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duckdb stuff

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  • 📅 Updated 4 months ago
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DuckDB
@duckdb.org
35 minutes ago
You can also try installing from r-universe: install.packages("duckdb", repos = c("https://duckdb.r-universe.dev", "https://cloud.r-project.org")) See r.duckdb.org for more details.
DBI Package for the DuckDB Database Management System

r.duckdb.org

DBI Package for the DuckDB Database Management System

The DuckDB project is an embedded analytical data management system with support for the Structured Query Language (SQL). This package includes all of DuckDB and an R Database Interface (DBI) connecto...
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Tom Dörr
@tom-doerr.bsky.social
about 8 hours ago
Timeseries lakehouse powered by DuckDB
Screenshot of the repository
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Tobias Müller
@tobilg.com
about 12 hours ago
DuckDB Terminal has been updated, it now supports auto-magic charts, data downloads and many other features: terminal.sql-workbench.com
DuckDB Terminal - Browser-based SQL Terminal

terminal.sql-workbench.com

DuckDB Terminal - Browser-based SQL Terminal

A browser-based SQL terminal powered by DuckDB WASM and Ghostty. Run SQL queries directly in your browser with interactive charts, multiple themes, and data export.
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Towards Data Science
@towardsdatascience.com
about 15 hours ago
Frustrated with how long Pandas operations take as your datasets grow? Benjamin Nweke shares a new guide on using Polars and DuckDB to speed up your data workflows. Learn to handle larger data without the wait.
Modern DataFrames in Python: A Hands-On Tutorial with Polars and DuckDB | Towards Data Science

towardsdatascience.com

Modern DataFrames in Python: A Hands-On Tutorial with Polars and DuckDB | Towards Data Science

How I learned to handle growing datasets without slowing down my entire workflow
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Maeevick (Aurel)
@maeevick.bsky.social
about 18 hours ago
#AoC Day 6 / 12 after a one-day break It was insane, visible in my ugly solution (maybe I should not have broken my streak, I lost momentum 🤔) Part 2 was really interesting, I know why I use polars and duckdb at work (don't reinvent the wheel, except in code challenges 🤪) #rustlang #challenge
Day 6 Part 1 ugly code in Rust
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Russell Harrower 🎙️
@russell.podcastindex.social.ap.brid.gy
about 21 hours ago
Well we have switched from DuckDB to Clickhouse as the engine to DataFlow for PodToo Cloud. I’ve also removed the Redis server that was caching the results from DuckDB. From what I can tell it’s now made it faster. But only time will tell. Fingers crossed. Oh and clickhouse was horrible to […]

podcastindex.social

Original post on podcastindex.social
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matsuu
@matsuu.bsky.social
1 day ago
DuckDBのIceberg extensionが1.4.0でINSERTに対応、1.4.2でUPDATE/DELETEにも対応。従来は限定的なSELECTだけ対応だったので大きな飛躍だ。わいわい。
Writes in DuckDB-Iceberg

duckdb.org

Writes in DuckDB-Iceberg

We shipped a number of features and improvements to the DuckDB-Iceberg extension: insert, update, and delete statements are all supported now.
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Mia 🏳️‍⚧️
@mia.pds.parakeet.at
1 day ago
Traded disk space for speed. Using something like an extra 5GB over the previous duckdb version atm (and this will increase once all the tables are ported tomorrow) but the speed increase (and lower cpu usage) in FTS is so high that it’s worth it.

The problem is less that it’s *slow* because I think it’s still fast enough to ingest all backfill in a week, but more that it pegs the CPU to 100% across all cores. I’d take the same (average) speed just without the pinning tbh

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Kyle Walker
@kylewalker.bsky.social
2 days ago
This is the most exciting time ever to be working in data, and I'm not talking about AI. 3 years ago, I wrote a database-centric guide in my book for analyzing the full 92 million record 1910 Census. Now, with #rstats and @duckdb? Analyze those 92 million rows in seconds.
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@taupirho.bsky.social
2 days ago
Want to know how you can bootstrap a data lake in an afternoon? Using AWS Athena, DuckDB, Iceberg and Spark, I show you how in my latest @towardsdatascience.com blog post. Read my in-depth article for free using the link below, towardsdatascience.com/bo….
Bootstrap a Data Lakehouse in an Afternoon | Towards Data Science

