All about Storage - Series 2 Defining DataDAGEOP LTD
All about Storage - Series 2 Defining Data
=> Data & Data Types
=> Text and Image Locations
=> Page Structures & Internals
by Dr. Subramani Paramasivam
The document discusses managing dynamic web content through a database. It explains that databases allow content to be programmatically generated and easier to manage than file-based systems. It provides an overview of key database concepts like tables, fields, queries, and the relational structure. Examples show how a student database could be implemented to allow flexible querying and updating of student records over time.
This document discusses managing dynamic web content through databases. It explains that databases allow content to be programmatically generated and easier to manage over time compared to file-based systems. It provides an overview of key database concepts like tables, fields, queries, and the benefits of relational databases. It also introduces phpMyAdmin as a tool for visually managing databases and provides examples of connecting to a MySQL database from PHP scripts to perform operations like selecting, inserting, and retrieving data.
This document discusses building dynamic web sites using databases. It begins by explaining that truly dynamic sites have content that changes over time, is customized for users, and can be automatically generated. It recommends using a database rather than storing content in files, as databases are faster, more efficient, and easier to manage when content grows large. The document then provides an overview of key database concepts like tables, fields, queries, and the relational structure. It gives an example of how a student database might be implemented and why a database is better than flat files for such an application. Finally, it discusses MySQL as a popular open-source database and shows basic concepts like connecting to the database, selecting a database, performing queries, and extracting record
Squirrel is a .NET library that provides tools for data processing, analytics, and visualization using small data. It features I/O blocks, data modeling, database connectors, data generation, data cleansing, statistics/math functions, and visualization adaptors. Squirrel also supports mobile integration through messaging with Android devices. Future releases will enhance connectors, provide a single API for visualization, and add voice/gesture recognition capabilities.
This document discusses using PostgreSQL as a schemaless database to store unstructured or semi-structured data. It describes how PostgreSQL supports schemaless data through data types like hstore and JSON. Performance tests show that while MongoDB is faster for writes, PostgreSQL with GiST indexes performs comparably to MongoDB for reads and offers benefits like transactions and constraints that MongoDB lacks. The document concludes that PostgreSQL can fulfill schemaless data requirements while avoiding the costs of migrating to a new database.
The document summarizes new features in SQL Server 2016 SP1, organized into three categories: performance enhancements, security improvements, and hybrid data capabilities. It highlights key features such as in-memory technologies for faster queries, always encrypted for data security, and PolyBase for querying relational and non-relational data. New editions like Express and Standard provide more built-in capabilities. The document also reviews SQL Server 2016 SP1 features by edition, showing advanced features are now more accessible across more editions.
All about Storage - Series 2 Defining DataDAGEOP LTD
All about Storage - Series 2 Defining Data
=> Data & Data Types
=> Text and Image Locations
=> Page Structures & Internals
by Dr. Subramani Paramasivam
The document discusses managing dynamic web content through a database. It explains that databases allow content to be programmatically generated and easier to manage than file-based systems. It provides an overview of key database concepts like tables, fields, queries, and the relational structure. Examples show how a student database could be implemented to allow flexible querying and updating of student records over time.
This document discusses managing dynamic web content through databases. It explains that databases allow content to be programmatically generated and easier to manage over time compared to file-based systems. It provides an overview of key database concepts like tables, fields, queries, and the benefits of relational databases. It also introduces phpMyAdmin as a tool for visually managing databases and provides examples of connecting to a MySQL database from PHP scripts to perform operations like selecting, inserting, and retrieving data.
This document discusses building dynamic web sites using databases. It begins by explaining that truly dynamic sites have content that changes over time, is customized for users, and can be automatically generated. It recommends using a database rather than storing content in files, as databases are faster, more efficient, and easier to manage when content grows large. The document then provides an overview of key database concepts like tables, fields, queries, and the relational structure. It gives an example of how a student database might be implemented and why a database is better than flat files for such an application. Finally, it discusses MySQL as a popular open-source database and shows basic concepts like connecting to the database, selecting a database, performing queries, and extracting record
Squirrel is a .NET library that provides tools for data processing, analytics, and visualization using small data. It features I/O blocks, data modeling, database connectors, data generation, data cleansing, statistics/math functions, and visualization adaptors. Squirrel also supports mobile integration through messaging with Android devices. Future releases will enhance connectors, provide a single API for visualization, and add voice/gesture recognition capabilities.
This document discusses using PostgreSQL as a schemaless database to store unstructured or semi-structured data. It describes how PostgreSQL supports schemaless data through data types like hstore and JSON. Performance tests show that while MongoDB is faster for writes, PostgreSQL with GiST indexes performs comparably to MongoDB for reads and offers benefits like transactions and constraints that MongoDB lacks. The document concludes that PostgreSQL can fulfill schemaless data requirements while avoiding the costs of migrating to a new database.
The document summarizes new features in SQL Server 2016 SP1, organized into three categories: performance enhancements, security improvements, and hybrid data capabilities. It highlights key features such as in-memory technologies for faster queries, always encrypted for data security, and PolyBase for querying relational and non-relational data. New editions like Express and Standard provide more built-in capabilities. The document also reviews SQL Server 2016 SP1 features by edition, showing advanced features are now more accessible across more editions.
Interactive ad-hoc analysis at petabyte scale with HDInsight Interactive QueryAshish Thapliyal
This document provides tips for creating accessible PowerPoint presentations, including using high color contrast, alternative text, slide layouts, and proper reading order. It recommends using the Color Contrast Analyzer tool, different shapes with a legend for color blindness, and running the Accessibility Checker. Videos should be captioned and audio described. Additional resources for photography, illustrations, and icons from Brand Central are also mentioned.
