#query — Public Fediverse posts

query
#kamloops #train #graffiti #art
#query

Two wonderful post about #Cypher, the #Neo4j #query language

https://systay.github.io/posts/2026-04-30-i-just-wanted-a-query-planner/ by @systay

and

https://www.thobe.org/work/cypher/ by Tobias Lindaaker

Two wonderful post about #Cypher, the #Neo4j #query language

https://systay.github.io/posts/2026-04-30-i-just-wanted-a-query-planner/ by @systay

and

https://www.thobe.org/work/cypher/ by Tobias Lindaaker

Two wonderful post about #Cypher, the #Neo4j #query language

https://systay.github.io/posts/2026-04-30-i-just-wanted-a-query-planner/ by @systay

and

https://www.thobe.org/work/cypher/ by Tobias Lindaaker

Two wonderful post about #Cypher, the #Neo4j #query language

https://systay.github.io/posts/2026-04-30-i-just-wanted-a-query-planner/ by @systay

and

https://www.thobe.org/work/cypher/ by Tobias Lindaaker

Two wonderful post about #Cypher, the #Neo4j #query language

https://systay.github.io/posts/2026-04-30-i-just-wanted-a-query-planner/ by @systay

and

https://www.thobe.org/work/cypher/ by Tobias Lindaaker

[Перевод] REST умер? Почему Java-разработчики уходят в GraphQL

Один экран в приложении, а на бэкенде несколько REST-вызовов , куча эндпоинтов и ответы, где 90% полей не используются. Теряем в скорости, усложняется фронтенд и приходится версионировать контракт, когда меняется формат данных. GraphQL предлагает другой подход : один API-эндпоинт и запрос, в котором клиент сам указывает, какие поля ему нужны. Это снижает overfetching , уменьшает количество сетевых затрат и упрощает договоренности между фронтом и бэком за счет схемы как явного контракта и живой документации. В новом переводе от команды Spring АйО разберем, где GraphQL реально помогает : как уйти от разрастания эндпоинтов, как держать контракт синхронизированным и что делать с типичными проблемами производительности и наблюдаемости, когда данные собираются из разных источников.

https://habr.com/ru/companies/spring_aio/articles/1026130/

#java #kotlin #spring #graphql #api #query #database #системное_программирование #backend

Successful Queries: Sabrina Taitz and “Harmless,” by Miranda Shulman

In this installment of Successful Queries, agent Sabrina Taitz and author Miranda Shulman discuss the query behind her debut, Harmless.
The post Successful Queries: Sabrina Taitz and “Harmless,” by Miranda Shulman appeared first on Writer's Digest.
https://www.writersdigest.com/successful-queries-sabrina-taitz-and-harmless-by-miranda-shulman

#GetPublished #WriteMyQuery #query #QueryAgents #successfulqueries

БАЗЫ ДАННЫХ db. SQL, REDIS, СУБД

Если серьезно, то сегодня мы поговорим про БАЗЫ данных. Как-то один мой друг разработчик сказал, что программирование можно понимать как

https://habr.com/ru/articles/1023194/

#redis #sql #sqlite #in_memory #java #query #jdbc #jpa

БАЗЫ ДАННЫХ db. SQL, REDIS, СУБД

Если серьезно, то сегодня мы поговорим про БАЗЫ данных. Как-то один мой друг разработчик сказал, что программирование можно понимать как

https://habr.com/ru/articles/1023194/

#redis #sql #sqlite #in_memory #java #query #jdbc #jpa

БАЗЫ ДАННЫХ db. SQL, REDIS, СУБД

Если серьезно, то сегодня мы поговорим про БАЗЫ данных. Как-то один мой друг разработчик сказал, что программирование можно понимать как

https://habr.com/ru/articles/1023194/

#redis #sql #sqlite #in_memory #java #query #jdbc #jpa

БАЗЫ ДАННЫХ db. SQL, REDIS, СУБД

Если серьезно, то сегодня мы поговорим про БАЗЫ данных. Как-то один мой друг разработчик сказал, что программирование можно понимать как

https://habr.com/ru/articles/1023194/

#redis #sql #sqlite #in_memory #java #query #jdbc #jpa

tl;dr Using https://thi.ng/column-store to accelerate tag intersection queries by a factor of 880x...

