The document discusses hypothetical partitioning, which allows users to define and test different partitioning schemes on tables without actually partitioning them. It introduces HypoPG, an open source tool that enables hypothetical partitioning in PostgreSQL. Key points include:
- HypoPG 2 will support defining and testing hypothetical partitioning schemes to help with partitioning design.
- It allows examining query plans and costs as if different partitioning strategies were applied, without modifying real tables.
- This helps users quickly try different schemes to optimize for queries involving partitioning, pruning, joins, and aggregation.
- Future work includes better PostgreSQL integration and an automated advisor for partitioning design.
YugaByte DB - "Designing a Distributed Database Architecture for GDPR Complia...Jimmy Guerrero
Join Karthik Ranganathan (YugaByte CTO) for an in-depth technical webinar to understand how developers and administrators alike, can design systems that enable users to control the sharing and protection of their personal data so that it complies with GDPR. Topics covered include schema design, data partitioning, encryption and replication. Karthik will draw on his experience helping scale Facebook's Messenger and Inbox Search along with real-world implementations which make use of YugaByte DB.
Optimizing Time Series Performance in the Real WorldDevOps.com
In this presentation, Sam Dillard of InfluxData, will provide practical tips and techniques learned from helping hundreds of customers to deploy a time series database, InfluxDB. These techniques include: hardware and architecture choices, schema design, configuration setup and running queries.
Sam Dillard [InfluxData] | Performance Optimization in InfluxDB | InfluxDays...InfluxData
Like my past talks on this, I will give a rundown of the different levers one can pull to make InfluxDB perform better for one's use case. As I do each iteration of this, I have additional slides to add to this topic.
Most of the presentation focuses on write procedure as that is what defines schema and, ultimately, how queries will work against the DB.
If you understand the rule engine, especially how works RETE algorithm, You may use this for Machine Learning. This slide used at Red Hat Forum Tokyo 2018 session.
AWS Earth and Space 2018 - Element 84 Processing and Streaming GOES-16 Data...Dan Pilone
Presentation from AWS Earth and Space summit in Washington DC June 2018 demonstrating Element 84's serverless data processing pipeline and video encoding approach using NOAA's GOES-16 Public Data Set. More information available at https://labs.element84.com/.
YugaByte DB - "Designing a Distributed Database Architecture for GDPR Complia...Jimmy Guerrero
Join Karthik Ranganathan (YugaByte CTO) for an in-depth technical webinar to understand how developers and administrators alike, can design systems that enable users to control the sharing and protection of their personal data so that it complies with GDPR. Topics covered include schema design, data partitioning, encryption and replication. Karthik will draw on his experience helping scale Facebook's Messenger and Inbox Search along with real-world implementations which make use of YugaByte DB.
Optimizing Time Series Performance in the Real WorldDevOps.com
In this presentation, Sam Dillard of InfluxData, will provide practical tips and techniques learned from helping hundreds of customers to deploy a time series database, InfluxDB. These techniques include: hardware and architecture choices, schema design, configuration setup and running queries.
Sam Dillard [InfluxData] | Performance Optimization in InfluxDB | InfluxDays...InfluxData
Like my past talks on this, I will give a rundown of the different levers one can pull to make InfluxDB perform better for one's use case. As I do each iteration of this, I have additional slides to add to this topic.
Most of the presentation focuses on write procedure as that is what defines schema and, ultimately, how queries will work against the DB.
If you understand the rule engine, especially how works RETE algorithm, You may use this for Machine Learning. This slide used at Red Hat Forum Tokyo 2018 session.
AWS Earth and Space 2018 - Element 84 Processing and Streaming GOES-16 Data...Dan Pilone
Presentation from AWS Earth and Space summit in Washington DC June 2018 demonstrating Element 84's serverless data processing pipeline and video encoding approach using NOAA's GOES-16 Public Data Set. More information available at https://labs.element84.com/.