Interactive ad-hoc analysis at petabyte scale with HDInsight Interactive QueryMicrosoft Tech Community
In this session, you will learn how technologies such as Low Latency Analytical Processing [LLAP] and Hive 2.x are making it possible to analyze petabytes of data with sub second latency with common file formats such as csv, json etc. without converting to columnar file formats like ORC/Parquet. We will go deep into LLAP’s performance and architecture benefits and how it compares with Spark and Presto. We also look at how business analysts can use familiar tools such as Microsoft Excel and Power BI and do interactive query over their data lake without moving data outside the data lake.
Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. You can start small for just $0.25 per hour with no commitment or upfront costs and scale to a petabyte or more for $1,000 per terabyte per year, less than a tenth of most other data warehousing solutions.
See a recording of the webinar based on this presentation here on YouTube: https://youtu.be/GgLKodmL5xE
Masterclass series webinars, including on-demand access to all of this years recorded webinars: http://aws.amazon.com/campaigns/emea/masterclass/
Journey Through the Cloud webinar series, including on-demand access to all webinars so far this year: http://aws.amazon.com/campaigns/emea/journey/
Hive is considered the de facto standard for interactively querying large datasets stored in Hadoop. It allows users to run SQL queries against data stored in Hadoop and supports data types and queries similar to a relational database. Data is organized in tables and partitions within databases in Hive and is stored in HDFS directories. Users can explore, structure and analyze heterogeneous data stored in Hadoop using Hive to gain business insights.
The document describes an online pharmacy web application created using HTML, CSS, PHP, and MySQL. The application allows users to purchase prescription and over-the-counter medications online conveniently. It provides accurate drug information and enhances medication safety. The application aims to automate pharmacy operations, improve customer service, and provide accessibility through an online platform. Technical details about the front-end and back-end technologies used like PHP, CSS, SQL are also included. Sample code for creating admin, item, and orders tables in the database is presented.
This document discusses revisiting SQL basics and advanced topics. It covers objectives, assumptions, and topics to be covered including staying clean with conventions, data types, revisiting basics, joining, subqueries, joins versus subqueries, group by, set operations, and case statements. The topics sections provides details on each topic with examples to enhance SQL knowledge and write better queries.
This is a run-through at a 200 level of the Microsoft Azure Big Data Analytics for the Cloud data platform based on the Cortana Intelligence Suite offerings.
Five Critical Success Factors for Big Data and Traditional BIInside Analysis
VelociData offers big data operations appliances that combine FPGAs, GPUs, and CPUs to enable high-speed parallel data processing. This allows VelociData to accelerate common data transformation and quality tasks by several orders of magnitude compared to conventional approaches. Examples included accelerating lookups from 3000 to 600,000 records per second. VelociData appliances can offload bottlenecks from ETL servers, mainframes, Hadoop, and data warehouses to improve overall performance. The presentation demonstrated how VelociData solutions provide 100x or greater acceleration through massively parallel hardware architectures.
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.
How to Radically Simplify Your Business Data ManagementClusterpoint
Relational databases were designed for tabular data storage model. It requires complex software: schemas, encoded data, inflexible relations, sophisticated indexes. Complexity of your IT systems increases over your database life-time many-fold. Your costs too. Yet, we have a solution for this.
Prague data management meetup 2018-03-27Martin Bém
This document discusses different data types and data models. It begins by describing unstructured, semi-structured, and structured data. It then discusses relational and non-relational data models. The document notes that big data can include any of these data types and models. It provides an overview of Microsoft's data management and analytics platform and tools for working with structured, semi-structured, and unstructured data at varying scales. These include offerings like SQL Server, Azure SQL Database, Azure Data Lake Store, Azure Data Lake Analytics, HDInsight and Azure Data Warehouse.
Saurabh_Patel_An Alternative way to Import Multiple Excel files with Multiple...Saurabh Patel
This document presents an alternative method for importing multiple Excel files with multiple worksheets into SAS datasets. The method uses VBScript to convert the Excel files to CSV format, unmerging cells and removing carriage returns. A SAS macro then processes the CSV files, importing the data with all variables in character format and maximum lengths to preserve precision. While it creates less user-friendly datasets than other methods, this dynamic process saves time by only requiring the input directory path.
Introduction to Azure Data Lake and U-SQL for SQL users (SQL Saturday 635)Michael Rys
Data Lakes have become a new tool in building modern data warehouse architectures. In this presentation we will introduce Microsoft's Azure Data Lake offering and its new big data processing language called U-SQL that makes Big Data Processing easy by combining the declarativity of SQL with the extensibility of C#. We will give you an initial introduction to U-SQL by explaining why we introduced U-SQL and showing with an example of how to analyze some tweet data with U-SQL and its extensibility capabilities and take you on an introductory tour of U-SQL that is geared towards existing SQL users.
slides for SQL Saturday 635, Vancouver BC, Aug 2017
In this presentation, you will get a look under the covers of Amazon Redshift, a fast, fully-managed, petabyte-scale data warehouse service for less than $1,000 per TB per year. Learn how Amazon Redshift uses columnar technology, optimized hardware, and massively parallel processing to deliver fast query performance on data sets ranging in size from hundreds of gigabytes to a petabyte or more. We'll also walk through techniques for optimizing performance and, you’ll hear from a specific customer and their use case to take advantage of fast performance on enormous datasets leveraging economies of scale on the AWS platform.
Speakers:
Ian Meyers, AWS Solutions Architect
Toby Moore, Chief Technology Officer, Space Ape
The document summarizes a presentation on developing hybrid applications with Informix. It discusses how the Informix wire listener allows unified access to JSON, relational, and time series data through MongoDB and REST APIs. It enables applications to execute SQL statements and perform joins across different data sources. Sample applications demonstrate basic CRUD operations using MongoDB and REST interfaces with Informix.
