Join ordering in fragment queries
Download as PPTX, PDF0 likes1,603 views
comprehensive lecture on join odering fragments queries. it is the topic of DDBMS and the content are taken from multiple sources including google, book, class lecture. prepared by IFZAL HUSSAIN student of CS in SHAHEED BENAZIR BHUTTO UNIVERSITY SHERINGAL DIR UPPER KPK, PAKISTAN.
1 of 13
Download to read offline
![Semijoin Algorithms (cont.)
• Consider the join of two relations
• R[A] (located at site 1)
• S[A] (located at site 2)
• Alternatives
• 1. Do the join R ⋈A S
• 2. Perform one of the semijoin equivalents
( ) ( )
( ) ( )
A A A A A
A A A
R S R S S R S R
R S S R
](https://image.slidesharecdn.com/joinorderinginfragmentqueries-210923091911/85/Join-ordering-in-fragment-queries-11-320.jpg)
Ad
Recommended
Distributed design alternatives
Distributed design alternativesPooja Dixit The document discusses different distribution design alternatives for tables in a distributed database management system (DDBMS), including non-replicated and non-fragmented, fully replicated, partially replicated, fragmented, and mixed. It describes each alternative and discusses when each would be most suitable. The document also covers data replication, advantages and disadvantages of replication, and different replication techniques. Finally, it discusses fragmentation, the different types of fragmentation, and advantages and disadvantages of fragmentation.
Database , 8 Query Optimization
Database , 8 Query OptimizationAli Usman The document discusses distributed query processing and optimization in distributed database systems. It covers topics like query decomposition, distributed query optimization techniques including cost models, statistics collection and use, and algorithms for query optimization. Specifically, it describes the process of optimizing queries distributed across multiple database fragments or sites including generating the search space of possible query execution plans, using cost functions and statistics to pick the best plan, and examples of deterministic and randomized search strategies used.
Distributed DBMS - Unit 8 - Distributed Transaction Management & Concurrency ...
Distributed DBMS - Unit 8 - Distributed Transaction Management & Concurrency ...Gyanmanjari Institute Of Technology Transaction concept, ACID property, Objectives of transaction management, Types of transactions, Objectives of Distributed Concurrency Control, Concurrency Control anomalies, Methods of concurrency control, Serializability and recoverability, Distributed Serializability, Enhanced lock based and timestamp based protocols, Multiple granularity, Multi version schemes, Optimistic Concurrency Control techniques
Distributed DBMS - Unit 6 - Query Processing
Distributed DBMS - Unit 6 - Query ProcessingGyanmanjari Institute Of Technology Query Processing : Query Processing Problem, Layers of Query Processing Query Processing in Centralized Systems – Parsing & Translation, Optimization, Code generation, Example Query Processing in Distributed Systems – Mapping global query to local, Optimization,
Lec 7 query processing
Lec 7 query processingMd. Mashiur Rahman This document discusses distributed query processing. It begins by defining what a query and query processor are. It then outlines the main problems in query processing, characteristics of query processors, and layers of query processing. The key layers are query decomposition, data localization, global query optimization, and distributed execution. Query decomposition takes a query expressed on global relations and decomposes it into an algebraic query on global relations.
Database , 12 Reliability
Database , 12 ReliabilityAli Usman The document outlines concepts related to distributed database reliability. It begins with definitions of key terms like reliability, availability, failure, and fault tolerance measures. It then discusses different types of faults and failures that can occur in distributed systems. The document focuses on techniques for ensuring transaction atomicity and durability in the face of failures, including logging, write-ahead logging, and various execution strategies. It also covers checkpointing and recovery protocols at both the local and distributed level, particularly two-phase commit.
Deadlock management
Deadlock managementAhmed kasim The document discusses different methods for deadlock management in distributed database systems. It describes deadlock prevention, avoidance, and detection and resolution. For deadlock prevention, transactions declare all resource needs upfront and the system reserves them to prevent cycles in the wait-for graph. Deadlock avoidance methods order resources or sites and require transactions to request locks in that order. Deadlock detection identifies cycles in the global wait-for graph using centralized, hierarchical, or distributed detection across sites. The system then chooses victim transactions to abort to break cycles.
Query processing in Distributed Database System
Query processing in Distributed Database SystemMeghaj Mallick This is an PPT of DBMS. It include the following topic"Query processing in Distributed Database System".
management of distributed transactions
management of distributed transactionsNilu Desai 1. Distributed transaction managers ensure transactions have ACID properties through implementing the 2-phase commit protocol for reliability, 2-phase locking for concurrency control, and timeouts for deadlock detection on top of local transaction managers.
2. The 2-phase commit protocol guarantees subtransactions of the same transaction will all commit or abort despite failures, while 2-phase locking requires subtransactions acquire locks in a growing phase and release in a shrinking phase.
