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Avoiding “OR” for Better Query Performance
OR in the WHERE condition of a PostgreSQL database query is usually a cause of bad query performance. How to rewrite queries without OR.
Top posts
Every blog post that took off on Hacker News, ranked by the votes of its best submission. 4,225 posts.
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The way CTRL-C in Postgres CLI cancels queries is incredibly hack-y
There are a few different reasons to hit the brakes on a Postgres query. Maybe it’s taking too long to finish. Maybe you realised you forgot to create an index that will make it orders of magnitude quicker. Maybe there’s some reason the results are no longer needed. Or maybe you, or your LLM buddy, […]
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Notes on the Amazon Aurora Paper
This is my notes on the paper: Amazon Aurora: Design Considerations for High Throughput Cloud-Native Relational Databases.
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Plotnine: Grammar of Graphics for Python (2019)
Blog article by Jeroen Janssens. Jul 7, 2024. 93 min read. Hey there, you’re reading an updated version of a post I published way back in 2019. Because of the 2024 Plotnine contest and the recent release of Polars 1.0, I decided to freshen things up. Changes include: Upgrade to Plotnine version 0.13.6 (from…
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BM25 in PostgreSQL
VectorChord-BM25 enhances PostgreSQL search with BM25 ranking, 3x faster than ElasticSearch. Supports BERT, Tocken, and Unicode tokenizers
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Multiranges in Postgres
Multiranges are a new feature in PostgreSQL 14. Here's a brief introduction on how to use them - learn the basics & important new uses.
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Do or undo – there is no VACUUM
What if PostgreSQL didn’t need VACUUM at all? This seems hard to imagine. After all, PostgreSQL uses multi-version concurrency control (MVC...
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PostgreSQL 10.2 Released
The PostgreSQL Global Development Group has released an update to all supported versions of our database system, including 10.2, 9.6.7, …
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Optimizing Postgres text search with trigrams
In this post, we’ll implement and optimize a text search system based on Postgres Trigrams
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Large language model data pipelines and Common Crawl
This article provides a short introduction to the pipeline used to create the data to train large language models (LLMs) such as LLaMA using Common Crawl (CC).
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A Simple Content-Based Recommendation Engine in Python
Let's pretend we need to build a recommendation engine for an eCommerce web site. There are basically two approaches you can take: content-based and collaborative-filtering. We'll look at some...
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How to think about creating a dataset for LLM fine-tuning evaluation
I summarise the kinds of evaluations that are needed for a structured data generation task.
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The World’s Largest Street-Level Imagery Dataset for Teaching Machines to See
Mapillary Vistas, the world’s largest and most diverse publicly available, pixel-accurately and instance-specifically annotated street-level imagery dataset, will empower autonomous mobility and transport at the global scale.
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Array languages vs. the curse of the spreadsheet
It has been said that the most popular programming language in the world is the spreadsheet (and in particular these days, Excel). There...
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