Pinterest Engineering’s Post

🚀 Exciting News! 🚀 I'm excited to share about a project that I have started working on recently. The News-Archiver Site! In today's media landscape, it's evident that news reporting can vary significantly depending on the source. With CNN and Fox News just a click away, you often find headlines that seem to originate from different universes. 🌍 That's why I'm excited to announce News-Archiver, a project aimed at providing historical insights into news reporting. Every 30 minutes, News-Archiver meticulously archives the trending articles from both Fox News and CNN, allowing users to delve into the past and witness how news is reported over time. 📊 But the vision doesn't stop there! In the future, I plan to expand the archiving capabilities to include other prominent news sources like CBS, MSNBC, The New York Times, and more. Together, we can gain a comprehensive understanding of the media landscape and foster informed discussions. 💡 On the technical side, I'll be leveraging Firebase's Cloud Functions to execute a background job every 30 minutes. Using a node environment and the amazing Puppeteer library, I'll scrape the latest trending articles from Fox News and CNN. This ensures that the archive remains up-to-date and comprehensive. ⚙️ To store this valuable data, I'm considering utilizing Firebase's Cloud Storage or exploring NoSQL databases like MongoDB. These options will provide scalability, flexibility, and efficient data management. 🗄️ For the frontend implementation, I'm excited to experiment with Svelte, a lightweight framework perfect for this type of application. However, if needed, I'll implement the frontend in React to create a more complete experience. 🖥️ News-Archiver is an open-source project, and I welcome any feedback or suggestions you may have. If you are experienced with any of the technologies mentioned or if you're interested in learning more about them, I encourage you to connect with me. Let's collaborate and make a difference in bridging the gap in news reporting! 🤝 https://lnkd.in/gzWGyFiF #NewsArchiver #MediaAnalysis #OpenSourceProject #TechCommunity

Discover how Pinterest overcame HBase limitations by leveraging TiDB's next-gen storage system for its Global Platform. 🌐 Learn why TiDB was selected as the best scalable solution 📈 by delivering cost reduction, stronger consistency, and better latency! The first article of the 3-part series provides an overview of how HBase was used at Pinterest, why #Pinterest ultimately decided to migrate away from it, and why TiDB was the clear upgrade. Dive into this article from Pinterest Engineering’s Alberto Ordonez Pereira, Senior Staff Software Engineer and Lianghong Xu, Senior Manager, Engineering to get all the insights. #DistributedSQL #NoSQL #HBase

Spent some time delving into the intricacies of the "MapReduce" research paper. MapReduce, a distributed system, serves as a illustration of scalability, high availability, fault tolerance, and consistency. Originally conceived by Google to streamline data processing on clusters. The essence of the paper revolves around the division of processing into map and reduce tasks, which execute in parallel across nodes in a cluster. The elegance lies in the fact that user applications can harness the abstracted nature of the MapReduce framework. This abstraction shields developers from the complexities of distributed processing, allowing them to focus solely on coding the essential business logic. Checkout my implementation of MapReduce paper in Go:

InfiniBox™ SSA II named Storage Product of the Year 2023 Know more:-https://lnkd.in/djnrZ4ve Infinidat #aitechparknews #aitechnology #artificialintelligence #technology #innovation #aitech #machinelearning #python #deeplearning  

Infinidat on the 2024 Storage 100 list for Software Defined Storage Know more:-https://lnkd.in/dENEk2jA #storage #aitechparknews #aitechnology #artificialintelligence #technology #innovation #aitech #machinelearning #python #deeplearning 

Second post of Clojure Adventures! It still takes too much time creating the post because of my laziness 🤣 Hope you all can learn from this tutorial! https://lnkd.in/gTX-V2sC

Writing a Partitioned Cache Using Go Map (x3 Faster than the Standard Map) https://lnkd.in/eKx-a_Zu