The eBITUG 2017 presentation that provides and overview of DBaaS capabilities delivered by NonStop SQL/MX. It also shows how DBS simplifies provision of databases and facilitates automation. It supports virtualized as well as regular NonStop X86-based systems.
Understanding NonStop SQLMX SDA and its impact on performanceFrans Jongma
This paper describes how the Session Data Area (SDA) is used and how its configuration affects performance. The
area is reserved on a session basis and query fragments of a session can only be reused by the same session. It differs in this from the database data cache in DP2, which is shared by all
clients. Because the area is a shared resource and the amount of data is limited, it is advised to track its usage and where possible, adjust the size of the area to the amount of sessions.
NonStop SQL/MX DBS demo with iTP WebserverFrans Jongma
This is a step-by-step overview of NonStop SQL/MX Database Services can be used to quickly provision a database and some additional functions. The demo was created using a few very simple HTML pages that invoke the DBS interface.
Many customers of NonStop SQL/MP are using the SQL/MX engine to access the data that is stored in SQL/MP tables. They enjoy the features of ANSI DML and use the JDBC drivers in Java programs and ODBC drivers for off-platform applications written in other languages.
This document summarizes the advantages of using the NonStop SQL/MX native tables. It is intended for architects, designers, developers of applications written for or being ported to NonStop Servers as well as database administrators (DBAs) that manage SQL/MP or SQL/MX databases.
A user guide that introduces a new User Interface to HPE NonStop SQL/MX DBS.
SQL/MX DBS is a solution that provides a multi-tenant database environment where the databases are isolated from each other while still sharing common resources such as compute power, storage, and network capacity. However, while the databases share the storage, each database uses dedicated, unshared, devices which prevents them from encountering database bottlenecks such as database cache and lock-space. Cache and lock space are part of the NonStop SQL Data Access Managers which are dedicated to only one database and not shared with others.
Understanding NonStop SQLMX SDA and its impact on performanceFrans Jongma
This paper describes how the Session Data Area (SDA) is used and how its configuration affects performance. The
area is reserved on a session basis and query fragments of a session can only be reused by the same session. It differs in this from the database data cache in DP2, which is shared by all
clients. Because the area is a shared resource and the amount of data is limited, it is advised to track its usage and where possible, adjust the size of the area to the amount of sessions.
NonStop SQL/MX DBS demo with iTP WebserverFrans Jongma
This is a step-by-step overview of NonStop SQL/MX Database Services can be used to quickly provision a database and some additional functions. The demo was created using a few very simple HTML pages that invoke the DBS interface.
Many customers of NonStop SQL/MP are using the SQL/MX engine to access the data that is stored in SQL/MP tables. They enjoy the features of ANSI DML and use the JDBC drivers in Java programs and ODBC drivers for off-platform applications written in other languages.
This document summarizes the advantages of using the NonStop SQL/MX native tables. It is intended for architects, designers, developers of applications written for or being ported to NonStop Servers as well as database administrators (DBAs) that manage SQL/MP or SQL/MX databases.
A user guide that introduces a new User Interface to HPE NonStop SQL/MX DBS.
SQL/MX DBS is a solution that provides a multi-tenant database environment where the databases are isolated from each other while still sharing common resources such as compute power, storage, and network capacity. However, while the databases share the storage, each database uses dedicated, unshared, devices which prevents them from encountering database bottlenecks such as database cache and lock-space. Cache and lock space are part of the NonStop SQL Data Access Managers which are dedicated to only one database and not shared with others.
Concepts of NonStop SQL/MX: Part 3 - Introduction to MetadataFrans Jongma
Series of articles written for DBA’s and developers who know Oracle and want to learn about NonStop SQL/MX. Useful for people who know NonStop, and would like to know about similarities and differences between the two products.
a striped down Version of a presentation about oracle architecture. Goal was a basic understanding and foundation about some components of Oracle, so subsequent discussions should be easier
Compare the capabilities of the Microsoft Access, Microsoft SQL Serv.pdfarihantplastictanksh
Compare the capabilities of the Microsoft Access, Microsoft SQL Server, Oracle’s MySQL, and
Oracle relational database management systems (RDBMSs). Your paper should discuss the
processing speeds, data storage capabilities, maximum users supported, platforms supported,
user interfaces, development tools, vendor support, and cost. Discuss and cite at least two
references in addition to our textbook. Your paper should be 3-5 pages in length (excluding title
and References pages)
Solution
Microsoft Access
Overview:
Microsoft Access is a part of Microsoft Office,
it is commercially available database in the market
Inexpensive/standard on most computers
users can create complex databases
database professionalas can use construct a database
customers of MS-Access:
It is mainly used in small corporate companies or IT Sectors with 1-80 endusers.
