This document discusses messaging queues and platforms. It begins with an introduction to messaging queues and their core components. It then provides a table comparing 8 popular open source messaging platforms: Apache Kafka, ActiveMQ, RabbitMQ, NATS, NSQ, Redis, ZeroMQ, and Nanomsg. The document discusses using Apache Kafka for streaming and integration with Google Pub/Sub, Dataflow, and BigQuery. It also covers benchmark testing of these platforms, comparing throughput and latency. Finally, it emphasizes that messaging queues can help applications by allowing producers and consumers to communicate asynchronously.
This document discusses using Rails as a backend for front (BFF) layer in a microservices architecture. It describes how Rails was used to build the BFF layer for an e-commerce site called HPB, acting as an API gateway between the client and various backend services. Key points discussed include using Puma to improve throughput, caching APIs to reduce response time, and implementing an API gateway to further optimize network performance between the BFF and backend services.
The document describes MongoDB's GridFS specification for storing and retrieving files that exceed the BSON document size limit of 16MB. It explains that GridFS splits files into chunks, which are stored as individual documents, and maintains metadata about the file such as length, MD5, and filename in a separate collection. It provides examples of using the mongofiles command line tool to list, search, put, and get files from GridFS.
The document shows examples of queries that can be performed on a MongoDB collection, including finding documents by field values, regular expressions, and querying embedded documents, as well as update operations like setting values, incrementing values, pulling from arrays, and adding to arrays. It also provides examples of MapReduce operations in MongoDB and using finalize functions.
This document discusses using Rails as a backend for front (BFF) layer in a microservices architecture. It describes how Rails was used to build the BFF layer for an e-commerce site called HPB, acting as an API gateway between the client and various backend services. Key points discussed include using Puma to improve throughput, caching APIs to reduce response time, and implementing an API gateway to further optimize network performance between the BFF and backend services.
The document describes MongoDB's GridFS specification for storing and retrieving files that exceed the BSON document size limit of 16MB. It explains that GridFS splits files into chunks, which are stored as individual documents, and maintains metadata about the file such as length, MD5, and filename in a separate collection. It provides examples of using the mongofiles command line tool to list, search, put, and get files from GridFS.
The document shows examples of queries that can be performed on a MongoDB collection, including finding documents by field values, regular expressions, and querying embedded documents, as well as update operations like setting values, incrementing values, pulling from arrays, and adding to arrays. It also provides examples of MapReduce operations in MongoDB and using finalize functions.
This document discusses MongoDB replication and sharding. It begins with an introduction to MongoDB and its data model. It then covers replication with master-slave and replica sets. It also discusses sharding components including shard servers, config servers, and mongos routers. It provides examples of setting up replica sets, adding shards, and combining replica sets with sharding. The document encourages trying these techniques yourself and sharing experiences.
The document discusses MongoDB, a non-relational database that uses documents with a flexible schema rather than tables, and is well-suited for applications that need to store data in complex, nested structures. It provides an overview of key MongoDB concepts like collections, queries, indexing, updating documents, and aggregation capabilities. Examples are given of how MongoDB can be used for applications involving user profiles, blogs, and logging.
The document provides an overview of MongoDB including key concepts like collections, documents, queries, indexes, aggregation, and more. It compares MongoDB to a traditional SQL database and shows examples of common operations like insert, update, find in MongoDB shell and Node.js driver. It also briefly covers more advanced topics like geospatial queries, optimization, replication and sharding.
Inside MongoDB: the Internals of an Open-Source DatabaseMike Dirolf
The document discusses MongoDB, including how it stores and indexes data, handles queries and replication, and supports sharding and geospatial indexing. Key points covered include how MongoDB stores data in BSON format across data files that grow in size, uses memory-mapped files for data access, supports indexing with B-trees, and replicates operations through an oplog.
