Mike,
I gather that Dmitriy is asking whether there are any smarts in the region
balancer based on heavy *read* traffic (i.e. if it turns out that your read
load is heavily skewed towards a small subset of regions). Which there aren't,
but could be if someone wanted to write the infrastructure
Ian
Understood.
Dmitry,
Could you show a use case where you see this happening?
If you have records that are being read that frequently, they would be cached
in memory.
I think you could use some concept of a systems table and then using
coprocessors you could update the table with the
Here is my SS: 259 71 2451
On May 26, 2012, at 9:25 AM, Michael Segel michael_se...@hotmail.com wrote:
Hi,
Jumping in on this late...
To cut a long story, is the region size the only current HBase
technique to balance load, esp. w.r.t query load? Or perhaps there are
some more advanced
Hello,
I'd like to collect opinions from HBase experts on the query
uniformity and whether there's any advance technique currently exists
in HBase to cope with the problems of query uniformity beyond just
maintaining the key uniform distribution.
I know we start with the statement that in order
Dmitriy,
If I understand you right, what you're asking about might be called Read
Hotspotting. For an obvious example, if I distribute my data nicely over the
cluster but then say:
for (int x = 0; x 100; x++) {
htable.get(new Get(Bytes.toBytes(row1)));
}
Then naturally I'm only
Thanks, Ian.
I am talking about situation when even when we have uniform keys, the
query distribution over them is still non-uniform and impossible to
predict without sampling query skewness, but skewness is surprisingly
great. (as in least active/most active user may differ in activity 100
times
Yeah, I think you're right Dmitriy; there's nothing like that in HBase today as
far as I know. If it'd be useful for you, maybe it would be for others, too;
work up a rough patch and see what people think on the dev list.
Ian
On May 25, 2012, at 1:02 PM, Dmitriy Lyubimov wrote:
Thanks, Ian.