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.
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 to use these best practices to give their entire organization access to analytic insights at scale.
Presented by: Alex Sinner, Solutions Architecture PMO, Amazon Web Services
Customer Guest: Luuk Linssen, Product Manager, Bannerconnect
The document discusses new features and enhancements in Apache Hive 3, including:
1) Materialized views which allow optimizing workloads and queries without changing SQL.
2) Improved ACID support which makes ACID transactions as fast as regular tables.
3) Enhancements to constraints, defaults, and surrogate keys which help the optimizer produce better plans and improve data integrity.
This document provides an introduction and overview of a course on C#. The goals are to introduce the C# programming language, the .NET framework, and object-oriented concepts. No prior programming experience is required, but students should be comfortable with object-oriented concepts and coding. The course will cover C# language constructs over 10 lectures and include assignments to be completed online and graded on a Satisfactory/Unsatisfactory basis. Example C# code is provided to demonstrate basic syntax like namespaces, classes, and inheritance.
This document provides an introduction and overview of Python. It discusses the major versions of Python, including CPython, Jython, and IronPython. It also covers popular Python integrated development environments like PyDev with Eclipse, Komodo, Emacs, and Vim. The document then describes common Python data types like lists, strings, tuples, and dictionaries. It shows how to access and manipulate elements within these data types. Finally, the document covers basic Python control flow structures like if/else statements, for loops, break, continue, and range.
Interactive ad-hoc analysis at petabyte scale with HDInsight Interactive QueryAshish Thapliyal
This document provides tips for creating accessible PowerPoint presentations, including using high color contrast, alternative text, slide layouts, and proper reading order. It recommends using the Color Contrast Analyzer tool, different shapes with a legend for color blindness, and running the Accessibility Checker. Videos should be captioned and audio described. Additional resources for photography, illustrations, and icons from Brand Central are also mentioned.
Interactive ad-hoc analysis at petabyte scale with HDInsight Interactive QueryMicrosoft Tech Community
In this session, you will learn how technologies such as Low Latency Analytical Processing [LLAP] and Hive 2.x are making it possible to analyze petabytes of data with sub second latency with common file formats such as csv, json etc. without converting to columnar file formats like ORC/Parquet. We will go deep into LLAP’s performance and architecture benefits and how it compares with Spark and Presto. We also look at how business analysts can use familiar tools such as Microsoft Excel and Power BI and do interactive query over their data lake without moving data outside the data lake.
Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. You can start small for just $0.25 per hour with no commitment or upfront costs and scale to a petabyte or more for $1,000 per terabyte per year, less than a tenth of most other data warehousing solutions.
See a recording of the webinar based on this presentation here on YouTube: https://youtu.be/GgLKodmL5xE
Masterclass series webinars, including on-demand access to all of this years recorded webinars: http://aws.amazon.com/campaigns/emea/masterclass/
Journey Through the Cloud webinar series, including on-demand access to all webinars so far this year: http://aws.amazon.com/campaigns/emea/journey/
Hive is considered the de facto standard for interactively querying large datasets stored in Hadoop. It allows users to run SQL queries against data stored in Hadoop and supports data types and queries similar to a relational database. Data is organized in tables and partitions within databases in Hive and is stored in HDFS directories. Users can explore, structure and analyze heterogeneous data stored in Hadoop using Hive to gain business insights.
The document describes an online pharmacy web application created using HTML, CSS, PHP, and MySQL. The application allows users to purchase prescription and over-the-counter medications online conveniently. It provides accurate drug information and enhances medication safety. The application aims to automate pharmacy operations, improve customer service, and provide accessibility through an online platform. Technical details about the front-end and back-end technologies used like PHP, CSS, SQL are also included. Sample code for creating admin, item, and orders tables in the database is presented.
This document discusses revisiting SQL basics and advanced topics. It covers objectives, assumptions, and topics to be covered including staying clean with conventions, data types, revisiting basics, joining, subqueries, joins versus subqueries, group by, set operations, and case statements. The topics sections provides details on each topic with examples to enhance SQL knowledge and write better queries.
This is a run-through at a 200 level of the Microsoft Azure Big Data Analytics for the Cloud data platform based on the Cortana Intelligence Suite offerings.
Five Critical Success Factors for Big Data and Traditional BIInside Analysis
VelociData offers big data operations appliances that combine FPGAs, GPUs, and CPUs to enable high-speed parallel data processing. This allows VelociData to accelerate common data transformation and quality tasks by several orders of magnitude compared to conventional approaches. Examples included accelerating lookups from 3000 to 600,000 records per second. VelociData appliances can offload bottlenecks from ETL servers, mainframes, Hadoop, and data warehouses to improve overall performance. The presentation demonstrated how VelociData solutions provide 100x or greater acceleration through massively parallel hardware architectures.
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.
How to Radically Simplify Your Business Data ManagementClusterpoint
Relational databases were designed for tabular data storage model. It requires complex software: schemas, encoded data, inflexible relations, sophisticated indexes. Complexity of your IT systems increases over your database life-time many-fold. Your costs too. Yet, we have a solution for this.
Prague data management meetup 2018-03-27Martin Bém
This document discusses different data types and data models. It begins by describing unstructured, semi-structured, and structured data. It then discusses relational and non-relational data models. The document notes that big data can include any of these data types and models. It provides an overview of Microsoft's data management and analytics platform and tools for working with structured, semi-structured, and unstructured data at varying scales. These include offerings like SQL Server, Azure SQL Database, Azure Data Lake Store, Azure Data Lake Analytics, HDInsight and Azure Data Warehouse.