This document provides an overview of NoSQL and CouchDB. It discusses different types of NoSQL databases like key-value, graph, and document-oriented databases. It then focuses on CouchDB, explaining that it is written in C and Erlang, supports ACID properties, master-master replication, and uses JSON and HTTP with a RESTful API. Examples are given of CRUD operations using HTTP requests. It also discusses CouchDB's views using MapReduce and describes CouchDB's advantages like simplicity, flexibility, and backups, with disadvantages around performance.
This document discusses refactoring Java code to Clojure using macros. It provides examples of refactoring Java code that uses method chaining to equivalent Clojure code using the threading macros (->> and -<>). It also discusses other Clojure features like type hints, the doto macro, and polyglot projects using Leiningen.
This document discusses using MongoDB as a log collector. It provides examples of storing log data from syslog-ng in MongoDB collections, including filtering and parsing logs. It also gives examples of analyzing the log data through map-reduce to find top IP addresses and provides ideas for other uses like CAPTCHAs, error localization, and analytics.
Map/reduce, geospatial indexing, and other cool features (Kristina Chodorow)MongoSF
The document appears to be notes from a MongoDB training session that discusses various MongoDB features like MapReduce, geospatial indexes, and GridFS. It also covers topics like database commands, indexing, and querying documents with embedded documents and arrays. Examples are provided for how to implement many of these MongoDB features and functions.
The document discusses using MongoDB as a log collector. It provides an agenda that includes who the presenter is, how logging is currently done, and ideas for using MongoDB for logging in the future. Specific topics covered include using syslog-ng to send logs to MongoDB, examples of logging Apache traffic, and map-reduce examples for analyzing logs like finding the top 10 IP addresses.
From mysql to MongoDB(MongoDB2011北京交流会)Night Sailer
The document summarizes differences between MySQL and MongoDB data types and operations. MongoDB uses BSON for data types rather than separate numeric, text and blob types. It supports embedded documents and arrays. Unlike MySQL, MongoDB does not have tables or rows, but collections and documents. Operations like insert, update, find, sort and index are discussed as alternatives to SQL equivalents.
This document summarizes a MongoDB live coding session presented by Tobias Trelle. It introduces MongoDB concepts like documents, collections, CRUD operations, queries including geospatial queries, replication, sharding, and the Java and Spring Data APIs. It also advertises MongoDB user groups in Dusseldorf and Frankfurt organized by codecentric AG.
Mapping Flatland: Using MongoDB for an MMO Crossword Game (GDC Online 2011)Grant Goodale
WordSquared is a massively multiplayer online scrabble crossword that uses MongoDB to store location data. Players place tiles in realtime, and compete to build the longest chain of words and earn points. WordSquared leverages MongoDB's built-in geospatial indexing, storing an x and y coordinate with each tile and using bounding box queries to
display a view of the board.
This presentation covers the architecture of the game, with a specific focus on the use of MongoDB, storing and querying location data, and learning how to structure and even shard geo data through the unlikely use
case of an infinitely large board game.
The document provides an agenda for a presentation on getting expertise with MongoDB design patterns. It includes sections on MongoDB recap, how MongoDB works, the _id field, query execution order, indexes, replication, sharding, and introduces the presenters.
MongoDB: Optimising for Performance, Scale & AnalyticsServer Density
MongoDB is easy to download and run locally but requires some thought and further understanding when deploying to production. At scale, schema design, indexes and query patterns really matter. So does data structure on disk, sharding, replication and data centre awareness. This talk will examine these factors in the context of analytics, and more generally, to help you optimise MongoDB for any scale.
Presented at MongoDB Days London 2013 by David Mytton.
The document discusses schema design basics for MongoDB, including terms, considerations for schema design, and examples of modeling different types of data structures like trees, single table inheritance, and many-to-many relationships. It provides examples of creating indexes, evolving schemas, and performing queries and updates. Key topics covered include embedding data versus normalization, indexing, and techniques for modeling one-to-many and many-to-many relationships.
