Set 1s timeout on search tab counts
Problem
At present when a user performs a search we load their results and then after the page loads we kick off many other searches to show the counts of results for all the tabs they aren't looking at. In most cases the amount of time it takes to load the tabs is considerably longer than loading their search results (eg. issue search may take 1s to load, but notes, blobs, wiki_blobs take 30s to load each). This doesn't seem like a problem on the face of things because they are async loaded after the results are loaded but the problem worsens when the user then performs another search before the tab counts are loaded.
At this point their new search is now queued behind all the slow tab counts since Elasticsearch limits how many concurrent searches it would perform. And again the problem compounds if they switch tabs or click the next page of results. Every single page load is again queueing up many more count searches which are again ahead of the users main search in Elasticsearch's queue.
Solution
We do really want to keep tab counts (discussed a little in #218565) due to the fact that they help the user decide if it's worth clicking on the tab to see results. People don't want to click on a tab and wait ages for results if it turns out the tab is just going to be empty anyway. But this is actually a self-perpetuating problem because the main reason switching tabs is slow is because of the counts loading in the first place. If we get the searches loading faster then the value of tab counts is lowered.
One main step we can take in the right direction (short of removing the counts per #218565 ) is to just set a timeout on count loads. We can set a 1s timeout and then if they don't load quickly you just won't see the tab count. Based on the Elasticsearch timeout implementation you actually get to see a count but it may be smaller than the full count because it stops counting when it hits the timeout.
Technical notes
I did some benchmarking which shows that setting a 1s timeout makes a big difference in terms of throughput for loading counts. My testing also showed that you still get results but when it times out the response looks like:
{
"took": 4393,
"timed_out": true,
"_shards": {
"total": 120,
"successful": 120,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 10000,
"relation": "gte"
},
"max_score": null,
"hits": []
}
}Weirdly though I set the timeout to 1s, as can be seen in the above response, it often took longer than 1s to timeout, likely due to the async nature of Elasticsearch. Either way it did indeed timeout and did remove the search from the queue quickly thus leading to higher throughput. Furthermore we can see in the above response that we do still get a count in the event of a timeout. That will give us the option to decide if we want to show the partial count to the user (minimal effort) or if we want to detect the timeout and show some indicator to the user that we could not fetch the count.
Benchmarking
benchmark-timeout.rb
#!/usr/bin/env ruby
require 'benchmark'
require 'rest-client'
require 'securerandom'
require 'json'
random = Random.new(1234) # Constant seed
N = 10
TERM_WORDS = ['auto', 'devops', 'hello', 'world', 'something', 'queryable', 'searching', 'somethingelse', 'search', 'issue', 'merge']
TERMS = N.times.map do
TERM_WORDS.sample(3, random: random).join(" | ")
end
CLUSTER_URL = ENV.fetch("CLUSTER_URL")
INDEX = ENV.fetch("INDEX")
