Le 16/09/2016 à 16:28, Guillaume Lederrey a écrit :
[...]
The enwiki_content example:
enwiki_content index is configured to have 6 shards and 3 replicas,
for a total number of 24 shards. It also has the additional constraint
that there is at most 1 enwiki_content per node. This ensures a
maximum spread of enwiki_content shards over the cluster. Since
enwiki_content is one of the index with the most traffic, this ensure
that the load is well distributed over the cluster.
side note: in mediawiki config
we updated shard count to 6 for
enwiki_content and set replica count to 4 for eqiad. This is still not
effective since we haven't rebuilt the eqiad enwiki index yet.
In short:
- eqiad effective settings for enwiki: 7*(3r+1p) => 28 shards
- eqiad future settings after a reindex: 6*(4r+1p) => 30 shards
- codfw for enwiki: 6*(3r+1p) => 28 shards
Now the bad news: for codfw, which is a 24 node
cluster, it means that
reaching this perfect equilibrium of 1 shard per node is a serious
challenge if you take into account the other constraint in place. Even
with relaxing the constraint to 2 enwiki shards per node, we have seen
unassigned shards during elasticsearch upgrade.
Potential improvements:
While ensuring that a large index has a number of shards close to the
number of nodes in the cluster allows for optimally spreading load
over the cluster, it degrade fast if all the stars are not aligned
perfectly. There are 2 opposite solutions
1) decrease the number of shards to leave some room to move them around
2) increase the number of shards and allow multiple shards of the same
index to be allocated on the same node
1) is probably impractical on our large indices, enwiki_content shards
are already ~30Gb and this makes it impractical to move them around
during relocation and recovery
I'm leaning towards 1, our shards are very big I agree and it takes a
non negligible time to move them around.
But we also noticed that the number of indices/shards is also a source
of pain for the master.
I don't think we should reduce the number of primary shards, I'm more
for reducing the number of replicas.
Historically I think enwiki has been set to 3 replicas for performance
reasons, not really for HA reasons.
Now that we moved all the prefix queries to a dedicated index I'd be
curious to see if we can serve fulltext queries for enwiki with only 2
replicas: 7*(2r+1p) => 21 shards total
I'd be curious to see how the load would look like if we isolate
autocomplete queries.
I think option 1 is more about how to trade HA vs shard count vs perf.
Another option would be 10*(1r+1p) => 20 smaller shards, we divide by 2
the total size required to store enwiki. But losing only 2 nodes can
cause enwiki to be red (partial results) vs 3 nodes today.
2) is probably our best bet. More smaller shards means that a single
query load will be spread over more nodes, potentially improving
response time. Increasing number of shards for enwiki_content from 6
to 20 (total shards = 80) means we have 80 / 24 = 3.3 shards per node.
Removing the 1 shards per node constraint and letting elasticsearch
spread the shards as best as it can means that in case 1 node is
missing, or during an upgrade, we still have the ability to move
shards around. Increasing this number even more might help keep the
load evenly spread across the cluster (the difference between 8 or 9
shards per node is smaller than the difference between 3 or 4 shards
per node).
We should be cautious here concerning response times, there are steps in
a lucene query that do not really benefit from having more shards. Only
collecting docs will really benefit from this, rewrite (scan the
lexicon) and rescoring (sorting the topN and then rescore) will add more
work if done on more shards. But we can certainly reduce the rescore
window with more primaries.
Could we estimate how many shards per node we will have in the end with
this strategy?
Today we have ~370 shards/node on codfw vs ~300 for eqiad.
David is going to do some tests to validate that those smaller shards
don't impact the scoring (smaller shards mean worse frequency
analysis).
Yes I'll try a 20 primaries enwiki index and see how it works.
I probably forgot a few points, but this email is more than long
enough already...
Thanks to all of you who kept reading until the end!
Thanks for writing it!