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A comment on Joining a billion rows 20x faster than Apache Spark. Parent comment

Re:Joining a billion rows 20x faster than Apache Spark by chx on Friday February 10, 2017 @02:41AM (#13613869)
https://twitter.com/garybernhardt/status/600783770925420546

> Consulting service: you bring your big data problems to me, I say "your data set fits in RAM", you pay me $10,000 for saving you $500,000.

Considering https://www.supermicro.com/products/system/4U/8048/SYS-8048B... which is a plain old 4U server not some fancy, super expensive NUMA machine can eat up 12TB memory, this quip and parent has quite some merits.

6TB is not even https://memory.net/product/s26361-f3843-e618-fujitsu-1x-64gb... horrible at 57 504 dollars. That's about 48 engineering days if your engineer related expenses are 150 an hour (and it's likely they are more).

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Re:Joining a billion rows 20x faster than Apache Spark by chx on Saturday February 11, 2017 @04:51AM (#13621958)
Note: https://www.sgi.com/products/servers/uv/uv_300_30ex.html

> SGI UV 300 now scales up to 64 CPU sockets and 64TB of cache-coherent shared memory in a single system.

This is the current limit of Linux hardware memory support so going above it is tricky. But still, 64TB.

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