Mule Transformers can alter message properties, variables, or payloads to prepare them for further processing. Standard transformers are provided to handle common data conversion scenarios, such as XML-to-Object. If no single transformer achieves the needed output, multiple transformers can be used sequentially. Transformer categories include those for Java Objects, Content, SAP, Scripting, Properties/Variables/Attachments. The DataWeave transformer provides powerful data querying and transformation capabilities.
Java is the native language in which Mule is coded.
The Java component enables the developer to package custom Java code that executes when the component receives a message.
The Java component can be used to enhance the functionality and capability of your web-based applications written in Java.
Java is the native language in which Mule is coded.
The Java component enables the developer to package custom Java code that executes when the component receives a message.
The Java component can be used to enhance the functionality and capability of your web-based applications written in Java.
This presentation provides an overview on Mule ESB's error handling capabilities. System and Messaging exception strategies are explained with examples in this presentation.
The objective of this tutorial is to demonstrate the implementation of Mule caching strategy with REDIS cache using Spring Data Redis module. Mule caching strategy is associated with Mule Cache scope and it is used to define the actions a cache scope takes when a message enters its subflow. In this tutorial, we will be using a simple use case to show the steps require to cache the query results of an Oracle database table into Redis cache using Spring Data Redis module.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
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.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
Navigating the Metaverse: A Journey into Virtual Evolution"Donna Lenk
Join us for an exploration of the Metaverse's evolution, where innovation meets imagination. Discover new dimensions of virtual events, engage with thought-provoking discussions, and witness the transformative power of digital realms."
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
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/
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
Enhancing Project Management Efficiency_ Leveraging AI Tools like ChatGPT.pdfJay Das
With the advent of artificial intelligence or AI tools, project management processes are undergoing a transformative shift. By using tools like ChatGPT, and Bard organizations can empower their leaders and managers to plan, execute, and monitor projects more effectively.
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.
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.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
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.
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
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.
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.
2. Instructions
• Prepares a message for further processing by
enhancing or altering the contents of the
message properties, variables, or payload
• Use a pre-built transformer to perform a
standard data conversion
3. Example
• Message source in a flow receives data in XML
format, but a downstream message processor
expects a Java object
• Use an XML-to-Object transformer to convert
the format of the message payload
4. Transformer Library
• Mule provides a set of standard transformers
to handle the most common data
transformation scenarios
• If Mule doesn’t have the particular
transformer, can arrange several transformers
in a sequence to achieve the output you need
5. Transformer Library Example
• Implement an A-to-C transformation but no such
transformer exists
• Arrange a sequence – A-to-B, B-to-C – which
effectively simulates an A-to-C transformer
• Example:
– convert XML to JSON, use an XML-to-Object
transformer followed by an Object-to-JSON
transformervely simulates an A-to-C transformer
6. Transformers categories - Java Object
• Each transformer in this group changes a Java
object into another Java object
• A Java object into a non-Java data type (such
as an HTTP request), or vice versa
• Example Transformers:
– JSON to Object
– XML to Object
7. Transformers categories - Content
• Transformers modifies messages by adding to,
deleting from, or converting a message
payload
• Example Transformers:
– Append String
– Expression
– Parse Template
– XSLT
8. Transformers categories - SAP
• Change SAP objects (JCo functions or IDoc
documents) into XML representations, or vice
versa
• Example Transformers:
– SAP Object to XML
– XML to SAP Function (BAPI)
– XML to SAP IDoc
9. Transformers categories - Script
• Utilizes a custom script to perform the
transformation
• Just add one of these to your flow, then write a script
in your favorite language to convert data as needed
• Example Transformers:
– Groovy
– JavaScript
– Python
– Ruby
– Script
10. Transformers categories - Properties,
Variables, and Attachments
• Add, remove, or copy properties, variables, and
attachments on the message
• Message processors doesn’t so much transform as
manipulate or enrich the contents of the message
header
• Example Transformers:
– Attachment
– Property
– Session Variable
– Variable
11. DataWeave Transformer
• Overview DataWeave:
– Simple, powerful tool used to query and transform data
inside of Mule
– Supports a variety of transformations: simple one-to-one,
one-to-many or many-to-one mappings from an
assortment of data structures
12. DataWeave Transformer
• Map an input field, such as last_name, to a different
output field, such as family_name
• Map multiple fields, such as title, first_name, and last_name,
to a composite output field such as full_name
• Retrieve session state information in a message to
facilitate conditional message routing
• Evaluation to facilitate conditional value recalculation
• Look up information in tables or other flows