This document summarizes a presentation about unit testing Spark applications. The presentation discusses why it is important to run Spark locally and as unit tests instead of just on a cluster for faster feedback and easier debugging. It provides examples of how to run Spark locally in an IDE and as ScalaTest unit tests, including how to create test RDDs and DataFrames and supply test data. It also discusses testing concepts for streaming applications, MLlib, GraphX, and integration testing with technologies like HBase and Kafka.
Ensuring High Availability for Real-time Analytics featuring Boxed Ice / Serv...MongoDB
This will cover what to consider for high write throughput performance from hardware configuration through to the use of replica sets, multi-data centre deployments, monitoring and sharding to ensure your database is fast and stays online.
MySQL flexible schema and JSON for Internet of ThingsAlexander Rubin
My presentation at Oracle Open World Conference 2017: Using MySQL Flexible Schema (Document Store/JSON) for IoT
Tuesday, Oct 03, 11:30 a.m. - 12:15 p.m. | Marriott Marquis (Yerba Buena Level) - Salon 14
Storing data from sensors (Internet of Things) may be challenging in many respects, specifically due to the changing nature of the data. For example, if you have a fixed table structure and a sensor will need to store new property, it will be hard to make this change. This session discusses different options for implementing flexible schemas with MySQL 5.7 and MySQL 8.0, using JSON and calculated fields as well as the MySQL Document Store feature. It includes a demo with IoT devices where data is stored in MySQL 8.0.
The document discusses NoSQL databases and MongoDB in particular. It provides examples of MongoDB documents with different data types like objects, arrays, etc. It also shows how data is stored across multiple shard servers and accessed via mongos query routers. Configuration servers store sharded cluster metadata. Log data can be stored in MongoDB but only aggregated results data may be needed. HDFS is better for temporary raw log storage.
An Introduction to Fluent & MongoDB PluginsTakahiro Inoue
This document discusses Fluent, an open source data collector. It has structured logging, a pluggable architecture, and reliable forwarding. It also mentions that Sadayuki Furuhashi of Treasure Data presented information on Fluent and its event collector service.
The document provides examples of using the TinkerGraph graph database and Gremlin traversal language. It shows how to:
1) Create a TinkerGraph, add vertices and edges, and get basic graph information and elements.
2) Perform common traversals in Gremlin such as getting vertex neighbors, paths, filtering, transforming properties, and looping through connections.
3) Demonstrate more complex multi-step traversals using pipes and filters, conditional branching, and other Gremlin steps and predicates.
1. Neo4j is a graph database that allows for modeling and querying of graph-like data structures.
2. The document demonstrates how to create a graph using Neo4j by adding nodes and relationships between them in a transaction.
3. Neo4j also supports indexing of node properties to enable efficient querying and retrieval of nodes by their properties. Different types of indexes like Lucene are supported.
Graph databases use endogenous indices to index vertices by their properties. This allows for efficient lookups of vertices that match specific property values. For example, a graph database may have indices on the "name" and "views" properties of vertices to enable fast lookups of vertices by those property values. The indices are part of the graph structure itself rather than being an external component.
The document describes different MongoDB collections and queries. It shows examples of collections that store products, orders, user profiles and analytics data. It also demonstrates queries that retrieve, update and aggregate data across multiple collections using operators like $inc, $push, $unset and $or. The document provides examples of indexing, explain plans, and journaling configurations.
"Zero-sales lost — Incident Management", Igor DrozdFwdays
In my presentation, I will discuss the key aspects of the Zero Sales Lost strategy, focusing on incident management in the context of E-commerce development and the "Silpo" ecosystem. I will share our experience in building an incident management process, the specifics of monitoring and alerting system architecture, and how we scaled these processes across 19 products and 41 teams.
Additionally, we will explore the role of DevOps culture and team responsibility in product development. Using real case studies, we will analyze whether critical failures can be prevented and how to achieve that effectively.
This is a comprehensive guide explaining how blockchain technology works, its key features, and real-world applications in industries like finance, supply chain, and retail. Learn about different blockchain networks (public, private, and consortium) and the challenges businesses face in adopting blockchain. Discover how blockchain consulting can help businesses implement secure, transparent, and efficient solutions, reducing risks and optimizing operations. This guide is ideal for businesses exploring blockchain adoption and seeking expert guidance.
