VIEWs allow users to select subsets of data from one or more tables. A VIEW acts like a virtual table but contains no data itself - it just represents the result set of a SELECT statement. VIEWs provide a layer of security by restricting access to specific rows, columns, or tables. The CREATE VIEW statement is used to define a new VIEW, ALTER VIEW modifies an existing VIEW definition, and DROP VIEW removes a VIEW.
Running queries across multiple tables. This will involve the concept of joins—that is, how we join tables together.
Using joins to run queries over multiple tables, including:
Natural, inner, and cross joins
Straight joins
Left and right joins
Writing subqueries
Using SELECT statement options
Loginworks Softwares is a USA & INDIA based provider of data mining services organisations. Our data mining services utilise advanced statistical and multivariate techniques to identify areas of opportunity within your organization’s data. Loginworks is a software and services provider, with particular expertise in processing, analyzing, visualizing and sharing market research data. The Data Mining Group has the capability and experience to identify value-adding trends and relationships within your data. These provide you with greater insight and empower you to improve your strategies, affordable costs and boost revenue.
https://www.loginworks.com/data-mining/
Running queries across multiple tables. This will involve the concept of joins—that is, how we join tables together.
Using joins to run queries over multiple tables, including:
Natural, inner, and cross joins
Straight joins
Left and right joins
Writing subqueries
Using SELECT statement options
Loginworks Softwares is a USA & INDIA based provider of data mining services organisations. Our data mining services utilise advanced statistical and multivariate techniques to identify areas of opportunity within your organization’s data. Loginworks is a software and services provider, with particular expertise in processing, analyzing, visualizing and sharing market research data. The Data Mining Group has the capability and experience to identify value-adding trends and relationships within your data. These provide you with greater insight and empower you to improve your strategies, affordable costs and boost revenue.
https://www.loginworks.com/data-mining/
After completing this lesson, you should be able
to do the following:
Describe a view
Create, alter the definition of, and drop a view
Retrieve data through a view
Insert, update, and delete data througha view
Create and use an inline view
Perform “Top-N” analysis
http://phpexecutor.com
After completing this lesson, you should be able
to do the following:
Describe a view
Create, alter the definition of, and drop a view
Retrieve data through a view
Insert, update, and delete data througha view
Create and use an inline view
Perform “Top-N” analysis
http://phpexecutor.com
MariaDB 10.5 new features for troubleshooting (mariadb server fest 2020)Valeriy Kravchuk
The recently released MariaDB 10.5 GA includes many new, useful features, but I’d like to concentrate on those helping DBAs and support engineers to find out what’s going on when a problem occurs.
Specifically I present and discuss the Performance Schema updates to match MySQL 5.7 instrumentation, new tables in the INFORMATION_SCHEMA to monitor the internals of a generic thread pool and improvements of ANALYZE for statements.
MySQL 8 -- A new beginning : Sunshine PHP/PHP UK (updated)Dave Stokes
MySQL 8 has many new features and this presentation covers the new data dictionary, improved JSON functions, roles, histograms, and much more. Updated after SunshinePHP 2018 after feedback
Modern query optimisation features in MySQL 8.Mydbops
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Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
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LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
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.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
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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.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
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Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
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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.
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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:
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.
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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…
2. •
•
•
•
•
•
•
•
VIEW is a virtual table, which acts like a table but actually it contains no data. That
is based on the result set of a SELECT statement. A VIEW consists rows and
columns from one or more than one tables. A VIEW is a query that?s stored as an
object. A VIEW is nothing more than a way to select a subset of table?s columns.
When you defined a view then you can reference it like any other table in a
database. A VIEW provides as a security mechanism also. VIEWS ensures that users
are able to modify and retrieve only that data which seen by them.
By using Views you can ensure about the security of data by restricting access to
the following data:
Specific columns of the tables.
Specific rows of the tables.
Specific rows and columns of the tables.
Subsets of another view or a subset of views and tables
Rows fetched by using joins.
Statistical summary of data in a given tables.
3. CREATE VIEW Statement
•
•
•
•
•
•
•
CREATE VIEW Statement is used to create a new database view. The general
syntax of CREATE VIEW Statement is:
CREATE VIEW view_name [(column_list)] [WITH ENCRYPTION] AS
select_statement [WITH CHECK OPTION]
View_name specifies the name for the new view.
column_list specifies the name of the columns to be used in view.
column_list must have the same number of columns that specified in
select_statement. If column_list option is not available then view is created
with the same columns that specified in select_statement.
WITH ENCRYPTION option encrypts the text to the view in the syscomments
table.
AS option specifies the action that is performed by the view.
select_statement is used to specify the SELECT statement that defines a view.
