zsv
k9s
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zsv
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Analyzing multi-gigabyte JSON files locally
If it could be tabular in nature, maybe convert to sqlite3 so you can make use of indexing, or CSV to make use of high-performance tools like xsv or zsv (the latter of which I'm an author).
https://github.com/BurntSushi/xsv
https://github.com/liquidaty/zsv/blob/main/docs/csv_json_sql...
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Show HN: Up to 100x Faster FastAPI with simdjson and io_uring on Linux 5.19
Parsing CSV doesn't have to be slow if you use something like xsv or zsv (https://github.com/liquidaty/zsv) (disclaimer: I'm an author). The speed of CSV parsers is fast enough that unless you are doing something ultra-trivial such as "count rows", your bottleneck will be elsewhere.
The benefits of CSV are:
- human readable
- does not need to be typed (sometimes, data in the raw such as date-formatted data is not amenable to typing without introducing a pre-processing layer that gets you further from the original data)
- accessible to anyone: you don't need to be a data person to dbl-click and open in Excel or similar
The main drawback is that if your data is already typed, CSV does not communicate what the type is. You can alleviate this through various approaches such as is described at https://github.com/liquidaty/zsv/blob/main/docs/csv_json_sql..., though I wouldn't disagree that if you can be assured that your starting data conforms to non-text data types, there are probably better formats than CSV.
The main benefit of Arrow, IMHO, is less as a format for transmitting / communicating but rather as a format for data at rest, that would benefit from having higher performance column-based read and compression
- Yq is a portable yq: command-line YAML, JSON, XML, CSV and properties processor
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csvkit: Command-line tools for working with CSV
I wanted so much to use csvkit and all the features it had, but its horrendous performance made it unscalable and therefore the more I used it, the more technical debt I accumulated.
This was one of the reasons I wrote zsv (https://github.com/liquidaty/zsv). Maybe csvkit could incorporate the zsv engine and we could get the best of both worlds?
Examples (using majestic million csv):
---
- Ask HN: Programs that saved you 100 hours? (2022 edition)
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Show HN: Split CSV into multiple files to avoid the Excel's 1M row limitation
}
```
This of course assumes that each line is a single record, so you'll need some preprocessing if your CSV might contain embedded line-ends. For the preprocessing, you can use something like the `2tsv` command of https://github.com/liquidaty/zsv (disclaimer: I'm its author), which converts CSV to TSV and replaces newline with \n.
You can also use something like `xsv split` (see https://lib.rs/crates/xsv) which frankly is probably your best option as of today (though zsv will be getting its own shard command soon)
- Run SQL on CSV, Parquet, JSON, Arrow, Unix Pipes and Google Sheet
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Ask HN: Best way to find help creating technical doc (open- or closed-source)?
Am looking for one-time help creating documentation (e.g. man pages, tutorials) for open source project (e.g. https://github.com/liquidaty/zsv) as well as product documentation for commercial products, but not enough need for a full-time job. Requires familiarity with, for lack of better term, data janitorial work, and preferably with methods of auto-generating documentation. Any suggestions as to forums or other ways to find folks who might fit the bill for ad-hoc or part-time work of this nature?
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Q – Run SQL Directly on CSV or TSV Files
Nice work. I am a fan of tools like this and look forward to giving this a try.
However, in my first attempted query (version 3.1.6 on MacOS), I ran into significant performance limitations and more importantly, it did not give correct output.
In particular, running on a narrow table with 1mm rows (the same one used in the xsv examples) using the command "select country, count() from worldcitiespop_mil.csv group by country" takes 12 seconds just to get an incorrect error 'no such column: country'.
using sqlite3, it takes two seconds or so to load, and less than a second to run, and gives me the correct result.
Using https://github.com/liquidaty/zsv (disclaimer, I'm one of its authors), I get the correct results in 0.95 seconds with the one-liner `zsv sql 'select country, count() from data group by country' worldcitiespop_mil.csv`.
I look forward to trying it again sometime soon
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A Trillion Prices
All this banter arguing over CSV, JSON, sqlite seems unnecessary when you can just push format X through a pipe and get whichever format Y you want back out: https://github.com/liquidaty/zsv/blob/main/docs/csv_json_sql...
(disclaimer: I'm one of the zsv authors)
k9s
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Upgrading Hundreds of Kubernetes Clusters
Pierre: The first tool I recommend is K9s. It's not just a time-saver but a productivity booster. With its intuitive interface, you can speed up all the usual kubectl commands, access logs, edit resources and configurations, and more. It's like having a personal assistant for your cluster management tasks.
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Easy Access to Terminal Commands in Neovim using FTerm
The last thing you really need is a common set of tools that you want fingertip access to. I really commonly use LazyGit and K9s in my day job so those are the tools I will show off in this article.
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🎀 Five tools to make your K8s experience more enjoyable 🎀
K9s is your best friend (get it? 🐶) when exploring your cluster via the terminal. It shares commonality with Vim for its interaction style using shortcuts and starting commands with: but don’t let that discourage you. K9s keeps a vigilant eye on Kubernetes activities, providing real-time information and intuitive commands for resource interaction.
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Building a Kubernetes Operator with the Operator Framework
k9s: brew install k9s
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Harlequin: SQL IDE for Your Terminal
I would like to put in a vote for k9s, which is also on the list at Terminal Trove. [0] It's the most convenient tool I've ever found for Kubernetes management. Based on that experience I'll definitely be checking out Harlequin.
[0] https://k9scli.io/
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Your First K8S+Istio
$ wget https://github.com/derailed/k9s/releases/download/v0.29.1/k9s_Darwin_amd64.tar.gz $ tar -xzf k9s_Darwin_amd64.tar.gz $ sudo mv k9s /usr/local/bin/
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Seeking Guidance for Transitioning to Kubernetes and SRE/DevOps for traditional infrastructure team
All in all, run things, do some kubectl apply -f something.yml every day, install k9s, and try to configure a big one cluster at some point.
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Architecting for Resilience: Crafting Opinionated EKS Clusters with Karpenter & Cilium Cluster Mesh — Part 1
(K9s is one of my favorite tools for navigating Kubernetes clusters through the CLI).
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Top 10 CLI Tools for DevOps Teams
K9s is an open-source, terminal-based UI for interacting with your Kubernetes clusters, making navigating, observing, and managing your apps easier. If you use Kubectl but wish it was easier and faster to use, K9s might be just what you're looking for!
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Use Tetragon to Limit Network Usage for a set of Binary
k9s
What are some alternatives?
visidata - A terminal spreadsheet multitool for discovering and arranging data
lens - Lens - The way the world runs Kubernetes
duckdb - DuckDB is an in-process SQL OLAP Database Management System
k8s - How to deploy Portainer inside a Kubernetes environment.
lnav - Log file navigator
minikube - Run Kubernetes locally
tsv-utils - eBay's TSV Utilities: Command line tools for large, tabular data files. Filtering, statistics, sampling, joins and more.
popeye - 👀 A Kubernetes cluster resource sanitizer
ClickHouse - ClickHouse® is a free analytics DBMS for big data
k3s - Lightweight Kubernetes
nio - Low Overhead Numerical/Native IO library & tools
stern - ⎈ Multi pod and container log tailing for Kubernetes