solidangle

This is my expectation as well. At CIDR this year there was a paper that presented an implementation of SQL/PGQ in DuckDB, and it outperforms Neo4J in a few selected benchmarks [1].

[1] https://www.cidrdb.org/cidr2023/papers/p66-wolde.pdf

> The ANN index IVF implemented in pgvector has very poor performance, with only around 50% recall.

My understanding is that this mostly due to the default settings that pgvector uses (nprobes = 3) and not due to the usage of IVF. The recall would improve significantly with better defaults. This of course would also increase the latency of vector searches, but that is the trade-off of using IVF instead of HNSW (worse latency at high recall, but much lower storage/memory costs).

This sounds like an interesting contrarian take. Would you care to elaborate?

But you don't have to write map-reduce jobs at all? You can just write SQL queries or Pandas programs, and they automatically get parallelized by Databricks. Databricks is a data warehouse (just like Snowflake).

https://www.databricks.com/product/databricks-sql

TIS-100 brought back some of the same joy that I had when I began with programming many years ago. Since then programming has become boring for me, but the weird limitations of TIS-100 almost made it feel like I was starting fresh again. I loved learning tons of small tricks that I could apply to beat the harder levels.

Shenzhen I/O otoh felt like work.

2-day delivery would be uncompetitive in The Netherlands. Next day delivery is the standard for webshops here, and most offer same day delivery as a paid upgrade when you either order before noon or live in a large city.

Wow, $14.99/month is a stark difference with the €2.99/month that they charge for a Prime subscription here in The Netherlands. I wonder if they will increase the subscription fee here to the same level once they reach the desired market share in the video streaming and e-commerce spaces here.

For those wondering what the differences between Raft and Paxos are: I can highly recommend the following paper https://arxiv.org/abs/2004.05074 It presents Paxos similarly to how Raft was originally presented.

You might be interested in this paper [1] which presents Paxos in the same way as Raft is presented in the Raft paper. In my view it really illustrates that most of the simplicity of Raft comes from its excellent presentation and not necessarily from its algorithmic simplicity.

[1]https://arxiv.org/pdf/2004.05074

(Multi-)Paxos and Raft are incredibly similar. I would even argue that Raft is just a variant of Paxos in the same way that e.g. Fast Paxos and EPaxos are variants of Paxos. Most of the Raft algorithm is identical to the Paxos algorithm. The main difference between the two algorithms is how leadership election works. In my view the main reason why Raft is considered to be simpler is because it was presented in a really clear paper. Paxos becomes equally simple when using a similar representation as used in that paper. See this paper: https://arxiv.org/pdf/2004.05074

Netflix is also the most expensive service that I am subscribed to. Netflix is €14 and Amazon Prime is only €6. I basically only watch Netflix for a few of their originals (which are arguably aren't that great).

Does anyone know why this post is no longer present on the first page (or the second) despite racking up over 60 points in less than 30 minutes?

Dutch: honderdvijfenzeventig (hundred five and seventy)

When was the last time you used Databricks? You should definitely try it again. Their product offering has improved a lot in the past few years.

> broad feature set

My experience is that the feature sets of Snowflake and Databricks are very similar. Both have time travel support. Snowflake has materialized views, but Databricks has Delta Live Tables. Databricks has a distributed Pandas API, but Snowflake recently introduced Snowpark. Databricks also has autoscaling and they recently launched a serverless offering that makes autoscaling super fast aswell.

Agreed! GCP should be broken up as well. It is incredibly unfair to third party services that Google is both supplying the platform and the competing services. This is probably a bigger problem on AWS though.

The post was edited to remove comments about hiring

The post was edited

Apple has filed a court case to block the publication of a report. Obviously the contents of the report will be discussed as part of the hearings. So if the hearings were public then the contents would become public as well, which would make the court case pointless. Hence the private hearings.

Comparing Apache Beam with Stripe's API is unfair in my opinion. Apache Beam can be operated outside Google Cloud, but the Stripe API is only useful for Stripe customers (as mentioned by the author). I don't think it's weird that a company provides more support to paying customers. The author should have raised the issue with Google Cloud's support team, instead of creating a Jira ticket for Apache Beam.

It could be, but it would be the size of a tennis ball. See https://news.ycombinator.com/item?id=28167058

``` if (node != next) { node = node->next; } ``` How does this work? Shouldn't this be ``` if (node != next) { node = next; } ```?

Hopefully the border tariff includes the CO2 cost of shipping. If the tariff is high enough then this might actually encourage local production, instead of shipping partially finished products 10 times around the world.

This is why I bought an iPhone 12. I had a Samsung Galaxy S8 before it and I was perfectly happy with it, except for the fact that it had reached the end of its scheduled security updates. The battery life was still good enough for my light usage, it still ran my apps without a hitch, and the OLED screen still looked great, but it had not received a proper software update in over a year and it had just received its final quarterly security patch. I don't care that much for Apple products (except for MacBooks), but it's the only phone manufacturer that actually supports its products beyond the first few years.

> As we expand the universe of software we wish to run on Fuchsia, we are encountering software that we wish to run on Fuchsia that we do not have the ability to recompile. For example, Android applications contain native code modules that have been compiled for Linux. In order to run this software on Fuchsia, we need to be able to run binaries without modifying them.

This seems to be new (circumstantial) evidence that Fuchsia is supposed to eventually replace Linux in Android.

FWIW, I do think this project is really cool. I should have taken a little bit more time to write this comment, as it's overly negative right now.

> Blazing fast results

I highly doubt this, given that the query engine is interpreted and non-vectorized. Queries are 10x to a 100x slower on a simple query, and 100x to 1000x slower on a query with large aggregations and joins without compilation of vectorization.

> Full SQL Exploration

Except for window functions it seems. These actually matter to data analysts.

Any query optimizer worth its salt will push the filters below the join.

What's a good source for practice questions? Many problems on Leetcode are completely unsuitable as interview questions.

Not just EU and US based users, but also Hong Kong and Taiwan based users.

At some point they will figure out that we're lying, and then they will elect another Trump.