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Show HN: BloomSearch – Keyword search with hierarchical Bloom filters

news.ycombinator.com Unknown 2025-07-20 18:02:19

BloomSearch Keyword search engine with hierarchical bloom filters for massive datasets BloomSearch provides extremely low memory usage and low cold-start searches through pluggable storage interfaces. Memory efficient : Bloom filters have constant size regardless of data volume : Bloom filters have constant size regardless of data volume Pluggable storage : DataStore and MetaStore interfaces for any backend (can be same or separate) : DataStore and MetaStore interfaces for any backend (can

Topics: bloom error field query row

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Show HN: BloomSearch – Keyword search with hierarchical bloom filters

news.ycombinator.com Unknown 2025-07-22 00:02:19

BloomSearch Keyword search engine with hierarchical bloom filters for massive datasets BloomSearch provides extremely low memory usage and low cold-start searches through pluggable storage interfaces. Memory efficient : Bloom filters have constant size regardless of data volume : Bloom filters have constant size regardless of data volume Pluggable storage : DataStore and MetaStore interfaces for any backend (can be same or separate) : DataStore and MetaStore interfaces for any backend (can

Topics: bloom error field query row

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To be a better programmer, write little proofs in your head

news.ycombinator.com Unknown 2025-07-26 23:05:39

This is a brief write-up of a trick I learned that helps me write code faster and more accurately. I say "trick", but it's really something I started to do without noticing as I moved further into my career. When you're working on something difficult, sketch a proof in your head as you go that your code will actually do what you want it to do. A simple idea, but easier said than done: doing this "online" without interrupting your flow takes a lot of practice. But once you get really good at it,

Topics: code fields function query recursive

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Context Engineering Guide

news.ycombinator.com Unknown 2025-07-26 16:59:48

What is Context Engineering? A few years ago, many, even top AI researchers, claimed that prompt engineering would be dead by now. Obviously, they were very wrong, and in fact, prompt engineering is now even more important than ever. It is so important that it is now being rebranded as context engineering. Yes, another fancy term to describe the important process of tuning the instructions and relevant context that an LLM needs to perform its tasks effectively. Much has been written already

Topics: agent context engineering prompt query

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Abstraction boundaries are optimization boundaries

news.ycombinator.com Unknown 2025-08-17 04:12:10

Abstraction boundaries are optimization boundaries The N+1 query problem occurs when your application code sends one SQL query per element in a collection. The N queries are redundant; since all of the data is in the database already, a single query should be enough. This problem is usually caused by a leaky abstraction; the ORM, or whatever database abstraction you are using, can’t anticipate that it would need to send N queries, so it can’t automatically optimize this down to a single query.

Topics: abstraction boundary orm problem query

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Scaling our observability platform by embracing wide events and replacing OTel

news.ycombinator.com Unknown 2025-09-01 21:23:21

TLDR # Observability at scale: Our internal system grew from 19 PiB to 100 PB of uncompressed logs and from ~40 trillion to 500 trillion rows. Efficiency breakthrough: We absorbed a 20× surge in event volume using under 10% of the CPU previously needed. OTel pitfalls: The required parsing and marshalling of events in OpenTelemetry proved a bottleneck and didn’t scale - our custom pipeline addressed this. Introducing HyperDX: ClickHouse-native observability UI for seamless exploration, correlatio

Topics: clickhouse data loghouse query time

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ClickHouse scales beyond 100 petabytes of logs

news.ycombinator.com Unknown 2025-09-02 02:23:21

TLDR # Observability at scale: Our internal system grew from 19 PiB to 100 PB of uncompressed logs and from ~40 trillion to 500 trillion rows. Efficiency breakthrough: We absorbed a 20× surge in event volume using under 10% of the CPU previously needed. OTel pitfalls: The required parsing and marshalling of events in OpenTelemetry proved a bottleneck and didn’t scale - our custom pipeline addressed this. Introducing HyperDX: ClickHouse-native observability UI for seamless exploration, correlatio

Topics: clickhouse data loghouse query time

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Asset sprawl, siloed data and CloudQuery’s search for unified cloud governance

venturebeat.com Taryn Plumb 2025-09-17 21:30:00

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more Gaining visibility — and, ultimately, insights — into enterprise cloud assets is growing ever more challenging. Cloud estates are sprawling and fragmented, and inventory capabilities in existing tools can be narrow and unintuitive, separating elements like cost and security data into disconnected platforms with limited flexibility. Cloud

Topics: aws cloud cloudquery data tools

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Latest Tech News

Show HN: BloomSearch – Keyword search with hierarchical Bloom filters

Show HN: BloomSearch – Keyword search with hierarchical bloom filters

To be a better programmer, write little proofs in your head

Context Engineering Guide

Abstraction boundaries are optimization boundaries

Scaling our observability platform by embracing wide events and replacing OTel

ClickHouse scales beyond 100 petabytes of logs

Asset sprawl, siloed data and CloudQuery’s search for unified cloud governance

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