MySQL 8.0: What Is New in Optimizer and Executor?Norvald Ryeng
There are substantial improvements in the MySQL 8.0 optimizer. Most noticeably, support for advanced SQL features including common table expressions and window functions. The updates also make DBAs' lives easier with invisible indexes and additional hints that can be used together with the query rewrite plugin. On the performance side, cost model changes will make a huge impact. JSON support is even more powerful with the new JSON table function, aggregation functions, and more.
Presto At Arm Treasure Data - 2019 UpdatesTaro L. Saito
Presentation at Presto Conference Tokyo 2019
- Arm Treasure Data
- Plazma DB Indexes
- Real-time, Archive Storages
- Schema-on-read data processing
- Physical partition maintenance via presto-stella plugin
Funnel Analysis with Apache Spark and DruidDatabricks
Every day, millions of advertising campaigns are happening around the world.
As campaign owners, measuring the ongoing campaign effectiveness (e.g “how many distinct users saw my online ad VS how many distinct users saw my online ad, clicked it and purchased my product?”) is super important.
However, this task (often referred to as “funnel analysis”) is not an easy task, especially if the chronological order of events matters.
One way to mitigate this challenge is combining Apache Druid and Apache DataSketches, to provide fast analytics on large volumes of data.
However, while that combination can answer some of these questions, it still can’t answer the question “how many distinct users viewed the brand’s homepage FIRST and THEN viewed product X page?”
In this talk, we will discuss how we combine Spark, Druid and DataSketches to answer such questions at scale.
Engineering with Open Source - Hyonjee JooTwo Sigma
Engineering systems using open source solutions can be a powerful way to leverage existing technology. However, not all open source solutions are made or supported equally, and it’s important to choose what you use carefully. In this talk, we’ll walk through building a metrics system for a high performance data platform, taking a look at some of the important factors to consider when choosing what open source offerings to use.
Charles sonigo - Demuxed 2018 - How to be data-driven when you aren't Netflix...Charles Sonigo
How can you improve complex video software when your performance indicators are highly variable? The answer is proper methodology, proper data infrastructure and analysis.
Why Open Source Works for DevOps MonitoringDevOps.com
Learn how to use open source tools for your performance monitoring of your Infrastructure, Application, & Cloud in a way that is faster, easier, and to scale. In this webinar we will provide you with step by step instruction on how to use InfluxDB, a complete Open Source Platform built from the ground up for metrics, events, and other time-based data. We will cover how to download & configure, how to collect metrics, build dashboards and alerts.
Journey of Migrating 1 Million Presto Queries - Presto Webinar 2020Taro L. Saito
Arm Treasure Data utilizes Presto as the query engine processing over 1 million queries per day to support the data business of 500+ companies in three regions; US, EU, and Asia. Arm Treasure Data had been using Presto 0.205 and in 2019 started a big migration project to Presto 317. Although we performed extensive query simulations to check any incompatibilities, we faced many unexpected challenges during the migration at production.
Predicting Startup Market Trends based on the news and social media - Albert ...GetInData
Did you like it? Check out our blog to stay up to date: https://getindata.com/blog
Nowadays, one tweet can have impact on the value of the company or cryptocurrency. It becomes important for companies to be able to know everything what's happening in the market, especially for startups or when entering the new market. The presentation is about presenting the complex platform used for creating and verifying the strategy for a startup from the Wellbeing market. We go through web scraping-based data ingestion to ElasticSearch, NLP pipelines to understand what people write and what is the possible future of each market predicted by PySpark job.
Author: Albert Lewandowski
Linkedin: https://www.linkedin.com/in/albert-lewandowski/
___
Getindata is a company founded in 2014 by ex-Spotify data engineers. From day one our focus has been on Big Data projects. We bring together a group of best and most experienced experts in Poland, working with cloud and open-source Big Data technologies to help companies build scalable data architectures and implement advanced analytics over large data sets.
Our experts have vast production experience in implementing Big Data projects for Polish as well as foreign companies including i.a. Spotify, Play, Truecaller, Kcell, Acast, Allegro, ING, Agora, Synerise, StepStone, iZettle and many others from the pharmaceutical, media, finance and FMCG industries.
https://getindata.com
"Today Silicon Valley startup Tachyum Inc. unveiled its new processor family – codenamed “Prodigy” – that combines the advantages of CPUs with GP-GPUs, and specialized AI chips in a single universal processor platform. According to Tachyum, the new chip has "ten times the processing power per watt" and is capable of running the world’s most complex compute tasks.
