81–90 of 98 posts
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SELECT * FROM [bigquery-public-data:hacker_news.stories] ORDER BY score DESC LIMIT 100
made a screenshot with Top 20 stories on HN http://i.imgur.com/czXYEyQ.png
Why? Because when Amazon and Microsoft announce something I know there's a good chance it will still exist 24 months later
Any chance of getting GNAF and some other Australian datasets up there? http://data.gov.au/dataset/geocoded-national-address-file-g-... A CKAN->BigQuery connector would be interesting (think of an "Open in BigQuery" button)
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I'm happy to respond to every single person that makes this argument in perpetuity :) There's a difference between experimental free services and Enterprise-grade SLA'd SLO'd fully-supported paid services with a very clear and recorded deprecation policy and an army of customers with contracts and full support from Google CEO and chairman.
Indeed, but who is paying to maintain 546GB of online storage ( plus backups ) for Reddit comments in BigQuery, for example? If the answer is "Google" then I think people are still right to be cautious. Or to invert the question; could I put 1TB of my own 'interesting' data into BigQuery and have Google maintain it in perpetuity for free? If not, then why are any of these datasets considered safer?
I remember the earlier Google attempt at the same thing. I was in undergrad and an engineer came to my Uni to give a presentation on the topic. A big area of concern was "Why won't Google just shut this down when the going gets rough?" The question was mostly batted away along the lines of "this is lunch money to Google anyway." But just a couple years later, it did indeed bite the dust. Covered in Wired: http://www.…
2008. I remember those days. GMail was still in beta and ' a big area of concern was "Why won't Google just shut this down when the going gets rough?" ' 8 years later GMail has a billion users, and not going anywhere but up. I haven't been to the future (yet), but I'll happily take any bet you have against BigQuery. Disclaimer: I'm Felipe Hoffa, and I work at Google. ( https://twitter.com/felipehoffa )
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> Especially in the sciences. Take a look at how Stanford is leveraging BigQuery for their genomics analysis: http://www.eventbrite.com/e/interactive-cloud-analytics-extr... > It manages that faster than just the latency to bigquery would be — 18ms over a test dataset of several gigabyte by now. Yes!!! Exactly! That's the whole point. If something is taking you less than a second, don't bring BigQuery into the mix. B…
> If something is taking you less than a second, don't bring BigQuery into the mix. But when you start hitting processes that take hours or days to run... try BigQuery But that's my entire point? Why are all the test datasets small enough to be faster in pgsql than the latency to Google would take? I mean, if I wanted to showcase my software, I'd use a huge dataset with a complex problem — say protein folding, or sup…
But if one day you do, please ping me, it will be fun to do a follow up.
I just ran a Markov text generator over the USA Name Database and created a few thousand girls' names, including: Aracella, Ashla, Blakelyne, Carylou, Damariah, Enchantrelle, Francenza, Iridia, Jalexius, Lilliotte and Scotlanta. Hey, maybe I can start a bespoke baby name business...
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I'm happy to respond to every single person that makes this argument in perpetuity :) There's a difference between experimental free services and Enterprise-grade SLA'd SLO'd fully-supported paid services with a very clear and recorded deprecation policy and an army of customers with contracts and full support from Google CEO and chairman.
Indeed, but who is paying to maintain 546GB of online storage ( plus backups ) for Reddit comments in BigQuery, for example? If the answer is "Google" then I think people are still right to be cautious. Or to invert the question; could I put 1TB of my own 'interesting' data into BigQuery and have Google maintain it in perpetuity for free? If not, then why are any of these datasets considered safer?
You can put 1TB of your own interesting data in BigQuery and pay $0.02/GB/month for the data storage fees. I'm sure Google will happily take your money as a paying customer, and keep your data for as long as you want to store it and pay for it.
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Some resources to get you started: - How to use the Hacker News dataset https://medium.com/google-cloud/big-data-stories-in-seconds-... - Discussion of the HN dataset announcement here https://news.ycombinator.com/item?id=10440502 - An iPython notebook: https://github.com/fhoffa/notebooks/blob/master/analyzing%20... - More: http://debarghyadas.com/writes/looking-back-at-9-years-of-ha... Disclaimer: I'm Felipe Hoffa,…
How fresh is the data, and how often is it refreshed? It doesn't seem to be described anywhere...