3. Timeouts are used to detect and abort transactions potentially experiencing a distributed deadlock.
Concurrency Control in Distributed Database.
Concurrency Control in Distributed Database.Meghaj Mallick The document discusses various techniques for concurrency control in distributed databases, including locking-based protocols and timestamp-based protocols. Locking-based protocols use exclusive and shared locks to control concurrent access to data items. They can be implemented using a single or distributed lock manager. Timestamp-based protocols assign each transaction a unique timestamp to determine serialization order and manage concurrent execution.
Query processing and optimization (updated)
Query processing and optimization (updated)Ravinder Kamboj The document discusses techniques used by a database management system (DBMS) to process, optimize, and execute high-level queries. It describes the phases of query processing which include syntax checking, translating the SQL query into an algebraic expression, optimization to choose an efficient execution plan, and running the optimized plan. Query optimization aims to minimize resources like disk I/O and CPU time by selecting the best execution strategy. Techniques for optimization include heuristic rules, cost-based methods, and semantic query optimization using constraints.
Distributed DBMS - Unit 5 - Semantic Data Control
Distributed DBMS - Unit 5 - Semantic Data ControlGyanmanjari Institute Of Technology Semantic Data Control : View Management, Authentication – database authentication, OS authentication, Access Rights, Semantic Integrity Control – Centralized & Distributed , Cost of enforcing semantic integrity
Ddbms1
Ddbms1pranjal_das The document summarizes key concepts in distributed database systems including:
1) Distributed database architectures have external, conceptual, and internal views of data. Common architectures include client-server and peer-to-peer.
2) Distributed databases can be designed top-down using a global schema or bottom-up without a global schema.
3) Fragmentation and allocation distribute data across sites for performance and availability. Correct fragmentation follows completeness, reconstruction, and disjointness rules.
Distributed Query Processing
Distributed Query ProcessingMythili Kannan This document discusses distributed database and distributed query processing. It covers topics like distributed database, query processing, distributed query processing methodology including query decomposition, data localization, and global query optimization. Query decomposition involves normalizing, analyzing, eliminating redundancy, and rewriting queries. Data localization applies data distribution to algebraic operations to determine involved fragments. Global query optimization finds the best global schedule to minimize costs and uses techniques like join ordering and semi joins. Local query optimization applies centralized optimization techniques to the best global execution schedule.
DDBMS_ Chap 7 Optimization of Distributed Queries
DDBMS_ Chap 7 Optimization of Distributed QueriesKhushali Kathiriya Query Optimization, Join Ordering, Semi- Join Ordering
Query Decomposition and data localization 
Query Decomposition and data localization Hafiz faiz This document discusses query processing in distributed databases. It describes query decomposition, which transforms a high-level query into an equivalent lower-level algebraic query. The main steps in query decomposition are normalization, analysis, redundancy elimination, and rewriting the query in relational algebra. Data localization then translates the algebraic query on global relations into a query on physical database fragments using fragmentation rules.
deadlock handling
deadlock handlingSuraj Kumar The document discusses deadlocks in database systems. It defines deadlock as a waiting state where transactions are unable to progress because each is holding a resource needed by another, forming a cyclic dependency. It outlines the four conditions for deadlock - mutual exclusion, hold and wait, no preemption, and circular wait. Methods for handling deadlocks include avoidance, prevention, detection and recovery. Prevention techniques involve locking protocols or transaction rollback with timestamps. Detection uses a wait-for graph to identify cycles indicating deadlocks, and recovery requires selecting victims to rollback to break cycles.
message passing
message passingAshish Kumar The document discusses various design issues related to interprocess communication using message passing. It covers topics like synchronization methods, buffering strategies, process addressing schemes, reliability in message passing, and group communication. The key synchronization methods are blocking and non-blocking sends/receives. Issues addressed include blocking forever if the receiving process crashes, buffering strategies like null, single-message and finite buffers, and naming schemes like explicit and implicit addressing. Reliability is achieved using protocols like four-message, three-message and two-message. Group communication supports one-to-many, many-to-one and many-to-many communication with primitives for multicast, membership and different ordering semantics.
Load Balancing in Parallel and Distributed Database
Load Balancing in Parallel and Distributed DatabaseMd. Shamsur Rahim This document discusses load balancing techniques in distributed database systems. It describes different types of parallelism including inter-query, intra-query, intra-operation, and inter-operation parallelism. It also discusses problems that can occur with parallel execution such as initialization, interference, and skew. The document then focuses on techniques for load balancing within operators and between operators, including adaptive and specialized techniques. It describes how activations, activation queues, and threads can be used to improve load balancing in shared-memory systems.
