Closed mlissner closed 1 month ago
mlissner
commented
4 months ago @blancoramiro, is it easy to make the elastic disks 2× faster temporarily to see if that helps?
@albertisfu I'm finding that performance is still kind of a bummer. Did we do the work to make counts estimates in RECAP? Could we try that? Could we do some benchmarks before and after this and Ramiro's change, like we did before?
It'd be nice if we could make it 10× faster or even 5× faster.
albertisfu
commented
4 months ago We do have counts estimates in the Search API, it'd be easy to also apply it to the frontend for both Cases and Documents.
You can see how the estimates works in the API: https://www.courtlistener.com/api/rest/v4/search/?q=apple&type=r
vs the frontend
We could use these queries we already have to perform the benchmarks without having to change anything in the code yet.
Any query would you like to use in the benchmark?
mlissner
commented
4 months ago Hm....can just grab 50 words or so, and go with it? Maybe add a phrase or two, or add a multi-word queries? Doesn't have to be rigorous? Simple is fine?
I opened https://github.com/freelawproject/courtlistener/issues/4255 to spec out the change itself.
albertisfu
commented
4 months ago Here are the scripts to assess the performance of RECAP search queries in the frontend and the API:
Common code:
import requests
import time
from cl.search.models import SEARCH_TYPES
search_terms = [
'',
'The Litigation Practice Group',
'"Alston v. Penn State Health"',
'Danny Ray Jackson',
'"MEMBER CASE OPENED:"',
'Parties to exchange Rule ',
'BROOKS v. CITY',
'UNITED STATES',
'ALABAMA NORTHERN DIVISION',
'ALSAIDI v.HUBERT',
'Stroman v.U.S.Treasury',
'United States v.Ainsworth',
'Ballester v.State of Florida',
'Sharma v.Eyebrows',
'Search Warrant Issued in case as to Priority Mail Package addressed to',
'"all parties must sign their names on the attached Consent"',
'proceedings',
'held',
'before',
'Magistrate ',
'Judge',
'description:ORDER AND plain_text:Motion',
'description:ORDER OR plain_text:Motion',
'Levi Haywood',
'EASTERN DISTRICT OF CALIFORNIA'
'"EASTERN DISTRICT OF CALIFORNIA"',
'Signed by Magistrate Judge',
'shall',
'file',
'further',
'amended',
'pleadings',
'without',
'first',
'MINUTE ORDER',
'Motions deadline',
'Continuance of Motions',
'Detention and Identity',
'Case Management',
'Scheduling Order',
'New York State',
'Supreme Court',
'MAGISTRATE CASE TERMINATED',
'Detention and Identity Hearing',
'"Detention and Identity Hearing"',
'All pretrial motions',
'Each',
'party',
'will',
'bear',
'own',
'Second Floor',
'Plaintiff',
]Frontend:
response_times = {}
for search_term in search_terms:
start_time = time.time()
search_params = {
"q": search_term,
"type": SEARCH_TYPES.RECAP,
}
url = "http://cl-python:80/"
print("Doing search term:", search_term)
start_time = time.time()
try:
r = requests.get(url, params=search_params, )
except Exception as e:
print(f"An error occurred on search: {search_term}: {e}")
continue
response_time = time.time() - start_time
response_times.update({search_term: response_time})
print("Response Times:", response_times, "\n")
times = [value for value in response_times.values()]
average_time = sum(times) / len(times)
max_term = max(response_times, key=response_times.get)
min_term = min(response_times, key=response_times.get)
max_time = response_times[max_term]
min_time = response_times[min_term]
print(f"Average response time: {average_time:.2f} seconds.\n")
print(f"Search term with maximum request time: '{max_term}' :{max_time:.2f} seconds.\n")
print(f"Search term with minimum request time: '{min_term}' :{min_time:.2f} seconds.\n")
API:
INITIAL_URL = "http://cl-django:8000/api/rest/v4/search/"
TOKEN = "API_TOKEN"
HEADERS = {'Authorization': f'Token {TOKEN}'}
response_times = {}
for search_term in search_terms:
search_params = {
"q": search_term,
"type": SEARCH_TYPES.RECAP,
}
url = INITIAL_URL
print("Doing search term:", search_term)
start_time = time.time()
try:
r = requests.get(url, params=search_params, headers=HEADERS)
except Exception as e:
print(f"An error occurred on search: {search_term}: {e}")
continue
response_time = time.time() - start_time
response_times.update({search_term: response_time})
print("Response Times:", response_times, "\n")
times = [value for value in response_times.values()]
average_time = sum(times) / len(times)
max_term = max(response_times, key=response_times.get)
min_term = min(response_times, key=response_times.get)
max_time = response_times[max_term]
min_time = response_times[min_term]
print(f"Average response time: {average_time:.2f} seconds.\n")
print(f"Search term with maximum request time: '{max_term}' :{max_time:.2f} seconds.\n")
print(f"Search term with minimum request time: '{min_term}' :{min_time:.2f} seconds.\n")The search terms were extracted from the actual results in production, so all of them will return results. Some of the terms are single words, multi-word phrases, and fielded queries. It also includes a match-all query.
I couldn't run the frontend script locally using the courtlistener.com domain since the CloudFront bot protection blocked the requests. So, maybe we should run these within a maintenance pod using the local interface http://cl-django:8000 as the base URL.
Another thing to consider in this approach is that the frontend responses are heavier than the API responses, which could influence response times.
We should also considering to perform the benchmarks under low and stable resource usage conditions, ensuring equal conditions for both tests. When the cluster is overloaded, response times are significantly slower.
Right now the cluster looks good:
mlissner
commented
4 months ago Running this now. Had to change the host to http://cl-python:80 (the docker image serves port 8000, but k8s maps it to 80).
I didn't run it on the API because I'm focused on the front end right now, and here are the results:
Response Times: {'': 12.72679328918457, 'The Litigation Practice Group': 4.4000794887542725, '"Alston v. Penn State Health"': 2.901895761489868, 'Danny Ray Jackson': 1.4988391399383545, '"MEMBER CASE OPENED:"': 3.345663547515869, 'Parties to exchange Rule ': 6.574068307876587, 'BROOKS v. CITY': 2.9397776126861572, 'UNITED STATES': 186.8716230392456, 'ALABAMA NORTHERN DIVISION': 3.087289810180664, 'ALSAIDI v.HUBERT': 2.9419922828674316, 'Stroman v.U.S.Treasury': 1.8923239707946777, 'United States v.Ainsworth': 2.8511767387390137, 'Ballester v.State of Florida': 2.462733030319214, 'Sharma v.Eyebrows': 1.9518721103668213, 'Search Warrant Issued in case as to Priority Mail Package addressed to': 4.180243253707886, '"all parties must sign their names on the attached Consent"': 5.403063774108887, 'proceedings': 6.067562580108643, 'held': 7.175939559936523, 'before': 8.487770080566406, 'Magistrate ': 6.1810996532440186, 'Judge': 10.150331735610962, 'description:ORDER AND plain_text:Motion': 2.4488093852996826, 'description:ORDER OR plain_text:Motion': 7.413483142852783, 'Levi Haywood': 1.444803237915039, 'EASTERN DISTRICT OF CALIFORNIA"EASTERN DISTRICT OF CALIFORNIA"': 12.86933159828186, 'Signed by Magistrate Judge': 11.687525272369385, 'shall': 3.837925434112549, 'file': 14.814674615859985, 'further': 4.451498985290527, 'amended': 8.610174894332886, 'pleadings': 3.954453945159912, 'without': 4.489995956420898, 'first': 6.471741199493408, 'MINUTE ORDER': 7.57893967628479, 'Motions deadline': 6.399441242218018, 'Continuance of Motions': 10.917569398880005, 'Detention and Identity': 2.7803921699523926, 'Case Management': 7.51436448097229, 'Scheduling Order': 11.391829252243042, 'New York State': 17.800521850585938, 'Supreme Court': 5.7317469120025635, 'MAGISTRATE CASE TERMINATED': 3.478390693664551, 'Detention and Identity Hearing': 3.153221607208252, '"Detention and Identity Hearing"': 3.5869739055633545, 'All pretrial motions': 4.075687646865845, 'Each': 3.4143118858337402, 'party': 5.735083103179932, 'will': 4.676147222518921, 'bear': 3.5608272552490234, 'own': 3.5920569896698, 'Second Floor': 2.9363274574279785, 'Plaintiff': 9.463297605514526}
Average response time: 9.31 seconds.
Search term with maximum request time: 'UNITED STATES' :186.87 seconds.
Search term with minimum request time: 'Levi Haywood' :1.44 seconds.Some of these queries are pretty nasty, but 9.3s is horrible. We have to do better.
mlissner
commented
3 months ago Hm, it really doesn't seem like this is helping:
Response Times: {'': 18.791208267211914, 'The Litigation Practice Group': 5.488582372665405, '"Alston v. Penn State Health"': 2.970630168914795, 'Danny Ray Jackson': 3.0387566089630127, '"MEMBER CASE OPENED:"': 5.681991338729858, 'Parties to exchange Rule ': 14.041479587554932, 'BROOKS v. CITY': 6.865917682647705, 'UNITED STATES': 175.2218804359436, 'ALABAMA NORTHERN DIVISION': 6.141289472579956, 'ALSAIDI v.HUBERT': 3.3412973880767822, 'Stroman v.U.S.Treasury': 2.4551193714141846, 'United States v.Ainsworth': 2.699310779571533, 'Ballester v.State of Florida': 5.875624895095825, 'Sharma v.Eyebrows': 1.7594366073608398, 'Search Warrant Issued in case as to Priority Mail Package addressed to': 6.98469614982605, '"all parties must sign their names on the attached Consent"': 5.930657386779785, 'proceedings': 5.324061870574951, 'held': 6.139306306838989, 'before': 6.155940055847168, 'Magistrate ': 6.4949586391448975, 'Judge': 13.00927734375, 'description:ORDER AND plain_text:Motion': 2.5427098274230957, 'description:ORDER OR plain_text:Motion': 6.364737272262573, 'Levi Haywood': 1.0771234035491943, 'EASTERN DISTRICT OF CALIFORNIA"EASTERN DISTRICT OF CALIFORNIA"': 13.544883251190186, 'Signed by Magistrate Judge': 11.198261499404907, 'shall': 4.069661378860474, 'file': 14.731014728546143, 'further': 5.110981702804565, 'amended': 9.103277444839478, 'pleadings': 4.2676122188568115, 'without': 12.3274245262146, 'first': 6.745590925216675, 'MINUTE ORDER': 8.751982927322388, 'Motions deadline': 8.40927267074585, 'Continuance of Motions': 11.018792629241943, 'Detention and Identity': 3.2815611362457275, 'Case Management': 9.135353088378906, 'Scheduling Order': 13.72115707397461, 'New York State': 16.117979764938354, 'Supreme Court': 4.59296178817749, 'MAGISTRATE CASE TERMINATED': 3.990290641784668, 'Detention and Identity Hearing': 2.776899576187134, '"Detention and Identity Hearing"': 3.5531041622161865, 'All pretrial motions': 5.297265291213989, 'Each': 3.5698962211608887, 'party': 6.834993362426758, 'will': 5.898565769195557, 'bear': 2.5243985652923584, 'own': 4.1746978759765625, 'Second Floor': 3.8925423622131348, 'Plaintiff': 14.044274091720581}
Average response time: 10.14 seconds.
Search term with maximum request time: 'UNITED STATES' :175.22 seconds.
Search term with minimum request time: 'Levi Haywood' :1.08 seconds.I've run it three different times and this is the best I got. Surprising.
albertisfu
commented
3 months ago Interesting and sad. But I think it makes sense. The three queries are executed (main and two count queries) using the multi-search API, so as soon as they are received in the cluster, they are executed in parallel most of the time, depending on available resources. The response is sent to the client once all three queries have finished. Therefore, the total query time will always be tied to the slowest query, in this case, the main query which is slow due to its parent-child nature. So it doesn't matter how fast the count queries are if the main query is slow.
However, there could still be a benefit in terms of resource usage since it's assumed that cardinality queries use less RAM.
Unfortunately, there is no data before July 30 in Grafana, but it appears there is a slight decrease in memory usage after August 1, which was the date cardinality queries were released.
We can also analyze the count times vs. the main query time by performing the following queries in Kibana:
There are three queries a "fast" one, a "medium" one, and a match-all query, which took the most time except for the "United States" query.