Features of MS-Access:
1.It is having GUI Interface for creating databases
2. A databae contains tables, forms, reports, queries, macros.
3. It facilitates autocontent wizards to build tables or forms or reports.
4. It acts as an interface to other DBMS using ODBC
5. It is used for small business companies
6. Provides security like password protection
7. Provides a Data dictionary
8. We can repair the database
9. We can create different views
10. External data can be imported into Access
11. We can create web pages based using the database
12. It has as built in Macro functions
13. It uses Structurered Query Language
14. We can create forms, reports etc by using Visual Basic Application programming
15. Provides Add in controls like calendars
16. It can merged into word and analysed with Excel etc.
Issues:
Security:
User level security is very difficult
Tuning:
It does not have the ability to split over multiple Hard Drives, multiple CPUs or to place tables
into memory.
Locking:
Basic handling of concurrent users Backup and recovery at basic level.
ANSI SQL standard often doesn\'t work,MS-Access has it\'s own modified version of ANSI
SQL.
MySQL
Overview
MySQL is a database engine. It has a command line interface that allows the creation of
database. It Requires Front-end applications to access it for end users. EX:- C#, PHP, Microsoft
ASP.Net.
Typical users
Small companies or workgroups, through to very large Internet databases with large numbers of
users
Ex:wikipedia,Moodle.
Features
1. Speed:One of the fastest databases available
2. Ease of use: when compared to larger databases such as Oracle Uses standard SQL
3. Capability: A multi-threaded server allowing many clients to connect at the same time Fully
networked for the Internet with built in security
4.Portability: Runs on a many operating systems and different hardware
5. Small size: when compared to other large databases e.g. Oracle
6. Availabliity and Cost: Open Source ,Free in most situations to use
7. Open distribution and source code: You can check how it works – if you have the knowledge.
8. interface to other DBMS’s using Open Database Connectivit.
Change Data Capture to Data Lakes Using Apache Pulsar and Apache Hudi - Pulsa...StreamNative
Apache Hudi is an open data lake platform, designed around the streaming data model. At its core, Hudi provides a transactions, upserts, deletes on data lake storage, while also enabling CDC capabilities. Hudi also provides a coherent set of table services, which can clean, compact, cluster and optimize storage layout for better query performance. Finally, Hudi's data services provide out-of-box support for streaming data from event systems into lake storage in near real-time.
In this talk, we will walk through an end-end use case for change data capture from a relational database, starting with capture changes using the Pulsar CDC connector and then demonstrate how you can use the Hudi deltastreamer tool to then apply these changes into a table on the data lake. We will discuss various tips to operationalizing and monitoring such pipelines. We will conclude with some guidance on future integrations between the two projects including a native Hudi/Pulsar connector and Hudi tiered storage.
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
Data Analytics Meetup: Introduction to Azure Data Lake Storage CCG
Microsoft Azure Data Lake Storage is designed to enable operational and exploratory analytics through a hyper-scale repository. Journey through Azure Data Lake Storage Gen1 with Microsoft Data Platform Specialist, Audrey Hammonds. In this video she explains the fundamentals to Gen 1 and Gen 2, walks us through how to provision a Data Lake, and gives tips to avoid turning your Data Lake into a swamp.
Learn more about Data Lakes with our blog - Data Lakes: Data Agility is Here Now https://bit.ly/2NUX1H6
Solutions for bi-directional integration between Oracle RDBMS & Apache KafkaGuido Schmutz
Apache Kafka is a popular distributed streaming data platform and more and more is the architectural backbone for integrating streaming data with a Data Lake, Microservices and Stream Processing. A lot of data necessary in stream processing is stored in traditional systems backed by relational databases. This session will present different approaches for integrating relational databases with Kafka, such as Kafka Connect, Oracle GoldenGate, ORDS APIs and bridging Kafka with Oracle AQ.
