Introduction to the Standard Query Language (SQL) to access data in relational databases. More information can be found at https://www.spiraltrain.nl/course-sql-fundamentals/?lang=en
When Web-based business applications communicate with each other, producer applications ENQUEUE messages and consumer applications DEQUEUE messages. Advanced Queuing provides database-integrated message queuing functionality. Advanced Queuing leverages the functions of the Oracle database so that messages can be stored persistently, propagated between queues on different machines and databases, and transmitted using Oracle Net Services, HTTP(S), and SMTP.
***First Half***
Introduction to Oracle Fusion Middleware and Oracle ADF
Getting started with JDeveloper
Building a Business Model with ADF Business Components
Querying and persisting data
Exposing Data
Declaratively Customizing Data Services
Programmatically Customizing Data Services
Validating User Inputs
***Second Half***
Understanding UI Technology
Binding UI Components to Data
Planning the User Interface
Passing values between UI Elements
Responding to Application Events
Implementing Transactional Capabilities
When Web-based business applications communicate with each other, producer applications ENQUEUE messages and consumer applications DEQUEUE messages. Advanced Queuing provides database-integrated message queuing functionality. Advanced Queuing leverages the functions of the Oracle database so that messages can be stored persistently, propagated between queues on different machines and databases, and transmitted using Oracle Net Services, HTTP(S), and SMTP.
***First Half***
Introduction to Oracle Fusion Middleware and Oracle ADF
Getting started with JDeveloper
Building a Business Model with ADF Business Components
Querying and persisting data
Exposing Data
Declaratively Customizing Data Services
Programmatically Customizing Data Services
Validating User Inputs
***Second Half***
Understanding UI Technology
Binding UI Components to Data
Planning the User Interface
Passing values between UI Elements
Responding to Application Events
Implementing Transactional Capabilities
Constraints are the rules enforced on the data columns of a table. These are used to limit the type of data that can go into a table. This ensures the accuracy and reliability of the data in the database.
Constraints can be divided into following two types:
Column level constraints : limits only column data
Table level constraints : limits whole table data
Aggregate Functions
Database such as MySQL and SQL server are an integral part of business, hospital, banks and universities. Immensely, Every person who have of access computer or technology eventually work on to store data.
This chapter covers the following:
- What is SQL
- Categories of SQL statements
- History of SQL
- Relational Database Structure
- MySQL Setup for practice
- SQL Basics (Lexical elements, Data types, Literals)
Oracle 11g developer on linux training in bangaloreSuvash Chowdary
Oracle 11g Developer on linux training in Bangalore
Duration: 30 - 35 daystraining classes
Location: Courses are run in our Bangalore offices
Timings & Schedules: Both on Weekdays / Weekends
Pre-Requisite: Graduate/Software Developer/Any
Extras: Interview Questions & Answers will be covered along with course
LAB Facility: The Training is designed tentatively for each batch with Hands on Experience exposures in the Lab session. The Lab sessions are followed along with the Theory in the respective day itself.
Certification: Industry Expertise trainers will guide students to get Oracle Certification in a Latest Version & DUMPS will be provided at free of cost.
Contact : 9008500244
An SQL JOIN clause combines columns from one or more tables in a relational database. It creates a set that can be saved as a table or used as it is. A JOIN is a means for combining columns from one (self-table) or more tables by using values common to each.
Waiting too long for Excel's VLOOKUP? Use SQLite for simple data analysis!Amanda Lam
** This workshop was conducted in the Hong Kong Open Source Conference 2017 **
Excel formulas can be quite slow when you're processing data files with thousands of rows. It's also especially difficult to maintain the files when you have some messy mixture of VLOOKUPs, Pivot Tables, Macros and VBAs.
In this interactive workshop targeted for non-coders, we will make use of SQLite, a very lightweight and portable open source database library, to perform some simple and repeatable data analysis on large datasets that are publicly available. We will also explore what you can further do with the data by using some powerful extensions of SQLite.