The optional WITH CHECK OPTION clause applies to the data modification
statement like INSERT and UPDATE statements to fulfill the criteria given in the
select_statement defining the view. This option also ensures that the data can
visible after the modifications are made permanent.
4. Rules for views
• A view can be created only in the current database.
• The view name must follow the rules for identifiers and
• The view name must not be the same as that of the base
table
• A view can be created only that time if there is a SELECT
permission on its base table.
• A SELECT INTO statement cannot be used in view
declaration statement.
• A trigger or an index cannot be defined on a view.
• The CREATE VIEW statement cannot be combined with
other SQL statements in a single batch.
5. •
•
•
Example :
In the following example we have two table Client and Products. And if you want to see only those
client records that are active in Products table also means right now they are supplying us the
products. For this we are creating the view by the name of Supp_Client.
mysql> SELECT * FROM Client; +------+---------------+----------+ | C_ID | Name | City | +------+--------------+----------+ | 1 | A K Ltd | Delhi | | 2 | V K Associate | Mumbai | | 3 | R K India | Banglore | | 4 | R
S P Ltd | Kolkata | | 5 | A T Ltd | Delhi | | 6 | D T Info | Delhi | +------+---------------+----------+ 6 rows
in set (0.00 sec) mysql> SELECT * FROM Products; +---------+-------------+------+ | Prod_ID |
Prod_Detail | C_ID | +---------+-------------+------+ | 111 | Monitor | 1 | | 112 | Processor | 2 | | 113 |
Keyboard | 2 | | 114 | Mouse | 3 | | 115 | CPU | 5 | +---------+-------------+------+ 5 rows in set (0.00
sec)
Example : Create View Statement
mysql> CREATE VIEW Supp_Client AS -> SELECT * FROM Client -> WHERE C_ID IN ( -> SELECT
C_ID FROM Products) -> WITH CHECK OPTION; Query OK, 0 rows affected (0.05 sec) mysql>
SELECT * FROM Supp_Client; +------+---------------+----------+ | C_ID | Name | City | +------+--------------+----------+ | 1 | A K Ltd | Delhi | | 2 | V K Associate | Mumbai | | 3 | R K India | Banglore | | 5 | A
T Ltd | Delhi | +------+---------------+----------+ 4 rows in set (0.03 sec) In the following example we
include the WHERE clause with the select statement of view. Then MySQL adds this condition to
the VIEW definition when executing the statement for further restricting the result. Example :
mysql> SELECT * FROM Supp_Client WHERE City='Delhi'; +------+---------+-------+ | C_ID | Name |
City | +------+---------+-------+ | 1 | A K Ltd | Delhi | | 5 | A T Ltd | Delhi | +------+---------+-------+ 2
rows in set (0.04 sec)
6. ALTER VIEW Statement
•
•
•
•
By the ALTER VIEW Statement we can change the definition of a view. This
statement is useful to modify a view without dropping it. ALTER VIEW statement
syntax is similar to CREATE VIEW Statement and effect is same as the CREATE OR
REPLACE VIEW. The general syntax of ALTER VIEW Statement is :
ALTER VIEW view_name [(column_list)] [WITH ENCRYPTION] AS
select_statement [WITH CHECK OPTION]
In the following example we are altering the view definition that we have created
above. In this we add one more column by the name of Prod_Detail of Products
table. Example of Altering the View Statement :
mysql> ALTER VIEW Supp_Client AS -> SELECT
Client.C_ID, Client.Name, Client.City, -> Products.Prod_Detail from
Client, Products -> WHERE Client.C_ID=Products.C_ID; Query OK, 0 rows affected
(0.01 sec)
mysql> SELECT * FROM Supp_Client; +------+---------------+----------+-------------+ |
C_ID | Name | City | Prod_Detail | +------+---------------+----------+-------------+ | 1 | A
K Ltd | Delhi | Monitor | | 2 | V K Associate | Mumbai | Processor | | 2 | V K
Associate | Mumbai | Keyboard | | 3 | R K India | Banglore | Mouse | | 5 | A T Ltd
| Delhi | CPU | +------+---------------+----------+-------------+ 5 rows in set (0.02 sec)
7. DROP VIEW Statement
• For dropping a view you can use the DROP VIEW
Statement. When view is dropped but it has no
effect on the underlying tables. After dropping a
view if you issue any query that reference a
dropped view then you get an error message. But
dropping a table that reference any view does not
drop the view automatically you have to dropt
the view explicitly. The general syntax of DROP
VIEW Statement is :
8. • DROP VIEW view_name;
• In the following example we are dropping the
view that we have created above. Example of
Dropping the View Statement :
• mysql> DROP VIEW Supp_Client; Query OK, 0
rows affected (0.00 sec) mysql> SELECT *
FROM Supp_Client; ERROR 1146 (42S02):
Table 'employee.supp_client' doesn't exist