishes unit testing from TDD and discusses unit testing frameworks like PHPUnit and SimpleTest. Finally, it provides examples of code for a simple game that could be used to learn TDD and unit testing techniques.
The document is a presentation about test-driven development (TDD) in PHP. It introduces TDD and the speaker, defines the TDD process, lists benefits and drawbacks, and demonstrates a live coding example of using TDD to build a calculator and tutor class. The example shows writing tests first, then code to pass the tests, and refactoring with confidence due to the tests. The goals are to provide a practical TDD example and demonstrate how TDD impacts design decisions.
The document provides information about hackathons hosted by Kayako including details about what a hackathon is, why Kayako hosts them, tips for participating, and resources available for developing apps for Kayako's platform. The key points are that a hackathon is a timed coding event where participants work in teams to build prototypes using Kayako's APIs and resources in areas like live chat and mobile app development.
The document discusses clean coding standards and best practices. It recommends following the Boy Scout Rule of leaving the code cleaner than you found it. It discusses using meaningful names for classes, methods, and variables without encodings. Functions should do one thing, use descriptive names, and avoid repeating code. Comments should explain intent, not make up for bad code. Error handling prefers exceptions over return codes. Formatting and style rules should be consistent within a team. Coding standards exist for many languages like Java, PHP, C#, Android and others.
Artificial intelligence (AI) is everywhere, promising self-driving cars, medical breakthroughs, and new ways of working. But how do you separate hype from reality? How can your company apply AI to solve real business problems?
Here’s what AI learnings your business should keep in mind for 2017.
As a developer, it is important to understand MySQL storage engines and how they can impact performance. The key factors to consider include the type of data being stored, concurrency needs, and requirements for transactions. The storage engine chosen affects aspects like locking granularity, indexing support, and performance for queries, inserts, and updates. Explain statements help analyze query execution plans and identify opportunities to improve performance through proper indexing.
The document discusses Snowflake, a cloud data warehouse that is built for the cloud, multi-tenant, and highly scalable. It uses a shared-data, multi-cluster architecture where compute resources can be scaled independently from storage. Data is stored immutably in micro-partitions across an object store. Virtual warehouses provide isolated compute resources that can access all the data.
Azure SQL Database is a relational database-as-a-service hosted in the Azure cloud that reduces costs by eliminating the need to manage virtual machines, operating systems, or database software. It provides automatic backups, high availability through geo-replication, and the ability to scale performance by changing service tiers. Azure Cosmos DB is a globally distributed, multi-model database that supports automatic indexing, multiple data models via different APIs, and configurable consistency levels with strong performance guarantees. Azure Redis Cache uses the open-source Redis data structure store with managed caching instances in Azure for improved application performance.
This document provides an overview of a presentation on building better SQL Server databases. The presentation covers how SQL Server stores and retrieves data by looking under the hood at tables, data pages, and the process of requesting data. It then discusses best practices for database design such as using the right data types, avoiding page splits, and tips for writing efficient T-SQL code. The presentation aims to teach attendees how to design databases for optimal performance and scalability.
Technical Introduction to PostgreSQL and PPASAshnikbiz
Let's take a look at:
PostgreSQL and buzz it has created
Architecture
Oracle Compatibility
Performance Feature
Security Features
High Availability Features
DBA Tools
User Stories
What’s coming up in v9.3
How to start adopting
Powering GIS Application with PostgreSQL and Postgres Plus Ashnikbiz
This document provides an overview of Postgres Plus Advanced Server and its features. It begins with introductions to PostgreSQL and PostGIS. It then discusses Postgres Plus Advanced Server's Oracle compatibility, performance enhancements, security features, high availability options, database administration tools, and migration toolkit. The document also provides information on scaling Postgres Plus Advanced Server through partitioning and infinite cache technologies. It concludes with summaries of the replication capabilities of Postgres Plus Advanced Server.
Slides presented at Great Indian Developer Summit 2016 at the session MySQL: What's new on April 29 2016.
Contains information about the new MySQL Document Store released in April 2016.
A storage engine is a software module that a database management system uses to create, read, update and delete data from a database. MySQL supports several storage engines that act as handlers for different table types. Storage engines are categorized as transactional or non-transactional. Transactional tables can auto-recover from failures while non-transactional tables cannot. Common storage engines include MyISAM, InnoDB, MEMORY, ARCHIVE, BLACKHOLE, and CSV. Each engine has different features for speed, storage limits, transactions, and other factors. The appropriate engine depends on the specific database needs and requirements.