Leadership u automatizaciji: RPA priče iz prakse!UiPathCommunity
Dobrodošli na "AI Powered Automation Leadership Talks", online događaj koji okuplja senior lidere i menadžere iz različitih industrija kako bi podelili svoja iskustva, izazove i strategije u oblasti RPA (Robotic Process Automation). Ovaj događaj pruža priliku da zavirite u način razmišljanja ljudi koji donose ključne odluke u automatizaciji i liderstvu.
📕 Kroz panel diskusiju sa tri izuzetna stručnjaka, istražićemo:
Kako uspešno započeti i skalirati RPA projekte u organizacijama.
Koji su najveći izazovi u implementaciji RPA-a i kako ih prevazići.
Na koje načine automatizacija menja radne procese i pomaže timovima da ostvare više.
Bez obzira na vaše iskustvo sa UiPath-om ili RPA uopšte, ovaj događaj je osmišljen kako bi bio koristan svima – od menadžera do tehničkih lidera, i svima koji žele da unaprede svoje razumevanje automatizacije.
Pridružite nam se i iskoristite ovu jedinstvenu priliku da naučite od onih koji vode automatizaciju u svojim organizacijama. Pripremite svoja pitanja i inspiraciju za sledeće korake u vašoj RPA strategiji!
Revolutionizing Field Service: How LLMs Are Powering Smarter Knowledge Access...Earley Information Science
Revolutionizing Field Service with LLM-Powered Knowledge Management
Field service technicians need instant access to accurate repair information, but outdated knowledge systems often create frustrating delays. Large Language Models (LLMs) are changing the game—enhancing knowledge retrieval, streamlining troubleshooting, and reducing technician dependency on senior staff.
In this webinar, Seth Earley and industry experts Sanjay Mehta, and Heather Eisenbraun explore how LLMs and Retrieval-Augmented Generation (RAG) are transforming field service operations. Discover how AI-powered knowledge management is improving efficiency, reducing downtime, and elevating service quality.
LLMs for Instant Knowledge Retrieval – How AI-driven search dramatically cuts troubleshooting time.
Structured Data & AI – Why high-quality, organized knowledge is essential for LLM success.
Real-World Implementation – Lessons from deploying LLM-powered knowledge tools in field service.
Business Impact – How AI reduces service delays, optimizes workflows, and enhances technician productivity.
Empower your field service teams with AI-driven knowledge access. Watch the webinar to see how LLMs are revolutionizing service efficiency.
Not a Kubernetes fan? The state of PaaS in 2025Anthony Dahanne
Kubernetes won the containers orchestration war. But has it made deploying your apps easier?
Let's explore some of Kubernetes extensive app developer tooling, but mainly what the PaaS space looks like in 2025; 18 years after Heroku made it popular.
Is Heroku still around? What about Cloud Foundry?
And what are those new comers (fly.io, railway, porter.sh, etc.) worth?
Did the Cloud giants replace them all?
Kickstart Your QA: An Introduction to Automated Regression Testing ToolsShubham Joshi
For teams eager to elevate their quality assurance practices, this guide offers an introductory look at automated regression testing tools. In the realm of software development, regression tests are vital to ensuring that recent code changes don’t inadvertently break existing functionality. This article demystifies how automated regression testing tools function and why they’re indispensable for maintaining software quality. It covers the basics of setting up automated tests, integrating these tests into your CI/CD pipelines, and choosing the right tool to match your project’s needs. With clear explanations and actionable insights, you’ll discover how these tools help reduce manual testing burdens and catch bugs early. The guide also highlights common challenges beginners face and offers practical solutions to overcome them. Whether you’re a QA professional or a developer stepping into the world of test automation, this resource will help you kickstart your journey toward more reliable, efficient, and scalable testing practices.
