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Apple vs the Law

https://formularsumo.co.uk/blog/2025/apple-vs-the-law/
79•tempodox•1h ago•35 comments

OpenFront: Realtime Risk-like multiplayer game in the browser

https://openfront.io/
30•thombles•1h ago•4 comments

Show HN: Pangolin – Open source alternative to Cloudflare Tunnels

https://github.com/fosrl/pangolin
220•miloschwartz•10h ago•33 comments

Postgres LISTEN/NOTIFY does not scale

https://www.recall.ai/blog/postgres-listen-notify-does-not-scale
422•davidgu•3d ago•165 comments

Batch Mode in the Gemini API: Process More for Less

https://developers.googleblog.com/en/scale-your-ai-workloads-batch-mode-gemini-api/
91•xnx•3d ago•27 comments

LLM Inference Handbook

https://bentoml.com/llm/
45•djhu9•5h ago•1 comments

The ChompSaw: A Benchtop Power Tool That's Safe for Kids to Use

https://www.core77.com/posts/137602/The-ChompSaw-A-Benchtop-Power-Tool-Thats-Safe-for-Kids-to-Use
157•surprisetalk•3d ago•93 comments

Show HN: Interactive pinout for the Raspberry Pi Pico 2

https://pico2.pinout.xyz
39•gadgetoid•3d ago•4 comments

Btrfs Allocator Hints

https://lwn.net/ml/all/cover.1747070147.git.anand.jain@oracle.com/
8•forza_user•1d ago•1 comments

What is Realtalk’s relationship to AI? (2024)

https://dynamicland.org/2024/FAQ/#What_is_Realtalks_relationship_to_AI
252•prathyvsh•16h ago•84 comments

Series of posts on HTTP status codes (2018)

https://evertpot.com/http/
35•antonalekseev•2d ago•6 comments

FOKS: Federated Open Key Service

https://foks.pub/
219•ubj•19h ago•44 comments

Show HN: Open source alternative to Perplexity Comet

https://www.browseros.com/
210•felarof•14h ago•74 comments

Flix – A powerful effect-oriented programming language

https://flix.dev/
263•freilanzer•18h ago•120 comments

Graphical Linear Algebra

https://graphicallinearalgebra.net/
236•hyperbrainer•16h ago•18 comments

Show HN: Cactus – Ollama for Smartphones

https://github.com/cactus-compute/cactus
140•HenryNdubuaku•12h ago•55 comments

Apple-1 Computer, handmade by Jobs and Woz [video]

https://www.youtube.com/watch?v=XdBKuBhdZwg
46•guiambros•2d ago•15 comments

Show HN: I built a playground to showcase what Flux Kontext is good at

https://fluxkontextlab.com
50•Zephyrion•1d ago•13 comments

Underwater turbine spinning for 6 years off Scotland's coast is a breakthrough

https://apnews.com/article/tidal-energy-turbine-marine-meygen-scotland-ffff3a7082205b33b612a1417e1ec6d6
165•djoldman•17h ago•154 comments

Red Hat Technical Writing Style Guide

https://stylepedia.net/style/
200•jumpocelot•17h ago•86 comments

Grok: Searching X for "From:Elonmusk (Israel or Palestine or Hamas or Gaza)"

https://simonwillison.net/2025/Jul/11/grok-musk/
300•simonw•7h ago•159 comments

Foundations of Search: A Perspective from Computer Science (2012) [pdf]

https://staffwww.dcs.shef.ac.uk/people/J.Marshall/publications/SFR09_16%20Marshall%20&%20Neumann_PP.pdf
23•mooreds•3d ago•0 comments

Orwell Diaries 1938-1942

https://orwelldiaries.wordpress.com/page/2/
106•bookofjoe•14h ago•60 comments

Measuring the impact of AI on experienced open-source developer productivity

https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/
598•dheerajvs•15h ago•392 comments

AI coding tools can reduce productivity

https://secondthoughts.ai/p/ai-coding-slowdown
151•gk1•8h ago•131 comments

eBPF: Connecting with Container Runtimes

https://h0x0er.github.io/blog/2025/06/29/ebpf-connecting-with-container-runtimes/
53•forxtrot•13h ago•7 comments

Analyzing database trends through 1.8M Hacker News headlines

https://camelai.com/blog/hn-database-hype/
143•vercantez•3d ago•71 comments

Matt Trout has died

https://www.shadowcat.co.uk/2025/07/09/ripples-they-cause-in-the-world/
190•todsacerdoti•1d ago•57 comments

Diffsitter – A Tree-sitter based AST difftool to get meaningful semantic diffs

https://github.com/afnanenayet/diffsitter
119•mihau•19h ago•29 comments

Launch HN: Leaping (YC W25) – Self-Improving Voice AI

59•akyshnik•14h ago•33 comments
Open in hackernews

Anatomy of a SQL Engine

https://www.dolthub.com/blog/2025-04-25-sql-engine-anatomy/
168•ingve•2mo ago

Comments

jimbokun•2mo ago
Very nice write up enumerating all the stages of SQL query execution. Interesting even if you don’t care about the DoIt database specifically.
Austizzle•2mo ago
Man, this title tripped me up for a minute because I pronounce it with the letters like Ess-Queue-Ell

So the "A" in "A ess-queue-ell" engine felt like it should have been an "An" until I realized it was meant to be pronounced like "sequel"

perching_aix•2mo ago
Not necessarily, I see native speakers completely ignore this a lot.