Concepts of NonStop SQL/MX: Part 3 - Introduction to MetadataFrans Jongma
Series of articles written for DBA’s and developers who know Oracle and want to learn about NonStop SQL/MX. Useful for people who know NonStop, and would like to know about similarities and differences between the two products.
a striped down Version of a presentation about oracle architecture. Goal was a basic understanding and foundation about some components of Oracle, so subsequent discussions should be easier
Compare the capabilities of the Microsoft Access, Microsoft SQL Serv.pdfarihantplastictanksh
Compare the capabilities of the Microsoft Access, Microsoft SQL Server, Oracle’s MySQL, and
Oracle relational database management systems (RDBMSs). Your paper should discuss the
processing speeds, data storage capabilities, maximum users supported, platforms supported,
user interfaces, development tools, vendor support, and cost. Discuss and cite at least two
references in addition to our textbook. Your paper should be 3-5 pages in length (excluding title
and References pages)
Solution
Microsoft Access
Overview:
Microsoft Access is a part of Microsoft Office,
it is commercially available database in the market
Inexpensive/standard on most computers
users can create complex databases
database professionalas can use construct a database
customers of MS-Access:
It is mainly used in small corporate companies or IT Sectors with 1-80 endusers.
Features of MS-Access:
1.It is having GUI Interface for creating databases
2. A databae contains tables, forms, reports, queries, macros.
3. It facilitates autocontent wizards to build tables or forms or reports.
4. It acts as an interface to other DBMS using ODBC
5. It is used for small business companies
6. Provides security like password protection
7. Provides a Data dictionary
8. We can repair the database
9. We can create different views
10. External data can be imported into Access
11. We can create web pages based using the database
12. It has as built in Macro functions
13. It uses Structurered Query Language
14. We can create forms, reports etc by using Visual Basic Application programming
15. Provides Add in controls like calendars
16. It can merged into word and analysed with Excel etc.
Issues:
Security:
User level security is very difficult
Tuning:
It does not have the ability to split over multiple Hard Drives, multiple CPUs or to place tables
into memory.
Locking:
Basic handling of concurrent users Backup and recovery at basic level.
ANSI SQL standard often doesn\'t work,MS-Access has it\'s own modified version of ANSI
SQL.
MySQL
Overview
MySQL is a database engine. It has a command line interface that allows the creation of
database. It Requires Front-end applications to access it for end users. EX:- C#, PHP, Microsoft
ASP.Net.
Typical users
Small companies or workgroups, through to very large Internet databases with large numbers of
users
Ex:wikipedia,Moodle.
Features
1. Speed:One of the fastest databases available
2. Ease of use: when compared to larger databases such as Oracle Uses standard SQL
3. Capability: A multi-threaded server allowing many clients to connect at the same time Fully
networked for the Internet with built in security
4.Portability: Runs on a many operating systems and different hardware
5. Small size: when compared to other large databases e.g. Oracle
6. Availabliity and Cost: Open Source ,Free in most situations to use
7. Open distribution and source code: You can check how it works – if you have the knowledge.
8. interface to other DBMS’s using Open Database Connectivit.
Change Data Capture to Data Lakes Using Apache Pulsar and Apache Hudi - Pulsa...StreamNative
Apache Hudi is an open data lake platform, designed around the streaming data model. At its core, Hudi provides a transactions, upserts, deletes on data lake storage, while also enabling CDC capabilities. Hudi also provides a coherent set of table services, which can clean, compact, cluster and optimize storage layout for better query performance. Finally, Hudi's data services provide out-of-box support for streaming data from event systems into lake storage in near real-time.
In this talk, we will walk through an end-end use case for change data capture from a relational database, starting with capture changes using the Pulsar CDC connector and then demonstrate how you can use the Hudi deltastreamer tool to then apply these changes into a table on the data lake. We will discuss various tips to operationalizing and monitoring such pipelines. We will conclude with some guidance on future integrations between the two projects including a native Hudi/Pulsar connector and Hudi tiered storage.
