Hi David, For productions, it will be recommanded to have good computers. But for testing, you can do with almost anything.
I'm running cluster in production with 6 region servers. My smallest computer is a P4 with only 500M of memory... I'm not saying that it's recommanded but it's working. I can't use big cache values else I'm getting out of memory and servers are closing (but not hadoop). But it's working. I have few tables. My biggest one is 15M but is growing every day. I have splitted it a lot to make sure to share the workload between all the servers. I'm expecting to be at about 30M by the end of the week. The only big computer I have is my master (8CPU, 12G) wich is also hosting a region server (not recommended for quality production schema). JM 2012/10/10, David Parks <[email protected]>: > In looking at the AWS MapReduce version of HBase, it doesn't even give an > option to run it on lower end hardware. > > I am considering HBase as an alternative to one large table we have in > MySQL > which is causing problems. It's 50M rows, a pretty straight forward set of > product items. > > The challenge is that I need to do 10+ range scans a day over about 7M > items each where we check for updates. This is ideal for HBase, but hell > for > MySQL (a join of a 7M row table with a 50M row table is giving us > fits-a-plenty). > > But beyond the daily range scans the actual workload on the boxes should be > reasonable, just random access reads. So it doesn't seem like I should need > significant memory/CPU requirements... > > But here's where I don't find a lot of information - as someone reasonably > new to HBase (I read a book, did the examples), am I missing anything in my > thinking? > > David > >