The document discusses different NoSQL data models including key-value, document, column family, and graph models. It provides examples of popular NoSQL databases that implement each model such as Redis, MongoDB, Cassandra, and Neo4j. The document argues that these NoSQL databases address limitations of relational databases in supporting modern web applications with requirements for scalability, flexibility, and high performance.
(ISM303) Migrating Your Enterprise Data Warehouse To Amazon RedshiftAmazon Web Services
Learn how Boingo Wireless and online media provider Edmunds gained substantial business insights and saved money and time by migrating to Amazon Redshift. Get an inside look into how they accomplished their migration from on-premises solutions. Learn how they tuned their schema and queries to take full advantage of the columnar MPP architecture in Amazon Redshift, how they leveraged third party solutions, and how they met their business intelligence needs in record time.
Take an in-depth look at data warehousing with Amazon Redshift and get answers to your technical questions. We will cover performance tuning techniques that take advantage of Amazon Redshift's columnar technology and massively parallel processing architecture. We will also discuss best practices for migrating from existing data warehouses, optimizing your schema, loading data efficiently, and using work load management and interleaved sorting.
Take an in-depth look at data warehousing with Amazon Redshift and get answers to your technical questions. We will cover performance tuning techniques that take advantage of Amazon Redshift's columnar technology and massively parallel processing architecture. We will also discuss best practices for migrating from existing data warehouses, optimizing your schema, loading data efficiently, and using work load management and interleaved sorting.
Optimizing Query is very important to improve the performance of the database. Analyse query using query execution plan, create cluster index and non-cluster index and create indexed views
AWS Webcast - Backup & Restore for ElastiCache/Redis: Getting Started & Best ...Amazon Web Services
ElastiCache is a web service that makes it easy to deploy, operate, and scale an in-memory cache in the cloud. With the introduction of Redis Backup and Restore, you can now create a snapshot of your entire ElastiCache for Redis cluster as it exists at a specific point in time. Schedule automatic, recurring daily snapshots, as well as initiate a manual snapshot at any time.
In this webinar, we'll discuss what you can do with this new capability, explain how it works, and describe how to get the most out of it. Key reasons to attend:
- Get a brief overview of Amazon ElastiCache for Redis
- Learn about use cases for the new backup/restore functionality
- Discover important best practices
- Get answers about the service
This document discusses handling massive writes for online transaction processing (OLTP) systems. It begins with an introduction and overview of the topics to be covered, including terminology, differences between massive reads versus writes, and potential solutions using relational databases, NoSQL databases, and code optimizations. Specific solutions discussed for massive writes include using memory, fast disks, caching, column-oriented databases, SQL tuning, database partitioning, reading from slaves, and sharding or splitting data across multiple databases. The document provides pros and cons of each approach and examples of performance improvements observed.
(BDT401) Amazon Redshift Deep Dive: Tuning and Best PracticesAmazon Web Services
Get a look under the covers: Learn tuning best practices for taking advantage of Amazon Redshift's columnar technology and parallel processing capabilities to improve your delivery of queries and improve overall database performance. This session explains how to migrate from existing data warehouses, create an optimized schema, efficiently load data, use work load management, tune your queries, and use Amazon Redshift's interleaved sorting features. Finally, learn how TripAdvisor uses these best practices to give their entire organization access to analytic insights at scale.
The document provides an overview of Amazon databases. It discusses Amazon's relational and non-relational database services including Amazon Aurora, Amazon RDS, Amazon Redshift, and DynamoDB. It covers their key features like scalability, availability, data security, and pricing. The objectives of exploring Amazon databases are to understand their flexibility to handle large data volumes and ability to adapt to changing demands. Another objective is to recognize the high availability and durability of Amazon databases to ensure continuous business operations.
This document discusses MySQL performance tuning and various MySQL products and features. It provides information on MySQL 5.6 including improved scalability, new InnoDB features for NoSQL access, and an improved optimizer. It also discusses MySQL Enterprise Monitor for performance monitoring, and the Performance Schema for instrumentation and monitoring internal operations.
This presentation provides a clear overview of how Oracle Database In-Memory optimizes both analytics and mixed workloads, delivering outstanding performance while supporting real-time analytics, business intelligence, and reporting. It provides details on what you can expect from Database In-Memory in both Oracle Database 12.1.0.2 and 12.2.