Distributed Shared Memory
Distributed Shared MemoryPrakhar Rastogi This document discusses distributed shared memory (DSM) systems. It defines DSM as providing a logical abstraction of shared memory across interconnected nodes with distributed physical memories. It describes different types of DSM implementations, advantages of DSM, and various hardware architectures like on-chip memory, bus-based multiprocessors, and switched multiprocessors. It also covers DSM design issues such as granularity of sharing, data structures, consistency models like strict, sequential, and weak consistency, and coherence protocols.
Inter-Process Communication in distributed systems
Inter-Process Communication in distributed systemsAya Mahmoud Inter-Process Communication is at the heart of all distributed systems, so we need to know the ways that processes can exchange information.
Communication in distributed systems is based on Low-level message passing as offered by the underlying network.
Distributed concurrency control
Distributed concurrency controlBinte fatima This document discusses concurrency control algorithms for distributed database systems. It describes distributed two-phase locking (2PL), wound-wait, basic timestamp ordering, and distributed optimistic concurrency control algorithms. For distributed 2PL, transactions lock data items in a growing phase and release locks in a shrinking phase. Wound-wait prevents deadlocks by aborting younger transactions that wait on older ones. Basic timestamp ordering orders transactions based on their timestamps to ensure serializability. The distributed optimistic approach allows transactions to read and write freely until commit, when certification checks for conflicts. Maintaining consistency across distributed copies is important for concurrency control algorithms.
Distributed operating system
Distributed operating systemudaya khanal A distributed system is a collection of independent computers that appears as a single coherent system to users. It provides advantages like cost-effectiveness, reliability, scalability, and flexibility but introduces challenges in achieving transparency, dependability, performance, and flexibility due to its distributed nature. A true distributed system that solves all these challenges perfectly is difficult to achieve due to limitations like network complexity and security issues.
Replication in Distributed Systems
Replication in Distributed SystemsKavya Barnadhya Hazarika Replication in computing involves sharing information so as to ensure consistency between redundant resources, such as software or hardware components, to improve reliability, fault-tolerance, or accessibility.
Distributed Mutual exclusion algorithms
Distributed Mutual exclusion algorithmsMNM Jain Engineering College 1. There are two main approaches to distributed mutual exclusion - token-based and non-token based. Token based approaches use a shared token to allow only one process access at a time, while non-token approaches use message passing to determine access order.
2. A common token based algorithm uses a centralized coordinator process that grants access to the requesting process. Ring-based algorithms pass a token around a logical ring, allowing the process holding it to enter the critical section.
3. Lamport's non-token algorithm uses message passing of requests and timestamps to build identical request queues at each process, allowing the process at the head of the queue to enter the critical section. The Ricart-Agrawala
Physical and Logical Clocks
Physical and Logical ClocksDilum Bandara Time in distributed systems. Lack of global time and logical clocks as alternatives. Lamport’s time stamp and Lamport’s Totally Ordered Multicast
Computer Networks Unit 2 UNIT II DATA-LINK LAYER & MEDIA ACCESS
Computer Networks Unit 2 UNIT II DATA-LINK LAYER & MEDIA ACCESSDr. SELVAGANESAN S The document discusses data link layer framing and protocols. It describes:
1) Two main approaches to framing - byte-oriented (using sentinel characters) and bit-oriented (using bit stuffing). Protocols discussed include BISYNC, DDCMP, and HDLC.
2) Features of PPP framing including negotiated field sizes and use of LCP control messages.
3) Functions of data link layer including framing, flow control, error control, and media access control. The relationship between the logical link control and media access control sublayers is also covered.
Synchronization in distributed systems 
Synchronization in distributed systems SHATHAN This document discusses various topics related to synchronization in distributed systems, including distributed algorithms, logical clocks, global state, and leader election. It provides definitions and examples of key synchronization concepts such as coordination, synchronization, and determining global states. Examples of logical clock algorithms like Lamport clocks and vector clocks are provided. Challenges around clock synchronization and calculating global system states are also summarized.
IEDM 2024 Tutorial2_Advances in CMOS Technologies and Future Directions for C...
IEDM 2024 Tutorial2_Advances in CMOS Technologies and Future Directions for C...organizerofv IEDM 2024 Tutorial2
Role of Data Annotation Services in AI-Powered Manufacturing
Role of Data Annotation Services in AI-Powered ManufacturingAndrew Leo From predictive maintenance to robotic automation, AI is driving the future of manufacturing. But without high-quality annotated data, even the smartest models fall short.
Discover how data annotation services are powering accuracy, safety, and efficiency in AI-driven manufacturing systems.
Precision in data labeling = Precision on the production floor.
Ad
More Related Content
What's hot (20)
management of distributed transactions
management of distributed transactionsNilu Desai 1. Distributed transaction managers ensure transactions have ACID properties through implementing the 2-phase commit protocol for reliability, 2-phase locking for concurrency control, and timeouts for deadlock detection on top of local transaction managers.