Working on the static website generator/export plugin for my personal knowledge tool has been one of the main projects this past month. A key part of this setup is tagging, not just simple flat keywords/categories, but actually treating tags as sets. The system doesn't just allow browsing content by a single tag, but also supports adding (or removing) tags to narrow or widen the current topic. E.g. The combination of "3d + geometry + typescript" would select only works which have all of these three tags...

In the local version of my tool there's no limit to the number of tags (and it also supports tag negation), but for the static site generation I have to limit the set size (due to combinatoric explosion) and pre-compute all possible permutations, then create HTML documents for each these individual combinations which actually produce results.

So far I'm having ~400 unique tags in use, meaning if I want to aim for a max set size of 3, there're theoretically ~64,000,000 possibilities to check[1]! For the roughly 3500 content items used for testing, a naive JS approach to filter the result array and only retain items matching the entire current permutation is so extremely slow, that I stopped the process after 3.5 minutes just for the first 250k (aka 0.4%) of the 64 million permutations, i.e. at that rate the full process would have taken ~15 hours, pretty slow for a SSG... :)

Naive approach 🫣:

```
permutation = ["3d", "geometry", "typescript"]
results.filter(item => permutation.every(tag => item.tags.includes(tag)))
```

But since I'm using https://thi.ng/column-store as my database, such queries can be optimized by a few magnitudes, since here these intersection queries are applied only to bitfields (explained in the pkg readme). This results in all 64+ million permutations being processed in just 62 seconds (1+ million per second). Quite the difference, i.e. ~880x faster than the above approach!

Also, of these 64 million initial possibilities, there're fewer unique ones (excluding duplicates and ignoring ordering), and currently only ~24,000 are actually producing a result. Still, that's 24,000 index pages to generate & host and it's, of course, far, far too much!

So I will have to also spend more effort curating and severely reducing the tag vocabulary, at least the subset used for the website. On the other hand, I think this system will really help with browsing this large body/archive of work much more meaningfully than the boring single-tag/category approach most websites are offering. And it will do so without any backend (other than file hosting)...

[1] Permutations = 400 + 400^2 + 400^3

#ThingUmbrella #Tagging #Intersection #Query #Bitfield #WebDev #JavaScript #TypeScript #Optimization

tl;dr Using https://thi.ng/column-store to accelerate tag intersection queries by a factor of 880x...

Working on the static website generator/export plugin for my personal knowledge tool has been one of the main projects this past month. A key part of this setup is tagging, not just simple flat keywords/categories, but actually treating tags as sets. The system doesn't just allow browsing content by a single tag, but also supports adding (or removing) tags to narrow or widen the current topic. E.g. The combination of "3d + geometry + typescript" would select only works which have all of these three tags...

In the local version of my tool there's no limit to the number of tags (and it also supports tag negation), but for the static site generation I have to limit the set size (due to combinatoric explosion) and pre-compute all possible permutations, then create HTML documents for each these individual combinations which actually produce results.

So far I'm having ~400 unique tags in use, meaning if I want to aim for a max set size of 3, there're theoretically ~64,000,000 possibilities to check[1]! For the roughly 3500 content items used for testing, a naive JS approach to filter the result array and only retain items matching the entire current permutation is so extremely slow, that I stopped the process after 3.5 minutes just for the first 250k (aka 0.4%) of the 64 million permutations, i.e. at that rate the full process would have taken ~15 hours, pretty slow for a SSG... :)

Naive approach 🫣:

```
permutation = ["3d", "geometry", "typescript"]
results.filter(item => permutation.every(tag => item.tags.includes(tag)))
```

But since I'm using https://thi.ng/column-store as my database, such queries can be optimized by a few magnitudes, since here these intersection queries are applied only to bitfields (explained in the pkg readme). This results in all 64+ million permutations being processed in just 62 seconds (1+ million per second). Quite the difference, i.e. ~880x faster than the above approach!