Saurabh_Patel_An Alternative way to Import Multiple Excel files with Multiple...Saurabh Patel
This document presents an alternative method for importing multiple Excel files with multiple worksheets into SAS datasets. The method uses VBScript to convert the Excel files to CSV format, unmerging cells and removing carriage returns. A SAS macro then processes the CSV files, importing the data with all variables in character format and maximum lengths to preserve precision. While it creates less user-friendly datasets than other methods, this dynamic process saves time by only requiring the input directory path.
Introduction to Azure Data Lake and U-SQL for SQL users (SQL Saturday 635)Michael Rys
Data Lakes have become a new tool in building modern data warehouse architectures. In this presentation we will introduce Microsoft's Azure Data Lake offering and its new big data processing language called U-SQL that makes Big Data Processing easy by combining the declarativity of SQL with the extensibility of C#. We will give you an initial introduction to U-SQL by explaining why we introduced U-SQL and showing with an example of how to analyze some tweet data with U-SQL and its extensibility capabilities and take you on an introductory tour of U-SQL that is geared towards existing SQL users.
slides for SQL Saturday 635, Vancouver BC, Aug 2017
In this presentation, you will get a look under the covers of Amazon Redshift, a fast, fully-managed, petabyte-scale data warehouse service for less than $1,000 per TB per year. Learn how Amazon Redshift uses columnar technology, optimized hardware, and massively parallel processing to deliver fast query performance on data sets ranging in size from hundreds of gigabytes to a petabyte or more. We'll also walk through techniques for optimizing performance and, you’ll hear from a specific customer and their use case to take advantage of fast performance on enormous datasets leveraging economies of scale on the AWS platform.
Speakers:
Ian Meyers, AWS Solutions Architect
Toby Moore, Chief Technology Officer, Space Ape
The document summarizes a presentation on developing hybrid applications with Informix. It discusses how the Informix wire listener allows unified access to JSON, relational, and time series data through MongoDB and REST APIs. It enables applications to execute SQL statements and perform joins across different data sources. Sample applications demonstrate basic CRUD operations using MongoDB and REST interfaces with Informix.
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.
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 to use these best practices to give their entire organization access to analytic insights at scale.
Presented by: Alex Sinner, Solutions Architecture PMO, Amazon Web Services
Customer Guest: Luuk Linssen, Product Manager, Bannerconnect
The document discusses new features and enhancements in Apache Hive 3, including:
1) Materialized views which allow optimizing workloads and queries without changing SQL.
2) Improved ACID support which makes ACID transactions as fast as regular tables.
3) Enhancements to constraints, defaults, and surrogate keys which help the optimizer produce better plans and improve data integrity.
This document provides an introduction and overview of a course on C#. The goals are to introduce the C# programming language, the .NET framework, and object-oriented concepts. No prior programming experience is required, but students should be comfortable with object-oriented concepts and coding. The course will cover C# language constructs over 10 lectures and include assignments to be completed online and graded on a Satisfactory/Unsatisfactory basis. Example C# code is provided to demonstrate basic syntax like namespaces, classes, and inheritance.
This document provides an introduction and overview of Python. It discusses the major versions of Python, including CPython, Jython, and IronPython. It also covers popular Python integrated development environments like PyDev with Eclipse, Komodo, Emacs, and Vim. The document then describes common Python data types like lists, strings, tuples, and dictionaries. It shows how to access and manipulate elements within these data types. Finally, the document covers basic Python control flow structures like if/else statements, for loops, break, continue, and range.
This document provides an overview of the Internet of Things (IoT). It defines IoT as the network of physical objects embedded with sensors that can collect and exchange data. The document outlines how IoT works by leveraging technologies like RFID, sensors, and nanotechnology. It also discusses the current status and future prospects of IoT, including its applications in various industries. Technological challenges and criticisms of IoT like privacy, security, and environmental impact are also summarized.
The document provides an introduction to programming in C++, covering topics such as:
- The software development cycle of compiling, linking, and executing code.
- Integrated development environments (IDEs) that support the entire development process with features like editing, compiling, debugging etc.
- Key components of a program including keywords, variables, operators, and constructs.
- Object oriented programming concepts in C++ like classes, objects, and inheritance hierarchies.
This document provides an overview of learning Python in three hours. It covers installing and running Python, basic data types like integers, floats and strings. It also discusses sequence types like lists, tuples and strings, including accessing elements, slicing, and using operators like + and *. The document explains basic syntax like comments, indentation and naming conventions. It provides examples of simple functions and scripts.
This document provides an introduction and overview of the R programming language and statistical software environment. It discusses R's open source development, interoperability with other languages, variety of statistical and numerical methods, and high quality visualization tools. It also introduces key R concepts like vectors, matrices, lists, data frames, functions, operators, subsetting, importing/exporting data, and gives examples of frequently used statistical and graphical functions. Finally, it provides an overview of the Bioconductor project for biological data analysis using R.
HBase is a distributed column-oriented database built on top of Hadoop that provides random real-time read/write access to big data stored in Hadoop. It uses a master server to assign regions to region servers and Zookeeper to track servers and coordinate tasks. HBase allows users to perform CRUD operations on tables through its shell interface using commands like create, put, get, and scan.
The document discusses MapReduce concepts including the Job, Mapper, Reducer, and implementation classes. It provides details on:
1) The Job class allows configuration, submission, and monitoring of MapReduce jobs. The Mapper class defines Map tasks to transform input key-value pairs into intermediate pairs.
2) The Reducer class defines Reduce tasks to combine intermediate pairs with the same key. It involves shuffle, sort, and reduce phases.
3) An example MapReduce program is provided to count word frequencies in a text file using WordCount, WordMapper, and WordReducer classes.