GET recap_vectors/_msearch
{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma v. Eyebrows","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}},"inner_hits":{"name":"filter_query_inner_recap_document","size":6,"_source":{"excludes":["plain_text"]},"highlight":{"fields":{"short_description":{"type":"fvh","matched_fields":["short_description","short_description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"description":{"type":"fvh","matched_fields":["description","description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"plain_text":{"type":"fvh","matched_fields":["plain_text","plain_text.exact"],"fragment_size":100,"no_match_size":500,"number_of_fragments":1,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}}}}},{"bool":{"filter":[{"match":{"docket_child":"docket"}}],"should":[{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^50","docketNumber^3.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^50","docketNumber^3.0"],"query":"Sharma v. Eyebrows","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}]}},"sort":[{"_score":{"order":"desc"}}],"highlight":{"fields":{"assignedTo":{"type":"fvh","matched_fields":["assignedTo","assignedTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"caseName":{"type":"fvh","matched_fields":["caseName","caseName.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"cause":{"type":"fvh","matched_fields":["cause","cause.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"court_citation_string":{"type":"fvh","matched_fields":["court_citation_string","court_citation_string.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"docketNumber":{"type":"fvh","matched_fields":["docketNumber","docketNumber.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"juryDemand":{"type":"fvh","matched_fields":["juryDemand","juryDemand.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"referredTo":{"type":"fvh","matched_fields":["referredTo","referredTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"suitNature":{"type":"fvh","matched_fields":["suitNature","suitNature.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}},"size":10,"from":0,"_source":{"excludes":[]}}
{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma v. Eyebrows","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}}},{"bool":{"filter":[{"match":{"docket_child":"docket"}}],"should":[{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^50","docketNumber^3.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^50","docketNumber^3.0"],"query":"Sharma v. Eyebrows","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"docket_id","precision_threshold":2000}}},"size":0,"track_total_hits":true}
{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma v. Eyebrows","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1,"filter":[{"match":{"docket_child":"recap_document"}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"id","precision_threshold":2000}}},"size":0,"track_total_hits":true}
GET recap_vectors/_msearch
{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE ORDER","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}},"inner_hits":{"name":"filter_query_inner_recap_document","size":6,"_source":{"excludes":["plain_text"]},"highlight":{"fields":{"short_description":{"type":"fvh","matched_fields":["short_description","short_description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"description":{"type":"fvh","matched_fields":["description","description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"plain_text":{"type":"fvh","matched_fields":["plain_text","plain_text.exact"],"fragment_size":100,"no_match_size":500,"number_of_fragments":1,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}}}}},{"bool":{"filter":[{"match":{"docket_child":"docket"}}],"should":[{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^4.0","docketNumber^3.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^4.0","docketNumber^3.0"],"query":"MINUTE ORDER","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}]}},"sort":[{"_score":{"order":"desc"}}],"highlight":{"fields":{"assignedTo":{"type":"fvh","matched_fields":["assignedTo","assignedTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"caseName":{"type":"fvh","matched_fields":["caseName","caseName.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"cause":{"type":"fvh","matched_fields":["cause","cause.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"court_citation_string":{"type":"fvh","matched_fields":["court_citation_string","court_citation_string.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"docketNumber":{"type":"fvh","matched_fields":["docketNumber","docketNumber.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"juryDemand":{"type":"fvh","matched_fields":["juryDemand","juryDemand.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"referredTo":{"type":"fvh","matched_fields":["referredTo","referredTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"suitNature":{"type":"fvh","matched_fields":["suitNature","suitNature.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}},"size":10,"from":0,"_source":{"excludes":[]}}
{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE ORDER","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}}},{"bool":{"filter":[{"match":{"docket_child":"docket"}}],"should":[{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^4.0","docketNumber^3.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^4.0","docketNumber^3.0"],"query":"MINUTE ORDER","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"docket_id","precision_threshold":2000}}},"size":0,"track_total_hits":true}
{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE ORDER","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1,"filter":[{"match":{"docket_child":"recap_document"}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"id","precision_threshold":2000}}},"size":0,"track_total_hits":true}GET recap_vectors/_msearch
{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"match_all":{}},"inner_hits":{"name":"filter_query_inner_recap_document","size":6,"_source":{"excludes":["plain_text"]},"highlight":{"fields":{"short_description":{"type":"fvh","matched_fields":["short_description","short_description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"description":{"type":"fvh","matched_fields":["description","description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"plain_text":{"type":"fvh","matched_fields":["plain_text","plain_text.exact"],"fragment_size":100,"no_match_size":500,"number_of_fragments":1,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}}}}},{"function_score":{"query":{"match":{"docket_child":"docket"}},"boost_mode":"replace","functions":[{"script_score":{"script":{"source":" return 0; "}}}]}}],"minimum_should_match":1}},"sort":[{"_score":{"order":"desc"}}],"highlight":{"fields":{"assignedTo":{"type":"fvh","matched_fields":["assignedTo","assignedTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"caseName":{"type":"fvh","matched_fields":["caseName","caseName.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"cause":{"type":"fvh","matched_fields":["cause","cause.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"court_citation_string":{"type":"fvh","matched_fields":["court_citation_string","court_citation_string.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"docketNumber":{"type":"fvh","matched_fields":["docketNumber","docketNumber.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"juryDemand":{"type":"fvh","matched_fields":["juryDemand","juryDemand.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"referredTo":{"type":"fvh","matched_fields":["referredTo","referredTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"suitNature":{"type":"fvh","matched_fields":["suitNature","suitNature.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}},"size":10,"from":0,"_source":{"excludes":[]}}
{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"match_all":{}}}},{"function_score":{"query":{"match":{"docket_child":"docket"}},"boost_mode":"replace","functions":[{"script_score":{"script":{"source":" return 0; "}}}]}}],"minimum_should_match":1}},"aggs":{"unique_documents":{"cardinality":{"field":"docket_id","precision_threshold":2000}}},"size":0,"track_total_hits":true}
{"index":["recap_vectors"]}
{"query":{"match":{"docket_child":"recap_document"}},"aggs":{"unique_documents":{"cardinality":{"field":"id","precision_threshold":2000}}},"size":0,"track_total_hits":true}This is the UNITED STATES query that took around 175 seconds. I added a profiling to this query. It'll be interesting to see which query stage is taking more time in this one.
GET recap_vectors/_msearch
{"index":["recap_vectors"]}
{"profile": true, "query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"UNITED AND STATES","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"UNITED STATES","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}},"inner_hits":{"name":"filter_query_inner_recap_document","size":6,"_source":{"excludes":["plain_text"]},"highlight":{"fields":{"short_description":{"type":"fvh","matched_fields":["short_description","short_description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"description":{"type":"fvh","matched_fields":["description","description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"plain_text":{"type":"fvh","matched_fields":["plain_text","plain_text.exact"],"fragment_size":100,"no_match_size":500,"number_of_fragments":1,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}}}}},{"bool":{"filter":[{"match":{"docket_child":"docket"}}],"should":[{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^4.0","docketNumber^3.0"],"query":"UNITED AND STATES","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^4.0","docketNumber^3.0"],"query":"UNITED STATES","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}]}},"sort":[{"_score":{"order":"desc"}}],"highlight":{"fields":{"assignedTo":{"type":"fvh","matched_fields":["assignedTo","assignedTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"caseName":{"type":"fvh","matched_fields":["caseName","caseName.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"cause":{"type":"fvh","matched_fields":["cause","cause.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"court_citation_string":{"type":"fvh","matched_fields":["court_citation_string","court_citation_string.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"docketNumber":{"type":"fvh","matched_fields":["docketNumber","docketNumber.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"juryDemand":{"type":"fvh","matched_fields":["juryDemand","juryDemand.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"referredTo":{"type":"fvh","matched_fields":["referredTo","referredTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"suitNature":{"type":"fvh","matched_fields":["suitNature","suitNature.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}},"size":10,"from":0,"_source":{"excludes":[]}}
{"index":["recap_vectors"]}
{"profile": true, "query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"UNITED AND STATES","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"UNITED STATES","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}}},{"bool":{"filter":[{"match":{"docket_child":"docket"}}],"should":[{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^4.0","docketNumber^3.0"],"query":"UNITED AND STATES","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^4.0","docketNumber^3.0"],"query":"UNITED STATES","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"docket_id","precision_threshold":2000}}},"size":0,"track_total_hits":true}
{"index":["recap_vectors"]}
{"profile": true, "query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"UNITED AND STATES","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"UNITED STATES","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1,"filter":[{"match":{"docket_child":"recap_document"}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"id","precision_threshold":2000}}},"size":0,"track_total_hits":true}
In terms of performance, I think it remains to test optimizations at the hardware level.
We could also test modifying the number of shards, which could reduce index fragmentation. What's the current size of the recap_index vectors?
Additionally, it seems that increasing the number of replicas can help improve response time; however, it could also impact indexing time.
mlissner
commented
3 months ago Here's the first response (I have to post them separately or Github says the comment is too large):
{
"took": 1276,
"responses": [
{
"took": 1276,
"timed_out": false,
"_shards": {
"total": 30,
"successful": 30,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 53,
"relation": "eq"
},
"max_score": 4465.1274,
"hits": [
{
"_index": "recap_vectors",
"_id": "68033039",
"_score": 4465.1274,
"_source": {
"docket_slug": "sharma-v-eyebrows-on-125th-inc",
"docket_absolute_url": "/docket/68033039/sharma-v-eyebrows-on-125th-inc/",
"court_exact": "nysd",
"party_id": [],
"party": [],
"attorney_id": [],
"attorney": [],
"firm_id": [],
"firm": [],
"docket_child": "docket",
"timestamp": "2024-03-27T09:12:21.368625",
"docket_id": 68033039,
"caseName": "Sharma v. Eyebrows on 125th Inc.",
"case_name_full": "",
"docketNumber": "1:23-cv-10309",
"suitNature": "Labor: Fair Standards",
"cause": "29:207(a) FLSA: Action for Overtime Wage Violation",
"juryDemand": "",
"jurisdictionType": "",
"dateArgued": null,
"dateFiled": "2023-11-24",
"dateTerminated": null,
"assignedTo": "Vernon Speede Broderick",
"assigned_to_id": 401,
"referredTo": null,
"referred_to_id": null,
"court": "District Court, S.D. New York",
"court_id": "nysd",
"court_citation_string": "S.D.N.Y.",
"chapter": null,
"trustee_str": null,
"date_created": "2023-11-24T17:09:12.945986+00:00",
"pacer_case_id": "610923"
},
"highlight": {
"caseName": [
"<mark>Sharma v. Eyebrows</mark> on 125th Inc."
]
},
"inner_hits": {
"filter_query_inner_recap_document": {
"hits": {
"total": {
"value": 27,
"relation": "eq"
},
"max_score": 2238.1729,
"hits": [
{
"_index": "recap_vectors",
"_id": "rd_395226098",
"_score": 2238.1729,
"_routing": "68033039",
"_source": {
"id": 395226098,
"docket_entry_id": 386601600,
"description": """ ORDER: Plaintiff filed this action on November 24, 2023, (Doc. 1), and filed affidavits of service on January 16, 2024, (Doc. 7), and January 26, 2024, (Doc. 8). The deadlines for Defendants Eyebrows on 125th, Inc. and Samira Nak (together, " ;Defendants") to respond to Plaintiff's complaint were January 10, 2024 and February 15, 2024, respectively. On March 28, 2024, the parties filed a joint stipulation to extend Defendants' deadline to answer the complaint to April 20 , 2024, (Doc. 9), which I endorsed, (Doc. 10). To date, Defendants have not appeared or responded to the complaint. Plaintiff, however, has taken no action to prosecute this case. Accordingly, if Plaintiff intends to seek a default judgment, she is directed to do so in accordance with Rule 4(H) of my Individual Rules and Practices in Civil Cases by no later than May 9, 2024. If Plaintiff fails to do so or otherwise demonstrate that she intends to prosecute this litigation, I may dismiss this case for failure to prosecute pursuant to Federal Rule of Civil Procedure 41(b). SO ORDERED. (Signed by Judge Vernon S. Broderick on 4/25/2024) (tg)""",
"entry_number": 14,
"entry_date_filed": "2024-04-25",
"short_description": "Order",
"document_type": "PACER Document",
"document_number": "14",
"pacer_doc_id": "127035359770",
"attachment_number": null,
"is_available": true,
"page_count": 2,
"filepath_local": "recap/gov.uscourts.nysd.610923/gov.uscourts.nysd.610923.14.0.pdf",
"absolute_url": "/docket/68033039/14/sharma-v-eyebrows-on-125th-inc/",
"cites": [],
"docket_child": {
"name": "recap_document",
"parent": 68033039
},
"timestamp": "2024-06-18T06:24:49.248822",
"docket_id": 68033039,
"caseName": "Sharma v. Eyebrows on 125th Inc.",
"case_name_full": "",
"docketNumber": "1:23-cv-10309",
"suitNature": "Labor: Fair Standards",
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"juryDemand": "",
"jurisdictionType": "",
"dateArgued": null,
"dateFiled": "2023-11-24",
"dateTerminated": null,
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"referred_to_id": null,
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"court_id": "nysd",
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"chapter": null,
"trustee_str": null,
"date_created": "2024-04-26T13:10:36.393617+00:00",
"pacer_case_id": "610923"
},
"highlight": {
"plain_text": [
""" :
BINITA <mark>SHARMA</mark>, on behalf of herself and all :
others similarly-situated"""
],
"description": [
""" ORDER: Plaintiff filed this action on November 24, 2023, (Doc. 1), and filed affidavits of service on January 16, 2024, (Doc. 7), and January 26, 2024, (Doc. 8). The deadlines for Defendants <mark>Eyebrows</mark> on 125th, Inc. and Samira Nak (together, " ;Defendants") to respond to Plaintiff's complaint were January 10, 2024 and February 15, 2024, respectively. On March 28, 2024, the parties filed a joint stipulation to extend Defendants' deadline to answer the complaint to April 20 , 2024, (Doc. 9), which I endorsed, (Doc. 10). To date, Defendants have not appeared or responded to the complaint. Plaintiff, however, has taken no action to prosecute this case. Accordingly, if Plaintiff intends to seek a default judgment, she is directed to do so in accordance with Rule 4(H) of my Individual Rules and Practices in Civil Cases by no later than May 9, 2024. If Plaintiff fails to do so or otherwise demonstrate that she intends to prosecute this litigation, I may dismiss this case for failure to prosecute pursuant to Federal Rule of Civil Procedure 41(b). SO ORDERED. (Signed by Judge Vernon S. Broderick on 4/25/2024) (tg)"""
]
}
},
{
"_index": "recap_vectors",
"_id": "rd_384379366",
"_score": 2226.9546,
"_routing": "68033039",
"_source": {
"id": 384379366,
"docket_entry_id": 376744678,
"description": "",
"entry_number": 8,
"entry_date_filed": "2024-01-26",
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"document_type": "PACER Document",
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"attachment_number": null,
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"docket_child": {
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},
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"date_created": "2024-01-26T18:09:09.731828+00:00",
"pacer_case_id": "610923"
},
"highlight": {
"plain_text": [
""
]
}
},
{
"_index": "recap_vectors",
"_id": "rd_383333944",
"_score": 2226.9546,
"_routing": "68033039",
"_source": {
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"entry_number": 7,
"entry_date_filed": "2024-01-16",
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"absolute_url": "/docket/68033039/7/sharma-v-eyebrows-on-125th-inc/",
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},
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"assignedTo": "Vernon Speede Broderick",
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"court_citation_string": "S.D.N.Y.",
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"date_created": "2024-01-16T18:08:51.936676+00:00",
"pacer_case_id": "610923"
},
"highlight": {
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""
]
}
},
{
"_index": "recap_vectors",
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"_score": 2226.9546,
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"_source": {
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"docket_entry_id": 371998449,
"description": "",
"entry_number": 4,
"entry_date_filed": "2023-11-30",
"short_description": "Civil Cover Sheet",
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"cites": [],
"docket_child": {
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},
"timestamp": "2024-06-15T05:39:24.917488",
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"court": "District Court, S.D. New York",
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"date_created": "2023-11-30T21:12:55.258382+00:00",
"pacer_case_id": "610923"
},
"highlight": {
"plain_text": [
""
]
}
},
{
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{
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"error": "Bad Gateway",
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}Shoot.
Finally,
What's the current size of the recap_index vectors?
Do you mean in terms of document count or disk size?
albertisfu
commented
3 months ago Thanks. Yeah, the responses confirmed that the query response time depends on the main query, even though the count queries are faster than the main query.
First query: Total time: "took": 1276 Main query: "took": 1276 Parent count query: "took": 562 Child count query: "took": 513
Second query: Total time: "took": 13922 Main query: "took": 13922 Parent count query: "took": 6545 Child count query: "took": 6118
Third query: Total time: "took": 17854 Main query: "took": 17854 Parent count query: "took": 6479 Child count query: "took": 6469
It seems that, on average, the count queries took less than 50% of the main query time.
It'd be interesting to see the relationship between query times before applying the cardinality counts. This query is the third one above but uses the exact counts.