Also, of these 64 million initial possibilities, there're fewer unique ones (excluding duplicates and ignoring ordering), and currently only ~24,000 are actually producing a result. Still, that's 24,000 index pages to generate & host and it's, of course, far, far too much!

So I will have to also spend more effort curating and severely reducing the tag vocabulary, at least the subset used for the website. On the other hand, I think this system will really help with browsing this large body/archive of work much more meaningfully than the boring single-tag/category approach most websites are offering. And it will do so without any backend (other than file hosting)...

[1] Permutations = 400 + 400^2 + 400^3

#ThingUmbrella #Tagging #Intersection #Query #Bitfield #WebDev #JavaScript #TypeScript #Optimization

tl;dr Using https://thi.ng/column-store to accelerate tag intersection queries by a factor of 880x...

Working on the static website generator/export plugin for my personal knowledge tool has been one of the main projects this past month. A key part of this setup is tagging, not just simple flat keywords/categories, but actually treating tags as sets. The system doesn't just allow browsing content by a single tag, but also supports adding (or removing) tags to narrow or widen the current topic. E.g. The combination of "3d + geometry + typescript" would select only works which have all of these three tags...

In the local version of my tool there's no limit to the number of tags (and it also supports tag negation), but for the static site generation I have to limit the set size (due to combinatoric explosion) and pre-compute all possible permutations, then create HTML documents for each these individual combinations which actually produce results.

So far I'm having ~400 unique tags in use, meaning if I want to aim for a max set size of 3, there're theoretically ~64,000,000 possibilities to check[1]! For the roughly 3500 content items used for testing, a naive JS approach to filter the result array and only retain items matching the entire current permutation is so extremely slow, that I stopped the process after 3.5 minutes just for the first 250k (aka 0.4%) of the 64 million permutations, i.e. at that rate the full process would have taken ~15 hours, pretty slow for a SSG... :)

Naive approach 🫣:

```
permutation = ["3d", "geometry", "typescript"]
results.filter(item => permutation.every(tag => item.tags.includes(tag)))
```

But since I'm using https://thi.ng/column-store as my database, such queries can be optimized by a few magnitudes, since here these intersection queries are applied only to bitfields (explained in the pkg readme). This results in all 64+ million permutations being processed in just 62 seconds (1+ million per second). Quite the difference, i.e. ~880x faster than the above approach!

Also, of these 64 million initial possibilities, there're fewer unique ones (excluding duplicates and ignoring ordering), and currently only ~24,000 are actually producing a result. Still, that's 24,000 index pages to generate & host and it's, of course, far, far too much!

So I will have to also spend more effort curating and severely reducing the tag vocabulary, at least the subset used for the website. On the other hand, I think this system will really help with browsing this large body/archive of work much more meaningfully than the boring single-tag/category approach most websites are offering. And it will do so without any backend (other than file hosting)...

[1] Permutations = 400 + 400^2 + 400^3

#ThingUmbrella #Tagging #Intersection #Query #Bitfield #WebDev #JavaScript #TypeScript #Optimization

tl;dr Using https://thi.ng/column-store to accelerate tag intersection queries by a factor of 880x...

Working on the static website generator/export plugin for my personal knowledge tool has been one of the main projects this past month. A key part of this setup is tagging, not just simple flat keywords/categories, but actually treating tags as sets. The system doesn't just allow browsing content by a single tag, but also supports adding (or removing) tags to narrow or widen the current topic. E.g. The combination of "3d + geometry + typescript" would select only works which have all of these three tags...

In the local version of my tool there's no limit to the number of tags (and it also supports tag negation), but for the static site generation I have to limit the set size (due to combinatoric explosion) and pre-compute all possible permutations, then create HTML documents for each these individual combinations which actually produce results.