towardsdatascience.com

Bootstrap a Data Lakehouse in an Afternoon | Towards Data Science

Using Apache Iceberg on AWS with Athena, Glue/Spark and DuckDB
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Joe Chelladurai
@joe.fyi
2 days ago
Making something with duckdb
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Mia 🏳️‍⚧️
@mia.pds.parakeet.at
3 days ago
Up to an average of a scrobble per second I think which is *fine* but I would really like to fix some of the FTS queries taking upwards of 5s to run. Going to run some tests on an SQLite db to see if FTS5 is faster than duckdb FTS. If it is, then I guess I’m switching DB
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Christopher Trudeau
@trudeau.dev
3 days ago
Some ideas: 1) solve the same problem using Polars, pandas, or DuckDB; 2) write some sort of normalized output instead of their existing format; 3) add some other constraints, like source of the ingredient or degree of freshness (could do fuzzy matching on that last one)
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Dirk Eddelbuettel
@eddelbuettel.com
3 days ago
Use `ccache` as the duckdb docs suggests (also via `ninja`). I wrote about that on my blog too. Even faster: don't compile. On #Ubuntu with #r2u: > system.time(install.packages("duckdb")) [...] user system elapsed 3.506 0.664 5.532 > as five and a half seconds is hard to beat.
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Kyle Walker
@kylewalker.bsky.social
3 days ago
On the technical side there is plenty to learn that AI can't easily do yet on its own. Vector tiles (PMTiles), databases / new formats (DuckDB, GeoParquet, SedonaDB), and everything around app deployment (where / how to host, security, optimizing performance).
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Simon Späti 🏔️
@ssp.sh
3 days ago
Simple OLAP cache based on DuckDB, adding instant speed up for your DuckDB queries. This is a deep dive into OLAP and Caches, a never-ending (love/hate) story 😃.
Simplicity of a Database, but the Speed of a Cache: OLAP Caches for DuckDB - MotherDuck Blog

motherduck.com

Simplicity of a Database, but the Speed of a Cache: OLAP Caches for DuckDB - MotherDuck Blog

Speed up slow dashboards without adding new infrastructure. Learn how DuckDB's caching extensions can drop query times from minutes to seconds. | Reading time: 18 min read
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Nikita Rokotyan
@rokotyan.com
3 days ago
🪐 Cosmograph 2.0 is finally here after two years of development! Work with larger datasets, use SQL, open Parquet files, save & share your graphs, integrate with Python or React, ... All thanks to open source tools like WASM DuckDB, Mosaic, SQLRooms and our cosmos.gl → cosmograph.app
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Mia 🏳️‍⚧️
@mia.pds.parakeet.at
4 days ago
caching is ofc a massive speed bump, now I just need to work out why some of the queries are inexplicably slow (I think it’s that duckdb macros don’t work how I thought and I should do cases in rust* instead) *I will not write a query builder. I will not write a query builder. I will not write a q—
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Sharon Machlis
@smachlis.bsky.social
4 days ago
I wouldn't be using GitHub Actions for my DuckDB and R projects it it wasn't for r2u.
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Dirk Eddelbuettel
@eddelbuettel.com
4 days ago
Back to CI though. It is a massive winner here: arrow, duckdb, mlpack, or whole tidyverse install in seconds. Moreover, it does not break: Maybe libproj* or libgeos* or libicu* or your DB library changed _but the binary CRAN package will *always* install_ as that is ensured via integration with apt.
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Mike Thomas
@mike-thomas.bsky.social
4 days ago
I believe there are DuckDB base images (Docker) that could help with the overhead of installing DuckDB
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Sharon Machlis
@smachlis.bsky.social
4 days ago
IMO if you haven't tested an R package installation setup with duckdb on Linux, you haven't really tested if something is fast. Or even tolerable. 😀
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Sharon Machlis
@smachlis.bsky.social
4 days ago
Yes I believe that's how it works but I haven't investigated. Most of my GitHub Actions are to pull from public data sets. The only time package versions have become an issue has been with DuckDB and ragnar updates.
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Mid terms are November 3rd 2026. Go register voters.
@usrbinr.bsky.social
4 days ago
I did this orginally (I think) but with duckdb it took 40 minutes - name: Install packages uses: r-lib/actions/setup-r-dependencies@v2 with: packages: | any::dplyr any::DBI any::duckdb
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