I defer to Erick on on this level of detail and experience.
Let's continue the discussion - some of it will be a matter of how to
configure and tune Solr, how to select, configure, and tune hardware, the
need for further Lucene/Solr improvements, and how much further we have to
go to get to the next level with Big Data. I mean, 20K events/sec is not
necessarily beyond the realm of reality these days with sensor data (20K/sec
= 1 event every 50 microseconds)
-- Jack Krupansky
-----Original Message-----
From: Erick Erickson
Sent: Saturday, March 22, 2014 11:02 PM
To: solr-user@lucene.apache.org ; shushuai zhu
Subject: Re: Best approach to handle large volume of documents with
constantly high incoming rate?
Well, the "commonsense limits" Jack is referring to in that post are
more (IMO) scales you should count on having to do some _serious_
prototyping/configuring/etc. As you scale out, you'll run into edge
cases that aren't the common variety, aren't reliably tested every
night, etc. I mean how would you set up a test bed that had 1,000
nodes? Sure, it can be done, but nobody's volunteered yet to provide
the Apache Solr project that much hardware. I suspect that it would
make Uwe's week if someone did though.
In the "practical limit" vein, one example: You'll run up against "the
laggard problem". Let's assume that you successfully put up 2,000
nodes, for simplicity's sake, no replicas, just leaders and they all
stay up all the time. To successfully do a search, you need to send
out a request to all 2,000 nodes. The chance that one of them is slow
for _any_ reason (GC, high CPU load, it's just tired) increases the
more nodes you have. And since you have to wait until the slowest node
responds, your query rate will suffer correspondingly.
I've seen 4 node clusters handle 5,000 docs/sec update rate FWIW. YMMV
of course.
However, you say "...dedicated indexing servers...". There's no such
thing in SolrCloud. Every document gets sent to every member of the
slice it belongs to. How else could NRT be supported? When I saw that
comment I wondered how well you understand SolrCloud. I flat guarantee
you'll understand SolrCloud really, really well if yo try to scale as
you indicate :). There'll be a whole bunch of "learning experiences"
along the way, some will be painful. I guarantee that too.
Responding to your points
1) Yes, no, and maybe. For relatively small docs on relatively modern
hardware, it's a good place to start. Then you have to push it until
it falls over to determine your _real_ rates. See:
http://searchhub.org/dev/2012/07/23/sizing-hardware-in-the-abstract-why-we-dont-have-a-definitive-answer/
2) Nobody knows. There's no theoretical reason why SolrCloud
shouldn't; no a-priori hard limits. I _strongly_ suspect you'll be on
the bleeding edge of size, though. Expect some things to be "learning
experiences".
3) No, it doesn't mean that at all. 64 is an arbitrary number that
means, IMO, "here there be dragons". As you start to scale out beyond
this you'll run into pesky issues I expect. Your network won't be as
reliable as you think. You'll find one of your VMs (which I expect
you'll be running on) has some glitches. Someone loaded a very CPU
intensive program on three of your machines and your Solrs on those
machines is being starved. Etc.
4) I've personally seen 1,000 node clusters. You ought to see the very
cool. SolrCloud admin graph I recently saw... But I expect you'll
actually be in for some kind of divide-and-conquer strategy whereby
you have a bunch of clusters that are significantly smaller. You
could, for instance, determine that the use-case you support is
searching across small ranges, say a week at a time and have 52
clusters of 128 machines or so. You could have 365 clusters of < 20
machines. It all depends on how the index will be used.
5) Not at all. See above, I've seen 5K/sec on 4 nodes, also supporting
simultaneous searching.
6) N/A
I really can't give you advice. You haven't, for instance, said
anything about searches. What kind of SLA are you aiming for? What
kind of queries? Faceting? Grouping? I can change the memory footprint
of Solr by firing off really ugly queries. In essence, you absolutely
must prototype, see the link above. And do a lot of homework defining
how you will search the corpus. Otherwise you're guessing. But at this
kind of scale, expect to do something other than throw all the docs at
a 64 node cluster and expect it to just work. It'll be a lot of work.