GET recap_vectors/_msearch
{"index":["recap_vectors"]}
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{"query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1,"filter":[{"match":{"docket_child":"recap_document"}}]}},"size":0,"track_total_hits":true}Since the profile query "United States" timed out, let's check the profile in this one which is faster:
GET recap_vectors/_msearch
{"index":["recap_vectors"]}
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{"profile": true, "query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"match_all":{}}}},{"function_score":{"query":{"match":{"docket_child":"docket"}},"boost_mode":"replace","functions":[{"script_score":{"script":{"source":" return 0; "}}}]}}],"minimum_should_match":1}},"aggs":{"unique_documents":{"cardinality":{"field":"docket_id","precision_threshold":2000}}},"size":0,"track_total_hits":true}
{"index":["recap_vectors"]}
{"profile": true, "query":{"match":{"docket_child":"recap_document"}},"aggs":{"unique_documents":{"cardinality":{"field":"id","precision_threshold":2000}}},"size":0,"track_total_hits":true}The response from this one will be massive, so it might be better to save on a txt file and attach it to the comment.
Do you mean in terms of document count or disk size?
Yeah, I mean disk size.
mlissner
commented
3 months ago Here's the exact counts one:
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}Thanks. Regarding the index size, at first glance, it seems that the number of shards we're using is appropriate. Documentation recommends keeping them around 10 to 50GB. According to these numbers 1.2TB and 30 shards they are around 40GB per shard.
I'll analyze the results from the profile query and will get back with my findings.
albertisfu
commented
3 months ago Some interesting results from the profile query:
I took the most relevant metrics from each query stage, measured in seconds:
The query performed here is a match_all query, so all the dockets and recap documents are matched.
Main query took: 21.189 seconds
Profiling:
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][14]
Boolean query: 1.149140938
next_doc time: 0.599310444
next_doc count: 1990584
match_count: 1917963
Children:
GlobalOrdinalsWithScoreQuery : 0.271533686
FunctionScoreQuery : 0.327857571
Rewrite time: 2.789440775
----------------------
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][18]
Boolean query: 1.128727705
next_doc time: 0.589950168
next_doc count: 1991365
match_count: 1916120
Children:
GlobalOrdinalsWithScoreQuery : 0.269129212
FunctionScoreQuery : 0.325178117
Rewrite time: 2.504126795
----------------------
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][8]
Boolean query: 1.199912978
next_doc time: 0.625858493
next_doc count: 1986247
match_count: 1913089
Children:
GlobalOrdinalsWithScoreQuery : 0.271916193
FunctionScoreQuery : 0.324458007
Rewrite time: 2.276829145
----------------------
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][13]
Boolean query: 1.383895526
next_doc time: 0.76141532
next_doc count: 2000612
match_count: 1916593
Children:
GlobalOrdinalsWithScoreQuery : 0.273540707
FunctionScoreQuery : 0.422633991
Rewrite time: 1.310406402
----------------------
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][2]
Boolean query: 11.66285407
next_doc time: 11.040170386
next_doc count: 1990780
match_count: 1914971
Children:
GlobalOrdinalsWithScoreQuery : 0.286678909
FunctionScoreQuery : 0.3999565
Rewrite time: 2.05183367
----------------------
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][7]
Boolean query: 2.425392605
next_doc time: 1.792442304
next_doc count: 1987995
match_count: 1914244
Children:
GlobalOrdinalsWithScoreQuery : 0.289275427
FunctionScoreQuery : 0.396708194
Rewrite time: 2.854360008
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][0]
Boolean query: 1.372273179
next_doc time: 0.700496661
next_doc count: 1987429
match_count: 1915711
Children:
GlobalOrdinalsWithScoreQuery : 0.29380652
FunctionScoreQuery : 0.399695185
Rewrite time: 2.055848606
Fetch 10.787348231
FetchSourcePhase : 1.5656e-05
HighlightPhase : 10.722527856
InnerHitsPhase : 0.047860326
StoredFieldsPhase : 1.1479e-05
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][11]
Boolean query: 1.356173961
next_doc time: 0.699856185
next_doc count: 1990537
match_count: 1914180
Children:
GlobalOrdinalsWithScoreQuery : 0.276228847
FunctionScoreQuery : 0.392256958
Rewrite time: 1.863693391
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][4]
Boolean query: 1.336949399
next_doc time: 0.69100977
next_doc count: 1984365
match_count: 1912431
Children:
GlobalOrdinalsWithScoreQuery : 0.306251396
FunctionScoreQuery : 0.380760208
Rewrite time: 1.356518327
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][5]
Boolean query: 1.670413371
next_doc time: 0.741345127
next_doc count: 1990221
match_count: 1913769
Children:
GlobalOrdinalsWithScoreQuery : 0.295186717
FunctionScoreQuery : 0.602928234
Rewrite time: 2.733974485
----------------------
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][15]
Boolean query: 1.26652474
next_doc time: 0.669461242
next_doc count: 1990041
match_count: 1915320
Children:
GlobalOrdinalsWithScoreQuery : 0.260785286
FunctionScoreQuery : 0.386011299
Rewrite time: 2.675710818
----------------------
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][23]
Boolean query: 1.241677129
next_doc time: 0.658713749
next_doc count: 1977303
match_count: 1914447
Children:
GlobalOrdinalsWithScoreQuery : 0.26973578
FunctionScoreQuery : 0.385961883
Rewrite time: 1.921310134
----------------------
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][25]
Boolean query: 1.200228
next_doc time: 0.619843624
next_doc count: 1922747
match_count: 1914971
Children:
GlobalOrdinalsWithScoreQuery : 1.401457648
FunctionScoreQuery : 0.378686316
Rewrite time: 2.479119849
----------------------
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][28]
Boolean query: 17.844437329
next_doc time: 17.243741057
next_doc count: 1989598
match_count: 1917679
Children:
GlobalOrdinalsWithScoreQuery : 0.363890004
FunctionScoreQuery : 0.401994226
Rewrite time: 1.551175455
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][10]
Boolean query: 1.445266934
next_doc time: 0.808907049
next_doc count: 1978686
match_count: 1916915
Children:
GlobalOrdinalsWithScoreQuery : 0.271964042
FunctionScoreQuery : 0.375455658
Rewrite time: 2.373416569
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][16]
Boolean query: 1.427722705
next_doc time: 0.821667121
next_doc count: 1980396
match_count: 1915965
Children:
GlobalOrdinalsWithScoreQuery : 0.271881919
FunctionScoreQuery : 0.369708932
Rewrite time: 1.141221784
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][1]
Boolean query: 1.362497525
next_doc time: 0.766043934
next_doc count: 1990121
match_count: 1916203
Children:
GlobalOrdinalsWithScoreQuery : 0.2570557
FunctionScoreQuery : 0.371698783
Rewrite time: 2.132193494
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][6]
Boolean query: 1.359441276
next_doc time: 0.763031092
next_doc count: 1988078
match_count: 1911995
Children:
GlobalOrdinalsWithScoreQuery : 0.276500775
FunctionScoreQuery : 0.368847406
Rewrite time: 2.347767292
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][22]
Boolean query: 0.960888855
next_doc time: 0.448035344
next_doc count: 1987366
match_count: 1913643
Children:
GlobalOrdinalsWithScoreQuery : 0.222549543
FunctionScoreQuery : 5.975003921
Rewrite time: 2.097626673
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][26]
Boolean query: 0.953082901
next_doc time: 0.447565337
next_doc count: 1991155
match_count: 1914423
Children:
GlobalOrdinalsWithScoreQuery : 0.21728484
FunctionScoreQuery : 0.343800378
Rewrite time: 1.944356577
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][27]
Boolean query: 0.955000888
next_doc time: 0.452163351
next_doc count: 1982598
match_count: 1915288
Children:
GlobalOrdinalsWithScoreQuery : 0.210397232
FunctionScoreQuery : 0.352277854
Rewrite time: 2.183583109
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][29]
Boolean query: 0.973286274
next_doc time: 0.464520008
next_doc count: 1986944
match_count: 1913427
Children:
GlobalOrdinalsWithScoreQuery : 0.237742787
FunctionScoreQuery : 0.346691993
Rewrite time: 2.470964524
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][12]
Boolean query: 1.203881776
next_doc time: 0.635688896
next_doc count: 1985407
match_count: 1915966
Children:
GlobalOrdinalsWithScoreQuery : 0.284795025
FunctionScoreQuery : 0.336961939
Rewrite time: 2.036485211
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][19]
Boolean query: 1.410838533
next_doc time: 0.654786597
next_doc count: 1975680
match_count: 1914269
Children:
GlobalOrdinalsWithScoreQuery : 0.278594495
FunctionScoreQuery : 0.371878306
Rewrite time: 2.879834845
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][3]
Boolean query: 1.251486733
next_doc time: 0.690457484
next_doc count: 1988682
match_count: 1913967
Children:
GlobalOrdinalsWithScoreQuery : 0.27963725
FunctionScoreQuery : 0.337119526
Rewrite time: 1.181618283
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][9]
Boolean query: 1.29860305
next_doc time: 0.735598692
next_doc count: 1940687
match_count: 1914614
Children:
GlobalOrdinalsWithScoreQuery : 0.346615506
FunctionScoreQuery : 0.33299498
Rewrite time: 1.428274735
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][17]
Boolean query: 1.147510148
next_doc time: 0.568096857
next_doc count: 1993979
match_count: 1916482
Children:
GlobalOrdinalsWithScoreQuery : 0.276526929
FunctionScoreQuery : 0.375037772
Rewrite time: 1.483313063
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][20]
Boolean query: 1.130241929
next_doc time: 0.554501772
next_doc count: 1979919
match_count: 1915993
Children:
GlobalOrdinalsWithScoreQuery : 0.254141576
FunctionScoreQuery : 0.368429899
Rewrite time: 1.817051731
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][21]
Boolean query: 1.641660828
next_doc time: 1.068206058
next_doc count: 1972721
match_count: 1910214
Children:
GlobalOrdinalsWithScoreQuery : 0.284420724
FunctionScoreQuery : 0.369171445
Rewrite time: 2.104193877
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][24]
Boolean query: 1.155535073
next_doc time: 0.578395729
next_doc count: 1990804
match_count: 1914188
Children:
GlobalOrdinalsWithScoreQuery : 0.284345492
FunctionScoreQuery : 0.368640339
Rewrite time: 2.473384488
----------------------In this match_all query, the Boolean query took an average of 2.19718 seconds, with common values around 1 to 1.5 seconds. However, there are some exceptions:
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][2]
Boolean query: 11.66285407
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][0]
Boolean query: 1.372273179
HighlightPhase : 10.722527856
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][28]
Boolean query: 17.844437329These are the shards that took more time. Shard 0 is special; it was the only one with a HighlightPhase, which took around 10 seconds. This is because the match_all query matched all results but only retrieved the first 10, which were allocated in Shard 0. Highlighting was applied to these results to return the snippet for the plain_text field, limiting it to the first 100 characters.
The situation in Shards 2 and 28 is different. In this case, the Boolean query took an unusual amount of time. What is strange is that these shards matched a similar number of documents as other shards, as shown by the next_doc count and match_count about 1.9 million documents on average.
This suggests that if shards are balanced in terms of the number of documents and the complexity of the query is the same across all of them (except for the one doing highlighting), the longer query times in some shards could be due to the workload on the node at that moment or a hardware issue in that specific node.
Docket count query took: 10.841
Profiling:
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][18]
Boolean query: 12.761728759
next_doc time: 12.329047036
next_doc count: 1991365
match_count: 1916120
Children:
BooleanQuery : 12.408661587
Rewrite time: 1.406728776
----------------------
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][5]
Boolean query: 1.276930591
next_doc time: 0.855946451
next_doc count: 1989967
match_count: 1913769
Children:
BooleanQuery : 0.925889317
Rewrite time: 2.446459596
----------------------
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][8]
Boolean query: 1.266405478
next_doc time: 0.845993419
next_doc count: 1986247
match_count: 1913089
Children:
BooleanQuery : 0.904172476
Rewrite time: 2.468408531
----------------------
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][9]
Boolean query: 5.663786532
next_doc time: 0.845171099
next_doc count: 1987374
match_count: 1914614
Children:
BooleanQuery : 5.281174888
Rewrite time: 1.786586492
----------------------
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][12]
Boolean query: 1.144439554
next_doc time: 0.856235487
next_doc count: 1978083
match_count: 1915966
Children:
BooleanQuery : 0.648816819
Rewrite time: 2.502853842
----------------------
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][13]
Boolean query: 0.978315316
next_doc time: 0.688506084
next_doc count: 2000612
match_count: 1916593
Children:
BooleanQuery : 0.665425788
Rewrite time: 2.52964694
----------------------
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][7]
Boolean query: 0.963840757
next_doc time: 0.677913647
next_doc count: 1987995
match_count: 1914244
Children:
BooleanQuery : 0.65566041
Rewrite time: 2.078242179
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][0]
Boolean query: 1.289643146
next_doc time: 0.707156242
next_doc count: 1987429
match_count: 1915711
Children:
BooleanQuery : 0.963648327
Rewrite time: 2.596404222
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][11]
Boolean query: 1.038255137
next_doc time: 0.735003786
next_doc count: 1990537
match_count: 1914180
Children:
BooleanQuery : 0.694536864
Rewrite time: 1.818054129
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][14]
Boolean query: 1.011664565
next_doc time: 0.707317668
next_doc count: 1988249
match_count: 1917963
Children:
BooleanQuery : 0.681686212
Rewrite time: 2.604686672
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][4]
Boolean query: 1.01489611
next_doc time: 0.711972068
next_doc count: 1984365
match_count: 1912431
Children:
BooleanQuery : 0.680776006
Rewrite time: 2.592852617
----------------------
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][15]
Boolean query: 1.082191102
next_doc time: 0.769237884
next_doc count: 1990041
match_count: 1915320
Children:
BooleanQuery : 0.75760746
Rewrite time: 1.633090642
----------------------
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][20]
Boolean query: 1.060145582
next_doc time: 0.748505301
next_doc count: 1924844
match_count: 1915993
Children:
BooleanQuery : 0.736182719
Rewrite time: 2.194722279
----------------------
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][23]
Boolean query: 1.127909802
next_doc time: 0.781891503
next_doc count: 1977303
match_count: 1914447
Children:
BooleanQuery : 0.808725995
Rewrite time: 2.550624833
----------------------
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][28]
Boolean query: 1.099405462
next_doc time: 0.772704606
next_doc count: 1989598
match_count: 1917679
Children:
BooleanQuery : 0.772423762
Rewrite time: 1.438533573
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][10]
Boolean query: 1.052024937
next_doc time: 0.745339427
next_doc count: 1978686
match_count: 1916915
Children:
BooleanQuery : 0.719929529
Rewrite time: 1.997497424
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][16]
Boolean query: 1.050863295
next_doc time: 0.741161229
next_doc count: 1980396
match_count: 1915965
Children:
BooleanQuery : 0.721378509
Rewrite time: 1.667898948
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][1]
Boolean query: 1.058002313
next_doc time: 0.751312127
next_doc count: 1990121
match_count: 1916203
Children:
BooleanQuery : 0.731554019
Rewrite time: 1.669596684
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][6]
Boolean query: 1.05429882
next_doc time: 0.748487038
next_doc count: 1988078
match_count: 1911995
Children:
BooleanQuery : 0.729856439
Rewrite time: 2.44639903
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][22]
Boolean query: 1.094922698
next_doc time: 0.799290219
next_doc count: 1987366
match_count: 1913643
Children:
BooleanQuery : 0.783355843
Rewrite time: 1.702940764
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][26]
Boolean query: 1.095693307
next_doc time: 0.803099557
next_doc count: 1991155
match_count: 1914423
Children:
BooleanQuery : 0.783955147
Rewrite time: 1.121822397
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][27]
Boolean query: 3.600513279
next_doc time: 3.303835812
next_doc count: 1982598
match_count: 1915288
Children:
BooleanQuery : 1.551554669
Rewrite time: 1.893334468
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][29]
Boolean query: 1.098133102
next_doc time: 0.80386955
next_doc count: 1986944
match_count: 1913427
Children:
BooleanQuery : 0.775091049
Rewrite time: 1.177010312
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][19]
Boolean query: 8.255496807
next_doc time: 0.71672592
next_doc count: 1975680
match_count: 1914269
Children:
BooleanQuery : 7.920384466
Rewrite time: 3.529400825
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][2]
Boolean query: 1.019132514
next_doc time: 0.714503633
next_doc count: 1991491
match_count: 1914971
Children:
BooleanQuery : 0.684709994
Rewrite time: 2.961098742
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][3]
Boolean query: 1.019026994
next_doc time: 0.714371629
next_doc count: 1988682
match_count: 1913967
Children:
BooleanQuery : 0.685184579
Rewrite time: 3.006552829
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][17]
Boolean query: 1.735156125
next_doc time: 0.692722424
next_doc count: 1993979
match_count: 1916482
Children:
BooleanQuery : 1.353689867
Rewrite time: 2.767437344
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][21]
Boolean query: 0.928381656
next_doc time: 0.655214678
next_doc count: 1972721
match_count: 1910214
Children:
BooleanQuery : 0.626568091
Rewrite time: 2.205690613
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][24]
Boolean query: 0.937254521
next_doc time: 0.663563497
next_doc count: 1990804
match_count: 1914188
Children:
BooleanQuery : 0.631797339
Rewrite time: 1.927572466
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][25]
Boolean query: 0.990624231
next_doc time: 0.712934424
next_doc count: 1992305
match_count: 1914971
Children:
BooleanQuery : 0.685542856
Rewrite time: 2.518122243
----------------------The average time in this query was: 1.958 seconds with common times around 1 second.