While SQLite may not totally replace Excel in many ways, after the workshop you will find that it can improve your work efficiency and make your life much easier in so many use cases!
Who should attend this workshop?
- If you're frustrated with the slow performance of Excel formulas when dealing with large datasets in your daily work
- No coding experience is required
Consists of the explanations of the basics of SQL and commands of SQL.Helpful for II PU NCERT students and also degree studeents to understand some basic things.
Constraints are the rules enforced on the data columns of a table. These are used to limit the type of data that can go into a table. This ensures the accuracy and reliability of the data in the database.
Constraints can be divided into following two types:
Column level constraints : limits only column data
Table level constraints : limits whole table data
Aggregate Functions
Database such as MySQL and SQL server are an integral part of business, hospital, banks and universities. Immensely, Every person who have of access computer or technology eventually work on to store data.
This chapter covers the following:
- What is SQL
- Categories of SQL statements
- History of SQL
- Relational Database Structure
- MySQL Setup for practice
- SQL Basics (Lexical elements, Data types, Literals)
Oracle 11g developer on linux training in bangaloreSuvash Chowdary
Oracle 11g Developer on linux training in Bangalore
Duration: 30 - 35 daystraining classes
Location: Courses are run in our Bangalore offices
Timings & Schedules: Both on Weekdays / Weekends
Pre-Requisite: Graduate/Software Developer/Any
Extras: Interview Questions & Answers will be covered along with course
LAB Facility: The Training is designed tentatively for each batch with Hands on Experience exposures in the Lab session. The Lab sessions are followed along with the Theory in the respective day itself.
Certification: Industry Expertise trainers will guide students to get Oracle Certification in a Latest Version & DUMPS will be provided at free of cost.
Contact : 9008500244
An SQL JOIN clause combines columns from one or more tables in a relational database. It creates a set that can be saved as a table or used as it is. A JOIN is a means for combining columns from one (self-table) or more tables by using values common to each.
Waiting too long for Excel's VLOOKUP? Use SQLite for simple data analysis!Amanda Lam
** This workshop was conducted in the Hong Kong Open Source Conference 2017 **
Excel formulas can be quite slow when you're processing data files with thousands of rows. It's also especially difficult to maintain the files when you have some messy mixture of VLOOKUPs, Pivot Tables, Macros and VBAs.
In this interactive workshop targeted for non-coders, we will make use of SQLite, a very lightweight and portable open source database library, to perform some simple and repeatable data analysis on large datasets that are publicly available. We will also explore what you can further do with the data by using some powerful extensions of SQLite.
While SQLite may not totally replace Excel in many ways, after the workshop you will find that it can improve your work efficiency and make your life much easier in so many use cases!
Who should attend this workshop?
- If you're frustrated with the slow performance of Excel formulas when dealing with large datasets in your daily work
- No coding experience is required
Consists of the explanations of the basics of SQL and commands of SQL.Helpful for II PU NCERT students and also degree studeents to understand some basic things.
Is SQLcl the Next Generation of SQL*Plus?Zohar Elkayam
Session from ILOUG I presented in May, 2016
Introducing the new tool from the developers of SQL Developer: SQLcl – a new command line tool from the SQL Developer team that might replace SQL*Plus and all of its functions which has been around for over 30 years!
In this session, we will explore the new functionality of the SQLcl, and use a live demonstration to show what SQLcl has to offer over the old SQL*Plus. We will use real life example to see what makes this tool such a time saver in day-to-day tasks for DBAs and developers who prefer using the command line interface.
SQL Server site utilization
Talk about “A5:SQL Mk-2”
* SQL development tools commonly used in SQL Server
* What is "A5:SQL Mk-2"?