On Sat, Mar 22, 2014 at 6:48 PM, shushuai zhu <ss...@yahoo.com> wrote:
Jack, thanks for your reply.
Sorry for the confusion about 4 nodes. What I meant was to use 4 nodes to
do some POC, mainly focusing on handling the high incoming rate in a few
days instead of storing data over one year.
You estimated the required nodes (6,308) and storage (322TB) based on the
incoming rate and doc size. I have a few questions regarding to them:
1) Is "100 million docs/node" some general capacity guideline for a Solr
node?
2) Assuming we can provide 6,308 nodes, can Solr Cloud really scale to
that level? I found you indicated some "common sense limits" of Solr
Cluster size of 64 nodes in the following mail thread
http://find.searchhub.org/document/d823643e65fe2015#84f0c89df2426990
3) If 64 nodes are something we know Solr Cloud can scale up to, then does
it mean I can only be sure that 1% of the mentioned workload can be handle
by Solr Cloud? (64 is about 1% of 6,308 nodes)
4) The above mentioned "Solr Limitations" mail thread did mention some
cluster with 512 nodes but not really verified whether it worked or not;
assuming it worked, it just means we may be able to handle a little less
than 10% of the desired workload.
5) Given above simple deduction, it seems 2K docs/sec (10% of the
mentioned incoming rate) is the practical limitation of Solr Cloud we can
guess for our use case?
6) If the incoming rate is controlled to be around 1k or 2k docs/sec and
we want to use Solr Cluster with 64 nodes (or more if it still works),
what kind of collection/shard/core structure should be?
I am more looking for architectural advice regarding to Solr Cloud
structure to handle high incoming rate of relatively small docs.
Regards.
Shushuai
On Saturday, March 22, 2014 2:17 PM, Jack Krupansky
<j...@basetechnology.com> wrote:
20K docs/sec = 20,000 * 60 * 60 * 24 = 1,728,000,000 = 1.7 billion
docs/day
* 365 = 630,720,000,000 = 631 billion docs/yr
At 100 million docs/node = 6,308 nodes!
And you think you can do it with 4 nodes?
Oh, and that's before replication!
0.5K/doc * 631 billion docs = 322 TB.
-- Jack Krupansky
-----Original Message-----
From: shushuai zhu
Sent: Saturday, March 22, 2014 11:32 AM
To: solr-user@lucene.apache.org
Subject: Re: Best approach to handle large volume of documents with
constantly high incoming rate?
Any thoughts? Can Solr Cloud support such use case with acceptable
performance?
On Thursday, March 20, 2014 7:51 PM, shushuai zhu <ss...@yahoo.com> wrote:
Hi,
I am looking for some advice to handle large volume of documents with a
very
high incoming rate. The size of each document is about 0.5 KB and the
incoming rate could be more than 20K per second and we want to store about
one year's documents in Solr for near real=time searching. The goal is to
achieve acceptable indexing and querying performance.
We will use techniques like soft commit, dedicated indexing servers, etc.
My
main question is about how to structure the collection/shard/core to
achieve
the goals. Since the incoming rate is very high, we do not want the
incoming
documents to affect the existing older indexes. Some thoughts are to
create
a latest index to hold the incoming documents (say latest half hour's
data,
about 36M docs) so queries on older data could be faster since the old
indexes are not affected. There seem three ways to grow the time dimension
by adding/splitting/creating a new object listed below every half hour:
collection
shard
core
Which is the best way to grow the time dimension? Any limitation in that
direction? Or there is some better approach?
As an example, I am thinking about having 4 nodes with the following
configuration to setup a Solr Cloud:
Memory: 128 GB
Storage: 4 TB
How to set the collection/shard/core to deal with the use case?
Thanks in advance.
Shushuai
