pinney.colton at bitwisedata.com
Thu Aug 30 10:59:20 EDT 2012
Hi all -
This is my first post to the list. I'm a relative Riak newbie, though I
have some experience working with multi-terabyte datasets on other
platforms. Last night, I kicked off my first "large" load of data as a
test of the platform with about 1,000,000 json objects being loaded into a
bucket. I had a couple performance issues, so I'm wondering if someone on
the list could be kind enough to answer a few questions that will help me
a) I haven't analyzed all of my load log data yet, but it look like writes
went from about 0.02 seconds per object to a couple minutes per object!
This is the typical "dev" setup from the tutorials, and I forgot to divide
available RAM by 4 to arrive at a number per node - is this likely the
result of a memory constraint, or should I be looking elsewhere, beyond
just bumping the memory on my VM? I looked at the logs, but I'm not sure
what I should be looking for.
b) I am using protocol buffers, and I saw similar initial performance when
running the load from a separate machine vs. having the data on the riak
machine itself. Is that what you would recommend? I'm wondering if there
is any hard/fast rule re: CPU/Memory contention on the machine vs. network
performance of loading from a different machine.
c) I'm using a sha256 hash as my bucket name. I read that buckets and keys
are concatenated internally and that all objects have just one "bucketkey".
Am I putting significantly more pressure on memory by using such a long
bucket name? Or is Riak managing that for me via some sort of compression?
If that long hash is being replicated for each of those million objects, I
can see where my memory estimates would have been low. I can always use an
integer ID for my bucket name, the hash just existed elsewhere in my
application, so I used it without thinking about it too much.
Thanks in advance for your help! Loving Riak so far, in spite of these
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