2. The 2-phase commit protocol guarantees subtransactions of the same transaction will all commit or abort despite failures, while 2-phase locking requires subtransactions acquire locks in a growing phase and release in a shrinking phase.
3. Timeouts are used to detect and abort transactions potentially experiencing a distributed deadlock.
Concurrency Control in Distributed Database.
Concurrency Control in Distributed Database.Meghaj Mallick The document discusses various techniques for concurrency control in distributed databases, including locking-based protocols and timestamp-based protocols. Locking-based protocols use exclusive and shared locks to control concurrent access to data items. They can be implemented using a single or distributed lock manager. Timestamp-based protocols assign each transaction a unique timestamp to determine serialization order and manage concurrent execution.
Query processing and optimization (updated)
Query processing and optimization (updated)Ravinder Kamboj The document discusses techniques used by a database management system (DBMS) to process, optimize, and execute high-level queries. It describes the phases of query processing which include syntax checking, translating the SQL query into an algebraic expression, optimization to choose an efficient execution plan, and running the optimized plan. Query optimization aims to minimize resources like disk I/O and CPU time by selecting the best execution strategy. Techniques for optimization include heuristic rules, cost-based methods, and semantic query optimization using constraints.
Distributed DBMS - Unit 5 - Semantic Data Control
Distributed DBMS - Unit 5 - Semantic Data ControlGyanmanjari Institute Of Technology Semantic Data Control : View Management, Authentication – database authentication, OS authentication, Access Rights, Semantic Integrity Control – Centralized & Distributed , Cost of enforcing semantic integrity
Ddbms1
Ddbms1pranjal_das The document summarizes key concepts in distributed database systems including:
1) Distributed database architectures have external, conceptual, and internal views of data. Common architectures include client-server and peer-to-peer.
2) Distributed databases can be designed top-down using a global schema or bottom-up without a global schema.
3) Fragmentation and allocation distribute data across sites for performance and availability. Correct fragmentation follows completeness, reconstruction, and disjointness rules.
Distributed Query Processing
Distributed Query ProcessingMythili Kannan This document discusses distributed database and distributed query processing. It covers topics like distributed database, query processing, distributed query processing methodology including query decomposition, data localization, and global query optimization. Query decomposition involves normalizing, analyzing, eliminating redundancy, and rewriting queries. Data localization applies data distribution to algebraic operations to determine involved fragments. Global query optimization finds the best global schedule to minimize costs and uses techniques like join ordering and semi joins. Local query optimization applies centralized optimization techniques to the best global execution schedule.
DDBMS_ Chap 7 Optimization of Distributed Queries
DDBMS_ Chap 7 Optimization of Distributed QueriesKhushali Kathiriya Query Optimization, Join Ordering, Semi- Join Ordering
Query Decomposition and data localization
Query Decomposition and data localization Hafiz faiz This document discusses query processing in distributed databases. It describes query decomposition, which transforms a high-level query into an equivalent lower-level algebraic query. The main steps in query decomposition are normalization, analysis, redundancy elimination, and rewriting the query in relational algebra. Data localization then translates the algebraic query on global relations into a query on physical database fragments using fragmentation rules.
deadlock handling
deadlock handlingSuraj Kumar The document discusses deadlocks in database systems. It defines deadlock as a waiting state where transactions are unable to progress because each is holding a resource needed by another, forming a cyclic dependency. It outlines the four conditions for deadlock - mutual exclusion, hold and wait, no preemption, and circular wait. Methods for handling deadlocks include avoidance, prevention, detection and recovery. Prevention techniques involve locking protocols or transaction rollback with timestamps. Detection uses a wait-for graph to identify cycles indicating deadlocks, and recovery requires selecting victims to rollback to break cycles.
message passing
message passingAshish Kumar The document discusses various design issues related to interprocess communication using message passing. It covers topics like synchronization methods, buffering strategies, process addressing schemes, reliability in message passing, and group communication. The key synchronization methods are blocking and non-blocking sends/receives. Issues addressed include blocking forever if the receiving process crashes, buffering strategies like null, single-message and finite buffers, and naming schemes like explicit and implicit addressing. Reliability is achieved using protocols like four-message, three-message and two-message. Group communication supports one-to-many, many-to-one and many-to-many communication with primitives for multicast, membership and different ordering semantics.
Load Balancing in Parallel and Distributed Database
Load Balancing in Parallel and Distributed DatabaseMd. Shamsur Rahim This document discusses load balancing techniques in distributed database systems. It describes different types of parallelism including inter-query, intra-query, intra-operation, and inter-operation parallelism. It also discusses problems that can occur with parallel execution such as initialization, interference, and skew. The document then focuses on techniques for load balancing within operators and between operators, including adaptive and specialized techniques. It describes how activations, activation queues, and threads can be used to improve load balancing in shared-memory systems.