With its disruptive architecture, Prodigy will enable a super-computational system for real-time full capacity human brain neural network simulation by 2020.
Tachyum’s universal processor offers the programming ease comparable to a CPU with performance and efficiency comparable to GP-GPU, for a universal-purpose processor that can handle hyperscale workloads, AI, HPC, and other demanding applications with ease. A typical hyperscale data center using servers equipped with Prodigy will provide ten times the compute performance at the same power budget. Prodigy will reduce data center TCO (total cost of ownership) by a factor of four; conversely, a Prodigy-based data center delivering the same performance as conventional servers can be built in as small as 1% the space and consume one-tenth the energy."
Learn more: https://wp.me/p3RLHQ-ivk
and
http://tachyum.com/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Big Data Pipeline for Analytics at Scale @ FIT CVUT 2014Jaroslav Gergic
The recent boom in big data processing and democratization of the big data space has been enabled by the fact that most of the concepts originated in the research labs of companies such as Google, Amazon, Yahoo and Facebook are now available as open source. Technologies such as Hadoop, Cassandra let businesses around the world to become more data driven and tap into their massive data feeds to mine valuable insights.
At the same time, we are still at a certain stage of the maturity curve of these new big data technologies and of the entire big data technology stack. Many of the technologies originated from a particular use case and attempts to apply them in a more generic fashion are hitting the limits of their technological foundations. In some areas, there are several competing technologies for the same set of use cases, which increases risks and costs of big data implementations.
We will show how GoodData solves the entire big data pipeline today, starting from raw data feeds all the way up to actionable business insights. All this provided as a hosted multi-tenant environment letting its customers to solve their particular analytical use case or many analytical use cases for thousands of their customers all using the same platform and tools while abstracting them away from the technological details of the big data stack.
HP operates a very complex HDP environment with key stakeholders and critical data across a variety of business areas: finance, supply chain, sales, and customer support. We load over 8,000 files per day, execute 1.5M lines of SQL via 6000 jobs running against 637B rows of data comprising over 5000 tables in 77 domains. Needless to say, defining our cluster size and monitoring job performance is essential for our success and the satisfaction of our stakeholders across the different business and IT organizations.
In this talk, we will describe the different sizing and allocation approaches that we went through. Our first method was a bottom-up storage-based calculation which took into account the legacy data, replication factors, overhead, and user space requirements. We quickly realized the current compute would not meet the needs of the follow-up phases of the project and that the bottom-up approach had too many assumptions and limitations.
The second method was to work top down to determine how many jobs could run with a set number of hours. This required us to calculate the number of slots for map and reduce tasks within set amount of YARN memory. To support this analysis, we developed advanced dashboards and reports that we will also share during the presentation. We captured statistics for every job and calculated the average map and reduce times. With this information, we could then calculate needed compute and storage to meet the required SLAs. And the result, the cluster grew by 88 nodes and now operates with 21 TB of YARN memory.
Speakers
Janet Li, HP inc, Big Data It Manager
Pranay Vyas, Hortonworks, Sr. Consultant
Distributed Database Architecture for GDPRYugabyte
The General Data Protection Regulation, often referred to as GDPR, came into effect on 25 May 2018 across the European Union. This regulation has implications on many global businesses, given the fines imposed if the organization is be found to be non-compliant. Making sure that the app architecture continues to ensure regulatory compliance is an on-going challenge for many businesses. This talk covesr some of the key requirements of GDPR that impact database architecture, what the inherent challenges are with requirements and how YugaByte DB can be used to implement these requirements.
Designing for Privacy in Amazon Web ServicesKrzysztofKkol1
Data privacy is one of the most critical issues that businesses face. This presentation shares insights on the principles and best practices for ensuring the resilience and security of your workload.
Drawing on a real-life project from the HR industry, the various challenges will be demonstrated: data protection, self-healing, business continuity, security, and transparency of data processing. This systematized approach allowed to create a secure AWS cloud infrastructure that not only met strict compliance rules but also exceeded the client's expectations.