Have you ever considered pronouncing it as squirrel by the way?

kreetx•2mo ago
Many (most?) non-native English speakers do pronounce it as ess-queue-ell, especially in their own languages, so yes, the use of "a" instead of "an" does look off from that perspective.
SloopJon•2mo ago
When I read SQL for Dummies almost thirty years ago, it made a point of distinguishing "sequel" as a historical predecessor to standard "SQL." As I recall, the author even asserted that SQL is not an acronym/initialism for structured query language. I felt funny saying sequel for the next decade or so, because I wasn't an old timer experienced with this pre-SQL technology.

Now I usually say sequel because everyone else does. That and it rolls off the tongue better than S-Q-L.

jtolmar•2mo ago
I prefer "ess queue ell" these days, but the first DBA I ever worked with pronounced it "squirrel".
gopalv•2mo ago
This is a great write up about a pull-style volcano SQL engine.

The IR I've used is the Calcite implementation, this looks very concept adjacent enough that it makes sense on the first read.

> tmp2/test-branch> explain plan select count() from xy join uv on x = u;

One of the helpful things we did was to build a graphviz dot export for the explains plans, which saved us days and years of work when trying to explain an optimization problem between the physical and logical layers.

My version would end up displayed as SVG like this

https://web.archive.org/web/20190724161156/http://people.apa...

But the calcite logical plans also have that dot export modes.

https://issues.apache.org/jira/browse/CALCITE-4197

th0ma5•2mo ago
This is really great!!
gavinray•2mo ago
Calcite also has a relatively-unknown web tool for plan visualization that lets you step through execution.

It's a method from "RuleMatchVisualizer":

https://github.com/apache/calcite/blob/36f6dddd894b8b79edeb5...

Here's a screenshot of what the webpage looks like, for anyone curious:

https://github.com/GavinRay97/GraphQLCalcite/blob/92b18a850d...

ignoreusernames•2mo ago
I recommend anyone who works with databases to write a simple engine. It's a lot simpler than you may think and it's a great exercise. If using python, sqlglot (https://github.com/tobymao/sqlglot) let's you skip all the parsing and it even does some simple optimizations. From the parsed query tree it's pretty straightforward to build a logical plan and execute that. You can even use python's builtin ast module to convert sql expressions into python ones (so no need for a custom interpreter!)
Abde-Notte•2mo ago
Second this - building even a simple engine gives real insight into query planning and execution. Once parsing is handled, the core ideas are a lot more approachable than they seem.
albert_e•2mo ago
Sorry for slight digression.

In a larger system we are building we need a text-to-sql capability for some structured data retrieval.

Is there a way one could utilize this library (sqlglot) to build a multi-dialect sql generator -- that is not currently solved by directly relying on a LLM that is better at code generation in general?

LtdJorge•2mo ago
This is a SQL to X library, though. I don’t think it’s what you need.
gavinray•2mo ago
You can use an LLM to generate query-builder expressions from popular libraries in whatever language.

For example, on the JVM there is jOOQ, which allows you to write something like:

  select(field("foo"), avg("bar")).from(table("todos"))
And then it will render dialect-specific SQL. It has very advanced emulation functionality for things like JSON aggregations and working around quirks of dialects.

Alternatively, you can ask an LLM to generate a specific dialect of SQL, and then use jOOQ to parse it to an AST, and then render it as a different dialect, like:

    val parser= DSL.using(SQLDialect.POSTGRES).parser()
    val parsedQuery = parser.parseQuery(postgresQuery)
    val renderedMySQL = DSL.using(SQLDialect.MYSQL).renderInlined(parsedQuery)
    println(renderedMySQL)
Unsure if functionality like this exists in other Query Builder libraries for other languages.
genai-analyst•2mo ago
another digression here... sorry... i see you're trying to diy text-to-sql—at some point you're gonna hit a bunch of hiccups. like, the model writes a query that “almost” works but joins the wrong tables, or it assumes column names that don’t exist, or it returns the wrong agg because it misread the intent. and retries won’t always save you—it’ll just confidently hallucinate again.

we’ve been through all of that at wobby.ai we ended up building a system where the data team defines guardrails and reusable query templates, so the agent doesn’t just make stuff up. it can still handle user prompts, but within a safe structure. if you want to save yourself from debugging this stuff endlessly, might be worth checking out wobby.ai.

KyleBrandt•2mo ago
Using dolthub's go-mysql-server for Grafana's upcoming SQL expressions feature (private preview in Grafana 12, but in the OSS version with a feature toggle).

GMS lets you provide your own table and database implementations, so we use GMS to perform SQL queries against Grafana's dataframes - so users can join or manipulate different data source queires, but we don't have to insert the data into SQL to do this thanks to GMS.