So far I'm having ~400 unique tags in use, meaning if I want to aim for a max set size of 3, there're theoretically ~64,000,000 possibilities to check[1]! For the roughly 3500 content items used for testing, a naive JS approach to filter the result array and only retain items matching the entire current permutation is so extremely slow, that I stopped the process after 3.5 minutes just for the first 250k (aka 0.4%) of the 64 million permutations, i.e. at that rate the full process would have taken ~15 hours, pretty slow for a SSG... :)

Naive approach 🫣:

```
permutation = ["3d", "geometry", "typescript"]
results.filter(item => permutation.every(tag => item.tags.includes(tag)))
```

But since I'm using https://thi.ng/column-store as my database, such queries can be optimized by a few magnitudes, since here these intersection queries are applied only to bitfields (explained in the pkg readme). This results in all 64+ million permutations being processed in just 62 seconds (1+ million per second). Quite the difference, i.e. ~880x faster than the above approach!

Also, of these 64 million initial possibilities, there're fewer unique ones (excluding duplicates and ignoring ordering), and currently only ~24,000 are actually producing a result. Still, that's 24,000 index pages to generate & host and it's, of course, far, far too much!

So I will have to also spend more effort curating and severely reducing the tag vocabulary, at least the subset used for the website. On the other hand, I think this system will really help with browsing this large body/archive of work much more meaningfully than the boring single-tag/category approach most websites are offering. And it will do so without any backend (other than file hosting)...

[1] Permutations = 400 + 400^2 + 400^3

#ThingUmbrella #Tagging #Intersection #Query #Bitfield #WebDev #JavaScript #TypeScript #Optimization

when you get a #rejection on a #query that is more than 6 months old, that you already marked as rejected (on a project you have since shelved):

#gif #WritingCommunity #Writing #Writers #querying

when you get a #rejection on a #query that is more than 6 months old, that you already marked as rejected (on a project you have since shelved):

#gif #WritingCommunity #Writing #Writers #querying

when you get a #rejection on a #query that is more than 6 months old, that you already marked as rejected (on a project you have since shelved):

#gif #WritingCommunity #Writing #Writers #querying

when you get a #rejection on a #query that is more than 6 months old, that you already marked as rejected (on a project you have since shelved):

#gif #WritingCommunity #Writing #Writers #querying

when you get a #rejection on a #query that is more than 6 months old, that you already marked as rejected (on a project you have since shelved):

#gif #WritingCommunity #Writing #Writers #querying

FYI: PostgreSQL JSONB: Query & Index Your Data! #shorts: Discover how PostgreSQL's JSONB field type can simplify handling and querying JSON data within your database. Learn how it indexes these fields for efficient data retrieval. #PostgreSQL #JSONB #database #query #indexing https://www.youtube.com/shorts/8giZMSjISo0

Pipelined Relational Query Language, Pronounced "Prequel"

https://prql-lang.org/

#HackerNews #Pipelined #Relational #Query #Language #Prequel #QueryLanguage #DataProcessing #TechInnovation

Wenn du anfängst, dich intensiver mit Softwaredesign zu beschäftigen, stolperst du relativ früh über Prinzipien mit großen Namen. Eins davon ist Command–Query Separation, kurz CQS. Klingt erstmal theoretisch, ist aber im Alltag extrem praktisch - gerade dann, wenn dein Code langsam größer w

https://magicmarcy.de/command–query-separation

#Command #Query #Separation #CQRS #Trennung #Programming

How to Avoid MySQL Using the Wrong Index

Optimizer can pick a slow index and tank queries.

#mysql #forceindex #optimizer #howto #performance #query

https://www.youtube.com/watch?v=cToErLbZx_w

#Search @[email protected] #query {vacatio legis} #Almost #all #results are #foreign #languages! #America has had 4 #decades since #Rex84 passed into #law to #protest #Minnesota #before it happened, 2½ decades since the #PatriotAct! You can't #force-vaccinate #military & #police & expect them to #thank you!

RE: https://bsky.app/profile/did:plc:iaifhbdrrvebksyobrbwysnw/post/3mdvldwwqhc2u

How to Stop Using LIKE for IDs

LIKE on numeric IDs forces scans.

