In this third, extensively illustrated post of his windowing blog series, Bill Bejeck demonstrates sliding windows in Kafka Streams, and their logical equivalent in #FlinkSQL, OVER aggregations. Learn about use cases, like running average calculations, and more, here ➡️ https://cnfl.io/3W7N7qS
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Looking for practical #ApacheFlink use case examples? Our go-to Flink experts, David Anderson, Martijn Visser, and Chesnay Schepler, have curated a collection of best practice solutions that showcase common patterns and use cases for Flink. These recipe examples can help you tackle a variety of common on-premise challenges such as: ⚪ Deserializing JSON from Kafka ⚪ Joining and deduplicating data ⚪ Doing complex event processing ⚪ Using session windows … and many more! Take a look and share what you are building with us!
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Team Lead | Integration Specialist at Conestoga College with expertise in Azure Data Factory & Data Warehousing & Azure Databricks
Lake architecture Spark Apache Delta Lake
Fabric Runtime 1.3, based on Apache Spark 3.5 and Delta Lake 3.0, has been released to all production regions as an Experimental Preview! You can now use it for early access to new features and improvements. Check the documentation: https://lnkd.in/dJFG9uE8 🙌 👏👏👏 Ashit Gosalia Justyna Lucznik Ajith S Akshay Tayal ABHISHEK UPMANYU Christopher Finlan Raghav Sidhanti Daniel Coelho Faruk Celik Mimi Gentz Andrew Fogarty
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🚀 Sharing a quick-read blog post on Apache Spark Unified Memory! This post helps you understand concepts like memory pools, reserved memory, and overhead memory. Check it out for insights on optimizing memory usage and improving Spark application performance. 📝 Read more - https://lnkd.in/ejh7EBZr #ApacheSpark #DataEngineering #MemoryManagement
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Let’s talk #ApacheKafka consumer Group IDs. 🪪 They play a key role in Kafka’s compute layer, making it highly scalable. Consumer Group IDs come into play in 2 areas that we’ll look at in this video: 🪓 Work sharing. ⚖️ Rebalancing. Consumers in the same group share work among themselves, given always that only one consumer in the group can read from a given topic partition at the same time. As far as rebalancing goes, consumers in a single group each send a heartbeat request 💗 to the broker– if the consumer does not respond in time, a rebalance is triggered. 🧱 Both of these processes are predicated on the presence of a Group ID to unify the consumer group! 🎥 Learn more about the purpose of Kafka consumer Group IDs with Lucia Cerchie in this byte-sized video.
Introduction to Consumer Group IDs | Apache Kafka® Explained
https://www.youtube.com/
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When sinking data from #ApacheKafka to #OpenSearch (or #ElasticSearch) via Kafka Connect, if the message includes a timestamp, you might need to change the format for it to be automatically recognised as such. Check out how you can to it using the TimestampConverter SMT
Kafka Connect sink to OpenSearch/ElasticSearch: how to sink unix timestamps
ftisiot.net
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📢 Expanding on last week's exploration of Apache Kafka use cases, we're excited to show you how Axual Governance can facilitate the implementation of these scenarios. In this demo, we show you: ✅ How to onboard an Aiven cluster ✅ How to invite a colleague ✅ How to assign topics and onboard applications 🔗 Eager to discuss your specific use case? Click the link in the comments to contact us!
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Practice processing with #FlinkSQL by completing a hands-on exercise that teaches you how to deduplicate events from an Apache Kafka stream. You'll learn about sub-queries, the PARTITION BY & ORDER BY clauses, & the ROW_NUMBER() function. Full test steps are included. Check it out here ➡️ https://cnfl.io/4bjhhfr
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Day 6: Producers, part of the Kafka client library, make it easy to send events to Kafka topics. They handle things like partition assignment, serialization, compression, and more https://lnkd.in/eK_54Z5h #100DaysOfCode #apachekafka
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This article will teach you how to install and manage Apache Kafka on Kubernetes with the Strimzi operator. More: https://lnkd.in/gzGK4Xdz
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