I need to scale an internal service / datastore that is currently hosted on
an HBase cluster and wanted to ask for advice from anyone out there who may
have some to share. The service does simple key value lookups on 20 byte
keys to 20-40 byte values. It currently has about 5 billion entries
(200GB), and processes about 40k random reads per second, and about 2k
random writes per second. It currently delivers a median response at 2ms,
90% at 20ms, 99% at 200ms, 99.5% at 5000ms - but the mean is 58ms which is
no longer meeting our needs very well. It is persistent and highly
available. I need to measure its working set more closely, but I believe
that around 20-30% (randomly distributed) of the data is accessed each
day. I want a system that can scale to at least 10x current levels (50
billion entries - 2TB, 400k requests per second) and achieve a mean < 5ms
(ideally 1-2ms) and 99.5% < 50ms response time for reads while maintaining
persistence and reasonably high availability (99.9%). Writes would ideally
be in the same as range but we could probably tolerate a mean more in the
Clearly for that latency, spinning disks won't cut it. The current service
is running out of an hbase cluster that is shared with many other things
and when those other things hit the disk and network hard is when it
degrades. The cluster has hundreds of nodes and this data is fits in a
small slice of block cache across most of them. The concerns are that its
performance is impacted by other loads and that as it continues to grow
there may not be enough space in the current cluster's shared block cache.
So I'm looking for something that will serve out of memory (backed by disk
for persistence) or from SSDs. A few questions that I would love to hear
- Does HBase sound like a good match as this grows?
- Does anyone have experience running HBase over SSDs? What sort of
latency and requests per second have you been able to achieve?
- Is anyone using a row cache on top of (or built into) HBase? I think
there's been a bit of discussion on occasion but it hasn't gone very far.
There would be some overhead for each row. It seems that if we were to
continue to rely on memory + disks this could reduce the memory required.
- Does anyone have alternate suggestions for such a service?
Amandeep Khurana 2012-10-20, 00:22
Andrew Purtell 2012-10-20, 01:16
Dave Latham 2012-10-22, 23:37
Pamecha, Abhishek 2012-10-20, 00:00
Dave Latham 2012-10-22, 23:30