Best Practices – Extreme Performance with Data Warehousing on Oracle Databa...Edgar Alejandro Villegas
The document discusses best practices for data warehousing performance on Oracle Database. It covers Oracle Exadata Database Machine capabilities like intelligent storage, hybrid columnar compression, and smart flash cache. It also discusses partitioning, parallelism, monitoring tools, and data loading techniques to maximize warehouse performance.
Similar to MySQL: Know more about open Source Database (20)
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
UiPath Test Automation using UiPath Test Suite series, part 5
MySQL: Know more about open Source Database
1. know more about MySQL open source database
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2. Storage engines
Schema
Normalization
Data types
Indexes
Know more about your SQL queries - Using EXPLAIN
Character set and Collation
Resources
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3. Generics are inefficient
• If you have chosen MySQL, take advantage of its
strengths
• Having an understanding of the database helps you
develop better-performing applications
better to design a well-performing database-driven
application from the start
than try to fix a slow one after the fact!
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4. MySQL supports several
storage engines that act
as handlers for different
table types
No other database
vendor offers this
capability
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5. Dynamically add and remove storage engines.
Change the storage engine on a table with
“ALTER TABLE <table> ENGINE=InnoDB;”
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6. Concurrency: some have more granular locks than
others
right locking can improve performance.
• Storage: how the data is stored on disk
page size for tables, indexes, format used
• Indexes: b-trees, hash
• Memory usage
caching strategy
• Transactions:
not every application table needs transactions
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7. “As a developer, what do I need to know
about storage engines, without being a
MySQL expert?”
• Keep in mind the following questions:
What type of data will you be storing?
Is the data constantly changing?
Is the data mostly logs (INSERTs)?
requirements for reports?
need for transaction control?
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8. Default MySQL engine
• high-speed Query and Insert capability
insert uses shared read lock
updates, deletes use table-level locking, slower
• full-text indexing
Good for text search
• Non-transactional, No foreign key support
• good choice for :
read-only or read-mostly application tables that don't
require transactions
Web, data warehousing, logging, auditing
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9. Transaction-safe and ACID
(atomicity, consistency, isolation, durability) compliant
crash recovery, foreign key constraints
• good query performance, depending on indexes
• row-level locking, Multi Version Concurrency Control
(MVCC)
allows fewer row locks by keeping data snapshots
– Depending on the isolation level, no locking for SELECT
– high concurrency possible
• uses more disk space and memory than ISAM
• Good for Online transaction processing (OLTP)
Lots of users: eBay, Google, Yahoo!, Facebook, etc.
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10. Entirely in-memory engine
stores all data in RAM for extremely fast access
Updated Data is not persisted
– table loaded on restart
• Hash index used by default
• Good for
Summary and transient data
"lookup" tables,
calculated table counts,
for caching, temporary tables
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11. Incredible insert speeds
• Great compression rates (zlib)?
Typically 6-8x smaller than MyISAM
• No UPDATEs
• Ideal for storing and retrieving large amounts of
historical data
audit data, log files,Web traffic records
Data that can never be updated
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12. You can use multiple
storage engines in a
single application
A storage engine for the
same table on a slave can
be different than that of
the master
• Choose storage engine
that's best for your
applications requirements
can greatly improve
performance
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13. Creating a table with a specified engine
CREATE TABLE t1 (...)
ENGINE=InnoDB;
• Changing existing tables
ALTER TABLE t1 ENGINE=MyISAM;
• Finding all your available engines
SHOW STORAGE ENGINES;
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14. Basic foundation of performance
• Normalization
• Data Types
Smaller, smaller, smaller
- Smaller tables use less disk, less memory, can give better
performance
• Indexing
Speeds up retrieval
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15. Eliminate redundant data:
Don't store the same data in more than one table
Only store related data in a table
reduces database size and errors
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16. updates are usually faster.
there's less data to change.
• tables are usually smaller, use less memory, which
can give better performance.
• better performance for distinct or group by queries
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17. However Normalized database causes joins for queries
• excessively normalized database:
queries take more time to complete, as data has to be
retrieved from more tables.
• Normalized better for writes OLTP
• De-normalized better for reads , reporting
• Real World Mixture:
normalized schema
Cache selected columns in memory table
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18. Smaller => less disk => less memory => better
performance
Use the smallest data type possible
• The smaller your data types, The more index (and data)
can fit into a block of memory, the faster your queries
will be.
Period.