* Features
* Demo
* Conclusion
Introduction in the JavaScript Programming language typically used in the front end of Web Applications. More information can be found at : https://www.spiraltrain.nl/course-javascript-programming/?lang=en
Overview of Spring Boot for the rapid development of Java Applications and Microservices. More information can be found at : https://www.spiraltrain.nl/course-spring-boot-development/?lang=en
Introduction to the component based Wicket Framework which is used to create Java Web Applications. More information can be found at : https://www.spiraltrain.nl/course-wicket-programming/?lang=en
Introduction to Data Analysis with R and the R programming language. More information can be found at https://www.spiraltrain.nl/course-data-analysis-with-r/?lang=en
Introduction to the Administration of the Apache Web Server. More information can be found at https://www.spiraltrain.nl/course-apache-administration/?lang=en
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
3. www.spiraltrain.nl
What is SQL?
• Abbreviation of Structured Query Language :
• Standard language to access relational database management systems (RDBMS)
• Actually three languages can be distinguished
• Declarative query language with procedural elements :
• Used to create database schemas and to insert, update, delete and query data
• Data Definition Language (DDL) :
• Language that defines database structure (relation schemas)
• This includes creating, altering, and dropping tables and establishing constraints
• Data Manipulation Language (DML) :
• Query language to create, read, update and delete tuples (CRUD operations)
• Data Control Language (DCL) :
• Used to controls a database includes administering privileges and committing data
• SQL language further deals with the following issues :
• Transaction control , integrity constraints, views, embedded SQL and dynamic SQL
3SQL Intro
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History of SQL
• SQL started with name SEQUEL in the 1970's :
• Abbreviation of structured english query language
• Developed by Raymond F. Boyce and Donald D. Chamberlin
• Access data stored in IBM's System R relational database
• In 1979 Oracle introduced first commercial version of SQL :
• Oracle V2 (Version2) for VAX computers.
• In 1986 SQL first became an ANSI standard :
• SQL-89 known as SQL 1 was rather incomplete
• SQL-92 is known as first solid standard known as SQL 2
• SQL-99 known as SQL 3 :
— Recursive queries, triggers, object-oriented features
• SQL-2003 :
— Window functions, XML-related features
• SQL-2006 offers XML Query Language (XQuery) support
• SQL-2011 has improved support for temporal databases
SQL Intro 4
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SQL Standard
• SQL is standard but is not completely portable among RDBMS :
• This is caused by ambiguities and vendor extensions
• Specific SQL implementation by database vendor is SQL dialect
• Vendors implement parts of the SQL standard, e.g. most implement SQL-92
• Vendors add their vendor-specific extensions
• Most vendors conform to a set of Core SQL features :
• Portability might still be limited due to missing or additional features
• Purpose of SQL-92 and SQL-99 Standards :
• Specify syntax/semantics for data definition and manipulation
• Define data structures
• Enable portability
• Specify minimal (level 1) and complete (level 2) standards
• Allow for later growth/enhancement to standard
5SQL Intro
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SQL Environment
• Catalog :
• A set of schemas that constitute the description of a database
• Schema :
• Structure containing descriptions of objects created by a user
• This includes base tables, views, constraints
SQL Intro 7
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Database Creation
• Creating of database differs for different relational databases :
• Often done through a GUI interface particular for a database
• According to the SQL standard :
• SQL environment contains one or more catalogues :
• Each catalogue manages various metadata :
• Set of schemas consisting of :
— Relations/tables
— Views
— Assertions
— Indexes
• Users and user groups
• Many database use client-server model :
• You must connect to a remote host on certain port, log in and manage database
• SQLite database does not use this model, databases are files