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
Data Analytics Meetup: Introduction to Azure Data Lake Storage CCG
Microsoft Azure Data Lake Storage is designed to enable operational and exploratory analytics through a hyper-scale repository. Journey through Azure Data Lake Storage Gen1 with Microsoft Data Platform Specialist, Audrey Hammonds. In this video she explains the fundamentals to Gen 1 and Gen 2, walks us through how to provision a Data Lake, and gives tips to avoid turning your Data Lake into a swamp.
Learn more about Data Lakes with our blog - Data Lakes: Data Agility is Here Now https://bit.ly/2NUX1H6
Solutions for bi-directional integration between Oracle RDBMS & Apache KafkaGuido Schmutz
Apache Kafka is a popular distributed streaming data platform and more and more is the architectural backbone for integrating streaming data with a Data Lake, Microservices and Stream Processing. A lot of data necessary in stream processing is stored in traditional systems backed by relational databases. This session will present different approaches for integrating relational databases with Kafka, such as Kafka Connect, Oracle GoldenGate, ORDS APIs and bridging Kafka with Oracle AQ.
The event, held on 11th December 2018, was a technical presentation about running MS SQL Server 2017 on Linux. We started off by using containers and proceeded in looking at High Availability and Data Protection, more specifically:
- Supported features & Linux differences
- Installing SQL Server on a Linux Container
- Accessing SMB 3.0 shared storage using Samba
- Setting up a Fail over Cluster using Pacemaker
- Setting up AlwaysOn Availability Groups using Pacemaker
- Authenticating to SQL Server using AD Authentication
- Setting up Read-Scale Cross-Platform Availability Groups
https://techspark.mt/sql-server-on-linux-11th-december-2018/
Rod Anderson
For the small business support person being able to provide PostgreSQL hosting for a small set of specific applications without having to build and support several Pg installations is necessary. By building a multi-tenant Pg cluster with one tenant per database and each application in it's own schema maintenance and support is much simpler. The issues that present themselves are how to provide and control dba and user access to the database and get the applications into their own schema. With this comes need to make logging in to the database (pg_hba.conf) as non-complex as possible.
Les mégadonnées représentent un vrai enjeu à la fois technique, business et de société
: l'exploitation des données massives ouvre des possibilités de transformation radicales au
niveau des entreprises et des usages. Tout du moins : à condition que l'on en soit
techniquement capable... Car l'acquisition, le stockage et l'exploitation de quantités
massives de données représentent des vrais défis techniques.
Une architecture big data permet la création et de l'administration de tous les
systèmes techniques qui vont permettre la bonne exploitation des données.
Il existe énormément d'outils différents pour manipuler des quantités massives de
données : pour le stockage, l'analyse ou la diffusion, par exemple. Mais comment assembler
ces différents outils pour réaliser une architecture capable de passer à l'échelle, d'être
tolérante aux pannes et aisément extensible, tout cela sans exploser les coûts ?
Le succès du fonctionnement de la Big data dépend de son architecture, son
infrastructure correcte et de son l’utilité que l’on fait ‘’ Data into Information into Value ‘’.
L’architecture de la Big data est composé de 4 grandes parties : Intégration, Data Processing
& Stockage, Sécurité et Opération.
Scaling SQL and NoSQL Databases in the Cloud RightScale
Database performance is the number-one cause of poor performance for scalable web applications, and the problem is magnified in cloud environments where I/O and bandwidth are generally slower and less predictable than in dedicated data centers. Database sharding is a highly effective method of removing the database scalability barrier by operating on top of proven RDBMS products such as MySQL and Postgres as well as the new NoSQL database platforms. In this session, you'll learn what it really takes to implement sharding, the role it plays in the effective end-to-end lifecycle management of your entire database environment, why it is crucial for ensuring reliability, and how to choose the best technology for a specific application. We'll also share a case study on a high-volume social networking application that demonstrates the effectiveness of database sharding for scaling cloud-based applications.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
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.
2. Agenda
– SQL/MX DBS, a cloud component added to SQL/MX
– Based on existing functionality
– What has been added
– Quick provision/deprovision
– User isolation
– Automation
2
4. But …. exactly which part of the cloud?
– Looking for the competitive edge for HPE NonStop
– Applications Stateless vs Stateful?
