Hystrix
ClickHouse
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Hystrix | ClickHouse | |
---|---|---|
19 | 208 | |
23,877 | 34,153 | |
0.3% | 2.3% | |
2.7 | 10.0 | |
6 months ago | 13 minutes ago | |
Java | C++ | |
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.
Hystrix
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Ask HN: Modern Node.js Request Fault Tolerance Library?
Oops, forgot to include the Hystrix link, https://github.com/Netflix/Hystrix
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[OC] Gender diversity in Tech companies
They had to figure out video compression that worked at the volume that they wanted to deliver. They had to build and maintain their own CDN to be able to have a always available and consistent viewing experience. Don’t even get me started on the resiliency tools like hystrix that they were kind enough to open source. I mean, they have their own fucking data science framework and they’re looking into using neural networks to downscale video.. Sound familiar? That’s cause that’s practically the same thing as Nvidia’s DLSS (which upscales instead of downscales).
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What is a service mesh?
When breaking up a monolithic app into microservices, the communication between these services becomes vital to the health and performance of the application. Technically, you could incorporate the features to manage this traffic directly into your application. This is what Twitter, Google, and Netflix did with massive internal libraries like Finagle, Stubby, and Hysterix.
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Timestone: Netflix’s High-Throughput, Low-Latency Priority Queueing System
Hystrix: https://github.com/Netflix/Hystrix Hollow: https://hollow.how/
- Circuit Breaker Explained
- Hystrix
- I love this and wanna build something similar, I know close to zero programming though (thinking about starting)
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A tentative comparison of fault tolerance libraries on the JVM
Have you actually read the article and maybe also https://github.com/Netflix/Hystrix status section??!
I came upon Resilience4J when I was running my talk on the Circuit Breaker pattern. The talk included a demo, and it relied on Hystrix. One day, I wanted to update the demo to the latest Hystrix version and noticed that maintainers had deprecated it in favor of Resilience4J.
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Summary of the AWS Service Event in the Northern Virginia (US-East-1) Region
Netflix was talking alot about circuit breaks a few years ago, and had the Hystrix project. Looks like Hystrix is discontinued, so I'm not sure if there are good library solutions that are easy to adopt. Overall I don't see it getting talked about that frequently... beyond just exponential backoff inside a retry loop.
- https://github.com/Netflix/Hystrix
ClickHouse
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We Built a 19 PiB Logging Platform with ClickHouse and Saved Millions
Yes, we are working on it! :) Taking some of the learnings from current experimental JSON Object datatype, we are now working on what will become the production-ready implementation. Details here: https://github.com/ClickHouse/ClickHouse/issues/54864
Variant datatype is already available as experimental in 24.1, Dynamic datatype is WIP (PR almost ready), and JSON datatype is next up. Check out the latest comment on that issue with how the Dynamic datatype will work: https://github.com/ClickHouse/ClickHouse/issues/54864#issuec...
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Build time is a collective responsibility
In our repository, I've set up a few hard limits: each translation unit cannot spend more than a certain amount of memory for compilation and a certain amount of CPU time, and the compiled binary has to be not larger than a certain size.
When these limits are reached, the CI stops working, and we have to remove the bloat: https://github.com/ClickHouse/ClickHouse/issues/61121
Although these limits are too generous as of today: for example, the maximum CPU time to compile a translation unit is set to 1000 seconds, and the memory limit is 5 GB, which is ridiculously high.
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Fair Benchmarking Considered Difficult (2018) [pdf]
I have a project dedicated to this topic: https://github.com/ClickHouse/ClickBench
It is important to explain the limitations of a benchmark, provide a methodology, and make it reproducible. It also has to be simple enough, otherwise it will not be realistic to include a large number of participants.
I'm also collecting all database benchmarks I could find: https://github.com/ClickHouse/ClickHouse/issues/22398
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How to choose the right type of database
ClickHouse: A fast open-source column-oriented database management system. ClickHouse is designed for real-time analytics on large datasets and excels in high-speed data insertion and querying, making it ideal for real-time monitoring and reporting.
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Writing UDF for Clickhouse using Golang
Today we're going to create an UDF (User-defined Function) in Golang that can be run inside Clickhouse query, this function will parse uuid v1 and return timestamp of it since Clickhouse doesn't have this function for now. Inspired from the python version with TabSeparated delimiter (since it's easiest to parse), UDF in Clickhouse will read line by line (each row is each line, and each text separated with tab is each column/cell value):
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The 2024 Web Hosting Report
For the third, examples here might be analytics plugins in specialized databases like Clickhouse, data-transformations in places like your ETL pipeline using Airflow or Fivetran, or special integrations in your authentication workflow with Auth0 hooks and rules.
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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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Proton, a fast and lightweight alternative to Apache Flink
Proton is a lightweight streaming processing "add-on" for ClickHouse, and we are making these delta parts as standalone as possible. Meanwhile contributing back to the ClickHouse community can also help a lot.
Please check this PR from the proton team: https://github.com/ClickHouse/ClickHouse/pull/54870
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1 billion rows challenge in PostgreSQL and ClickHouse
curl https://clickhouse.com/ | sh
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We Executed a Critical Supply Chain Attack on PyTorch
But I continue to find garbage in some of our CI scripts.
Here is an example: https://github.com/ClickHouse/ClickHouse/pull/58794/files
The right way is to:
- always pin versions of all packages;
What are some alternatives?
Akka - Build highly concurrent, distributed, and resilient message-driven applications on the JVM
loki - Like Prometheus, but for logs.
Apache ZooKeeper - Apache ZooKeeper
duckdb - DuckDB is an in-process SQL OLAP Database Management System
Zuul - Zuul is a gateway service that provides dynamic routing, monitoring, resiliency, security, and more.
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
Ribbon - Ribbon is a Inter Process Communication (remote procedure calls) library with built in software load balancers. The primary usage model involves REST calls with various serialization scheme support.
VictoriaMetrics - VictoriaMetrics: fast, cost-effective monitoring solution and time series database
Hazelcast - Hazelcast is a unified real-time data platform combining stream processing with a fast data store, allowing customers to act instantly on data-in-motion for real-time insights.
TimescaleDB - An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
JGroups - The JGroups project
arrow-datafusion - Apache DataFusion SQL Query Engine