In this case shards that took the more time:
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][18]
Boolean query: 12.761728759
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][9]
Boolean query: 5.663786532
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][19]
Boolean query: 8.255496807Child count query took: 14.97
Profiling:
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][14]
Boolean query: 2.386647388
next_doc time: 2.385760068
next_doc count: 16531071
match_count: 0
Children:
TermQuery : 0.857677638
Rewrite time: 3.758e-06
----------------------
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][24]
Boolean query: 2.413320015
next_doc time: 2.412590853
next_doc count: 16682781
match_count: 0
Children:
TermQuery : 0.863473844
Rewrite time: 3.618e-06
----------------------
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][5]
Boolean query: 2.594158624
next_doc time: 2.592982469
next_doc count: 17001117
match_count: 0
Children:
TermQuery : 0.871896045
Rewrite time: 4.21e-06
----------------------
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][9]
Boolean query: 2.371423529
next_doc time: 2.370121727
next_doc count: 16416412
match_count: 0
Children:
TermQuery : 0.851958963
Rewrite time: 4.004e-06
----------------------
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][12]
Boolean query: 1.982878092
next_doc time: 1.981914602
next_doc count: 15268062
match_count: 0
Children:
TermQuery : 0.716204085
Rewrite time: 6.67e-06
----------------------
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][13]
Boolean query: 2.036490965
next_doc time: 2.035478811
next_doc count: 15893537
match_count: 0
Children:
TermQuery : 0.736274507
Rewrite time: 4.095e-06
----------------------
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][3]
Boolean query: 2.050947061
next_doc time: 2.049964239
next_doc count: 15576556
match_count: 0
Children:
TermQuery : 0.72799041
Rewrite time: 3.4667e-05
----------------------
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][7]
Boolean query: 2.213377185
next_doc time: 2.212473944
next_doc count: 17223608
match_count: 0
Children:
TermQuery : 0.793815192
Rewrite time: 3.537e-06
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][10]
Boolean query: 2.22085609
next_doc time: 2.219828012
next_doc count: 16204674
match_count: 0
Children:
TermQuery : 0.88272812
Rewrite time: 4.234e-06
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][1]
Boolean query: 13.104195599
next_doc time: 13.103167869
next_doc count: 16398015
match_count: 0
Children:
TermQuery : 0.884479295
Rewrite time: 4.234e-06
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][4]
Boolean query: 2.315099009
next_doc time: 2.314101854
next_doc count: 17011164
match_count: 0
Children:
TermQuery : 0.915542008
Rewrite time: 3.931e-06
----------------------
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][15]
Boolean query: 2.03501764
next_doc time: 2.034215874
next_doc count: 15112081
match_count: 0
Children:
TermQuery : 0.77994559
Rewrite time: 3.085e-06
----------------------
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][17]
Boolean query: 2.138290897
next_doc time: 2.137341127
next_doc count: 15765619
match_count: 0
Children:
TermQuery : 0.815146557
Rewrite time: 3.7e-06
----------------------
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][20]
Boolean query: 2.150749713
next_doc time: 2.149734681
next_doc count: 15763667
match_count: 0
Children:
TermQuery : 0.822973026
Rewrite time: 3.397e-06
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][0]
Boolean query: 2.223007944
next_doc time: 2.222208018
next_doc count: 15875123
match_count: 0
Children:
TermQuery : 0.903218768
Rewrite time: 3.692e-06
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][11]
Boolean query: 2.340351371
next_doc time: 2.337263765
next_doc count: 16701692
match_count: 0
Children:
TermQuery : 0.948214269
Rewrite time: 3.865e-06
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][16]
Boolean query: 2.209441408
next_doc time: 2.208669492
next_doc count: 15978716
match_count: 0
Children:
TermQuery : 0.898131351
Rewrite time: 3.413e-06
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][6]
Boolean query: 2.242255206
next_doc time: 2.24146898
next_doc count: 15981206
match_count: 0
Children:
TermQuery : 0.903206088
Rewrite time: 3.692e-06
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][21]
Boolean query: 2.356573964
next_doc time: 2.355704666
next_doc count: 15880310
match_count: 0
Children:
TermQuery : 1.03665897
Rewrite time: 3.693e-06
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][23]
Boolean query: 2.464702379
next_doc time: 2.463863683
next_doc count: 16815750
match_count: 0
Children:
TermQuery : 1.08173455
Rewrite time: 3.881e-06
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][27]
Boolean query: 2.482457321
next_doc time: 2.481619026
next_doc count: 17033361
match_count: 0
Children:
TermQuery : 1.074129296
Rewrite time: 3.553e-06
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][29]
Boolean query: 2.343308232
next_doc time: 2.342232001
next_doc count: 14573897
match_count: 0
Children:
TermQuery : 1.105776414
Rewrite time: 3.888e-06
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][18]
Boolean query: 2.221301083
next_doc time: 2.220708582
next_doc count: 16328842
match_count: 0
Children:
TermQuery : 0.892682695
Rewrite time: 3.323e-06
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][19]
Boolean query: 2.4292477
next_doc time: 2.428428116
next_doc count: 16460967
match_count: 0
Children:
TermQuery : 0.913961627
Rewrite time: 3.011e-06
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][2]
Boolean query: 2.273092484
next_doc time: 2.272468412
next_doc count: 16734750
match_count: 0
Children:
TermQuery : 0.896484174
Rewrite time: 2.978e-06
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][8]
Boolean query: 12.495959673
next_doc time: 12.495263767
next_doc count: 15881095
match_count: 0
Children:
TermQuery : 0.897151851
Rewrite time: 3.053e-06
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][22]
Boolean query: 10.9477632
next_doc time: 10.94689856
next_doc count: 15226741
match_count: 0
Children:
TermQuery : 0.632675982
Rewrite time: 3.166e-06
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][25]
Boolean query: 1.865628445
next_doc time: 1.864828478
next_doc count: 16434261
match_count: 0
Children:
TermQuery : 0.637171095
Rewrite time: 3.849e-06
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][26]
Boolean query: 1.903881186
next_doc time: 1.903019443
next_doc count: 16613313
match_count: 0
Children:
TermQuery : 0.631526527
Rewrite time: 3.273e-06
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][28]
Boolean query: 1.893517077
next_doc time: 1.892745584
next_doc count: 16438302
match_count: 0
Children:
TermQuery : 0.635110072
Rewrite time: 3.619e-06
----------------------
The average time for this query was 3.22 seconds, with common values around 2.5 seconds.
In brief, the shards that took the most time on each query are:
Main Query:
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][2]
Boolean query: 11.66285407
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][0]
Boolean query: 1.372273179
HighlightPhase : 10.722527856
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][28]
Boolean query: 17.844437329Docket Count Query:
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][18]
Boolean query: 12.761728759
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][9]
Boolean query: 5.663786532
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][19]
Boolean query: 8.255496807RECAPDocument Count query:
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][1]
Boolean query: 13.104195599
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][8]
Boolean query: 12.495959673
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][22]
Boolean query: 10.9477632From here we can see that are different shards which took the more time also different nodes, but we can see some common nodes between queries.
nmLgdM-aSDCkZNmyVoOodg
3zrjVUmdQbejwIdnw1XrAA
0cQl85qiTiyiNppgQkkPOAThis could indicate that those nodes were particularly overloaded during the query.
It's also interesting to note that the shard that took the most time in the main query (17 seconds)
[UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][28]
Used a different node in the RECAPDocument count query and took only (1.89 seconds)
[sRr5leJqQTucQqYSh3lPDA][recap_vectors][28]
The difference in the node is likely due to the fact that the other query was executed on a replica instead of the primary shard, meaning the replica could have been less overloaded at that moment. This suggests that adding more nodes and replicas might help.
In this case, if all the shards had performed at the average level, the match_all query, which is one of the most expensive, could have been completed in around 10 seconds (the longer time which belong to highlighting) seconds instead of 21.
I assume something similar might be happening with other common queries. Specifically, I would like to see how highlighting performs when the matched documents belong to different shards instead of just one, as in this case.
Here are two text queries with profiling enabled that should match HL.
{"index":["recap_vectors"]}
{"profile": true, "query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma v. Eyebrows","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}},"inner_hits":{"name":"filter_query_inner_recap_document","size":6,"_source":{"excludes":["plain_text"]},"highlight":{"fields":{"short_description":{"type":"fvh","matched_fields":["short_description","short_description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"description":{"type":"fvh","matched_fields":["description","description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"plain_text":{"type":"fvh","matched_fields":["plain_text","plain_text.exact"],"fragment_size":100,"no_match_size":500,"number_of_fragments":1,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}}}}},{"bool":{"filter":[{"match":{"docket_child":"docket"}}],"should":[{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^50","docketNumber^3.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^50","docketNumber^3.0"],"query":"Sharma v. Eyebrows","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}]}},"sort":[{"_score":{"order":"desc"}}],"highlight":{"fields":{"assignedTo":{"type":"fvh","matched_fields":["assignedTo","assignedTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"caseName":{"type":"fvh","matched_fields":["caseName","caseName.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"cause":{"type":"fvh","matched_fields":["cause","cause.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"court_citation_string":{"type":"fvh","matched_fields":["court_citation_string","court_citation_string.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"docketNumber":{"type":"fvh","matched_fields":["docketNumber","docketNumber.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"juryDemand":{"type":"fvh","matched_fields":["juryDemand","juryDemand.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"referredTo":{"type":"fvh","matched_fields":["referredTo","referredTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"suitNature":{"type":"fvh","matched_fields":["suitNature","suitNature.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}},"size":10,"from":0,"_source":{"excludes":[]}}
{"index":["recap_vectors"]}
{"profile": true, "query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma v. Eyebrows","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}}},{"bool":{"filter":[{"match":{"docket_child":"docket"}}],"should":[{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^50","docketNumber^3.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^50","docketNumber^3.0"],"query":"Sharma v. Eyebrows","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"docket_id","precision_threshold":2000}}},"size":0,"track_total_hits":true}
{"index":["recap_vectors"]}
{"profile": true, "query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma v. Eyebrows","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1,"filter":[{"match":{"docket_child":"recap_document"}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"id","precision_threshold":2000}}},"size":0,"track_total_hits":true}{"index":["recap_vectors"]}
{"profile": true, "query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE ORDER","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}},"inner_hits":{"name":"filter_query_inner_recap_document","size":6,"_source":{"excludes":["plain_text"]},"highlight":{"fields":{"short_description":{"type":"fvh","matched_fields":["short_description","short_description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"description":{"type":"fvh","matched_fields":["description","description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"plain_text":{"type":"fvh","matched_fields":["plain_text","plain_text.exact"],"fragment_size":100,"no_match_size":500,"number_of_fragments":1,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}}}}},{"bool":{"filter":[{"match":{"docket_child":"docket"}}],"should":[{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^4.0","docketNumber^3.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^4.0","docketNumber^3.0"],"query":"MINUTE ORDER","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}]}},"sort":[{"_score":{"order":"desc"}}],"highlight":{"fields":{"assignedTo":{"type":"fvh","matched_fields":["assignedTo","assignedTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"caseName":{"type":"fvh","matched_fields":["caseName","caseName.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"cause":{"type":"fvh","matched_fields":["cause","cause.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"court_citation_string":{"type":"fvh","matched_fields":["court_citation_string","court_citation_string.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"docketNumber":{"type":"fvh","matched_fields":["docketNumber","docketNumber.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"juryDemand":{"type":"fvh","matched_fields":["juryDemand","juryDemand.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"referredTo":{"type":"fvh","matched_fields":["referredTo","referredTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"suitNature":{"type":"fvh","matched_fields":["suitNature","suitNature.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}},"size":10,"from":0,"_source":{"excludes":[]}}
{"index":["recap_vectors"]}
{"profile": true, "query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE ORDER","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}}},{"bool":{"filter":[{"match":{"docket_child":"docket"}}],"should":[{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^4.0","docketNumber^3.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","cause","juryDemand","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","caseName^4.0","docketNumber^3.0"],"query":"MINUTE ORDER","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"docket_id","precision_threshold":2000}}},"size":0,"track_total_hits":true}
{"index":["recap_vectors"]}
{"profile": true, "query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["case_name_full","suitNature","juryDemand","cause","assignedTo","referredTo","court","court_id","court_citation_string","chapter","trustee_str","short_description","plain_text","document_type","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE ORDER","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1,"filter":[{"match":{"docket_child":"recap_document"}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"id","precision_threshold":2000}}},"size":0,"track_total_hits":true}That's interesting and a little troubling how one node being busy can have such a big impact.