– Applications on-platform or off-platform?
– Killer application?
– Without real application at hand, cloud database is a good start
– Provide cloud capabilities, not cloud-dependent
– Easy provisioning
– Self-service
– Fast
– Multi-tenant
4
5. a
Let’s do cloud?
NonStop competitive edge
– First, we look at database services on NonStop
– Cloud scalability of RDBMS data does not come easy
– Sharding of data adds complexity
– Each shard requires a separate instance
– Oracle 12c announced shard support in 2016
– Promise of the cloud
– Self-provisioning of resources
– Quick provisioning and quick de-provisioning
– Pay for what you use
– Implementation of cloud services
– Very often, cloud = virtualized
– How good is that for databases? (critical DBs are often on
bare-metal)
– Enter multi-tenant databases
5
Cloud scalability with database shards
Region A
instance
Region B
instance
Region C
instance
Shard-aware application
6. Multi-tenant database
– Virtualized database servers lead to database “sprawl”
– Add complexity and management efforts
– Multi-tenant databases allow sharing DBMS Software
and system data between (isolated) users
– Examples
– Oracle 12c Pluggable Databases in a Container Database
instance
– Shares SGA, undo, redo space amongst all tenants
– Microsoft SQL Server Shared database, tenant’s schemas
– Shares system database and temp database
– NonStop SQL/MX DBS
– Shares system software
– Exclusive use of volumes (=lock space, cache buffers) to tenants
– Catalog / Datasource represents a database
6
NonStop SQL scalable database
Applications
8. Databases and Instances
Slightly different meanings
– NonStop SQL Database
– The Operating System data files that represent database objects (tables, views, indexes etc.)
– NonStop SQL follows the ANSI model: Catalog.schema.<object>
– In NonStop SQL DBS, catalog maps to Database name defined by tenant when provisioned.
– NonStop SQL Instance
– NonStop SQL is integral part of the NonStop OS
– Find database engine components in libraries and Disk Access Managers (DAM)
– If the system is up, the database is up
– The OS equals “the instance”; all databases on a system are managed by the same version of the software
– Database locks and cache are managed by the DAMs in a shared-nothing model
– More processors allow more memory and processing capacity which leads to more volumes and more lock space and cache space
– NonStop DBS “Instance”
– The data source name through which a tenant’s catalog and schema can be accessed
– Data source name equals the catalog name and “is” the database. Schemas can be added
– A data source can be stopped/started by a system administrator. This does not bring a NonStop database “down”
8
9. NonStop SQL DBS Data Source
– The Data Source is the port of
access to the data
– Referred to as Database Name
(ODBC) or serverDataSource
(JDBC)
– Usually contains address and port
of the database listener
– Often listeners use a known port
– SQL/MX: 18650
– Oracle: 1521
– SQL Server: 1433
– MySQL: 3306
– …
– The standard listening port is not a
requirement
10
Client
Application
ODBC/JDBC
Driver
SQL/MX
Database
Database
objects
Association server
Port: 18650
Data source
MXCSer
MXCS SQL
Server
1
2
3
4
NonStop Server
Connectivity
Objects
11. Database schemas in SQL/MX DBS
12
Database (SQL/MX Catalog)
INFORMATION_SCHEMA
DEFINITION_SCHEMA_
VERSION_3500
DEFAULT_SCHEMA
<Optional user schema>
HR
12. Two important schemas in a database
INFORMATION_SCHEMA
– Information about the database
– Datasource
– Schemas
– Storage
– CPUs
– Users
– Privilege groups
DEFINITION_SCHEMA_VERSION_3500
– SQL/MX standard metadata
– Per schema information about
– Tables
– Partitions
– Access paths
– Constraints
– Indexes
– Privileges
– Partitions
– Etc.