8SQL Intro
Demo01
Create Database
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DDL Create Table
• Relational databases contain data in tables :
• Uniquely identified by their names and are comprised of columns and rows
• Columns contain the column name, data type, and other attributes
• Rows contain the records or data for the columns
• Tables are created through CREATE TABLE statement of SQL DDL :
CREATE TABLE inventory (
StockNumber INTEGER PRIMARY KEY,
Descrip VARCHAR(50),
OnHandQuan INTEGER,
PackQty INTEGER,
PackCost FLOAT
);
• Typically columns are created of certain data type
9SQL Intro
Demo02
DDL Create Table
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SQL Data Types
• Columns in a table are of certain data type :
• Often used data types are character strings, numbers and date types
• Character String types :
• CHAR(n) – fixed-length character data, n characters long bytes
• VARCHAR(n) – variable length character data
• LONG – variable-length character data
• Numeric types :
• NUMBER(p,q) – general purpose numeric data type
• INTEGER(p) – signed integer, p digits wide
• INTEGER - signed integer
• FLOAT(p) – floating point in scientific notation with p binary digits precision
• FLOAT – floating point in scientific notation
• Date/time type :
• DATE – fixed-length date/time in dd-mm-yy form
10SQL Intro
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SQL Language Elements
• Clauses :
• Constituent components of statements and queries, in some cases optional
• Expressions :
• Can produce either scalar values, or tables consisting of columns and rows of data
• Predicates :
• Specify conditions that can be evaluated to true, false or unknown) values
• Used to limit the effects of statements and queries or to change program flow
• Queries :
• Retrieve the data based on specific criteria
• Statements :
• May have a persistent effect on schemata and data
• May control transactions, program flow, connections, sessions or diagnostics
• SQL statements also include the semicolon (";") statement terminator
• Insignificant whitespace is generally ignored :
• Makes it easier to format SQL code for readability
11SQL Intro
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DML Insert Into
• Database table is filled with SQL INSERT INTO statements :
INSERT INTO inventory(StockNumber,Descrip,OnHandQuan,PackQty,PackCost)
VALUES (51002,'AA Dry Cells 4 Pack',173,12,9.00);
INSERT INTO inventory(StockNumber,Descrip,OnHandQuan,PackQty,PackCost)
VALUES (51004,'AA Dry Cells 8 Pack',5,12,16.80);
INSERT INTO inventory(StockNumber,Descrip,OnHandQuan,PackQty,PackCost)
VALUES (43512,'10W-30 Motor Oil, Quart',36,12,18.20);
INSERT INTO inventory(StockNumber,Descrip,OnHandQuan,PackQty,PackCost)
VALUES (51013,'D Dry Cells 8 Pack',19,12,90.20);
INSERT INTO inventory(StockNumber,Descrip,OnHandQuan,PackQty,PackCost)
VALUES (23155,'Shovel Pointed Long Handle',1500,1,9.82);
INSERT INTO inventory(StockNumber,Descrip,OnHandQuan,PackQty,PackCost)
VALUES (51001,'AAA Dry Cells 4 Pack ',92,12,9.00);
INSERT INTO inventory(StockNumber,Descrip,OnHandQuan,PackQty,PackCost)
VALUES (43111,'White Gas Gallon Can',14,4,14.75);
• Values listed in INSERT INTO statement :
• Must be in the same order as appearing in CREATE TABLE
• Character strings are surrounded with quotes, number not
12SQL Intro
Demo03
DML Insert Values
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SQL Errors
• SQL State Error Codes are defined by ISO/ANSI SQL Standards :
• 5-character string consisting of 2-characters followed by 3-character subclass value
• "00" indicates success, "01" indicates a warning
• Other class values normally indicate an exception
• Example Error Code :
• SQL0208 - ORDER BY column not in result table
• Typical error is duplicate primary key error :
• Trying to insert row with key already present
13SQL Intro
Demo04
Duplicate Key Error
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Select Query
• SELECT clause is used to retrieve data from database tables :
SELECT StockNumber,Descrip,OnHandQuan,PackQty,PackCost from inventory
• SELECT is followed by column names separated by comma’s
• Alternatively wild cards may be used to retrieve all columns :
SELECT * FROM inventory;
• SELECT can be combined with clauses WHERE, ORDER_BY etc.
14SQL Intro
Demo05
Select Query