Druid
rust-analyzer
Our great sponsors
Druid | rust-analyzer | |
---|---|---|
24 | 132 | |
13,149 | 13,479 | |
0.5% | 2.4% | |
9.9 | 10.0 | |
4 days ago | about 4 hours ago | |
Java | Rust | |
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.
Druid
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How to choose the right type of database
Apache Druid: Focused on real-time analytics and interactive queries on large datasets. Druid is well-suited for high-performance applications in user-facing analytics, network monitoring, and business intelligence.
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Choosing Between a Streaming Database and a Stream Processing Framework in Python
Online analytical processing (OLAP) databases like Apache Druid, Apache Pinot, and ClickHouse shine in addressing user-initiated analytical queries. You might write a query to analyze historical data to find the most-clicked products over the past month efficiently using OLAP databases. When contrasting with streaming databases, they may not be optimized for incremental computation, leading to challenges in maintaining the freshness of results. The query in the streaming database focuses on recent data, making it suitable for continuous monitoring. Using streaming databases, you can run queries like finding the top 10 sold products where the “top 10 product list” might change in real-time.
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Show HN: The simplest tiny analytics tool – storywise
https://github.com/apache/druid
It's always a question of tradeoffs.
The awesome-selfhosted project has a nice list of open-source analytics projects. It's really good inspiration to dig into these projects and find out about the technology choices that other open-source tools in the space have made.
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Analysing Github Stars - Extracting and analyzing data from Github using Apache NiFi®, Apache Kafka® and Apache Druid®
As part of the developer relations team in Imply, I thought it would be interesting to extract data about users who had starred the apache/druid repository. Stars don’t just help us understand how many people find Druid interesting, they also give insight into what other repositories people find interesting. And that is really important to me as an advocate – I can work out what topics people might be interested in knowing more about in my articles and at Druid meetups.
Spencer Kimball (now CEO at CockroachDB) wrote an interesting article on this topic in 2021 where they created spencerkimball/stargazers based on a Python script. So I started thinking: could I create a data pipeline using Nifi and Kafka (two OSS tools often used with Druid) to get the API data into Druid - and then use SQL to do the analytics? The answer was yes! And I have documented the outcome below. Here’s my analytical pipeline for Github stars data using Nifi, Kafka and Druid.
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Real Time Data Infra Stack
Apache Druid
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When you should use columnar databases and not Postgres, MySQL, or MongoDB
But then you realize there are other databases out there focused specifically on analytical use cases with lots of data and complex queries. Newcomers like ClickHouse, Pinot, and Druid (all open source) respond to a new class of problem: The need to develop applications using endpoints published on analytical queries that were previously confined only to the data warehouse and BI tools.
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Druids by Datadog
Datadog's product is a bit too close to Apache Druid to have named their design system so similarly.
From https://druid.apache.org/ :
> Druid unlocks new types of queries and workflows for clickstream, APM, supply chain, network telemetry, digital marketing, risk/fraud, and many other types of data. Druid is purpose built for rapid, ad-hoc queries on both real-time and historical data.
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Mom at 54 is thinking about coding and a complete career shift. Thoughts?
Maybe rare for someone to be seeking their first coding job at that age. But plenty of us are in our 50s or older and still coding up a storm. And not necessarily ancient tech or anything. My current project exposes analytics data from Apache Druid and Cassandra via Go microservices hosted in K8s.
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Building an arm64 container for Apache Druid for your Apple Silicon
Fortunately, it is super easy to build your own leveraging the binary distribution and existing docker.sh.
rust-analyzer
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Cranelift code generation comes to Rust
go build 3.62s user 0.76s system 171% cpu 2.545 total
I was looking forward to parallel front-end[4], but I have not seen any improvement for these small changes.
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A guide on Neovim's LSP client
For example, intelephense can show diagnostics in real time, there is no need to save the file to get new diagnostics. But rust-analyzer, the language server for rust, can only update diagnostics after saving the file.
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Top 10 Rusty Repositories for you to start your Open Source Journey
6. Rust Analyzer
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LSP could have been better
Agree this is not a problem. rust-analyzer also includes a boatload of custom extensions. Here's how "query type of selected expression" works, for example:
https://github.com/rust-lang/rust-analyzer/blob/master/docs/...
For example: https://github.com/rust-lang/rust-analyzer/blob/master/docs/...
> If you create an LSP, it will work best in VS Code.
Any editor can work just as well as (or even better than) VS Code.
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Mastering Emacs: What's new in Emacs 29.1
I am not a Rust dev. It surely looks great.
However, from what I understand it seems to supply just a parser separate from the Rust compiler (https://github.com/rust-lang/rust-analyzer/tree/master/crate...) trying to keep up with Rust‘s development. So, in principle, it could have been just another treesitter parser plugin, too.
So, again, the LSP framework does not directly provide any magical benefit over a static parsing framework. All the semantic analysis capabilities stem from a good parser.
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rust-analyzer significantly slowing down compilation
You may file issue at github rust-analyzer
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Any new Opensource projects in (rust) looking for contributors. I want to start my journey as an OSS contributor.
I've contributed to rust-analyzer and nushell and had a great experience in both! Tons of open issues with a huge range of difficulties, and the maintainers are really helpful in providing hints to get started.
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I want to contribute in a big project
For something more concrete you can try and ask around on their zulip or browse their issues.
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Microsoft is rewriting core Windows libraries in Rust
More info here: https://rust-analyzer.github.io/ and here: https://rust-analyzer.github.io/manual.html#installation
What are some alternatives?
vscode-rust - Rust extension for Visual Studio Code
iced - A cross-platform GUI library for Rust, inspired by Elm
cube.js - 📊 Cube — The Semantic Layer for Building Data Applications
intellij-rust - Rust plugin for the IntelliJ Platform
Apache Cassandra - Mirror of Apache Cassandra
Apache HBase - Apache HBase
egui - egui: an easy-to-use immediate mode GUI in Rust that runs on both web and native
Scylla - NoSQL data store using the seastar framework, compatible with Apache Cassandra
rustfmt - Format Rust code
sublime-rust - The official Sublime Text 4 package for the Rust Programming Language
coc-rust-analyzer - rust-analyzer extension for coc.nvim
eglot - A client for Language Server Protocol servers