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
This presentation was provided by Racquel Jemison, Ph.D., Christina MacLaughlin, Ph.D., and Paulomi Majumder. Ph.D., all of the American Chemical Society, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
THE SACRIFICE HOW PRO-PALESTINE PROTESTS STUDENTS ARE SACRIFICING TO CHANGE T...indexPub
The recent surge in pro-Palestine student activism has prompted significant responses from universities, ranging from negotiations and divestment commitments to increased transparency about investments in companies supporting the war on Gaza. This activism has led to the cessation of student encampments but also highlighted the substantial sacrifices made by students, including academic disruptions and personal risks. The primary drivers of these protests are poor university administration, lack of transparency, and inadequate communication between officials and students. This study examines the profound emotional, psychological, and professional impacts on students engaged in pro-Palestine protests, focusing on Generation Z's (Gen-Z) activism dynamics. This paper explores the significant sacrifices made by these students and even the professors supporting the pro-Palestine movement, with a focus on recent global movements. Through an in-depth analysis of printed and electronic media, the study examines the impacts of these sacrifices on the academic and personal lives of those involved. The paper highlights examples from various universities, demonstrating student activism's long-term and short-term effects, including disciplinary actions, social backlash, and career implications. The researchers also explore the broader implications of student sacrifices. The findings reveal that these sacrifices are driven by a profound commitment to justice and human rights, and are influenced by the increasing availability of information, peer interactions, and personal convictions. The study also discusses the broader implications of this activism, comparing it to historical precedents and assessing its potential to influence policy and public opinion. The emotional and psychological toll on student activists is significant, but their sense of purpose and community support mitigates some of these challenges. However, the researchers call for acknowledging the broader Impact of these sacrifices on the future global movement of FreePalestine.
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumMJDuyan
(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏)-𝐏𝐫𝐞𝐥𝐢𝐦𝐬
𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
-Define entrepreneurship, distinguishing it from general business activities by emphasizing its focus on innovation, risk-taking, and value creation. Students will describe the characteristics and traits of successful entrepreneurs, including their roles and responsibilities, and discuss the broader economic and social impacts of entrepreneurial activities on both local and global scales.
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
CapTechTalks Webinar Slides June 2024 Donovan Wright.pptxCapitolTechU
Slides from a Capitol Technology University webinar held June 20, 2024. The webinar featured Dr. Donovan Wright, presenting on the Department of Defense Digital Transformation.
How Barcodes Can Be Leveraged Within Odoo 17Celine George
In this presentation, we will explore how barcodes can be leveraged within Odoo 17 to streamline our manufacturing processes. We will cover the configuration steps, how to utilize barcodes in different manufacturing scenarios, and the overall benefits of implementing this technology.
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1- مُترجمة ترجمة تُناسب جميع المستويات
2- تحتوي على 78 رسم توضيحي لكل كلمة موجودة بالملزمة (لكل كلمة !!!!)
#فهم_ماكو_درخ
3- دقة الكتابة والصور عالية جداً جداً جداً
4- هُنالك بعض المعلومات تم توضيحها بشكل تفصيلي جداً (تُعتبر لدى الطالب أو الطالبة بإنها معلومات مُبهمة ومع ذلك تم توضيح هذهِ المعلومات المُبهمة بشكل تفصيلي جداً
5- الملزمة تشرح نفسها ب نفسها بس تكلك تعال اقراني
6- تحتوي الملزمة في اول سلايد على خارطة تتضمن جميع تفرُعات معلومات الجهاز الهيكلي المذكورة في هذهِ الملزمة
واخيراً هذهِ الملزمة حلالٌ عليكم وإتمنى منكم إن تدعولي بالخير والصحة والعافية فقط
كل التوفيق زملائي وزميلاتي ، زميلكم محمد الذهبي 💊💊
🔥🔥🔥🔥🔥🔥🔥🔥🔥
2. Building Data Dynamic Web Sites
Truly dynamic web sites
Content changes over time
Content customised for individual user
Content automatically generated
Content Programmatically generated
Can be File system based
HTML and Images stored on File System
Gets hard to manage over time
Database based
HTML, Images etc all generated from database
Easier to manage
If data is too large, can overload the database
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4. Database
• Structured collection of data.
• Tables
• Fields
• Query
• Reports
• Essentially a much more sophisticated
implementation of the flat files.
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6. Relational Database
• Stores data in separate tables instead of
a single store.
• Relationships between tables are set
• In theory, this provides a faster, more
flexible database system.
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7. Example
• We wish to maintain a database of student names, IDs, addresses,
and any other information.
• Will be updated frequently with new names and information.
• Will want to retrieve data based on some predicate.
• e.g, ‘give me the names of all Massey students who live in
Albany’.
• Will want to update database with new information about students,
not previously recorded.
• e.g., may decide we want to include IRD nos.
• Very difficult to manage using ‘flat file’ systems
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8. Databases
Fast, Efficient back end storage
Easier to manage than file system based approach
Relational Database structure
Well developed theory and practise
Multi-user capable
Multithreaded, multiprocessor, sometimes cluster
based systems
Standards based queries
Structured Query Language (SQL)
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9. MySQL Database
world's most popular open source database
because of its consistent fast performance, high
reliability and ease of use
Open Source License:- free
GNU General Public License
Free to modify and distribute but all modification must
be available in source code format
Commercial:- not free
Fully paid up professional support
• used by Google, Facebook Nokia, YouTube,
Yahoo!, Alcatel-Lucent, Zappos.com, etc.
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10. Basic Database Server Concepts
Database runs as a server
Attaches to either a default port or an administrator
specified port
Clients connect to database
For secure systems
authenticated connections
usernames and passwords
Clients make queries on the database
Retrieve content
Insert content
SQL (Structured Query Language) is the language used
to insert and retrieve content
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12. Database Management System
• Manages the storage and retrieval of data
to and from the database and hides the
complexity of what is actually going on
from the user.
