Hey friends, here is my "query tree" assignment. :-) I have searched a lot to get this master piece :p and I can guarantee you that this one gonna help you In Sha ALLAH more than any else document on the subject. Have a good day :-)
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,
This Presentation is about NoSQL which means Not Only SQL. This presentation covers the aspects of using NoSQL for Big Data and the differences from RDBMS.
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,
This Presentation is about NoSQL which means Not Only SQL. This presentation covers the aspects of using NoSQL for Big Data and the differences from RDBMS.
State Space Search Strategies in Artificial Intelligence (AI)RSAISHANKAR
Search is the systematic examination of states to find path from the start/root state to the goal state.
Search is the systematic examination of states to find path from the start/root state to the goal state.
Artificial Intelligence: Introduction, Typical Applications. State Space Search: Depth Bounded
DFS, Depth First Iterative Deepening. Heuristic Search: Heuristic Functions, Best First Search,
Hill Climbing, Variable Neighborhood Descent, Beam Search, Tabu Search. Optimal Search: A
*
algorithm, Iterative Deepening A*
, Recursive Best First Search, Pruning the CLOSED and OPEN
Lists
State Space Search Strategies in Artificial Intelligence (AI)RSAISHANKAR
Search is the systematic examination of states to find path from the start/root state to the goal state.
Search is the systematic examination of states to find path from the start/root state to the goal state.
Artificial Intelligence: Introduction, Typical Applications. State Space Search: Depth Bounded
DFS, Depth First Iterative Deepening. Heuristic Search: Heuristic Functions, Best First Search,
Hill Climbing, Variable Neighborhood Descent, Beam Search, Tabu Search. Optimal Search: A
*
algorithm, Iterative Deepening A*
, Recursive Best First Search, Pruning the CLOSED and OPEN
Lists
• Process for heuristics optimization
1. The parser of a high-level query generates an initial internal representation;
2. Apply heuristics rules to optimize the internal representation.
3. A query execution plan is generated to execute groups of operations based on the access paths available on the files involved in the query.
해당 자료는 풀잎스쿨 18기 중 "설명가능한 인공지능 기획!" 진행 중 Counterfactual Explanation 세션에 대해서 정리한 자료입니다.
논문, Youtube 및 하기 자료를 바탕으로 정리되었습니다.
https://christophm.github.io/interpretable-ml-book/
Extracts objects from the entire collection, without modifying the objects themselves. where the goal is to select whole sentences (without modifying them)
Description of everything necessary for startupShefa Idrees
This doc comprises all important points that you must focus to elevate your fyp or startup. Like about project reports, proposals, leaflets, handbooks, brochures, thesis an much more. I recommend all the entrepreneurs to follow this doc in order to turn their small business into a vast one.
I am busy in exams :p. Can't write much description to be very honest. Anyways if you have any query regarding any slide, you can freely ask. Thank You
This presentation gives a complete idea of what a cover idea is.
Before you go through this presentation, keep it in mind that many people don't consider it important but it is as important as an index of a book.
Index highlights topics of the book where cover letter highlights acheivemens and skills of applicant
A very important topic... I have mentioned here from its formal definition to its example. This presentation also explains the recommended format to write an effective project proposal. If any of its reader finds any point to be difficult to him/her, he/she can freely ask in comments or through inbox. Thank you :-)
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
A Comprehensive Look at Generative AI in Retail App Testing.pdfkalichargn70th171
Traditional software testing methods are being challenged in retail, where customer expectations and technological advancements continually shape the landscape. Enter generative AI—a transformative subset of artificial intelligence technologies poised to revolutionize software testing.
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
Advanced Flow Concepts Every Developer Should KnowPeter Caitens
Tim Combridge from Sensible Giraffe and Salesforce Ben presents some important tips that all developers should know when dealing with Flows in Salesforce.
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
Strategies for Successful Data Migration Tools.pptxvarshanayak241
Data migration is a complex but essential task for organizations aiming to modernize their IT infrastructure and leverage new technologies. By understanding common challenges and implementing these strategies, businesses can achieve a successful migration with minimal disruption. Data Migration Tool like Ask On Data play a pivotal role in this journey, offering features that streamline the process, ensure data integrity, and maintain security. With the right approach and tools, organizations can turn the challenge of data migration into an opportunity for growth and innovation.
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
How Does XfilesPro Ensure Security While Sharing Documents in Salesforce?XfilesPro
Worried about document security while sharing them in Salesforce? Fret no more! Here are the top-notch security standards XfilesPro upholds to ensure strong security for your Salesforce documents while sharing with internal or external people.
To learn more, read the blog: https://www.xfilespro.com/how-does-xfilespro-make-document-sharing-secure-and-seamless-in-salesforce/
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
2. Query Trees
• A query tree is a tree structure that corresponds to a relational algebra expression such that:
Each leaf node represents an input relation.
Each internal node represents a relation obtained by applying one relational operator to
its child nodes.
The root relation represents the answer to the query.
• It specifies what operations to apply, and the order to apply them, but not how to actually
implement the operations.
• A logical query tree does not select a particular algorithm to implement each relational
operator.
• Two query trees are equivalent if their root relations are the same (query result).
