Rustup VS Druid

I got it to finally work by following this

If you are someone actively using such relative-path toolchains, please contact us (Discord / Github issues).

We had a snap package; we removed it in mid 2022

I don't know. The PR references prior discussion without a link, so it may have been private.

As long as he doesn't put hidden folders in your root like rust. https://github.com/rust-lang/rustup/issues/341

I think you're being upvoted by folks who don't know better, which is a shame because you're making things up :/. The telemetry feature in rustup kept everything local and never "pinged home". And you had to enable it with a command `rustup telemetry enable`. And it just logged JSON files at the path you mentioned. By 2019, the feature was disabled (see: https://github.com/rust-lang/rustup/issues/341 ) because no one worked on it and it just gathered bugs.

FWIW, there is a proposal to add telemetry to LLVM [0] and Rust used to have telemetry [1], both off by default. Some things in the node.js world have telemetry enabled by default, like Next.js [3].

Some people are posting here as if this as already decided -- AFIACT, that's not the case. It's not even a formal proposal yet, and the stated intent was to start a conversation around something concrete. (For context, this is standard for how I've seen the Go project approaches large topics, including for example I think there were something like ~8 very detailed generics design drafts from the core Go team over ~10 years).

It sounds like the Go team is going to take some time to look into some of the alternative approaches suggested in the feedback collected so far.

In any event, this is obviously a topic people are very passionate about, especially opt-in vs. opt-out, but I guess I would suggest not giving up hope quite yet.

[0] https://discourse.llvm.org/t/rfc-lldb-telemetry-metrics/6458...

[1] https://github.com/rust-lang/rustup/issues/341

[2] https://nextjs.org/telemetry

Rust (Specifically Rust Up) seems to have planned to include telemetry but they paused and cancelled the decision, possibly after implementing it initially.

https://github.com/rust-lang/rustup/issues/341 and rust installation uses telemetry

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.

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.

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.

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.

Apache Druid is part of the modern data architecture. It uses a special data format designed for analytical workloads, using extreme parallelisation to get data in and get data out. A shared-nothing, microservices architecture helps you to build highly-available, extreme scale analytics features into your applications.

Apache Druid

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.

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.

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.

Fortunately, it is super easy to build your own leveraging the binary distribution and existing docker.sh.