#mysql #like #ids #performance #howto #query

https://www.youtube.com/watch?v=VxrZCnuN5K0

ICYMI: PostgreSQL JSONB: Query & Index Your Data! #shorts: Discover how PostgreSQL's JSONB field type can simplify handling and querying JSON data within your database. Learn how it indexes these fields for efficient data retrieval. #PostgreSQL #JSONB #database #query #indexing https://www.youtube.com/shorts/8giZMSjISo0

Prisma ORM на скорости чистого SQL? Конвертация JSON-запросов в SQL-строку

В 1974 году, когда SQL только вышел из исследовательских лабораторий IBM, работа с базами данных выглядела просто: разработчик писал запрос и получал результат. Без слоёв, абстракций и фреймворков — только строки, описывающие нужные данные. Эта прямота дорого обходилась. Переименование колонки превращалось в поиск по тысячам строк кода в надежде отловить все упоминания. Неаккуратная работа с пользовательским вводом приводила к SQL-инъекциям. Миграция с Oracle на PostgreSQL часто означала переписывание значительной части запросов из-за различий диалектов. К середине 1990-х проблема стала настолько заметной, что начали появляться Object-Relational Mapper’ы (ORM). Идея выглядела привлекательно: работать с таблицами как с объектами, писать код на «родном» языке программирования вместо SQL-строк, а перевод на SQL оставлять фреймворку.

https://habr.com/ru/articles/986772/

#prisma #sql #query #optimizer #postgresql #sqlite #performance #typescript #generator

PostgreSQL JSONB: Query & Index Your Data! #shorts: Discover how PostgreSQL's JSONB field type can simplify handling and querying JSON data within your database. Learn how it indexes these fields for efficient data retrieval. #PostgreSQL #JSONB #database #query #indexing https://www.youtube.com/shorts/8giZMSjISo0

🐣🎩 Oh, what a shocker! #pgvector isn't the silver bullet, and running it in #production is like trying to teach a penguin to fly. Turns out, you'd be better off reading a #query #planner #manual than relying on this "cutting-edge" technology! 🚀💥
https://alex-jacobs.com/posts/the-case-against-pgvector/ #challenges #technology #pitfalls #cutting #edge #HackerNews #ngated

SQL Workbench – Republicans not welcome
https://www.sql-workbench.eu/
#ycombinator #sql #query #tool #analyzer #gui #jdbc #database #isql #viewer #frontend #java #dbms #oracle #postgres #h2database #firebirdsql #hsql #hsqldb #sqlplus #replacement #import #export #csv #unload #convert #insert #blob #clob #xml #etl #migrate #compare #diff #structure #table

Here is the CLI + SQL crossover you didn't see coming! 🤯

📁 **fselect**: Find files with SQL-like queries

🔥 Supports human-friendly queries, metadata search, interactive mode, diverse outputs

🦀 Written in Rust!

⭐ GitHub: https://github.com/jhspetersson/fselect

#rustlang #commandline #find #ls #sql #query #filesystem #tool #utility #opensource

每年聯徵中心的免費查詢額度到 12/31...

看到 Ptt 上面的「[閒聊] 年度聯徵中心免費查詢個人信用一次」這篇，提到「財團法人金融聯合徵信中心-個人線上查閱信用報告服務系統」這個服務。

每年聯徵中心提供一次紙本與電子的免費額度，如果沒有用掉的話可以趁年底要 reset quota 前免費查，其中電子的需要自然人憑證或是券商的

https://blog.gslin.org/archives/2024/12/29/12165/%e6%af%8f%e5%b9%b4%e8%81%af%e5%be%b5%e4%b8%ad%e5%bf%83%e7%9a%84%e5%85%8d%e8%b2%bb%e6%9f%a5%e8%a9%a2%e9%a1%8d%e5%ba%a6%e5%88%b0-12-31/

#Computer #Financial #Murmuring #Network #Service #credit #financial #free #query #quota #report #taiwan

Here is a lightweight TUI for working with CSV files!