It's also, perhaps, worth noting that the opinions index is getting a LOT of queries right now due to the citator. Probably isn't helping and is worth being aware of.
Still would love to see what happened if we upped our IOPs, say.
albertisfu
commented
3 months ago Thanks, here are the insights for the two queries above:
The first query took 2.583 seconds and is considered "small," as it only returned 53 dockets and 130 documents. On average, the boolean query time was 1.148 seconds, with common values around 0.7 seconds.
There were two shards where the queries deviated from the average:
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][28]
Boolean query: 1.607831676Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][29]
Boolean query: 14.415567881It’s surprising that the second one took 14 seconds, which is more than the total query time of 2.5 seconds.
Investigating about this issue it seems that this can occur during profiling because the times are relative to the operations performed in the query, and the process involves some sampling. Therefore, the times are approximations, and it's possible for components in the profile to show durations greater than the total query time. However, it is still useful to compare times between different shards and the query components themselves.
In this case, we can see that these two shards are the ones impacting performance the most.
Regarding highlighting, we can see that the HighlightPhase occurred in 7 shards. This means those shards contained the documents shown in the results, where highlighting was performed.
We can see HL is an expensive operation relative to other times in the query, ranging between 0.4 to 0.9 seconds for this query.
Main query took: 2.583
Profiling:
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][15]
Boolean query: 0.736800192
next_doc time: 0.303045966
next_doc count: 1980203
match_count: 1915531
Rewrite time: 0.186742462
----------------------
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][18]
Boolean query: 0.750751279
next_doc time: 0.284585339
next_doc count: 1991763
match_count: 1916319
Rewrite time: 0.166057726
----------------------
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][24]
Boolean query: 0.757525458
next_doc time: 0.296373345
next_doc count: 1991381
match_count: 1914437
Rewrite time: 0.090823433
----------------------
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][12]
Boolean query: 0.726744458
next_doc time: 0.25095527
next_doc count: 1978509
match_count: 1916214
Rewrite time: 0.137479616
----------------------
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][13]
Boolean query: 0.71018642
next_doc time: 0.252847242
next_doc count: 2001014
match_count: 1916836
Rewrite time: 0.243136079
----------------------
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][3]
Boolean query: 0.688643559
next_doc time: 0.248476791
next_doc count: 1985417
match_count: 1914203
Rewrite time: 0.232981537
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][0]
Boolean query: 0.273263974
next_doc time: 0.020559897
next_doc count: 7854
match_count: 6273
Rewrite time: 0.181158771
Fetch 1.031194435
FetchSourcePhase : 4.572e-06
HighlightPhase : 0.904988458
InnerHitsPhase : 0.125354968
StoredFieldsPhase : 4.93e-06
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][11]
Boolean query: 0.773315457
next_doc time: 0.257724006
next_doc count: 1990930
match_count: 1914403
Rewrite time: 0.170254584
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][14]
Boolean query: 0.156026711
next_doc time: 0.006614084
next_doc count: 90931
match_count: 85718
Rewrite time: 0.112184528
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][4]
Boolean query: 0.687925694
next_doc time: 0.255344475
next_doc count: 1984508
match_count: 1912655
Rewrite time: 0.21603024
Fetch 0.77759143
FetchSourcePhase : 1.937e-06
HighlightPhase : 0.662191618
InnerHitsPhase : 0.114465648
StoredFieldsPhase : 2.65e-06
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][5]
Boolean query: 0.730461209
next_doc time: 0.247839478
next_doc count: 1990660
match_count: 1914000
Rewrite time: 0.175955972
Fetch 0.856594574
FetchSourcePhase : 1.338e-06
HighlightPhase : 0.705610053
InnerHitsPhase : 0.150814563
StoredFieldsPhase : 1.789e-06
----------------------
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][23]
Boolean query: 0.708948871
next_doc time: 0.243208965
next_doc count: 1977370
match_count: 1914657
Rewrite time: 0.154885199
Fetch 0.723568522
FetchSourcePhase : 2.946e-06
HighlightPhase : 0.599949396
InnerHitsPhase : 0.112626836
StoredFieldsPhase : 2.002e-06
----------------------
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][28]
Boolean query: 1.607831676
next_doc time: 1.162615137
next_doc count: 1989974
match_count: 1917898
Rewrite time: 0.161929437
----------------------
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][29]
Boolean query: 14.415567881
next_doc time: 0.240373006
next_doc count: 1990592
match_count: 1913647
Rewrite time: 0.162123851
Fetch 0.791069819
FetchSourcePhase : 2.486e-06
HighlightPhase : 0.615194175
InnerHitsPhase : 0.171899881
StoredFieldsPhase : 5.088e-06
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][10]
Boolean query: 0.631761028
next_doc time: 0.238653667
next_doc count: 1979083
match_count: 1917170
Rewrite time: 0.062839492
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][16]
Boolean query: 0.751166297
next_doc time: 0.2285272
next_doc count: 1977250
match_count: 1914282
Rewrite time: 0.151349938
Fetch 0.55775287
FetchSourcePhase : 1.485e-06
HighlightPhase : 0.494883997
InnerHitsPhase : 0.062553493
StoredFieldsPhase : 1.748e-06
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][1]
Boolean query: 0.356030818
next_doc time: 0.102517885
next_doc count: 1772990
match_count: 1756058
Rewrite time: 0.195595732
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][6]
Boolean query: 0.638853351
next_doc time: 0.241738459
next_doc count: 1988463
match_count: 1912208
Rewrite time: 0.157758801
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][7]
Boolean query: 0.662754875
next_doc time: 0.245123347
next_doc count: 1990531
match_count: 1914471
Rewrite time: 0.168600046
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][19]
Boolean query: 0.762124948
next_doc time: 0.309950327
next_doc count: 1920966
match_count: 1914511
Rewrite time: 0.131694913
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][21]
Boolean query: 0.749797134
next_doc time: 0.318928981
next_doc count: 1972470
match_count: 1910419
Rewrite time: 0.180457965
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][27]
Boolean query: 0.794908265
next_doc time: 0.319039924
next_doc count: 1982812
match_count: 1915504
Rewrite time: 0.138961807
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][2]
Boolean query: 0.617193288
next_doc time: 0.242569313
next_doc count: 1991917
match_count: 1915195
Rewrite time: 0.090242882
Fetch 0.586715493
FetchSourcePhase : 5.145e-06
HighlightPhase : 0.499994914
InnerHitsPhase : 0.084062675
StoredFieldsPhase : 4.021e-06
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][8]
Boolean query: 0.671640456
next_doc time: 0.242101411
next_doc count: 1985042
match_count: 1913324
Rewrite time: 0.206257508
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][9]
Boolean query: 0.708002068
next_doc time: 0.248702816
next_doc count: 1941028
match_count: 1914841
Rewrite time: 0.166719722
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][17]
Boolean query: 0.617621519
next_doc time: 0.241172659
next_doc count: 1994279
match_count: 1916711
Rewrite time: 0.089775881
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][20]
Boolean query: 0.723637766
next_doc time: 0.242111276
next_doc count: 1980297
match_count: 1916193
Rewrite time: 0.164038476
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][22]
Boolean query: 0.76852272
next_doc time: 0.345871506
next_doc count: 1987875
match_count: 1913880
Rewrite time: 0.156595913
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][25]
Boolean query: 0.65212178
next_doc time: 0.243489316
next_doc count: 1991917
match_count: 1915205
Rewrite time: 0.127839779
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][26]
Boolean query: 0.613594991
next_doc time: 0.24162616
next_doc count: 1990152
match_count: 1914639
Rewrite time: 0.096956896
----------------------
Average time boolean; 1.1481241381000002The second query took 16.311 seconds and returned 1,142,666 dockets and 4,102,039 documents. On average, the boolean query time was 0.376 seconds, with common values around 0.2 seconds.
In this query, the operation that took the most relative time was highlighting, ranging from 5 to 8.65 seconds.
None of the shards in this query took longer than the total query time of 16 seconds. However, this time can be influenced by two factors:
Main query took: 16.311
Profiling:
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][14]
Boolean query: 0.238043742
next_doc time: 0.142742692
next_doc count: 72284
match_count: 55891
Rewrite time: 1.876817387
----------------------
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][15]
Boolean query: 0.209756171
next_doc time: 0.114563266
next_doc count: 54704
match_count: 42614
Rewrite time: 1.508245768
----------------------
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][24]
Boolean query: 0.229461056
next_doc time: 0.120820168
next_doc count: 211528
match_count: 189668
Rewrite time: 1.237936465
Fetch 6.326894308
FetchSourcePhase : 1.608e-06
HighlightPhase : 6.165551636
InnerHitsPhase : 0.160282513
StoredFieldsPhase : 2.199e-06
----------------------
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][4]
Boolean query: 0.949666578
next_doc time: 0.858686646
next_doc count: 56358
match_count: 43301
Rewrite time: 1.423048068
----------------------
Shard: [0cQl85qiTiyiNppgQkkPOA][recap_vectors][5]
Boolean query: 0.292866375
next_doc time: 0.214349506
next_doc count: 54655
match_count: 38537
Rewrite time: 1.801345592
Fetch 8.767344151
FetchSourcePhase : 2.183e-06
HighlightPhase : 8.659476346
InnerHitsPhase : 0.104650274
StoredFieldsPhase : 3.143e-06
----------------------
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][16]
Boolean query: 0.286142073
next_doc time: 0.201141775
next_doc count: 106494
match_count: 92134
Rewrite time: 2.34920159
Fetch 5.574720359
FetchSourcePhase : 2.749e-06
HighlightPhase : 5.418118768
InnerHitsPhase : 0.15504762
StoredFieldsPhase : 2.823e-06
----------------------
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][6]
Boolean query: 0.453422976
next_doc time: 0.130281604
next_doc count: 121174
match_count: 107675
Rewrite time: 1.90156547
----------------------
Shard: [1nSYxAz0Qb2rz_-d8z7bcw][recap_vectors][7]
Boolean query: 0.236109057
next_doc time: 0.157704668
next_doc count: 74329
match_count: 58094
Rewrite time: 1.886541154
----------------------
Shard: [3zrjVUmdQbejwIdnw1XrAA][recap_vectors][1]
Boolean query: 0.171967883
next_doc time: 0.090810364
next_doc count: 75840
match_count: 62050
Rewrite time: 2.211449445
----------------------
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][17]
Boolean query: 0.287008153
next_doc time: 0.141954104
next_doc count: 62260
match_count: 44695
Rewrite time: 2.147809223
Fetch 5.878162472
FetchSourcePhase : 1.822e-06
HighlightPhase : 5.796898865
InnerHitsPhase : 0.079406738
StoredFieldsPhase : 2.781e-06
----------------------
Shard: [UkMvqJ2UQQqjcVU9Dxq7_w][recap_vectors][23]
Boolean query: 0.482981892
next_doc time: 0.116565454
next_doc count: 121979
match_count: 106455
Rewrite time: 1.788949606
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][0]
Boolean query: 0.37045318
next_doc time: 0.264939164
next_doc count: 105757
match_count: 89497
Rewrite time: 1.589507968
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][10]
Boolean query: 0.225173358
next_doc time: 0.143999863
next_doc count: 57193
match_count: 44315
Rewrite time: 1.162117935
----------------------
Shard: [jqcLbOYxQvuudg-SqWb8cg][recap_vectors][11]
Boolean query: 0.180506461
next_doc time: 0.111457087
next_doc count: 56519
match_count: 39991
Rewrite time: 1.339690828
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][26]
Boolean query: 0.374340945
next_doc time: 0.29070232
next_doc count: 64150
match_count: 46447
Rewrite time: 2.020536303
Fetch 6.113781517
FetchSourcePhase : 1.723e-06
HighlightPhase : 6.029904685
InnerHitsPhase : 0.082666826
StoredFieldsPhase : 2.338e-06
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][27]
Boolean query: 0.758614779
next_doc time: 0.5854651
next_doc count: 139884
match_count: 123083
Rewrite time: 2.060061607
Fetch 6.134325905
FetchSourcePhase : 2.043e-06
HighlightPhase : 6.051479132
InnerHitsPhase : 0.081426911
StoredFieldsPhase : 1.649e-06
----------------------
Shard: [nL1wCXyqQCW64ODQvubEnA][recap_vectors][29]
Boolean query: 0.161656618
next_doc time: 0.07786763
next_doc count: 116098
match_count: 99123
Rewrite time: 0.77614845
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][12]
Boolean query: 0.173728099
next_doc time: 0.121862356
next_doc count: 55929
match_count: 41910
Rewrite time: 1.948737694
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][13]
Boolean query: 0.36670091
next_doc time: 0.222986009
next_doc count: 117442
match_count: 96771
Rewrite time: 1.992547977
Fetch 6.968885205
FetchSourcePhase : 2.814e-06
HighlightPhase : 6.873625766
InnerHitsPhase : 0.092830891
StoredFieldsPhase : 2.56e-06
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][18]
Boolean query: 0.239205995
next_doc time: 0.126003674
next_doc count: 57789
match_count: 43316
Rewrite time: 1.942288147
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][19]
Boolean query: 0.696449194
next_doc time: 0.58611002
next_doc count: 126974
match_count: 112820
Rewrite time: 1.848986279
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][2]
Boolean query: 0.344163501
next_doc time: 0.150047078
next_doc count: 86885
match_count: 66830
Rewrite time: 1.879295607
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][3]
Boolean query: 0.195023326
next_doc time: 0.127088714
next_doc count: 89867
match_count: 72504
Rewrite time: 1.836359446
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][8]
Boolean query: 1.929299371
next_doc time: 1.714718661
next_doc count: 54179
match_count: 39669
Rewrite time: 1.980760453
Fetch 7.374609581
FetchSourcePhase : 3.242e-06
HighlightPhase : 7.220519209
InnerHitsPhase : 0.135198811
StoredFieldsPhase : 3.946e-06
----------------------
Shard: [nmLgdM-aSDCkZNmyVoOodg][recap_vectors][9]
Boolean query: 0.28871354
next_doc time: 0.195449716
next_doc count: 49102
match_count: 41674
Rewrite time: 2.074638478
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][20]
Boolean query: 0.177945612
next_doc time: 0.102748156
next_doc count: 112985
match_count: 95665
Rewrite time: 1.858892178
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][21]
Boolean query: 0.351380438
next_doc time: 0.157184664
next_doc count: 80139
match_count: 66626
Rewrite time: 1.737052332
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][22]
Boolean query: 0.182847762
next_doc time: 0.110589042
next_doc count: 57108
match_count: 41080
Rewrite time: 1.787712377
Fetch 5.172538514
FetchSourcePhase : 2.314e-06
HighlightPhase : 5.038521958
InnerHitsPhase : 0.124168138
StoredFieldsPhase : 4.718e-06
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][25]
Boolean query: 0.233307084
next_doc time: 0.152671944
next_doc count: 83791
match_count: 65951
Rewrite time: 1.836253033
----------------------
Shard: [sRr5leJqQTucQqYSh3lPDA][recap_vectors][28]
Boolean query: 0.203588791
next_doc time: 0.12884844
next_doc count: 63615
match_count: 49249
Rewrite time: 1.757608713
----------------------
Average time boolean; 0.3763508306666667In brief:
In these more "common" queries, where the number of matched results is limited, the Boolean query is not the main component that takes the most time. Instead, highlighting is the component that takes the most time.