• A query tree may have different execution plans.
• Some query trees and plans are more efficient to execute than others.
Representation
• Query tree is a representation of a select statement.
Canonical form of select.
• Order of operation in canonical rep.:
Project
Select
Join
The Parser
The role of the parser is to convert an SQL statement represented as a string of characters
into a parse tree.
A parse tree consists of nodes, and each node is either an:
Atom - lexical elements such as words (WHERE), attribute or relation names, constants,
operator symbols, etc.
Syntactic category - are names for query subparts.
E.g. <SFW> represents a query in select-from-where form.
Nodes that are atoms have no children. Nodes that correspond to categories have children
based on one of the rules of the grammar for the language.
3. General Example:
Parse Trees to Logical Query Trees
Converting Simplest Parse Trees to Logical Query Trees
The simplest parse tree to convert is one where there is only one select-from-where (<SFW>)
construct, and the <Condition> construct has no nested queries.
The logical query tree produced consists of:
The cross-product (×) of all relations mentioned in the <FromList> which are inputs to:
A selection operator, σC, where C is the <Condition> expression in the construct being
replaced which is the input to:
A projection, πL, where L is the list of attributes in the <SelList>
5. Converting Nested Parse Trees to Logical Query Trees
Converting a parse tree that contains a nested query is slightly more challenging. A nested query
may be correlated with the outside query if it must be re-computed for every tuple produced by
the outside query. Otherwise, it is uncorrelated, and the nested query can be converted to a non-
nested query using joins.
The nested subquery translation algorithm involves defining a tree from root to leaves as
follows:
Root node is a projection, πL, where L is the list of attributes in the <SelList> of the outer
query.
Child of root is a selection operator, σC, where C is the <Condition> expression in the
outer query ignoring the subquery.
The two-operand selection operator σ with left-child as the cross-product (×) of all relations
mentioned in the <FromList> of the outer query, and right child as the <Condition>
expression for the subquery.
The subquery itself involved in the <Condition> expression is translated to relational
algebra.
Example 3:
6. Uncorrelated
Now, we must remove the two-operand selection and replace it by relational algebra
operators.
Rule for replacing two-operand selection (uncorrelated):
Let R be the first operand, and the second operand is a <Condition> of the form t IN S. (S
is uncorrelated subquery.)
Replace <Condition> by the tree that is expression for S.
May require applying duplicate elimination if expression has duplicates.
Replace two-operand selection by one-argument selection, σC, where C is the condition
that equates each component of the tuple t to the corresponding attribute of relation S.
Give σC an argument that is the product of R and S.
7. So, example 3 becomes:
Correlated
Translating correlated subqueries is more difficult because the result of the subquery depends on
a value defined outside the query itself.
In general, correlated subqueries may require the subquery to be evaluated for each tuple of the
outside relation as an attribute of each tuple is used as the parameter for the subquery.
We will not study translation of correlated subqueries.
Distributed Query Optimization
Dynamic Approach
• The dynamic approach can be illustrated with the algorithm of Distributed INGRES.
• The objective function of the algorithm is to minimize a combination of both the
communication time and the response time.
• However, these two objectives may be conflicting. For instance, increasing communication
time (by means of parallelism) may well decrease response time.
• This query optimization algorithm ignores the cost of transmitting the data to the result
site.
8. • The algorithm also takes advantage of fragmentation, but only horizontal fragmentation is
handled for simplicity.
• Since both general and broadcast networks are considered, the optimizer takes into account
the network topology.
• In broadcast networks, the same data unit can be transmitted from one site to all the other
sites in a single transfer, and the algorithm explicitly takes advantage of this capability. For
example, broadcasting is used to replicate fragments and then to maximize the degree of
parallelism.
Static Approach
• Static approach can be illustrated with the algorithm of R*.
• This algorithm performs an exhaustive search of all alternative strategies in order to choose
the one with the least cost.
• Although predicting and enumerating these strategies may be costly, the overhead of
exhaustive search is rapidly amortized if the query is executed frequently.
• Two methods are supported for inter-site data transfers.
o Ship-whole. The entire relation is shipped to the join site and stored in a temporary
relation before being joined. If the join algorithm is merge join, the relation does
not need to be stored, and the join site can process incoming tuples in a pipeline
mode, as they arrive.
o Fetch-as-needed. The external relation is sequentially scanned, and for each tuple
the join value is sent to the site of the internal relation, which selects the internal
tuples matching the value and sends the selected tuples to the site of the external
relation. This method is equivalent to the semijoin of the internal relation with each
external tuple.
Semijoin-based Approach
• The semijoin-based approach can be illustrated with the algorithm of SDD-1 which takes
full advantage of the semijoin to minimize communication cost.
Hybrid Approach
• The hybrid query optimization technique using dynamic QEPs is general enough to
incorporate site and copy selection decisions.
9. • Several hybrid techniques have been proposed to optimize queries in distributed systems.
• They essentially rely on the following two-step approach:
o At compile time, generate a static plan that specifies the ordering of operations and
the access methods, without considering where relations are stored.
o At startup time, generate an execution plan by carrying out site and copy selection
and allocating the operations to the sites.