Distributed Shared Memory
Distributed Shared MemoryPrakhar Rastogi This document discusses distributed shared memory (DSM) systems. It defines DSM as providing a logical abstraction of shared memory across interconnected nodes with distributed physical memories. It describes different types of DSM implementations, advantages of DSM, and various hardware architectures like on-chip memory, bus-based multiprocessors, and switched multiprocessors. It also covers DSM design issues such as granularity of sharing, data structures, consistency models like strict, sequential, and weak consistency, and coherence protocols.
Inter-Process Communication in distributed systems
Inter-Process Communication in distributed systemsAya Mahmoud Inter-Process Communication is at the heart of all distributed systems, so we need to know the ways that processes can exchange information.
Communication in distributed systems is based on Low-level message passing as offered by the underlying network.
Distributed concurrency control
Distributed concurrency controlBinte fatima This document discusses concurrency control algorithms for distributed database systems. It describes distributed two-phase locking (2PL), wound-wait, basic timestamp ordering, and distributed optimistic concurrency control algorithms. For distributed 2PL, transactions lock data items in a growing phase and release locks in a shrinking phase. Wound-wait prevents deadlocks by aborting younger transactions that wait on older ones. Basic timestamp ordering orders transactions based on their timestamps to ensure serializability. The distributed optimistic approach allows transactions to read and write freely until commit, when certification checks for conflicts. Maintaining consistency across distributed copies is important for concurrency control algorithms.
Distributed operating system
Distributed operating systemudaya khanal A distributed system is a collection of independent computers that appears as a single coherent system to users. It provides advantages like cost-effectiveness, reliability, scalability, and flexibility but introduces challenges in achieving transparency, dependability, performance, and flexibility due to its distributed nature. A true distributed system that solves all these challenges perfectly is difficult to achieve due to limitations like network complexity and security issues.
Replication in Distributed Systems
Replication in Distributed SystemsKavya Barnadhya Hazarika Replication in computing involves sharing information so as to ensure consistency between redundant resources, such as software or hardware components, to improve reliability, fault-tolerance, or accessibility.
Distributed Mutual exclusion algorithms
Distributed Mutual exclusion algorithmsMNM Jain Engineering College 1. There are two main approaches to distributed mutual exclusion - token-based and non-token based. Token based approaches use a shared token to allow only one process access at a time, while non-token approaches use message passing to determine access order.
2. A common token based algorithm uses a centralized coordinator process that grants access to the requesting process. Ring-based algorithms pass a token around a logical ring, allowing the process holding it to enter the critical section.
3. Lamport's non-token algorithm uses message passing of requests and timestamps to build identical request queues at each process, allowing the process at the head of the queue to enter the critical section. The Ricart-Agrawala
Physical and Logical Clocks
Physical and Logical ClocksDilum Bandara Time in distributed systems. Lack of global time and logical clocks as alternatives. Lamport’s time stamp and Lamport’s Totally Ordered Multicast
Computer Networks Unit 2 UNIT II DATA-LINK LAYER & MEDIA ACCESS
Computer Networks Unit 2 UNIT II DATA-LINK LAYER & MEDIA ACCESSDr. SELVAGANESAN S The document discusses data link layer framing and protocols. It describes:
1) Two main approaches to framing - byte-oriented (using sentinel characters) and bit-oriented (using bit stuffing). Protocols discussed include BISYNC, DDCMP, and HDLC.
2) Features of PPP framing including negotiated field sizes and use of LCP control messages.
3) Functions of data link layer including framing, flow control, error control, and media access control. The relationship between the logical link control and media access control sublayers is also covered.
Synchronization in distributed systems
Synchronization in distributed systems SHATHAN This document discusses various topics related to synchronization in distributed systems, including distributed algorithms, logical clocks, global state, and leader election. It provides definitions and examples of key synchronization concepts such as coordination, synchronization, and determining global states. Examples of logical clock algorithms like Lamport clocks and vector clocks are provided. Challenges around clock synchronization and calculating global system states are also summarized.
Recently uploaded (20)
IEDM 2024 Tutorial2_Advances in CMOS Technologies and Future Directions for C...
IEDM 2024 Tutorial2_Advances in CMOS Technologies and Future Directions for C...organizerofv IEDM 2024 Tutorial2
Role of Data Annotation Services in AI-Powered Manufacturing
Role of Data Annotation Services in AI-Powered ManufacturingAndrew Leo From predictive maintenance to robotic automation, AI is driving the future of manufacturing. But without high-quality annotated data, even the smartest models fall short.
Discover how data annotation services are powering accuracy, safety, and efficiency in AI-driven manufacturing systems.