The size of the profiles is massive, as you can see. The reason is that the profile explains every part of the query by breaking it down. This can also explain why the rewrite time is high; for every term in the query, a smaller query is created for each synonym and for each field to search in. So, it’s something like terms synonyms fields, which causes the query expansion to grow quickly.
Currently, the fields to search in the query string are:
Parent query:
"case_name_full",
"suitNature",
"juryDemand",
"cause",
"assignedTo",
"referredTo",
"court",
"court_id",
"court_citation_string",
"chapter",
"trustee_str",
"caseName^4.0",
"docketNumber^3.0",Child query:
"case_name_full",
"suitNature",
"juryDemand",
"cause",
"assignedTo",
"referredTo",
"court",
"court_id",
"court_citation_string",
"chapter",
"trustee_str",
"short_description",
"plain_text",
"document_type",
"caseName^4.0",
"docketNumber^3.0",
"description^2.0"I was wondering if we really need all of those fields in the query string.
We could run some tests to see if removing certain fields might help reduce query times.
For instance, suitNature, assignedTo, referredTo, and court_id are already filters. Other fields like juryDemand, court, court_citation_string, chapter, trustee_str, and document_type could potentially be removed while still being matched using advanced syntax. This might reduce the query overhead for regular queries.
We could start by testing the same queries but limiting the query string fields to:
"case_name_full",
"short_description",
"plain_text",
"caseName^50",
"docketNumber^3.0",
"description^2.0"And see if there is a noticeable improvement.
GET /recap_vectors/_msearch
{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","short_description","plain_text","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND"}},{"query_string":{"fields":["case_name_full","short_description","plain_text","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE ORDER","type":"phrase","quote_field_suffix":".exact"}}],"minimum_should_match":1}},"inner_hits":{"name":"filter_query_inner_recap_document","size":6,"_source":{"excludes":["plain_text"]},"highlight":{"fields":{"short_description":{"type":"fvh","matched_fields":["short_description","short_description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"description":{"type":"fvh","matched_fields":["description","description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"plain_text":{"type":"fvh","matched_fields":["plain_text","plain_text.exact"],"fragment_size":100,"no_match_size":500,"number_of_fragments":1,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}}}}},{"bool":{"filter":[{"match":{"docket_child":"docket"}}],"should":[{"query_string":{"fields":["case_name_full","caseName^4.0","docketNumber^3.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND"}},{"query_string":{"fields":["case_name_full","caseName^4.0","docketNumber^3.0"],"query":"MINUTE ORDER","type":"phrase","quote_field_suffix":".exact"}}],"minimum_should_match":1}}]}},"sort":[{"_score":{"order":"desc"}}],"highlight":{"fields":{"assignedTo":{"type":"fvh","matched_fields":["assignedTo","assignedTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"caseName":{"type":"fvh","matched_fields":["caseName","caseName.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"cause":{"type":"fvh","matched_fields":["cause","cause.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"court_citation_string":{"type":"fvh","matched_fields":["court_citation_string","court_citation_string.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"docketNumber":{"type":"fvh","matched_fields":["docketNumber","docketNumber.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"juryDemand":{"type":"fvh","matched_fields":["juryDemand","juryDemand.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"referredTo":{"type":"fvh","matched_fields":["referredTo","referredTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"suitNature":{"type":"fvh","matched_fields":["suitNature","suitNature.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}},"size":10,"from":0,"_source":{"excludes":[]}}
{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","short_description","plain_text","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND"}},{"query_string":{"fields":["case_name_full","short_description","plain_text","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE ORDER","type":"phrase","quote_field_suffix":".exact"}}],"minimum_should_match":1}}}},{"bool":{"filter":[{"match":{"docket_child":"docket"}}],"should":[{"query_string":{"fields":["case_name_full","caseName^4.0","docketNumber^3.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND"}},{"query_string":{"fields":["case_name_full","caseName^4.0","docketNumber^3.0"],"query":"MINUTE ORDER","type":"phrase","quote_field_suffix":".exact"}}],"minimum_should_match":1}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"docket_id","precision_threshold":2000}}},"size":0,"track_total_hits":true}
{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","short_description","plain_text","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE AND ORDER","quote_field_suffix":".exact","default_operator":"AND"}},{"query_string":{"fields":["case_name_full","short_description","plain_text","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"MINUTE ORDER","type":"phrase","quote_field_suffix":".exact"}}],"minimum_should_match":1,"filter":[{"match":{"docket_child":"recap_document"}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"id","precision_threshold":2000}}},"size":0,"track_total_hits":true}{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","short_description","plain_text","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND"}},{"query_string":{"fields":["case_name_full","short_description","plain_text","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma v. Eyebrows","type":"phrase","quote_field_suffix":".exact"}}],"minimum_should_match":1}},"inner_hits":{"name":"filter_query_inner_recap_document","size":6,"_source":{"excludes":["plain_text"]},"highlight":{"fields":{"short_description":{"type":"fvh","matched_fields":["short_description","short_description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"description":{"type":"fvh","matched_fields":["description","description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"plain_text":{"type":"fvh","matched_fields":["plain_text","plain_text.exact"],"fragment_size":100,"no_match_size":500,"number_of_fragments":1,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}}}}},{"bool":{"filter":[{"match":{"docket_child":"docket"}}],"should":[{"query_string":{"fields":["case_name_full","caseName^50","docketNumber^3.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND"}},{"query_string":{"fields":["case_name_full","caseName^50","docketNumber^3.0"],"query":"Sharma v. Eyebrows","type":"phrase","quote_field_suffix":".exact"}}],"minimum_should_match":1}}]}},"sort":[{"_score":{"order":"desc"}}],"highlight":{"fields":{"assignedTo":{"type":"fvh","matched_fields":["assignedTo","assignedTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"caseName":{"type":"fvh","matched_fields":["caseName","caseName.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"cause":{"type":"fvh","matched_fields":["cause","cause.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"court_citation_string":{"type":"fvh","matched_fields":["court_citation_string","court_citation_string.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"docketNumber":{"type":"fvh","matched_fields":["docketNumber","docketNumber.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"juryDemand":{"type":"fvh","matched_fields":["juryDemand","juryDemand.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"referredTo":{"type":"fvh","matched_fields":["referredTo","referredTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"suitNature":{"type":"fvh","matched_fields":["suitNature","suitNature.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}},"size":10,"from":0,"_source":{"excludes":[]}}
{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","short_description","plain_text","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND"}},{"query_string":{"fields":["case_name_full","short_description","plain_text","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma v. Eyebrows","type":"phrase","quote_field_suffix":".exact"}}],"minimum_should_match":1}}}},{"bool":{"filter":[{"match":{"docket_child":"docket"}}],"should":[{"query_string":{"fields":["case_name_full","caseName^50","docketNumber^3.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND"}},{"query_string":{"fields":["case_name_full","caseName^50","docketNumber^3.0"],"query":"Sharma v. Eyebrows","type":"phrase","quote_field_suffix":".exact"}}],"minimum_should_match":1}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"docket_id","precision_threshold":2000}}},"size":0,"track_total_hits":true}
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{"query":{"bool":{"should":[{"query_string":{"fields":["case_name_full","short_description","plain_text","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND"}},{"query_string":{"fields":["case_name_full","short_description","plain_text","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma v. Eyebrows","type":"phrase","quote_field_suffix":".exact"}}],"minimum_should_match":1,"filter":[{"match":{"docket_child":"recap_document"}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"id","precision_threshold":2000}}},"size":0,"track_total_hits":true}
I agree, increasing the IOPs is something we should try, as it could reduce or eliminate the time spent in the queue for a query and improve the overall performance of the cluster.
Finally, I noticed that the count queries are still returning the total hits alongside the estimation. So, we're still not seeing the benefit of doing only the estimation query. I'm working on a tweak to fix this issue.
{
"took": 8141,
"timed_out": false,
"_shards": {
"total": 30,
"successful": 30,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1142666,
"relation": "eq"
},
"max_score": null,
"hits": []
},
"aggregations": {
"unique_documents": {
"value": 1132771
}
}Thanks this is more great research. I don't understand: Why is highlighting so slow? Like, do you know what it's actually doing that takes so long? I assume it pulls the content from disk (IO), applies some text manipulation to find the right things and mark them up (CPU), and then...that's it? I could see IO being the slow part of that...the CPU part seems like it'd be close to instant?
For the fields, you're right, we can remove a few:
These are all on both the parent and the child query:
I guess there's a reason for that?
I wouldn't want to remove too many of the other fields though. The idea is that somebody should be able to search for a judge's name or docket number or any of the fields we have boxes for and get back their cases.
I'll hold off on running your queries until we have decided on the fields. :)
albertisfu
commented
3 months ago Regarding HL, here's an explanation of how it works: https://www.elastic.co/guide/en/elasticsearch/reference/current/highlighting.html#how-es-highlighters-work-internally
Basically:
HL needs to break a text into fragments. First, it retrieves the content field from disk, which can be time consuming if the document is large. I have seen in forums that it is recommended to explicitly store the field for faster retrieval. However, I am not certain about this. We don't store the fields separately because they are already stored in the _source field by default, as the documentation recommends. Currently, when HL is applied, the field content is extracted from _source. Storing the fields separately might not be very helpful since we are highlighting many fields, including the plain_text field, which is the one slowing down the HL process. Storing HL fields would make more sense if we were not highlighting the plain_text field, as it would avoid retrieving and parsing this large content. However, I can do some tests to confirm if storing the fields independently helps in any way.
The text needs to be analyzed to find the best fragments those containing the terms that contributed to generating the hit. Since we use FVH, this process is faster than plain HL, as the terms and their offsets are indexed, allowing for efficient matching within the content. However, it can still be slow for large fields because each fragment generated in the previous step needs to be scored.Currently, our fragment_size is 100 characters. Let's say we have a content field with 1,000,000 characters; this would result in approximately 10,000 fragments to analyze and score and then the best fragment can be returned. We have documents (with plain_text field) that are even larger than that; I've seen documents exceeding 40MB in size. So when at least one large document is matched, it slows down the entire query.
The final step is to apply the HL tags to the best fragment, which should be instantaneous.
In summary:
Regarding the query string fields.
These are all on both the parent and the child query:
Yes, the reason for including both parent and child fields in the child query is that these parent fields are indexed within each RECAPDocument. To ensure queries match RECAPDocuments that combine parent and child terms, both fields need to be queried.
I agree; it’s better to keep some fields.