13
13. User management
– Multi-tenant support requires additional user management functionality
– Allow user names that were defined elsewhere
– Deny access other other user’s metadata
– Allow an end-user to add other users to access a database
14
14. Additions to SYSTEM_SECURITY_SCHEMA
– Allow “external users” access via MXCS
– Also known as database users
– An email address (Joe@hpe.com)
– Windows user name (ASIAPACSenthil)
– Privilege groups are used to assign privileges to multiple
users (even to future members of the group)
– In DBS: all users of a database belong to a group
– Group is created when a database is provisioned
– Introducing SCHEMA privileges
– Simplifies management at schema level using privilege groups
– DDL (manage objects)
– DML (manage data)
– DATABASE_USERS
– DATABASE_USERS_EXT
– PRIVILEGE_GROUPS
– PRIVILEGE_GROUP_GRANTS
– PRIVILEGE_GROUP_MEMBERSHIP
15
16. SQL/MX 3.5: Database Services
17
DBS thin provisioning interface
mxdbs CLI
Create a database
Share a database
Delete a database
Add more storage
Add additional users
Change user’s access level
Change user’s password
Delete a user
Show databases
usage: mxdbs [-h] [-V]
{ db-create | db-alter-share | db-delete | db-add-user |
db-remove-user | db-add-storage | db-user-change-access |
user-change-password | show-databases } ...
The API should be kept simple, database agnostic
The goal is to cover the life cycle management scope
from long term projects to ad-hoc projects.
17. One API to support multiple clients and protocols
– Protocol examples
– SSH
– HTTPS
– Message bus (AMQP)
– Local execute/launch
– Client examples
– HPE Operations Orchestration
– Ansible
– Client issuing REST API calls
– Openstack Trove
18
SQL/MX
DB
mxdbs CLI
Adapter Adapter Adapter
18. Functions of “create-db”
– Based on requested database size, (free) storage is assigned
– Use physical drives that are partitioned
– Use dedicated volumes for database
– Security ACLs assigned
– Catalog and initial schema created
– Datasource created and started
– Database is now ready to roll
– All you need is the appropriate driver
19
> mxdbs db-create dbs_fj 1000 emea_fjongma Welcome-1234 --schema default_schema
200GB 200GB 200GB 200GB 200GB
19. Use it
20
>rmxci -h 172.17.197.173:2100 -dsn DBS_FJ –u
emea_fjongma -p Welcome-1234
Welcome to the NonStop(TM) SQL/MX Remote
Conversational Interface
(c) Copyright 2015-2016 Hewlett Packard Enterprise
Development Company, LP
Connected to Data Source: DBS_FJ
SQL>CREATE TABLE departments
+> ( department_id NUMBER(4) NOT NULL
+> PRIMARY KEY
+> , department_name VARCHAR2(30)
+> CONSTRAINT dept_name_nn NOT NULL
+> , manager_id NUMBER(6)
+> , location_id NUMBER(4)
+> ) ;
--- SQL operation complete.
SQL>showddl departments;
CREATE TABLE DBS_FJ.DEFAULT_SCHEMA.DEPARTMENTS
(
DEPARTMENT_ID NUMERIC(4, 0) NO DEFAULT
-- NOT NULL NOT DROPPABLE
, DEPARTMENT_NAME VARCHAR2(30) CHARACTER
SET ISO88591
COLLATE DEFAULT NO DEFAULT -- NOT NULL NOT DROPPABLE
, MANAGER_ID NUMERIC(6, 0) DEFAULT
NULL
, LOCATION_ID NUMERIC(4, 0) DEFAULT
NULL
, CONSTRAINT
DBS_FJ.DEFAULT_SCHEMA.DEPARTMENTS_486497159_5192 PRIMARY KEY
(DEPARTMENT_ID ASC) NOT DROPPABLE
, CONSTRAINT
DBS_FJ.DEFAULT_SCHEMA.DEPARTMENTS_776297159_5192 CHECK
(DBS_FJ.DEFAULT_SCHEMA.DEPARTMENTS.DEPARTMENT_ID IS NOT
NULL AND
DBS_FJ.DEFAULT_SCHEMA.DEPARTMENTS.DEPARTMENT_NAME IS NOT
NULL) NOT
DROPPABLE
)
LOCATION NSX09.$HD0300.ZSDV34TJ.FTDKSC00
NAME NSX09_HD0300_ZSDV34TJ_FTDKSC00
ATTRIBUTES BLOCKSIZE 4096
STORE BY (DEPARTMENT_ID ASC)
;
--- SQL operation complete.