Precision in data labeling = Precision on the production floor.
2025-05-Q4-2024-Investor-Presentation.pptx
2025-05-Q4-2024-Investor-Presentation.pptxSamuele Fogagnolo Cloudflare Q4 Financial Results Presentation
Manifest Pre-Seed Update | A Humanoid OEM Deeptech In France
Manifest Pre-Seed Update | A Humanoid OEM Deeptech In Francechb3 The latest updates on Manifest's pre-seed stage progress.
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdf
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdfAbi john Analyze the growth of meme coins from mere online jokes to potential assets in the digital economy. Explore the community, culture, and utility as they elevate themselves to a new era in cryptocurrency.
TrsLabs - Fintech Product & Business Consulting
TrsLabs - Fintech Product & Business ConsultingTrs Labs Hybrid Growth Mandate Model with TrsLabs
Strategic Investments, Inorganic Growth, Business Model Pivoting are critical activities that business don't do/change everyday. In cases like this, it may benefit your business to choose a temporary external consultant.
An unbiased plan driven by clearcut deliverables, market dynamics and without the influence of your internal office equations empower business leaders to make right choices.
Getting things done within a budget within a timeframe is key to Growing Business - No matter whether you are a start-up or a big company
Talk to us & Unlock the competitive advantage
AI Changes Everything – Talk at Cardiff Metropolitan University, 29th April 2...
AI Changes Everything – Talk at Cardiff Metropolitan University, 29th April 2...Alan Dix Talk at the final event of Data Fusion Dynamics: A Collaborative UK-Saudi Initiative in Cybersecurity and Artificial Intelligence funded by the British Council UK-Saudi Challenge Fund 2024, Cardiff Metropolitan University, 29th April 2025
https://alandix.com/academic/talks/CMet2025-AI-Changes-Everything/
Is AI just another technology, or does it fundamentally change the way we live and think?
Every technology has a direct impact with micro-ethical consequences, some good, some bad. However more profound are the ways in which some technologies reshape the very fabric of society with macro-ethical impacts. The invention of the stirrup revolutionised mounted combat, but as a side effect gave rise to the feudal system, which still shapes politics today. The internal combustion engine offers personal freedom and creates pollution, but has also transformed the nature of urban planning and international trade. When we look at AI the micro-ethical issues, such as bias, are most obvious, but the macro-ethical challenges may be greater.
At a micro-ethical level AI has the potential to deepen social, ethnic and gender bias, issues I have warned about since the early 1990s! It is also being used increasingly on the battlefield. However, it also offers amazing opportunities in health and educations, as the recent Nobel prizes for the developers of AlphaFold illustrate. More radically, the need to encode ethics acts as a mirror to surface essential ethical problems and conflicts.
At the macro-ethical level, by the early 2000s digital technology had already begun to undermine sovereignty (e.g. gambling), market economics (through network effects and emergent monopolies), and the very meaning of money. Modern AI is the child of big data, big computation and ultimately big business, intensifying the inherent tendency of digital technology to concentrate power. AI is already unravelling the fundamentals of the social, political and economic world around us, but this is a world that needs radical reimagining to overcome the global environmental and human challenges that confront us. Our challenge is whether to let the threads fall as they may, or to use them to weave a better future.
What is Model Context Protocol(MCP) - The new technology for communication bw...
What is Model Context Protocol(MCP) - The new technology for communication bw...Vishnu Singh Chundawat The MCP (Model Context Protocol) is a framework designed to manage context and interaction within complex systems. This SlideShare presentation will provide a detailed overview of the MCP Model, its applications, and how it plays a crucial role in improving communication and decision-making in distributed systems. We will explore the key concepts behind the protocol, including the importance of context, data management, and how this model enhances system adaptability and responsiveness. Ideal for software developers, system architects, and IT professionals, this presentation will offer valuable insights into how the MCP Model can streamline workflows, improve efficiency, and create more intuitive systems for a wide range of use cases.
HCL Nomad Web – Best Practices und Verwaltung von Multiuser-Umgebungen
HCL Nomad Web – Best Practices und Verwaltung von Multiuser-Umgebungenpanagenda Webinar Recording: https://www.panagenda.com/webinars/hcl-nomad-web-best-practices-und-verwaltung-von-multiuser-umgebungen/
HCL Nomad Web wird als die nächste Generation des HCL Notes-Clients gefeiert und bietet zahlreiche Vorteile, wie die Beseitigung des Bedarfs an Paketierung, Verteilung und Installation. Nomad Web-Client-Updates werden “automatisch” im Hintergrund installiert, was den administrativen Aufwand im Vergleich zu traditionellen HCL Notes-Clients erheblich reduziert. Allerdings stellt die Fehlerbehebung in Nomad Web im Vergleich zum Notes-Client einzigartige Herausforderungen dar.