TROUBLESHOOTING 9 TYPES OF OUTOFMEMORYERRORTier1 app
Even though at surface level ‘java.lang.OutOfMemoryError’ appears as one single error; underlyingly there are 9 types of OutOfMemoryError. Each type of OutOfMemoryError has different causes, diagnosis approaches and solutions. This session equips you with the knowledge, tools, and techniques needed to troubleshoot and conquer OutOfMemoryError in all its forms, ensuring smoother, more efficient Java applications.
More Related Content
Similar to Hypothetical Partitioning for PostgreSQL
MySQL 8.0: What Is New in Optimizer and Executor?Norvald Ryeng
There are substantial improvements in the MySQL 8.0 optimizer. Most noticeably, support for advanced SQL features including common table expressions and window functions. The updates also make DBAs' lives easier with invisible indexes and additional hints that can be used together with the query rewrite plugin. On the performance side, cost model changes will make a huge impact. JSON support is even more powerful with the new JSON table function, aggregation functions, and more.
Presto At Arm Treasure Data - 2019 UpdatesTaro L. Saito
Presentation at Presto Conference Tokyo 2019
- Arm Treasure Data
- Plazma DB Indexes
- Real-time, Archive Storages
- Schema-on-read data processing
- Physical partition maintenance via presto-stella plugin
Funnel Analysis with Apache Spark and DruidDatabricks
Every day, millions of advertising campaigns are happening around the world.
As campaign owners, measuring the ongoing campaign effectiveness (e.g “how many distinct users saw my online ad VS how many distinct users saw my online ad, clicked it and purchased my product?”) is super important.
However, this task (often referred to as “funnel analysis”) is not an easy task, especially if the chronological order of events matters.
One way to mitigate this challenge is combining Apache Druid and Apache DataSketches, to provide fast analytics on large volumes of data.
However, while that combination can answer some of these questions, it still can’t answer the question “how many distinct users viewed the brand’s homepage FIRST and THEN viewed product X page?”
In this talk, we will discuss how we combine Spark, Druid and DataSketches to answer such questions at scale.
Engineering with Open Source - Hyonjee JooTwo Sigma
Engineering systems using open source solutions can be a powerful way to leverage existing technology. However, not all open source solutions are made or supported equally, and it’s important to choose what you use carefully. In this talk, we’ll walk through building a metrics system for a high performance data platform, taking a look at some of the important factors to consider when choosing what open source offerings to use.
Charles sonigo - Demuxed 2018 - How to be data-driven when you aren't Netflix...Charles Sonigo
How can you improve complex video software when your performance indicators are highly variable? The answer is proper methodology, proper data infrastructure and analysis.
Why Open Source Works for DevOps MonitoringDevOps.com
Learn how to use open source tools for your performance monitoring of your Infrastructure, Application, & Cloud in a way that is faster, easier, and to scale. In this webinar we will provide you with step by step instruction on how to use InfluxDB, a complete Open Source Platform built from the ground up for metrics, events, and other time-based data. We will cover how to download & configure, how to collect metrics, build dashboards and alerts.
Journey of Migrating 1 Million Presto Queries - Presto Webinar 2020Taro L. Saito
Arm Treasure Data utilizes Presto as the query engine processing over 1 million queries per day to support the data business of 500+ companies in three regions; US, EU, and Asia. Arm Treasure Data had been using Presto 0.205 and in 2019 started a big migration project to Presto 317. Although we performed extensive query simulations to check any incompatibilities, we faced many unexpected challenges during the migration at production.
Predicting Startup Market Trends based on the news and social media - Albert ...GetInData
Did you like it? Check out our blog to stay up to date: https://getindata.com/blog
Nowadays, one tweet can have impact on the value of the company or cryptocurrency. It becomes important for companies to be able to know everything what's happening in the market, especially for startups or when entering the new market. The presentation is about presenting the complex platform used for creating and verifying the strategy for a startup from the Wellbeing market. We go through web scraping-based data ingestion to ElasticSearch, NLP pipelines to understand what people write and what is the possible future of each market predicted by PySpark job.