I have removed the indicated fields, so the fields to be looked at in the following queries are:
"suitNature",
"assignedTo",
"referredTo",
"court",
"court_id",
"court_citation_string",
"short_description",
"plain_text",
"caseName^4.0",
"docketNumber^3.0",
"description^2.0"GET /recap_vectors/_msearch
{"index":["recap_vectors"]}
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{"index":["recap_vectors"]}
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{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"query_string":{"fields":["suitNature","assignedTo","referredTo","court","court_id","court_citation_string","short_description","plain_text","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"Minute AND Order","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["suitNature","assignedTo","referredTo","court","court_id","court_citation_string","short_description","plain_text","caseName^4.0","docketNumber^3.0","description^2.0"],"query":"Minute Order","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1,"filter":[{"match":{"docket_child":"recap_document"}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"id","precision_threshold":2000}}},"size":0,"track_total_hits":false}{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"bool":{"should":[{"query_string":{"fields":["suitNature","assignedTo","referredTo","court","court_id","court_citation_string","short_description","plain_text","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["suitNature","assignedTo","referredTo","court","court_id","court_citation_string","short_description","plain_text","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}},"inner_hits":{"name":"filter_query_inner_recap_document","size":6,"_source":{"excludes":["plain_text"]},"highlight":{"fields":{"short_description":{"type":"fvh","matched_fields":["short_description","short_description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"description":{"type":"fvh","matched_fields":["description","description.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"plain_text":{"type":"fvh","matched_fields":["plain_text","plain_text.exact"],"fragment_size":100,"no_match_size":500,"number_of_fragments":1,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}}}}},{"bool":{"filter":[{"match":{"docket_child":"docket"}}],"should":[{"query_string":{"fields":["suitNature","assignedTo","referredTo","court","court_id","court_citation_string","caseName^50","docketNumber^3.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["suitNature","assignedTo","referredTo","court","court_id","court_citation_string","caseName^50","docketNumber^3.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}]}},"sort":[{"_score":{"order":"desc"}}],"highlight":{"fields":{"assignedTo":{"type":"fvh","matched_fields":["assignedTo","assignedTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"caseName":{"type":"fvh","matched_fields":["caseName","caseName.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"cause":{"type":"fvh","matched_fields":["cause","cause.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"court_citation_string":{"type":"fvh","matched_fields":["court_citation_string","court_citation_string.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"docketNumber":{"type":"fvh","matched_fields":["docketNumber","docketNumber.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"juryDemand":{"type":"fvh","matched_fields":["juryDemand","juryDemand.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"referredTo":{"type":"fvh","matched_fields":["referredTo","referredTo.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]},"suitNature":{"type":"fvh","matched_fields":["suitNature","suitNature.exact"],"fragment_size":0,"no_match_size":0,"number_of_fragments":0,"pre_tags":["<mark>"],"post_tags":["</mark>"]}}},"size":10,"track_total_hits":false,"from":0,"_source":{"excludes":[]}}
{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"has_child":{"type":"recap_document","score_mode":"max","query":{"bool":{"should":[{"query_string":{"fields":["suitNature","assignedTo","referredTo","court","court_id","court_citation_string","short_description","plain_text","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["suitNature","assignedTo","referredTo","court","court_id","court_citation_string","short_description","plain_text","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}}},{"bool":{"filter":[{"match":{"docket_child":"docket"}}],"should":[{"query_string":{"fields":["suitNature","assignedTo","referredTo","court","court_id","court_citation_string","caseName^50","docketNumber^3.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["suitNature","assignedTo","referredTo","court","court_id","court_citation_string","caseName^50","docketNumber^3.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"docket_id","precision_threshold":2000}}},"size":0,"track_total_hits":false}
{"index":["recap_vectors"]}
{"query":{"bool":{"should":[{"query_string":{"fields":["suitNature","assignedTo","referredTo","court","court_id","court_citation_string","short_description","plain_text","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","tie_breaker":0.3,"fuzziness":2}},{"query_string":{"fields":["suitNature","assignedTo","referredTo","court","court_id","court_citation_string","short_description","plain_text","caseName^50","docketNumber^3.0","description^2.0"],"query":"Sharma AND v. AND Eyebrows","quote_field_suffix":".exact","default_operator":"AND","type":"phrase","fuzziness":2}}],"minimum_should_match":1,"filter":[{"match":{"docket_child":"recap_document"}}]}},"aggs":{"unique_documents":{"cardinality":{"field":"id","precision_threshold":2000}}},"size":0,"track_total_hits":false}Here are the two queries:
And I re-ran the performance tweaks since https://github.com/freelawproject/courtlistener/pull/4294 is fixed:
Response Times: {'': 13.413657426834106, 'The Litigation Practice Group': 6.110074758529663, '"Alston v. Penn State Health"': 2.8999249935150146, 'Danny Ray Jackson': 2.344912052154541, '"MEMBER CASE OPENED:"': 3.9162790775299072, 'Parties to exchange Rule ': 8.006431818008423, 'BROOKS v. CITY': 3.8826067447662354, 'UNITED STATES': 177.82695603370667, 'ALABAMA NORTHERN DIVISION': 4.354727745056152, 'ALSAIDI v.HUBERT': 2.6585328578948975, 'Stroman v.U.S.Treasury': 2.476323366165161, 'United States v.Ainsworth': 2.9488751888275146, 'Ballester v.State of Florida': 3.4867286682128906, 'Sharma v.Eyebrows': 2.01751446723938, 'Search Warrant Issued in case as to Priority Mail Package addressed to': 6.130659580230713, '"all parties must sign their names on the attached Consent"': 6.62768030166626, 'proceedings': 5.782422304153442, 'held': 7.666126728057861, 'before': 7.025049448013306, 'Magistrate ': 8.00907278060913, 'Judge': 13.804168462753296, 'description:ORDER AND plain_text:Motion': 3.082529067993164, 'description:ORDER OR plain_text:Motion': 7.7227818965911865, 'Levi Haywood': 1.5846326351165771, 'EASTERN DISTRICT OF CALIFORNIA"EASTERN DISTRICT OF CALIFORNIA"': 15.423184633255005, 'Signed by Magistrate Judge': 13.404972314834595, 'shall': 4.716362237930298, 'file': 18.79629611968994, 'further': 5.5303263664245605, 'amended': 8.993834733963013, 'pleadings': 4.534790515899658, 'without': 8.69023609161377, 'first': 9.77959394454956, 'MINUTE ORDER': 12.289389610290527, 'Motions deadline': 8.711485147476196, 'Continuance of Motions': 14.934560537338257, 'Detention and Identity': 3.425201654434204, 'Case Management': 10.357580661773682, 'Scheduling Order': 20.103005170822144, 'New York State': 25.062979459762573, 'Supreme Court': 6.669983863830566, 'MAGISTRATE CASE TERMINATED': 5.362343788146973, 'Detention and Identity Hearing': 3.407471179962158, '"Detention and Identity Hearing"': 4.394794940948486, 'All pretrial motions': 7.0320658683776855, 'Each': 5.271927833557129, 'party': 7.979886054992676, 'will': 7.593557834625244, 'bear': 3.3768773078918457, 'own': 4.735814332962036, 'Second Floor': 3.843183755874634, 'Plaintiff': 18.96124577522278}
Average response time: 10.91 seconds.
Search term with maximum request time: 'UNITED STATES' :177.83 seconds.
Search term with minimum request time: 'Levi Haywood' :1.58 seconds.No major difference, unfortunately.
mlissner
commented
3 months ago @blancoramiro and I chatted a bit about this today. One of his goals is to evaluate AWS reservations and get them right, but he can't do so until we're sure we've got the right instance size and IOPS for Elastic. He's going to do some evaluation on the hardware side and see if he sees anything. I looked very briefly at IOPS today and didn't see any issues, but he's the expert.
albertisfu
commented
3 months ago No major difference, unfortunately.
Thanks. It seems that the main query's impact on the request is still the issue, even though the count queries have become more efficient.
For instance, the query for Minute Order before the count query fixes:
"took": 9726"took": 4328"took": 3266After the fix:
"took": 9517"took": 2550"took": 2584So, while the count queries took proportionally less time, the main query remains the largest component of the request, making it the bottleneck.
I performed the benchmarks described above to assess whether tweaking the fragment size or storing the fields can help. Here are my findings:
Control benchmark, current query: Fragment size 100 and fields not stored:
The testing index contains around 20,000 documents, and the query retrieves large RECAPDocuments on the first page, one around 20 MB and another 15 MB, with the others being average-sized documents.
I performed two measurements; one of them performed better.
| Min Throughput | search_recap fragment size 100 | 7.6 | ops/s |
| Mean Throughput | search_recap fragment size 100 | 8.17 | ops/s |
| Median Throughput | search_recap fragment size 100 | 8.23 | ops/s |
| Max Throughput | search_recap fragment size 100 | 8.44 | ops/s |
| 50th percentile latency | search_recap fragment size 100 | 339.536 | ms |
| 90th percentile latency | search_recap fragment size 100 | 347.043 | ms |
| 99th percentile latency | search_recap fragment size 100 | 360.197 | ms |
| 100th percentile latency | search_recap fragment size 100 | 399.558 | ms |
| 50th percentile service time | search_recap fragment size 100 | 339.536 | ms |
| 90th percentile service time | search_recap fragment size 100 | 347.043 | ms |
| 99th percentile service time | search_recap fragment size 100 | 360.197 | ms |
| 100th percentile service time | search_recap fragment size 100 | 399.558 | ms |
| Min Throughput | search_recap fragment size 100 | 9.05 | ops/s |
| Mean Throughput | search_recap fragment size 100 | 9.13 | ops/s |
| Median Throughput | search_recap fragment size 100 | 9.13 | ops/s |
| Max Throughput | search_recap fragment size 100 | 9.19 | ops/s |
| 50th percentile latency | search_recap fragment size 100 | 323.037 | ms |
| 90th percentile latency | search_recap fragment size 100 | 335.72 | ms |
| 99th percentile latency | search_recap fragment size 100 | 358.84 | ms |
| 100th percentile latency | search_recap fragment size 100 | 363.589 | ms |
| 50th percentile service time | search_recap fragment size 100 | 323.037 | ms |
| 90th percentile service time | search_recap fragment size 100 | 335.72 | ms |
| 99th percentile service time | search_recap fragment size 100 | 358.84 | ms |
| 100th percentile service time | search_recap fragment size 100 | 363.589 | ms |Fragment size 200 and not stored fields:
| Min Throughput | search_recap fragment size 200 | 8.49 | ops/s |
| Mean Throughput | search_recap fragment size 200 | 8.65 | ops/s |
| Median Throughput | search_recap fragment size 200 | 8.68 | ops/s |
| Max Throughput | search_recap fragment size 200 | 8.72 | ops/s |
| 50th percentile latency | search_recap fragment size 200 | 337.872 | ms |
| 90th percentile latency | search_recap fragment size 200 | 345.716 | ms |
| 99th percentile latency | search_recap fragment size 200 | 374.062 | ms |
| 100th percentile latency | search_recap fragment size 200 | 387.585 | ms |
| 50th percentile service time | search_recap fragment size 200 | 337.872 | ms |
| 90th percentile service time | search_recap fragment size 200 | 345.716 | ms |
| 99th percentile service time | search_recap fragment size 200 | 374.062 | ms |
| 100th percentile service time | search_recap fragment size 200 | 387.585 | ms |Fragment size 500 and not stored fields:
| Min Throughput | search_recap fragment size 500 | 8.66 | ops/s |
| Mean Throughput | search_recap fragment size 500 | 8.73 | ops/s |
| Median Throughput | search_recap fragment size 500 | 8.73 | ops/s |
| Max Throughput | search_recap fragment size 500 | 8.76 | ops/s |
| 50th percentile latency | search_recap fragment size 500 | 338.235 | ms |
| 90th percentile latency | search_recap fragment size 500 | 345.614 | ms |
| 99th percentile latency | search_recap fragment size 500 | 380.523 | ms |
| 100th percentile latency | search_recap fragment size 500 | 566.597 | ms |
| 50th percentile service time | search_recap fragment size 500 | 338.235 | ms |
| 90th percentile service time | search_recap fragment size 500 | 345.614 | ms |
| 99th percentile service time | search_recap fragment size 500 | 380.523 | ms |
| 100th percentile service time | search_recap fragment size 500 | 566.597 | ms |Fragment size 1000 and not stored fields:
| Min Throughput | search_recap fragment size 1000 | 8.69 | ops/s |
| Mean Throughput | search_recap fragment size 1000 | 8.77 | ops/s |
| Median Throughput | search_recap fragment size 1000 | 8.78 | ops/s |
| Max Throughput | search_recap fragment size 1000 | 8.83 | ops/s |
| 50th percentile latency | search_recap fragment size 1000 | 337.776 | ms |
| 90th percentile latency | search_recap fragment size 1000 | 345.019 | ms |
| 99th percentile latency | search_recap fragment size 1000 | 381.843 | ms |
| 100th percentile latency | search_recap fragment size 1000 | 413.431 | ms |
| 50th percentile service time | search_recap fragment size 1000 | 337.776 | ms |
| 90th percentile service time | search_recap fragment size 1000 | 345.019 | ms |
| 99th percentile service time | search_recap fragment size 1000 | 381.843 | ms |
| 100th percentile service time | search_recap fragment size 1000 | 413.431 | ms |As you can observe, increasing the fragment size when performing HL doesn't seem to significantly improve the request throughput. There appears to be a slight improvement, but it's not statistically significant enough to confirm.
In these benchmarks, I kept the fragment size fixed at 100 and moved the documents to a new index with a mapping where fields are explicitly stored.
Store all the parent and child HL fields.
| Min Throughput | search_recap fragment size 100 | 4.33 | ops/s |
| Mean Throughput | search_recap fragment size 100 | 4.38 | ops/s |
| Median Throughput | search_recap fragment size 100 | 4.39 | ops/s |
| Max Throughput | search_recap fragment size 100 | 4.4 | ops/s |
| 50th percentile latency | search_recap fragment size 100 | 673.649 | ms |
| 90th percentile latency | search_recap fragment size 100 | 693.949 | ms |
| 99th percentile latency | search_recap fragment size 100 | 726.465 | ms |
| 100th percentile latency | search_recap fragment size 100 | 763.673 | ms |
| 50th percentile service time | search_recap fragment size 100 | 673.649 | ms |
| 90th percentile service time | search_recap fragment size 100 | 693.949 | ms |
| 99th percentile service time | search_recap fragment size 100 | 726.465 | ms |
| 100th percentile service time | search_recap fragment size 100 | 763.673 | ms |Store only the biggest field plain_text
| Min Throughput | search_recap fragment size 100 | 6.68 | ops/s |
| Mean Throughput | search_recap fragment size 100 | 6.75 | ops/s |
| Median Throughput | search_recap fragment size 100 | 6.75 | ops/s |
| Max Throughput | search_recap fragment size 100 | 6.83 | ops/s |
| 50th percentile latency | search_recap fragment size 100 | 428.858 | ms |
| 90th percentile latency | search_recap fragment size 100 | 460.94 | ms |
| 99th percentile latency | search_recap fragment size 100 | 490.777 | ms |
| 100th percentile latency | search_recap fragment size 100 | 563.319 | ms |
| 50th percentile service time | search_recap fragment size 100 | 428.858 | ms |
| 90th percentile service time | search_recap fragment size 100 | 460.94 | ms |
| 99th percentile service time | search_recap fragment size 100 | 490.777 | ms |
| 100th percentile service time | search_recap fragment size 100 | 563.319 | ms |As you can observe, explicitly storing fields seems to worsen performance. The more fields are stored, the more performance is affected. This can be explained by the fact that when fields are stored, each one is accessed independently, increasing the number of IO operations. When fields are not stored, only one large IO operation is performed to retrieve the document from the_source field. This suggests that IO operations are the bottleneck during HL.
Fragment size 100, number of queried fields reduced In this bench mark I tested the same query with the number of fields limited to:
"suitNature",
"assignedTo",
"referredTo",
"court",
"court_id",
"court_citation_string",
"short_description",
"plain_text",
"caseName^4.0",
"docketNumber^3.0",
"description^2.0"| Min Throughput | search_recap fragment size 100 | 9.14 | ops/s |
| Mean Throughput | search_recap fragment size 100 | 9.21 | ops/s |
| Median Throughput | search_recap fragment size 100 | 9.22 | ops/s |
| Max Throughput | search_recap fragment size 100 | 9.24 | ops/s |
| 50th percentile latency | search_recap fragment size 100 | 319.636 | ms |
| 90th percentile latency | search_recap fragment size 100 | 332.008 | ms |
| 99th percentile latency | search_recap fragment size 100 | 369.359 | ms |
| 100th percentile latency | search_recap fragment size 100 | 372.878 | ms |
| 50th percentile service time | search_recap fragment size 100 | 319.636 | ms |
| 90th percentile service time | search_recap fragment size 100 | 332.008 | ms |
| 99th percentile service time | search_recap fragment size 100 | 369.359 | ms |
| 100th percentile service time | search_recap fragment size 100 | 372.878 | ms |It performed slightly better than the second control measure but still not great improvement.
Same query not HL at all:
| Min Throughput | search_recap fragment size 100 | 41.91 | ops/s |
| Mean Throughput | search_recap fragment size 100 | 42.35 | ops/s |
| Median Throughput | search_recap fragment size 100 | 42.23 | ops/s |
| Max Throughput | search_recap fragment size 100 | 43.1 | ops/s |
| 50th percentile latency | search_recap fragment size 100 | 70.3343 | ms |
| 90th percentile latency | search_recap fragment size 100 | 75.3417 | ms |
| 99th percentile latency | search_recap fragment size 100 | 106.796 | ms |
| 100th percentile latency | search_recap fragment size 100 | 122.628 | ms |
| 50th percentile service time | search_recap fragment size 100 | 70.3343 | ms |
| 90th percentile service time | search_recap fragment size 100 | 75.3417 | ms |
| 99th percentile service time | search_recap fragment size 100 | 106.796 | ms |
| 100th percentile service time | search_recap fragment size 100 | 122.628 | ms |In this benchmark we can clearly see how much highlighting impact query times, without HL the throughput is 5 times greater.