Database User
Database
Management
Ssytem
• MySQL is a relational database
management systemhttp://www.allsoftsolutions.in
13. Client: makes a request
Client
(browser)
Web
browser
os
Web
server
os
Server
Internet
requests an Internet
resource by
specifying a URL and
providing input via HTTP
encoded strings
Network Core
GET hello.php HTTP/1.1
Host: www.massey.ac.nz:80
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16. • MySQL can be controlled through a
simple command-line interface; however,
we can use phpMyAdmin as an interface
to MySQL.
• phpMyAdmin is a very powerful tool; it
provides a large number of facilities for
customising a database management
system.
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24. In MySQL there are three main types :
• text
• number
• Date/Time.
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25. CHAR(size) Holds a fixed length string (can contain letters, numbers, and special
characters). The fixed size is specified in parenthesis. Can store up to
255 characters
VARCHAR(size) Holds a variable length string (can contain letters, numbers, and special
characters). The maximum size is specified in parenthesis. Can store up
to 255 characters. Note: If you put a greater value than 255 it will be
converted to a TEXT type
TINYTEXT Holds a string with a maximum length of 255 characters
TEXT Holds a string with a maximum length of 65,535 characters
MEDIUMTEXT Holds a string with a maximum length of 16,777,215 characters
LONGTEXT Holds a string with a maximum length of 4,294,967,295 characters
ENUM(x,y,z,etc.) Let you enter a list of possible values. You can list up to 65535 values in
an ENUM list. If a value is inserted that is not in the list, a blank value will
be inserted.Note: The values are sorted in the order you enter them.
You enter the possible values in this format: ENUM('X','Y','Z')
http://www.w3schools.com/sql/sql_datatypes.asp
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26. TINYINT(size) -128 to 127 normal. 0 to 255 UNSIGNED*. The maximum number of digits
may be specified in parenthesis
SMALLINT(size) -32768 to 32767 normal. 0 to 65535 UNSIGNED*. The maximum number
of digits may be specified in parenthesis
MEDIUMINT(size) -8388608 to 8388607 normal. 0 to 16777215 UNSIGNED*. The maximum
number of digits may be specified in parenthesis
INT(size) -2147483648 to 2147483647 normal. 0 to 4294967295 UNSIGNED*. The
maximum number of digits may be specified in parenthesis
BIGINT(size) -9223372036854775808 to 9223372036854775807 normal. 0 to
18446744073709551615 UNSIGNED*. The maximum number of digits may
be specified in parenthesis
FLOAT(size,d) A small number with a floating decimal point. The maximum number of
digits may be specified in the size parameter. The maximum number of
digits to the right of the decimal point is specified in the d parameter
DOUBLE(size,d) A large number with a floating decimal point. The maximum number of
digits may be specified in the size parameter. The maximum number of
digits to the right of the decimal point is specified in the d parameter
DECIMAL(size,d) A DOUBLE stored as a string , allowing for a fixed decimal point. The
maximum number of digits may be specified in the size parameter. The
maximum number of digits to the right of the decimal point is specified in
the d parameter
http://www.w3schools.com/sql/sql_datatypes.asp
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27. DATE() A date. Format: YYYY-MM-DDNote: The supported range is from '1000-01-
01' to '9999-12-31'
DATETIME() *A date and time combination. Format: YYYY-MM-DD HH:MM:SSNote: The
supported range is from '1000-01-01 00:00:00' to '9999-12-31 23:59:59'
TIMESTAMP() *A timestamp. TIMESTAMP values are stored as the number of seconds since
the Unix epoch ('1970-01-01 00:00:00' UTC). Format: YYYY-MM-DD
HH:MM:SSNote: The supported range is from '1970-01-01 00:00:01' UTC to
'2038-01-09 03:14:07' UTC
TIME() A time. Format: HH:MM:SSNote: The supported range is from '-838:59:59' to
'838:59:59'
YEAR() A year in two-digit or four-digit format.Note: Values allowed in four-digit
format: 1901 to 2155. Values allowed in two-digit format: 70 to 69,
representing years from 1970 to 2069
http://www.w3schools.com/sql/sql_datatypes.asp
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45. Summary
• Concept of databases
• Tables and Fields
• Field Types
• phpMyAdmin Tool for manipulating databases
• Creation of a database
• How to add and edit records
• How to back-up a database
• Database Design
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47. Connecting to a MySQL DBMS
• In order for our PHP script to access a
database we need to form a connection
from the script to the database
management system.
resourceId = mysql_connect(server, username, password);
• Server is the DBMS server
• username is your username
• password is your password
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48. Connecting to a MySQL DBMS
• In order for our PHP script to access a
database we need to form a connection
from the script to the database
management system.
resourceId = mysql_connect(server, username, password);
• The function returns a resource-identifier type.
• a PHP script can connect to a DBMS anywhere in the world,
so long as it is connected to the internet.
• we can also connect to multiple DBMS at the same time.http://www.allsoftsolutions.in
49. Selecting a database
• Once connected to a DBMS, we can
select a database.
mysql_select_db(databasename, resourceId);
• the resourceId is the one returned by mysql_connect()
• the function returns true if the selection succeeded; false,
otherwise.
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50. Example: Connect to a DBMS and
access database
<?php
$dbLocalhost = mysql_connect("localhost", "root", "")
or die("Could not connect: " . mysql_error());
mysql_select_db("glassesrus", $dbLocalhost)
or die("Could not find database: " . mysql_error());
echo "<h1>Connected To Database</h1>";
?>
• die() stops execution of script if the database connection
attempt failed.
• mysql_error() returns an error message from the previous
MYSQL operation.
