If you can fit it on a thumb drive, it's not Big Data.
Big data on the cheapest MacBook
51–60 of 321 posts
Re: Big data on the cheapest MacBook
#52> compared to 3–5 GB/s
Their numbers are a bit outdated. M5 Macbook pro SSDs are literally 5x this speed. It's wild.
Re: Big data on the cheapest MacBook
#53This is as much an indictment of AWS compute as it is anything else.
Kinda comparing apples to oranges. AWS was using EBS and not local instance storage. So you’re easily looking at another order of magnitude latency when transmitting data over the network versus a local pcie bus. That’s gonna be a huge factor in what I assume is a heavy random seek load.
Re: Big data on the cheapest MacBook
#54I’ve been tempted to buy one and do “real dev work” on it just to show people it’s not this handicapped little machine. I built multiple iOS apps and went through two start up acquisitions with my M1 MBA as my primary computer, as a developer. And the neo is better than the M1 MBA. I edited my 30-45 min long 4k race videos in FCP on that air just fine.
I just retired my m1 air to being a server this month. They’re very capable laptops. If the neo is even comparable in spec it’s excellent for the price
I just bought a second hand M1 64GB as my main work laptop, haha. They definitely are capable laptops
Re: Big data on the cheapest MacBook
#55> compared to 3–5 GB/s Their numbers are a bit outdated. M5 Macbook pro SSDs are literally 5x this speed. It's wild.
I'm seeing ~6GB/sec: https://www.tomshardware.com/laptops/macbooks/m5-macbook-pro...
That's decently fast but not especially remarkable, most Gen4 NVMe drives can hit 6-7GB/sec.
Re: Big data on the cheapest MacBook
#56I'm interested by one (not for big data) but only 8 GB or RAM is kinda really sad. My good old LG Gram (from 2017? 2015? don't even remember) already had 24 GB of RAM. That was 10 years ago. A decade later I cannot see myself being a laptop with 1/3rd the mem.
Did your LG Gram cost $450 (to make for $600 in today's money) in 2015-17?
If it didn't, Apple has other laptops today with more RAM.
Re: Big data on the cheapest MacBook
#57I think it’s relevant to first read [1] to see why they’re doing this. It’s basically done as a meme. [1] https://motherduck.com/blog/big-data-is-dead/
> An alternate definition of Big Data is “when the cost of keeping data around is less than the cost of figuring out what to throw away.”
That couldn't be more accurate
Re: Big data on the cheapest MacBook
#58That's an awesome idea to get a bricked MacBook Neo really fast because those idiots soldered the SSD inside
Not sure about the ssd in particular but the neo is apparently pretty modular https://www.youtube.com/watch?v=5k7Lv7f-5CQ
Fantastic tear down. Thank you. Amazing for Apple. I hope this is the trend going forward but probably not. But still a gazillion screws? I just replaced the keyboard for my old hp elitebook with two screws.
Re: Big data on the cheapest MacBook
#59I’ve been tempted to buy one and do “real dev work” on it just to show people it’s not this handicapped little machine. I built multiple iOS apps and went through two start up acquisitions with my M1 MBA as my primary computer, as a developer. And the neo is better than the M1 MBA. I edited my 30-45 min long 4k race videos in FCP on that air just fine.
I just retired my m1 air to being a server this month. They’re very capable laptops. If the neo is even comparable in spec it’s excellent for the price
Yeah! My M1 air is now my iOS build server since GH actions bill macOS mins at 10x the price.
Re: Big data on the cheapest MacBook
#60Earlier quoted context omitted.
Yeah, this is really about how ludicrously overpriced big cloud is. I’ve got a first gen M1 Max and it destroys all but the largest cloud instances (that cost its entire current market value per month!), at least in compute. It’s a laptop! A decent bare metal server in a rack will destroy any laptop. It’s staggering. Jaw dropping. Bandwidth is even worse, like 10000X markup. Yet cloud is how we do things. There’s a g…
I agree and disagree, the benefit with cloud is you "don't need to manage it", it scales automatically, redundancy, and automatic backups etc. I do think you are right; in the future there will be more infrastructure as code as cost pressures become more obvious.
Those benefits are at least partly lies though.
The tooling — K8S with all its YAML, Terraform, Docker, cloud CLI tools, etc. — is pretty hideously ugly and complicated. I watch people struggle to beat it into shape just like they did with sysadmin automation tools like Puppet and Chef a decade or more ago. We have not removed complexity, only moved it.
The auto scaling thing is a half truth. It can do this if you deploy correctly but the zero downtime promise is only true maybe half the time. It also does this at greatly inflated cost.
Today you can scale with bare metal. Nobody except huge companies physically racks anymore. Companies like Hetzner and DataPacket have APIs to bring boxes up. There’s a delay, but you solve that by a bit of over provisioning. Very very few companies have work loads that are so bursty and irregular that they need full limitless up and down scaling. That’s one of those niche problems everyone thinks they have.
The uptime promise is false in my experience. Cloud goes down for cluster upgrades and any myriad other reasons just as often as self managed stuff. I’ve seen serious unplanned outages with cloud too. I don’t have hard numbers but I would definitely wager that if cloud is better for uptime at all it’s not enough of an improvement to justify that gigantic markup.
For what cloud charges I should, as the deploying user, receive five nines without having to think about it ever. It does not deliver that, and it makes me think about it a lot with all the complexity.
The only technical promise it makes good on, and it does do this well, is not losing data. They’ve clearly put more thought into that than any other aspect of the internal architecture. But there’s other ways to not lose data that don’t require you to pay a 10X markup on compute and a 10000X markup on transfer.
I think the real selling point of cloud is blame.
When cloud goes down, it’s not your fault. You can blame the cloud provider.
IT people like it, and it’s usually not their money anyway. Companies like it. They’re paying through the nose for the ability to tell the customer that the outage is Amazon’s fault.
Cloud took over during the ZIRP era anyway when money was infinite. If you have growth raise more. COGS doesn’t matter.
Maybe cloud is ZIRPslop.