Begleiten Sie Christoph und Marc, während sie demonstrieren, wie der Fehlerbehebungsprozess in HCL Nomad Web vereinfacht werden kann, um eine reibungslose und effiziente Benutzererfahrung zu gewährleisten.
In diesem Webinar werden wir effektive Strategien zur Diagnose und Lösung häufiger Probleme in HCL Nomad Web untersuchen, einschließlich
- Zugriff auf die Konsole
- Auffinden und Interpretieren von Protokolldateien
- Zugriff auf den Datenordner im Cache des Browsers (unter Verwendung von OPFS)
- Verständnis der Unterschiede zwischen Einzel- und Mehrbenutzerszenarien
- Nutzung der Client Clocking-Funktion
How analogue intelligence complements AI
How analogue intelligence complements AIPaul Rowe
Artificial Intelligence is providing benefits in many areas of work within the heritage sector, from image analysis, to ideas generation, and new research tools. However, it is more critical than ever for people, with analogue intelligence, to ensure the integrity and ethical use of AI. Including real people can improve the use of AI by identifying potential biases, cross-checking results, refining workflows, and providing contextual relevance to AI-driven results.
News about the impact of AI often paints a rosy picture. In practice, there are many potential pitfalls. This presentation discusses these issues and looks at the role of analogue intelligence and analogue interfaces in providing the best results to our audiences. How do we deal with factually incorrect results? How do we get content generated that better reflects the diversity of our communities? What roles are there for physical, in-person experiences in the digital world?
AI EngineHost Review: Revolutionary USA Datacenter-Based Hosting with NVIDIA ...
AI EngineHost Review: Revolutionary USA Datacenter-Based Hosting with NVIDIA ...SOFTTECHHUB I started my online journey with several hosting services before stumbling upon Ai EngineHost. At first, the idea of paying one fee and getting lifetime access seemed too good to pass up. The platform is built on reliable US-based servers, ensuring your projects run at high speeds and remain safe. Let me take you step by step through its benefits and features as I explain why this hosting solution is a perfect fit for digital entrepreneurs.
Massive Power Outage Hits Spain, Portugal, and France: Causes, Impact, and On...
Massive Power Outage Hits Spain, Portugal, and France: Causes, Impact, and On...Aqusag Technologies In late April 2025, a significant portion of Europe, particularly Spain, Portugal, and parts of southern France, experienced widespread, rolling power outages that continue to affect millions of residents, businesses, and infrastructure systems.
TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...
TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...TrustArc Most consumers believe they’re making informed decisions about their personal data—adjusting privacy settings, blocking trackers, and opting out where they can. However, our new research reveals that while awareness is high, taking meaningful action is still lacking. On the corporate side, many organizations report strong policies for managing third-party data and consumer consent yet fall short when it comes to consistency, accountability and transparency.
This session will explore the research findings from TrustArc’s Privacy Pulse Survey, examining consumer attitudes toward personal data collection and practical suggestions for corporate practices around purchasing third-party data.
Attendees will learn:
- Consumer awareness around data brokers and what consumers are doing to limit data collection
- How businesses assess third-party vendors and their consent management operations
- Where business preparedness needs improvement
- What these trends mean for the future of privacy governance and public trust
This discussion is essential for privacy, risk, and compliance professionals who want to ground their strategies in current data and prepare for what’s next in the privacy landscape.
DevOpsDays Atlanta 2025 - Building 10x Development Organizations.pptx
DevOpsDays Atlanta 2025 - Building 10x Development Organizations.pptxJustin Reock Building 10x Organizations with Modern Productivity Metrics
10x developers may be a myth, but 10x organizations are very real, as proven by the influential study performed in the 1980s, ‘The Coding War Games.’
Right now, here in early 2025, we seem to be experiencing YAPP (Yet Another Productivity Philosophy), and that philosophy is converging on developer experience. It seems that with every new method we invent for the delivery of products, whether physical or virtual, we reinvent productivity philosophies to go alongside them.
But which of these approaches actually work? DORA? SPACE? DevEx? What should we invest in and create urgency behind today, so that we don’t find ourselves having the same discussion again in a decade?
Mobile App Development Company in Saudi Arabia
Mobile App Development Company in Saudi ArabiaSteve Jonas EmizenTech is a globally recognized software development company, proudly serving businesses since 2013. With over 11+ years of industry experience and a team of 200+ skilled professionals, we have successfully delivered 1200+ projects across various sectors. As a leading Mobile App Development Company In Saudi Arabia we offer end-to-end solutions for iOS, Android, and cross-platform applications. Our apps are known for their user-friendly interfaces, scalability, high performance, and strong security features. We tailor each mobile application to meet the unique needs of different industries, ensuring a seamless user experience. EmizenTech is committed to turning your vision into a powerful digital product that drives growth, innovation, and long-term success in the competitive mobile landscape of Saudi Arabia.