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51. Reading from a database
• We can now send an SQL query to the
database to retrieve some data records.
resourceRecords = mysql_query(query, resourceId);
• the resourceId is the one returned by mysql_connect()
• the function returns a resource identifier to the returned data.
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52. Example: Connect to a DBMS,
access database, send query
<?php
$dbLocalhost = mysql_connect("localhost", "root", "")
or die("Could not connect: " . mysql_error());
mysql_select_db("glassesrus", $dbLocalhost)
or die("Could not find database: " . mysql_error());
$dbRecords = mysql_query("SELECT * FROM customers", $dbLocalhost)
or die("Problem reading table: " . mysql_error());
echo "<h1>Connected To Database</h1>";
?>
• the function will return a resource pointer (not the actual
data) to all the records that match the query.
• If all goes well, this script will output nothing on screen.http://www.allsoftsolutions.in
53. Extract contents of one record
• We can now extract the actual data from
the resource pointer returned by
mysql_query().
fieldData= mysql_result(resourceRecords, row, field);
• the resourceRecords is the one returned by mysql_query()
• field – database field to return
• the function returns the data stored in the field.
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54. Example: Connect to a DBMS,
access database, send query
<?php
$dbLocalhost = mysql_connect("localhost", "root", "")
or die("Could not connect: " . mysql_error());
mysql_select_db("glassesrus", $dbLocalhost)
or die("Could not find database: " . mysql_error());
$dbRecords = mysql_query("SELECT * FROM customers", $dbLocalhost)
or die("Problem reading table: " . mysql_error());
$strSurname = mysql_result($dbRecords, 0, "Surname");
echo "<p>$strSurname</p>";
?>
• the function will return a resource pointer (not the actual
data) to all the records that match the query.
• If all goes well, this script will output a surname on screen.
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55. SQL statement
SELECT * FROM customers
• Go and obtain from the database
• every field
• FROM the
• customers table
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56. Separating the database
connection
It is worth separating the database
connectivity from our scripts and placing
it in a separate file.
•It provides a convenient means of moving your scripts from
one database platform to another.
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57. Example: Separating the database
connection
<?php
// File: database2.php
$strLocation = "Home";
//$strLocation = "Work";
if ($strLocation == "Home") {
$dbLocalhost = mysql_connect("localhost", "root", "")
or die("Could not connect: " . mysql_error());
mysql_select_db("glassesrus", $dbLocalhost)
or die("Could not find database: " . mysql_error());
} else {
$dbLocalhost = mysql_connect("localhost", "username", "password")
or die("Could not connect: " . mysql_error());
mysql_select_db("anotherdatabase", $dbLocalhost)
or die("Could not find database: " . mysql_error());
}
?>
• $strLocation could be easily switched between ‘Home’ or ‘Work’http://www.allsoftsolutions.in
58. Viewing a whole record
To view the whole record returned from
mysql_query(), we need another
function...
• resourceRecords – resource identifier returned from
mysql_query().
• it returns an array containing the database record.
array = mysql_fetch_row(resourceRecords)
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59. Example: Displaying all customer
records
<?php
require_once("database2.php");
$dbRecords = mysql_query("SELECT * FROM customers", $dbLocalhost)
or die("Problem reading table: " . mysql_error());
while ($arrRecord = mysql_fetch_row($dbRecords)) {
echo "<p>" . $arrRecord[0] . " ";
echo $arrRecord[1] . " ";
echo $arrRecord[2] . " ";
echo $arrRecord[3] . "</p>";
}
?>
• The function returns false when the last record is returned; thus, stopping
the loop.
• Note, however, that the fields are referred to by using numbers – not very
easy to read and mistakes can be introduced.
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60. Limiting the records returned
SELECT Surname FROM customers
•Retrieves only the Surname field from the table customers
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61. Limiting the records returned
SELECT * FROM customers LIMIT 3,4
• Select a certain number of records form a table
• 3 is the starting row
• 4 is the number of records to be selected after the starting
row
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62. Searching for matching records
SELECT * FROM customers WHERE Title=‘Mr’
•The WHERE attribute specifies what to search for within the
database records.
• in this example, only records which have a title of ‘Mr’ will be
returned.
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63. Searching for matching records
SELECT * FROM customers WHERE Title=‘Mr’
OR Title=‘Mrs’
•The WHERE attribute specifies what to search for within the
database records.
• in this example, only records which have a title of ‘Mr’ or
‘Mrs’ will be returned.
• we can also use AND and OR to formulate more
sophisticated conditions.
•
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64. Searching for matching records
SELECT * FROM customers WHERE Title=‘Mr’
AND Surname=‘Smith’ OR Title=‘Mrs’
•The WHERE attribute specifies what to search for within the
database records.
• in this example, only records which have a surname of ‘Smith
and title of ‘Mr’ or the title of ‘Mrs’ will be returned.
• we can also use AND and OR to formulate more
sophisticated conditions.
•
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65. Sorting records
The ORDER BY attribute can be used to sort
the order in which records are obtained.
• the ORDER BY attribute is followed by the data field on
which to sort the record
• DESC or ASC – from high to low, or from low to high
SELECT * FROM cutomers ORDER BY Surname DESC
Example15-12.php
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68. Using records to read another table
Read a customer record, and then show the
products purchased by that customer.
Tables
• Customers
• Products
• Purchases
• PurchaseProducts
Example15-14.php
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69. Using records to read another table
Example15-14.php
...