🔍 **tabiew**: View and query CSV and TSV files.

🔥 Supports SQL querying such as filtering, sorting, and aggregations.

🚀 Has Vim-like key bindings.

🦀 Written in Rust & built with @ratatui_rs

⭐ GitHub: https://github.com/shshemi/tabiew

#rustlang #ratatui #tui #csv #tsv #files #sql #parser #query #commandline

Does anyone know someone who does writes query letters for a fee? And helps authors with the query process?

I know a neurodivergent children's author who needs help with her query letter and the process! She is happy to pay for the service.

NO ADVICE OR "HOW TO'" LINKS PLEASE - Only legimate persons who sell this kind of service!!

Please share!

#writer #author #neurodivergent #query #queryletter #literaryagent #writingexchange #help

Ecco un’altra #idea per il #MicroBlog che ebbi da subito, ma che non avevo avuto modo di #realizzare: #collezioni di #dati riguardanti il #sito stesso, visualizzati in maniera #interessante; #grafici colorati e non, in poche parole. 😳️

Oggi mi è capitato di trovare un #plugin #WordPress che facesse proprio al caso mio, permettendo di prelevare #informazioni dal #database tramite #query #MySQL, e generare un #istogramma, un #aereogramma, o altra roba. E allora, ho creato una #pagina dedicata, nello stesso spirito di cosa già feci per la mia #OcttKB (da lì viene anche un po’ l’idea), che cercherò di riempire di #visualizzazioni #intriganti: “Dati e Grafici 📊️“. Per ora ci sono quella dei #post al giorno, e delle #parole per ogni giorno.

Se come me #amate queste robe, fatevi un giro, e magari datemi qualche #suggerimento su che #illustrazioni in più #programmare… ho anche modificato il #codice del plugin per fargli sputare il #source #SQL utilizzato per ciascun grafico, che potete #copiare ed usare sui vostri #siti. ❤️ (Se volete la stessa #modifica, sappiate che vi basta aggiungere, nel file wp-content/plugins/sql-chart-builder/functions.php, alla funzione guaven_sqlcharts_local_shortcode, la seguente stringa in una parte che preferite della zona HTML: <?php echo htmlspecialchars($sql);?>)

https://octospacc.altervista.org/2024/01/16/la-pagina-dei-grafi-novi/

#aereogramma #amate #CMS #codice #collezioni #copiare #database #dati #grafici #home #idea #illustrazioni #informazioni #interessante #intriganti #istogramma #MicroBlog #modifica #MySQL #OcttKB #pagina #parole #plugin #post #programmare #query #realizzare #siti #sito #source #SQL #SQLCharts #suggerimento #tag #visualizzazioni #WordPress

I just discovered a "#Job" that consists of a single #SQL. The #query uses just two nested #selects. So far so good.
The nested select uses all but one table from the first one. It's running through 6 tables.
It uses "#distinct" instead if "group by" and a grand total of 31 "AND" Conditions in the "WHERE" part.
It runs at least 4:30h.
Humankind deserves its extinction.

How to choose the right API style and technology for your software architecture

https://www.redhat.com/architect/api-styles

"The key aspect of these five API styles is that there is no "best style." When choosing an API style, it all boils down to the following three classes: problem, consumers, and context." -- #BoburUmurzokov #RedHat

#api360 #Resource #Hypermedia #Query #Tunnel #EventBased

This is my Boxer #dog Dougal, chewing so intently on his big slab of moose antler, he hasn't eaten anything else yet and it's after 12 noon. This is a happy day for me, too, because I just got a request to send my #manuscript for "The Nitty Gritty & Other Complications" from a #publisher I had queried. My fingers are crossed for that collection.
#dogs #writing #amwriting #submitting #shortstories #publishing #query #CompanionAnimals #dogsofmastodon

Airpal - A web-based query execution tool built on top of Facebook's PrestoDB. Airpal reduces the friction involved in data analysis by making it easy to find tables, run queries, save analysis, and get... https://airbnb.io/airpal/ #Internet #PrestoDB #Query by @[email protected]