BLOBS_QUERY = '{ "query": { "bool": { "must": [], "must_not": [], "should": [], "filter": [ { "simple_query_string": { "_name": "blob:match:search_terms", "fields": [ "blob.content", "blob.file_name", "blob.path" ], "query": "<QUERY>", "default_operator": "and" } }, { "has_parent": { "_name": "blob:authorized:project", "parent_type": "project", "query": { "bool": { "should": [ { "bool": { "filter": [ { "terms": { "_name": "blob:authorized:project:membership:id", "id": [ 13083, 13764, 14022, 14288, 14289, 19776, 20086, 20699, 23081, 27468, 27470, 27726, 29286, 32732, 36743, 72724, 74823, 83282, 95156, 116212, 143237, 145205, 150440, 227582, 250324, 250833, 278964, 280425, 387896, 430285, 443787, 444821, 480929, 554859, 593728, 684698, 730448, 734943, 766015, 818896, 876090, 928825, 931715, 998792, 1075790, 1254421, 1265999, 1329047, 1379171, 1441932, 1470839, 1507906, 1777822, 1794617, 1911766, 1990920, 2009901, 2127625, 2317465, 2337675, 2383700, 2645585, 2645607, 2645621, 2645625, 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"term": { "type": { "_name": "doc:is_a:blob", "value": "blob" } } } ] } }, "size": 0, "from": 0, "sort": [ "_score" ] }'
WIKI_BLOBS_QUERY = '{ "query": { "bool": { "must": [], "must_not": [], "should": [], "filter": [ { "simple_query_string": { "_name": "blob:match:search_terms", "fields": [ "blob.content", "blob.file_name", "blob.path" ], "query": "<QUERY>", "default_operator": "and" } }, { "has_parent": { "_name": "blob:authorized:project", "parent_type": "project", "query": { "bool": { "should": [ { "bool": { "filter": [ { "terms": { "_name": "blob:authorized:project:membership:id", "id": [ 14022, 19776, 20086, 23081, 27468, 27470, 32732, 83282, 95156, 116212, 227582, 387896, 480929, 684698, 730448, 734943, 818896, 876090, 998792, 1379171, 1441932, 1470839, 1507906, 1794617, 1911766, 1990920, 2127625, 2317465, 2383700, 2651596, 2670515, 2725567, 2953390, 3010986, 3010998, 3094319, 3101096, 3362933, 3588247, 3605985, 3631141, 3651684, 3662668, 3842996, 3843116, 3844141, 3871132, 3871556, 3885956, 3885980, 3933206, 3933372, 3991945, 4108541, 4149988, 4157550, 4176070, 4186742, 4262096, 4341757, 4534254, 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def search(term, query, timeout: nil)
query = query.sub("<QUERY>", term)
url = "#{CLUSTER_URL}/#{INDEX}/_search"
url += "?timeout=#{timeout}" if timeout
RestClient::Request.execute(method: :post, url: url, payload: query, headers: {content_type: :json, accept: :json}, timeout: 300)
end
def concurrent_searches(timeout: nil)
threads = []
TERMS.each do |term|
threads << Thread.new { search(term, BLOBS_QUERY, timeout: timeout) }
threads << Thread.new { search(term, WIKI_BLOBS_QUERY, timeout: timeout) }
threads << Thread.new { search(term, NOTES_QUERY, timeout: timeout) }
end
threads.each { |thread| thread.join }
end
Benchmark.bm(40) do |x|
x.report("no timeout (warmup)") { concurrent_searches }
x.report("no timeout") { concurrent_searches }
x.report("timeout=1s") { concurrent_searches(timeout: '1s') }
x.report("timeout=5s") { concurrent_searches(timeout: '5s') }
x.report("timeout=10s") { concurrent_searches(timeout: '10s') }
end user system total real
no timeout (warmup) 0.442852 0.055740 0.498592 ( 58.505819)
no timeout 0.488786 0.066158 0.554944 ( 51.707479)
timeout=1s 0.610661 0.066515 0.677176 ( 20.290569)
timeout=5s 0.415424 0.035180 0.450604 ( 39.979972)
timeout=10s 0.527192 0.054592 0.581784 ( 56.859809)Client side timeouts
At present the default timeouts for our Elasticsearch client are 60s. We can configure this in the admin UI too. But we could have a separate client side default for the count queries. I looked into this too as I wanted to ensure that if the client side times out and closes the connection it would additionally be quickly removed from the queue on the server side and thus quickly free up threads. This seemed to work as hoped and setting a client side timeout of 1s will massively improve throughput even further than the server side timeouts. But it will have the tradeoff that we won't get back a partial count. So it depends if we want the partial count or not as to whether we should use the client side timeout.
More examples of queuing causing problems
There is more evidence that these counts are causing queuing which is causing slow searches in #292439 (comment 499088147) and #292439 (comment 478042497)
Edited by Dylan Griffith