Especially for indexed fields
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19. MySQL has 9 numeric data types
Compared to Oracle's 1
• Integer:
TINYINT , SMALLINT, MEDIUMINT, INT, BIGINT
Require 8, 16, 24, 32, and 64 bits of space.
• Use UNSIGNED when you don't need negative numbers – one more level of data
integrity
• BIGINT is not needed for AUTO_INCREMENT
INT UNSIGNED stores 4.3 billion values!
Summation of values... yes, use BIGINT
Floating Point: FLOAT, DOUBLE
Approximate calculations
• Fixed Point: DECIMAL
Always use DECIMAL for monetary/currency fields, never use FLOAT or
DOUBLE!
• Other: BIT
Store 0,1 values
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20. VARCHAR(n) variable length
uses only space it needs
– Can save disk space = better performance
Use :
– Max column length > avg
– when updates rare (updates fragment)
• CHAR(n) fixed length
Use:
– short strings, Mostly same length, or changed frequently
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21. Always define columns as NOT NULL
– unless there is a good reason not to
Can save a byte per column
nullable columns make indexes, index statistics, and
value comparisons more complicated.
• Use the same data types for columns that will be
compared in JOINs
Otherwise converted for comparison
• Use BLOBs very sparingly
Use the filesystem for what it was intended
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22. “The more records you can fit into a single page of
memory/disk, the faster your seeks and scans will be.”
• Use appropriate data types
• Keep primary keys small
• Use TEXT sparingly
Consider separate tables
• Use BLOBs very sparingly
Use the filesystem for what it was intended
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23. Indexes Speed up Queries,
SELECT...WHERE name = 'carol'
only if there is good selectivity:
– % of distinct values in a column
• But... each index will slow down INSERT, UPDATE, and
DELETE operations
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24. Always have an index on join conditions
• Look to add indexes on columns used in WHERE and
GROUP BY expressions
• PRIMARY KEY, UNIQUE , and Foreign key Constraint
columns are automatically indexed.
other columns can be indexed (CREATE INDEX..)
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25. use the MySQL slow query log and use Explain
• Append EXPLAIN to your SELECT statement
shows how the MySQL optimizer has chosen to execute
the query
• You Want to make your queries access less data:
are queries accessing too many rows or columns?
– select only the columns that you need
• Use to see where you should add indexes
Consider adding an index for slow queries or cause a lot
of load.
– ensures that missing indexes are picked up early in the
development process
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26. Find and fix problem SQL:
• how long a query took
• how the optimizer handled it
Drill downs, results of EXPLAIN statements
• Historical and real-time analysis
query execution counts, run time
“Its not just slow running queries that are a problem,
Sometimes its SQL that executes a lot that kills your
system”
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27. Just append EXPLAIN to
your SELECT statement
• Provides the execution plan
chosen by the MySQL
optimizer for a specific
SELECT statement
Shows how the MySQL
optimizer executes the
query
• Use to see where you should
add indexes
ensures that missing
indexes are picked up early
in the development
process
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28. A character set is a set of symbols and encodings.
A collation is a set of rules for comparing characters in a
character set.
MySQL can do these things for you:
Store strings using a variety of character sets
Compare strings using a variety of collations
Mix strings with different character sets or collations in the
same server, the same database, or even the same table
Allow specification of character set and collation at any level
- Mysql > SET NAMES 'utf8';
- Mysql > SHOW CHARACTER SET
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29. Two different character sets cannot have the same
collation.
Each character set has one collation that is the default
collation. For example, the default collation for latin1 is
latin1_swedish_ci. The output for “SHOW CHARACTER
SET” indicates which collation is the default for each
displayed character set.
There is a convention for collation names: They start with
the name of the character set with which they are
associated, they usually include a language name, and they
end with _ci (case insensitive), _cs (case sensitive), or _bin
(binary).
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30. <meta http-equiv="Content-Type" content="text/html;
charset=utf-8" />
<?php mysql_query('SET NAMES utf8'); ?>
CREATE DATABASE mydatabase DEFAULT CHARACTER
SET utf8 COLLATE utf8_general_ci;
CREATE TABLE mytable (
mydata VARCHAR(128) NOT NULL
) ENGINE=MyISAM DEFAULT CHARACTER SET utf8
COLLATE utf8_general_ci;
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31. MySQL Forge and the Forge Wiki
http://forge.mysql.com/
Planet MySQL
http://planetmysql.org/
MySQL DevZone
http://dev.mysql.com/
High Performance MySQL book
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