Apache Kafka
Apache Superset
Our great sponsors
| Apache Kafka | Apache Superset | |
|---|---|---|
| 26 | 3 | |
| 27,335 | 34,745 | |
| 1.3% | - | |
| 9.9 | 9.9 | |
| about 6 hours ago | about 3 years ago | |
| Java | Python | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Apache Kafka
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On Implementation of Distributed Protocols
Apache Kafka — a distributed event streaming platform implementing a variant of the Raft consensus protocol (written in Java, integrated with Scala);
- Implementing tagged fields for Kafka Protocol
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Help me identify this design pattern
Spring does this during autoconfiguration. For example this and this. When the user adds a configuration then it gets to overwrite the default from the template. I am looking for something similar, perhaps simpler approach.
- Kafka Broker Config properties
- Scala DevInTraining looking to contribute to projects
- *bip*
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What is Kafka ?
Source and documentation on GitHub
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A simple file source/sink connector?
Code is still in trunk though. https://github.com/apache/kafka/tree/trunk/connect/file/src/main/java/org/apache/kafka/connect/file
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Can someone please eli5 how the hierarchical timing wheel algorithm works?
I briefly described the algorithm in this article and there is a wonderful article from Kafka that goes into more depth in their general purpose implementation. My implementation is specialized and over optimized in comparison, e.g. by using bit manipulation to avoid more expensive division/modulus instructions. Tokio rewrote their timerwheel after I showed them mine, borrowing some ideas but also staying more general. Hope that helps!
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How-to-Guide: Contributing to Open Source
Apache Kafka
Apache Superset
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Using KeyCloak(OpenID Connect) with Apache SuperSet
The first difference is that after pull request 4565 was merged, you can no longer do:
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Open Source Analytics Stack: Bringing Control, Flexibility, and Data-Privacy to Your Analytics
Open-source BI platforms such as Metabase (website, GitHub) and Apache SuperSet (website, GitHub) are easy to deploy without IT involvement. Metabase lets you build dashboards from the data in your warehouse easily, with no SQL, or, if you have data engineering or science know-how, inside more powerful and flexible notebooks or with SQL itself. Similarly, Apache SuperSet helps businesses explore and visualize data from simple line charts to detailed geospatial charts.
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Ask HN: What low-code “dashboarding“ SaaS would you recommend in 2021?
Check out Superset. https://github.com/apache/incubator-superset
It’s modern, easy to extend. From the same author of apache airflow.
What are some alternatives?
celery - Distributed Task Queue (development branch)
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
Apache ActiveMQ Artemis - Mirror of Apache ActiveMQ Artemis
Grafana - The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
redpanda - Redpanda is a streaming data platform for developers. Kafka API compatible. 10x faster. No ZooKeeper. No JVM!
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
jetstream - JetStream Utilities
Redash - Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
Aeron - Efficient reliable UDP unicast, UDP multicast, and IPC message transport
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
NATS - High-Performance server for NATS.io, the cloud and edge native messaging system.
cube.js - 📊 Cube — The Semantic Layer for Building Data Applications