Author: Albert Lewandowski
Linkedin: https://www.linkedin.com/in/albert-lewandowski/
___
Getindata is a company founded in 2014 by ex-Spotify data engineers. From day one our focus has been on Big Data projects. We bring together a group of best and most experienced experts in Poland, working with cloud and open-source Big Data technologies to help companies build scalable data architectures and implement advanced analytics over large data sets.
Our experts have vast production experience in implementing Big Data projects for Polish as well as foreign companies including i.a. Spotify, Play, Truecaller, Kcell, Acast, Allegro, ING, Agora, Synerise, StepStone, iZettle and many others from the pharmaceutical, media, finance and FMCG industries.
https://getindata.com
"Today Silicon Valley startup Tachyum Inc. unveiled its new processor family – codenamed “Prodigy” – that combines the advantages of CPUs with GP-GPUs, and specialized AI chips in a single universal processor platform. According to Tachyum, the new chip has "ten times the processing power per watt" and is capable of running the world’s most complex compute tasks.
With its disruptive architecture, Prodigy will enable a super-computational system for real-time full capacity human brain neural network simulation by 2020.
Tachyum’s universal processor offers the programming ease comparable to a CPU with performance and efficiency comparable to GP-GPU, for a universal-purpose processor that can handle hyperscale workloads, AI, HPC, and other demanding applications with ease. A typical hyperscale data center using servers equipped with Prodigy will provide ten times the compute performance at the same power budget. Prodigy will reduce data center TCO (total cost of ownership) by a factor of four; conversely, a Prodigy-based data center delivering the same performance as conventional servers can be built in as small as 1% the space and consume one-tenth the energy."
Learn more: https://wp.me/p3RLHQ-ivk
and
http://tachyum.com/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Big Data Pipeline for Analytics at Scale @ FIT CVUT 2014Jaroslav Gergic
The recent boom in big data processing and democratization of the big data space has been enabled by the fact that most of the concepts originated in the research labs of companies such as Google, Amazon, Yahoo and Facebook are now available as open source. Technologies such as Hadoop, Cassandra let businesses around the world to become more data driven and tap into their massive data feeds to mine valuable insights.
At the same time, we are still at a certain stage of the maturity curve of these new big data technologies and of the entire big data technology stack. Many of the technologies originated from a particular use case and attempts to apply them in a more generic fashion are hitting the limits of their technological foundations. In some areas, there are several competing technologies for the same set of use cases, which increases risks and costs of big data implementations.
We will show how GoodData solves the entire big data pipeline today, starting from raw data feeds all the way up to actionable business insights. All this provided as a hosted multi-tenant environment letting its customers to solve their particular analytical use case or many analytical use cases for thousands of their customers all using the same platform and tools while abstracting them away from the technological details of the big data stack.
HP operates a very complex HDP environment with key stakeholders and critical data across a variety of business areas: finance, supply chain, sales, and customer support. We load over 8,000 files per day, execute 1.5M lines of SQL via 6000 jobs running against 637B rows of data comprising over 5000 tables in 77 domains. Needless to say, defining our cluster size and monitoring job performance is essential for our success and the satisfaction of our stakeholders across the different business and IT organizations.
In this talk, we will describe the different sizing and allocation approaches that we went through. Our first method was a bottom-up storage-based calculation which took into account the legacy data, replication factors, overhead, and user space requirements. We quickly realized the current compute would not meet the needs of the follow-up phases of the project and that the bottom-up approach had too many assumptions and limitations.
The second method was to work top down to determine how many jobs could run with a set number of hours. This required us to calculate the number of slots for map and reduce tasks within set amount of YARN memory. To support this analysis, we developed advanced dashboards and reports that we will also share during the presentation. We captured statistics for every job and calculated the average map and reduce times. With this information, we could then calculate needed compute and storage to meet the required SLAs. And the result, the cluster grew by 88 nodes and now operates with 21 TB of YARN memory.
