hulahoof

For anyone not from aus the Betoota is a (great) satire publication similar to the onion

It’s somewhat sad to read that after 1430 years being family run the oldest company on this list went into liquidation in 2006 and was acquired

It's astonishing that N.A. has over half of the IPv4 allocations! My country doesn't even appear until zoom level 5

This is true for Eth, but there are many chains where DeFi exchange transaction fees are a rounding error

Not sure about GP but I’m in aus and can confirm the Coke is that bad

FFXIV has a decent gathering approach

As an Australian I agreed with your comment, but the link you shared indicate that petroleum actually is a larger export for us

> The top exports of Australia are Iron Ore ($79.6B), Coal Briquettes ($36.4B), Petroleum Gas ($26.8B), Gold ($17.7B), and Frozen Bovine Meat ($4B)

Maybe the point is just to prevent shortages

I was just wondering this, does including his name have the same effect as the trending on art station stuff ?

What a wild story. Complete with diss track towards Sony[1].

[1] https://www.youtube.com/watch?v=9iUvuaChDEg

Ignition! is one of my all time favourite reads, that I picked up from a previous comment similar to this - highly recommend if it piques the interest of any passer bys

While the 3.5mm headphone jack is only ~70 years old [1], the quarter inch jack has it's roots in the late 1870's [2].

[1] https://en.wikipedia.org/wiki/Phone_connector_(audio)#Miniat...

[2] https://www.bbc.com/news/magazine-35253398

> Netflix recommendations seem crap because they don't have a lot of third party content to recommend in the first place.

Their recommendations used to be world class until they got rid of the user feedback mechanisms.

When they mention tearing them in half, I’d imagine this more closely resembles what we would think of as slicing and just has the tearing effect due to the size of the material

Give a man the world and he will rob himself

A lot of people use databricks for the analytical and ML workloads (leveraging it as a sort of extended spark environment)

I find DDG to be better than anything other than finding local stores, but I just use (google) maps for that anyway.

I mean, you may think it's a long way down the road to the chemist, but that's just peanuts to space.

Seems like a great way to prevent recordings by having one officer move towards onlookers and force them an arbitrary distance away

Agreed, NSA is much more likely

I can’t find the exact video but I have seen similar to these in videos from military expo’s

https://www.thedronebird.com/aves/

I would expect people new to the code base would look at this gigantuan file and ask why it hasn’t been refactored, and this probably was seen as an opportunity to familiarise new hires with the code base as well as get them on the same level as to the effort involved in a refactor.

I agree with you, a rewrite is probably how they should have tackled this one.

That sounds really interesting and I have not heard of this before, where would you suggest to start reading into surgical sedatives?

I don't think you are missing anything, but allowing DBT to contain all the models that make up your various pipelines and reference each other mean that you can schedule your various pipelines at different cadences and use tags to refresh the relevant DBT models from a single code base.

It sounds like in your approach this would be writing this dependency logic into each DAG you schedule on airflow.

In the same way you would interpolate your jinja SQL before copying it into the database, you would use dbt compile or the output from a dbt run from the target/ folder and copy that SQL into your DB console or to share.

EDIT: This means your T is a single airflow node in each DAG, though I then still use airflow for the E/L tasks around it

This reflects how I often deploy Airflow as well (usually on GCP as Composer)

We use DBT to manage the DAG for the BQ transformations, put this in a container and deploy it into the kubernetes cluster that airflow is running on as a single node.

Airflow can then handle the scheduling and DAG nodes for non DWH dependencies such as loading/checking for files, kicking off tasks that need to run after the DWH refresh and the like.

I find once it is set up it is extremely easy for small teams to follow the pattern, and the single view of all the pipelines running is a great benefit - as well as handling the logic around last successful runs etc., that would need to be implemented manually if using simple cron jobs.

Because you let the high frequencies pass through on a high pass filter and vice versa

Or alternatively “the featured article” is common

> You'd think, as a billionaire they have a plane waiting for them 24/7 to get out of the country.

I guess disappeared could mean they are on a beach somewhere under an alias, but I don't think we can assume that for all of them

But Israel isn't a part of any of those agreements, it would be just as likely they spy on the US via a direct partnership with US agencies