Quantum Computing Quick Research Guide by Arthur Morgan
Quantum Computing Quick Research Guide by Arthur MorganArthur Morgan This is a Quick Research Guide (QRG).
QRGs include the following:
- A brief, high-level overview of the QRG topic.
- A milestone timeline for the QRG topic.
- Links to various free online resource materials to provide a deeper dive into the QRG topic.
- Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic.
QRGs planned for the series:
- Artificial Intelligence QRG
- Quantum Computing QRG
- Big Data Analytics QRG
- Spacecraft Guidance, Navigation & Control QRG (coming 2026)
- UK Home Computing & The Birth of ARM QRG (coming 2027)
Any questions or comments?
- Please contact Arthur Morgan at [email protected].
100% human made.
tecnologias de las primeras civilizaciones.pdf
tecnologias de las primeras civilizaciones.pdffjgm517 descaripcion detallada del avance de las tecnologias en mesopotamia, egipto, roma y grecia.
Procurement Insights Cost To Value Guide.pptx
Procurement Insights Cost To Value Guide.pptxJon Hansen Procurement Insights integrated Historic Procurement Industry Archives, serves as a powerful complement — not a competitor — to other procurement industry firms. It fills critical gaps in depth, agility, and contextual insight that most traditional analyst and association models overlook.
Learn more about this value- driven proprietary service offering here.
What is Model Context Protocol(MCP) - The new technology for communication bw...
What is Model Context Protocol(MCP) - The new technology for communication bw...Vishnu Singh Chundawat
Ad
Join ordering in fragment queries
- 1. Join Ordering in Fragment Queries By Shehab Uddin and Ifzal Hussain
- 2. Join Ordering in Fragment Queries • Join ordering is important in centralized DB, and is more important in distributed DB.
- 3. Join Ordering in Fragment Queries (cont.) • R site j: “relation R is transferred to site j” • 1. EMP site 2; site 2 computes EMP’ • EMP’->site 3; site 3 computes the result. • 2.ASG->site 1: site 1 computes EMP’, EMP’->site 3; site 3 computes the result • 3. ASG->site 3; computeASG’;ASG’->site 1 • 4. PROJ->site 2; compute PROJ’; PROJ’->site 1 • 5. EMP->site 2; PROJ->site 2; site 2 compute the join.
- 4. Join Ordering in Fragment Queries (cont.) • Join ordering • Distributed INGRES • System R* • Semijoin ordering • SDD-1
- 5. Join Ordering • Consider two relations only • R ⋈ S • Transfer the smaller size • Multiple relations more difficult because too many alternatives • Compute the cost of all alternatives and select the best one • Necessary to compute the size of intermediate relations which is difficult. • Use heuristics
- 6. Join Ordering - Example • Consider: PROJ ⋈PNO ASG ⋈ENO EMP
- 7. Join Ordering – Example (cont.) • Execution alternatives: • 1. EMP Site 2 • Site 2 computes EMP’=EMP⋈ASG • EMP’ Site 3 • Site 3 computes EMP’⋈PROJ • 2.ASG Site 1 • Site 1 computes EMP’=EMP⋈ASG • EMP’ Site 3 • Site 3 computes EMP’⋈PROJ
- 8. Join Ordering – Example (cont.) 3. ASG Site 3 Site 3 computes ASG’=ASG⋈PROJ ASG’ Site 1 Site 1 computes ASG’⋈EMP 4. PROJ Site 2 Site 2 computes PROJ’=PROJ⋈ASG PROJ’ Site 1 Site 1 computes PROJ’ ⋈ EMP
- 9. cont,d 5. EMP Site 2 PROJ Site 2 Site 2 computes EMP⋈ PROJ⋈ASG
- 10. Semijoin Algorithms • Shortcoming of the joining method • Transfer the entire relation which may contain some useless tuples • Semi-join reduces the size of operand relation to be transferred • Semi-join is beneficial if the cost to produce and send to the other site is less than sending the whole relation.
- 11. Semijoin Algorithms (cont.) • Consider the join of two relations • R[A] (located at site 1) • S[A] (located at site 2) • Alternatives • 1. Do the join R ⋈A S • 2. Perform one of the semijoin equivalents ( ) ( ) ( ) ( ) A A A A A A A A R S R S S R S R R S S R
- 12. Cnt,d • Perform the join • Send R to site 2 • Site 2 computes R ⋈A S • Consider semijoin • S’ = A(S) • S’ Site 1 • Site 1 computes • R’ Site 2 • Site 2 computes • Semijoin is better if ( ) A A R S S ' ' A R R S ' A R S ( ( ( )) ( )) ( ) A A size S size R S size R