Speakers
Janet Li, HP inc, Big Data It Manager
Pranay Vyas, Hortonworks, Sr. Consultant
Distributed Database Architecture for GDPRYugabyte
The General Data Protection Regulation, often referred to as GDPR, came into effect on 25 May 2018 across the European Union. This regulation has implications on many global businesses, given the fines imposed if the organization is be found to be non-compliant. Making sure that the app architecture continues to ensure regulatory compliance is an on-going challenge for many businesses. This talk covesr some of the key requirements of GDPR that impact database architecture, what the inherent challenges are with requirements and how YugaByte DB can be used to implement these requirements.
Similar to Hypothetical Partitioning for PostgreSQL (20)
Designing for Privacy in Amazon Web ServicesKrzysztofKkol1
Data privacy is one of the most critical issues that businesses face. This presentation shares insights on the principles and best practices for ensuring the resilience and security of your workload.
Drawing on a real-life project from the HR industry, the various challenges will be demonstrated: data protection, self-healing, business continuity, security, and transparency of data processing. This systematized approach allowed to create a secure AWS cloud infrastructure that not only met strict compliance rules but also exceeded the client's expectations.
TROUBLESHOOTING 9 TYPES OF OUTOFMEMORYERRORTier1 app
Even though at surface level ‘java.lang.OutOfMemoryError’ appears as one single error; underlyingly there are 9 types of OutOfMemoryError. Each type of OutOfMemoryError has different causes, diagnosis approaches and solutions. This session equips you with the knowledge, tools, and techniques needed to troubleshoot and conquer OutOfMemoryError in all its forms, ensuring smoother, more efficient Java applications.
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JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
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Globus Connect Server Deep Dive - GlobusWorld 2024Globus
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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/
Into the Box Keynote Day 2: Unveiling amazing updates and announcements for modern CFML developers! Get ready for exciting releases and updates on Ortus tools and products. Stay tuned for cutting-edge innovations designed to boost your productivity.
Your Digital Assistant.
Making complex approach simple. Straightforward process saves time. No more waiting to connect with people that matter to you. Safety first is not a cliché - Securely protect information in cloud storage to prevent any third party from accessing data.
Would you rather make your visitors feel burdened by making them wait? Or choose VizMan for a stress-free experience? VizMan is an automated visitor management system that works for any industries not limited to factories, societies, government institutes, and warehouses. A new age contactless way of logging information of visitors, employees, packages, and vehicles. VizMan is a digital logbook so it deters unnecessary use of paper or space since there is no requirement of bundles of registers that is left to collect dust in a corner of a room. Visitor’s essential details, helps in scheduling meetings for visitors and employees, and assists in supervising the attendance of the employees. With VizMan, visitors don’t need to wait for hours in long queues. VizMan handles visitors with the value they deserve because we know time is important to you.
Feasible Features
One Subscription, Four Modules – Admin, Employee, Receptionist, and Gatekeeper ensures confidentiality and prevents data from being manipulated
User Friendly – can be easily used on Android, iOS, and Web Interface
Multiple Accessibility – Log in through any device from any place at any time
One app for all industries – a Visitor Management System that works for any organisation.
Stress-free Sign-up
Visitor is registered and checked-in by the Receptionist
Host gets a notification, where they opt to Approve the meeting
Host notifies the Receptionist of the end of the meeting
Visitor is checked-out by the Receptionist
Host enters notes and remarks of the meeting
Customizable Components
Scheduling Meetings – Host can invite visitors for meetings and also approve, reject and reschedule meetings
Single/Bulk invites – Invitations can be sent individually to a visitor or collectively to many visitors
VIP Visitors – Additional security of data for VIP visitors to avoid misuse of information
Courier Management – Keeps a check on deliveries like commodities being delivered in and out of establishments
Alerts & Notifications – Get notified on SMS, email, and application
Parking Management – Manage availability of parking space
Individual log-in – Every user has their own log-in id
Visitor/Meeting Analytics – Evaluate notes and remarks of the meeting stored in the system
Visitor Management System is a secure and user friendly database manager that records, filters, tracks the visitors to your organization.
"Secure Your Premises with VizMan (VMS) – Get It Now"
In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
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.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
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.
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?
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.
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.