$strSurname = "Jones";
$dbCustRecords = mysql_query("SELECT * FROM customers WHERE Surname = '$strSurname' ",...)
while ($arrCustRecords = mysql_fetch_array($dbCustRecords)) { //#1
$intId = $arrCustRecords["Id"];
//display customer’s details
$dbPurRecords = mysql_query("SELECT * FROM purchases WHERE customers_Id = '$intId'", ...)
while ($arrPurRecords = mysql_fetch_array($dbPurRecords)) {//#2
$intPurId = $arrPurRecords["Id"];
//display purchase date
$dbProRecords=mysql_query("SELECT * FROM purchaseProducts WHERE purchases_Id='$intPurId' ",..)
while ($arrProRecords = mysql_fetch_array($dbProRecords)) { //#3
$intProductId = $arrProRecords["products_Id"];
//display Quantity
$dbProductRecords = mysql_query("SELECT * FROM products WHERE Id = '$intProductId'",..)
$arrProductRecord = mysql_fetch_array($dbProductRecords);
//display product details
} #3
} #2
} //#1
BIRD’S EYEVIEW
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70. Using records to read another table
Example15-14.php
<?php
require_once("database2.php");
$strSurname = "Jones";
$dbCustRecords = mysql_query("SELECT * FROM customers WHERE Surname = '$strSurname'
", $dbLocalhost)
or die("Problem reading table: " . mysql_error());
while ($arrCustRecords = mysql_fetch_array($dbCustRecords)) {
$intId = $arrCustRecords["Id"];
echo "<p>Customer: ";
echo $arrCustRecords["Title"] . " ";
echo $arrCustRecords["Surname"] . " ";
echo $arrCustRecords["Firstname"] . "</p>";
$dbPurRecords = mysql_query("SELECT * FROM purchases WHERE customers_Id = '$intId'",
$dbLocalhost)
or die("Problem reading table: " . mysql_error());
Complete version
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71. Using records to read another table
Example15-14.php
while ($arrPurRecords = mysql_fetch_array($dbPurRecords)) {
$intPurId = $arrPurRecords["Id"];
echo "<p>Purchased On: ";
echo $arrPurRecords["Day"] . "/";
echo $arrPurRecords["Month"] . "/";
echo $arrPurRecords["Year"] . "</p>";
$dbProRecords= mysql_query("SELECT * FROM purchaseProducts WHERE purchases_Id='$intPurId' ",
$dbLocalhost)
or die("Problem reading table: " . mysql_error());
while ($arrProRecords = mysql_fetch_array($dbProRecords)) {
$intProductId = $arrProRecords["products_Id"];
echo "<p>" . $arrProRecords["Quantity"] . " ";
$dbProductRecords = mysql_query("SELECT * FROM products WHERE Id = '$intProductId'",
$dbLocalhost)
or die("Problem reading table: " . mysql_error());
$arrProductRecord = mysql_fetch_array($dbProductRecords);
echo $arrProductRecord["Name"] . " (" . $arrProductRecord["Description"] . ") at £";
echo $arrProRecords["Cost"] . " each.</p>";
}
}
}
?>
Example15-14.php
Complete version
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72. Inserting records
How to create new database records and insert
them into a table?
INSERT INTO table (field1, field2,...) VALUES (‘value1’, ‘value2’,...)
Example15-15.php
INSERT INTO table VALUES (‘value1’, ‘value2’,...)
•Alternatively, we have a simplified syntax:
$dbProdRecords = mysql_query("INSERT INTO products
VALUES ( ' ', 'Beer Mug', '600 ml Beer Mug', '100', '5.99')",
$dbLocalhost)
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74. Deleting records
How to delete database records from tables?
DELETE FROM table WHERE field=‘value’
Example15-16.php
e.g.
$dbCustRecords = mysql_query("DELETE FROM customers
WHERE Id='3'", $dbLocalhost)
Note: If you have a relational database, you should tidy-up the other tables, based on
their connection with the record you’ve deleted.
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75. Deleting records
How to delete database records from tables?
DELETE FROM table
Example15-17.php
This will delete all records from a table!
Note: back-up your database first!
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76. Amending records
How to modify the contents of an existing
database record?
UPDATE table SET field=‘value1’, field=‘value2’...WHERE
field=‘value’
Example15-18.php
• requires you to specify the table, the list of fields with their
updated values, and a condition for selection (WHERE).
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77. Amending records
Example15-14.php
<?php
// File: example15-18.php
require_once("database2.php");
$dbCustRecords = mysql_query("UPDATE products SET Description='250 ml Tall
Glass' WHERE Id='6'", $dbLocalhost)
or die("Problem updating table: " . mysql_error());
$dbProdRecords = mysql_query("SELECT * FROM products", $dbLocalhost)
or die("Problem reading table: " . mysql_error());
while ($arrProdRecords = mysql_fetch_array($dbProdRecords)) {
echo "<p>" . $arrProdRecords["Id"] . " ";
echo $arrProdRecords["Name"] . " ";
echo $arrProdRecords["Description"] . " ";
echo $arrProdRecords["Quantity"] . " ";
echo $arrProdRecords["Cost"] . "</p>";
}
?> Example15-18.php
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78. Amending records
How to modify the contents of an existing
database record?
$dbCustRecords = mysql_query("UPDATE products SET Name='Beer
and Lager Glass' WHERE Name='Beer Glass'", $dbLocalhost)
Example15-19.php
•A number of records will be updated in this example.
Another Example:
UPDATE table SET field=‘value1’, field=‘value2’...WHERE
field=‘value’
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79. Counting the number of records
How to count the number of records after
running a query?
$dbProdRecords = mysql_query("SELECT * FROM products",
$dbLocalhost)
or die("Problem reading table: " . mysql_error());
$intProductCount = mysql_num_rows($dbProdRecords);
Example15-20.php
• you can also use the same function to determine if a record
exists.
Example15-21.php
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80. Select a substring
How to count the number of records after
running a query?
SELECT * FROM products WHERE substring(Name,1,4)=‘Wine’
•This will return all records from the products table where the
first four characters in the name field equals ‘Wine’
Example15-22.php
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