Dev Dives: Unlock the future of automation with UiPath Agent BuilderUiPathCommunity
This webinar will offer you a first look at the powerful capabilities of UiPath Agent Builder, designed to streamline your automation processes and enhance your workflow efficiency.
📕 During the session, you will:
- Discover how to build agents with low-code experience, making it accessible for both developers and business users.
- Learn how to leverage automations and activities as tools within your agents, enabling them to handle complex and dynamic workflows.
- Gain insights into the AI Trust Layer, which provides robust management and monitoring capabilities, ensuring trust and transparency in your automation processes.
- See how agents can be deployed and integrated with your existing UiPath cloud and Studio environments.
👨🏫 Speaker:
Zach Eslami, Sr. Manager, Product Management Director, UiPath
⏩ Register for our upcoming Dev Dives March session:
Unleash the power of macOS Automation with UiPath
👉 AMER: https://bit.ly/Dev_Dives_AMER_March
👉 EMEA & APJ:https://bit.ly/Dev_Dives_EMEA_APJ_March
This session was streamed live on February 27, 2025, 15:00 GMT.
Check out future Dev Dives 2025 sessions at:
🚩 https://bit.ly/Dev_Dives_2025
Big Data Analytics Quick Research Guide by Arthur Morgan (PREVIEW)Arthur 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 (coming 2025)
- 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.
The Constructor's Digital Transformation Playbook: Reducing Risk With TechnologyAggregage
https://www.professionalconstructorcentral.com/frs/27678427/the-constructor-s-digital-transformation-playbook--reducing-risk-with-technology
Reduce risk and boost efficiency with digital transformation in construction. Join us to explore how AI, automation, and data-driven insights can improve project safety and streamline operations.
Supercharge Your Career with UiPath CertificationsDianaGray10
Join us on February 25th as we discuss how you can supercharge your career with the updated 2025 UiPath Certifications.
Diana Gray, UiPath Senior Community Marketing Manager, Americas, will walk us through:
-- Workforce Trends
-- Value of UiPath Certifications
-- Certification Program
-- Steps to Earning a Certificate
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 (coming 2025)
- 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.
"Reality of Managing 100+ “Managed” RDS Postgres Databases", Mykyta HlushakFwdays
During the lecture, Mykyta will share the story of Solidgate's journey in building a high-performing and reliable fintech company, striving for 99.999% uptime on AWS’s SaaS platform. He'll uncover numerous caveats in doing things right without full system access, addressing product requirements, and staying up to date.
In this pdf inculde the slide that shows about the use of nano technology in agriculture that is also a content for BSC agriculture and MSc agriculture ( in favour agronomy support)
Caching for Performance Masterclass: The In-Memory DatastoreScyllaDB
Understanding where in-memory data stores help most and where teams get into trouble.
- Where in the stack to cache
- Memcached as a tool
- Modern cache primitives
Recipes are a major leap forward for adopting Drupal and website building in general. Learn how they can also make it easier than ever to manage dates and times in your website.
Webinar: LF Energy GEISA: Addressing edge interoperability at the meterDanBrown980551
This webinar will introduce the Grid Edge Security and Interoperability Alliance, or GEISA, an effort within LF Energy to address application interoperability at the very edge of the utility network: meters and other distribution automation devices. Over the last decade platform manufacturers have introduced the ability to run applications on electricity meters and other edge devices. Unfortunately, while many of these efforts have been built on Linux, they haven’t been interoperable. APIs and execution environment have varied from one manufacturer to the next making it impossible for utilities to obtain applications that they can run across a fleet of different devices. For utilities that want to minimize their supply chain risk by obtaining equipment from multiple suppliers, they are forced to run and maintain multiple separate management systems. Applications available for one device may need to be ported to run on another, or they may not be available at all.
GEISA addresses this by creating a vendor neutral specification for utility edge computing environments. This webinar will discuss why GEISA is important to utilities, the specific issues GEISA will solve and the new opportunities it creates for utilities, platform vendors, and application vendors.