Same query no Parent HL fields
| Min Throughput | search_recap fragment size 100 | 9.72 | ops/s |
| Mean Throughput | search_recap fragment size 100 | 9.85 | ops/s |
| Median Throughput | search_recap fragment size 100 | 9.84 | ops/s |
| Max Throughput | search_recap fragment size 100 | 9.94 | ops/s |
| 50th percentile latency | search_recap fragment size 100 | 295.757 | ms |
| 90th percentile latency | search_recap fragment size 100 | 315.693 | ms |
| 99th percentile latency | search_recap fragment size 100 | 363.77 | ms |
| 100th percentile latency | search_recap fragment size 100 | 415.356 | ms |
| 50th percentile service time | search_recap fragment size 100 | 295.757 | ms |
| 90th percentile service time | search_recap fragment size 100 | 315.693 | ms |
| 99th percentile service time | search_recap fragment size 100 | 363.77 | ms |
| 100th percentile service time | search_recap fragment size 100 | 415.356 | ms |In this benchmark we can see that HL parent fields it's not the issue. Since the throughput is similar than HL parent + child documents.
Same query no Child HL fields
| Min Throughput | search_recap fragment size 100 | 29.49 | ops/s |
| Mean Throughput | search_recap fragment size 100 | 29.86 | ops/s |
| Median Throughput | search_recap fragment size 100 | 29.91 | ops/s |
| Max Throughput | search_recap fragment size 100 | 30.07 | ops/s |
| 50th percentile latency | search_recap fragment size 100 | 96.8208 | ms |
| 90th percentile latency | search_recap fragment size 100 | 100.634 | ms |
| 99th percentile latency | search_recap fragment size 100 | 111.949 | ms |
| 100th percentile latency | search_recap fragment size 100 | 116.243 | ms |
| 50th percentile service time | search_recap fragment size 100 | 96.8208 | ms |
| 90th percentile service time | search_recap fragment size 100 | 100.634 | ms |
| 99th percentile service time | search_recap fragment size 100 | 111.949 | ms |
| 100th percentile service time | search_recap fragment size 100 | 116.243 | ms |With this benchmark we can confirm the issue is the child fields HL.
Additional benchmarks to check if one of the child fields HL is the problematic one.
Same query no parent HL fields, no plain_text HL
| Min Throughput | search_recap fragment size 100 | 12.94 | ops/s |
| Mean Throughput | search_recap fragment size 100 | 13.19 | ops/s |
| Median Throughput | search_recap fragment size 100 | 13.19 | ops/s |
| Max Throughput | search_recap fragment size 100 | 13.38 | ops/s |
| 50th percentile latency | search_recap fragment size 100 | 216.931 | ms |
| 90th percentile latency | search_recap fragment size 100 | 230.963 | ms |
| 99th percentile latency | search_recap fragment size 100 | 259.773 | ms |
| 100th percentile latency | search_recap fragment size 100 | 270.772 | ms |
| 50th percentile service time | search_recap fragment size 100 | 216.931 | ms |
| 90th percentile service time | search_recap fragment size 100 | 230.963 | ms |
| 99th percentile service time | search_recap fragment size 100 | 259.773 | ms |
| 100th percentile service time | search_recap fragment size 100 | 270.772 | ms |Same query no parent HL fields, no description HL
| Min Throughput | search_recap fragment size 100 | 12.03 | ops/s |
| Mean Throughput | search_recap fragment size 100 | 12.1 | ops/s |
| Median Throughput | search_recap fragment size 100 | 12.1 | ops/s |
| Max Throughput | search_recap fragment size 100 | 12.15 | ops/s |
| 50th percentile latency | search_recap fragment size 100 | 241.675 | ms |
| 90th percentile latency | search_recap fragment size 100 | 257.003 | ms |
| 99th percentile latency | search_recap fragment size 100 | 304.894 | ms |
| 100th percentile latency | search_recap fragment size 100 | 356.061 | ms |
| 50th percentile service time | search_recap fragment size 100 | 241.675 | ms |
| 90th percentile service time | search_recap fragment size 100 | 257.003 | ms |
| 99th percentile service time | search_recap fragment size 100 | 304.894 | ms |
| 100th percentile service time | search_recap fragment size 100 | 356.061 | ms |Same query no parent HL fields, no short_description HL
| Min Throughput | search_recap fragment size 100 | 11.92 | ops/s |
| Mean Throughput | search_recap fragment size 100 | 12.03 | ops/s |
| Median Throughput | search_recap fragment size 100 | 12.04 | ops/s |
| Max Throughput | search_recap fragment size 100 | 12.12 | ops/s |
| 50th percentile latency | search_recap fragment size 100 | 242.785 | ms |
| 90th percentile latency | search_recap fragment size 100 | 253.996 | ms |
| 99th percentile latency | search_recap fragment size 100 | 287.265 | ms |
| 100th percentile latency | search_recap fragment size 100 | 298.066 | ms |
| 50th percentile service time | search_recap fragment size 100 | 242.785 | ms |
| 90th percentile service time | search_recap fragment size 100 | 253.996 | ms |
| 99th percentile service time | search_recap fragment size 100 | 287.265 | ms |
| 100th percentile service time | search_recap fragment size 100 | 298.066 | ms |From these benchmarks, we can see that none of the child fields in HL are specifically problematic. The performance is almost the same whether highlighting one child field or three simultaneously. This suggests that the issue lies in reading the _source content from disk, which must be done to highlight any of the child fields.
Finally, the following benchmark matches results that don't contain large documents.
| Min Throughput | search_recap fragment size 100 | 117.32 | ops/s |
| Mean Throughput | search_recap fragment size 100 | 123.64 | ops/s |
| Median Throughput | search_recap fragment size 100 | 124.57 | ops/s |
| Max Throughput | search_recap fragment size 100 | 129.05 | ops/s |
| 50th percentile latency | search_recap fragment size 100 | 18.7089 | ms |
| 90th percentile latency | search_recap fragment size 100 | 23.7095 | ms |
| 99th percentile latency | search_recap fragment size 100 | 40.8766 | ms |
| 100th percentile latency | search_recap fragment size 100 | 50.3157 | ms |
| 50th percentile service time | search_recap fragment size 100 | 18.7089 | ms |
| 90th percentile service time | search_recap fragment size 100 | 23.7095 | ms |
| 99th percentile service time | search_recap fragment size 100 | 40.8766 | ms |
| 100th percentile service time | search_recap fragment size 100 | 50.3157 | ms |This is a query with a response size of 180.41 KB without excluding any fields from _source. We can observe that the performance is more than 10 times better than the query that matches large documents. The latter is a request with a size of 32.68 MB if we include the plain_text field, which is excluded in production. However, ES requires reading the entire source to perform highlighting, even when there are no matched terms, and to retrieve the snippet with only 500 characters from the plain text.
I also conducted some other experiments regarding HL settings that could help improve performance:
boundary_scanner default from chars to sentence or word worsened the performance.phrase_limit from the default of 256 to 1 showed no improvement.order from the default none, which retrieves the first matched fragment, to score did not show any improvement.In brief, IO operations seem to be the main bottleneck affecting performance. Therefore, hopefully changes in hardware can significantly help, as limiting the size of indexed documents is not an option.
mlissner
commented
3 months ago OK, so summarizing:
That's a lot of experimentation, thanks.
So I guess I have three thoughts:
We need to try increasing IOPS, like you say, or at least figuring out the pricing difference of doing so.
Are there ways we can disable highlighting? We talked about this before, but I think we have to have highlighting if we're going to show results, right?
We serve five child results per query. You say it doesn't enhance performance if a "large document is still matched in hits", but wouldn't returning only three docs increase the chances of that being true, and therefore speed up lots of queries?
albertisfu
commented
3 months ago Are there ways we can disable highlighting? We talked about this before, but I think we have to have highlighting if we're going to show results, right?
Yes, it's possible to disable highlighting entirely to get the boost improvement. That's what we did in the API, where HL is disabled by default. So, even to retrieve the document snippets, we don't use HL; instead, they are retrieved from the database. To highlight results, highlight=on should be passed.
However, as we talked before, not showing highlights in the frontend seemed a bad idea, as it can make the results confusing for users.
We serve five child results per query. You say it doesn't enhance performance if a "large document is still matched in hits", but wouldn't returning only three docs increase the chances of that being true, and therefore speed up lots of queries?
Yes, we actually serve 6 child results per parent because one of them is used to determine if there are more than 5 results and to display the "View more results" button.
You're right decreasing the number of child documents can make it less likely for larger child documents to be included in the results, which can be beneficial in some searches. However, I think larger documents are more likely to appear as the first child result because they contain more terms that can be matched, and we sort child documents by score. But we could do the tweak and monitor in the ES metrics if query times are reduced in average.
mlissner
commented
3 months ago I think larger documents are more likely to appear as the first child result because they contain more terms that can be matched
I'm not so sure. We don't use TF/IDF, but I assume the ranking algo we use does something similar. In TF/IDF, results are penalized by the length of the document (IDF = "Inverse document frequency."). The theory is that you want to calculate the density of the keywords in a document, so longer docs that contain the word once are less relevant than longer ones that contain it several times.
Either way, it's sure to help a bit — let's do it while we wait for Ramiro to do his piece. It's sort of all we've got.
The only other thought I have is on the user interface:
A toggle users can turn on and off that lets them understand the tradeoff.
A spinner to help people wait that gives them something to stare at.
The spinner is easy enough. Might as well do that. The toggle is something to think more about, I think.
albertisfu
commented
3 months ago Either way, it's sure to help a bit — let's do it while we wait for Ramiro to do his piece. It's sort of all we've got.
Sure, this is easy. We just need to tweak the setting: RECAP_CHILD_HITS_PER_RESULT.
Does setting it to 3 child documents sound good? (4 will actually be retrieved). Alternatively, I can make the setting configurable so we can test different values by tweaking an environment variable.
This setting will also affect the child documents nested in the V4 API for RECAP. Is that OK, or should we make the setting independent of the API's nested documents?
The spinner is easy enough. Might as well do that. The toggle is something to think more about, I think.
Yeah, I think we just need to move the results rendering to HTMX. Does that sound good?
mlissner
commented
3 months ago It's ok that the api changes. Let's set it to show three results.
Moving to HTMX is the plan. Not yet though!
albertisfu
commented
3 months ago Great, reduced to 3: https://github.com/freelawproject/courtlistener/pull/4301
Moving to HTMX is the plan. Not yet though!
Correct, so the spinner will wait until we move to HTMX.
mlissner
commented
3 months ago Here's the latest performance with three child docs:
Response Times: {'': 14.814864158630371, 'The Litigation Practice Group': 7.9153382778167725, '"Alston v. Penn State Health"': 4.9190354347229, 'Danny Ray Jackson': 2.3072078227996826, '"MEMBER CASE OPENED:"': 3.8427939414978027, 'Parties to exchange Rule ': 10.254294872283936, 'BROOKS v. CITY': 3.441192388534546, 'UNITED STATES': 189.5496120452881, 'ALABAMA NORTHERN DIVISION': 3.7789692878723145, 'ALSAIDI v.HUBERT': 3.4089794158935547, 'Stroman v.U.S.Treasury': 4.019840478897095, 'United States v.Ainsworth': 4.487348556518555, 'Ballester v.State of Florida': 5.223628759384155, 'Sharma v.Eyebrows': 3.1194257736206055, 'Search Warrant Issued in case as to Priority Mail Package addressed to': 11.940662145614624, '"all parties must sign their names on the attached Consent"': 6.189635753631592, 'proceedings': 8.309628963470459, 'held': 9.440803527832031, 'before': 10.771430969238281, 'Magistrate ': 9.621043682098389, 'Judge': 16.12711262702942, 'description:ORDER AND plain_text:Motion': 3.283374309539795, 'description:ORDER OR plain_text:Motion': 8.788982391357422, 'Levi Haywood': 1.3994431495666504, 'EASTERN DISTRICT OF CALIFORNIA"EASTERN DISTRICT OF CALIFORNIA"': 13.191789388656616, 'Signed by Magistrate Judge': 12.30390214920044, 'shall': 6.083232879638672, 'file': 18.249871253967285, 'further': 5.525480031967163, 'amended': 10.611781120300293, 'pleadings': 3.5949957370758057, 'without': 10.93119192123413, 'first': 8.984928131103516, 'MINUTE ORDER': 10.09019947052002, 'Motions deadline': 13.84327745437622, 'Continuance of Motions': 15.193717241287231, 'Detention and Identity': 3.1134297847747803, 'Case Management': 12.586815595626831, 'Scheduling Order': 21.619269371032715, 'New York State': 18.717662811279297, 'Supreme Court': 7.434284448623657, 'MAGISTRATE CASE TERMINATED': 3.6594936847686768, 'Detention and Identity Hearing': 7.318808078765869, '"Detention and Identity Hearing"': 4.289843797683716, 'All pretrial motions': 5.007880449295044, 'Each': 3.493130683898926, 'party': 7.145432710647583, 'will': 5.596843004226685, 'bear': 2.3601088523864746, 'own': 5.71677041053772, 'Second Floor': 3.2293624877929688, 'Plaintiff': 15.962221622467041}
Average response time: 11.59 seconds.
Search term with maximum request time: 'UNITED STATES' :189.55 seconds.
Search term with minimum request time: 'Levi Haywood' :1.40 seconds.It's the worst! Somehow all our changes are making things slower so far. :(
albertisfu
commented
3 months ago :/ maybe testing it again in a different hour? Just to confirm cluster load is not impacting query times.
The query times in the metrics don't seem to show worse performance in general. Since August 10, the fixed count queries have been deployed, and since August 12, the reduction of child documents has been implemented.
These metrics are for the whole cluster, but considering that Opinions is not yet public, this might mostly be related to RECAP.
mlissner
commented
3 months ago Well, it's not as good as the very first run (9.3s), but it's close!
Response Times: {'': 12.704928398132324, 'The Litigation Practice Group': 5.70060396194458, '"Alston v. Penn State Health"': 2.4071221351623535, 'Danny Ray Jackson': 1.802358865737915, '"MEMBER CASE OPENED:"': 3.900282859802246, 'Parties to exchange Rule ': 7.067942380905151, 'BROOKS v. CITY': 3.1223747730255127, 'UNITED STATES': 182.7806396484375, 'ALABAMA NORTHERN DIVISION': 4.1240386962890625, 'ALSAIDI v.HUBERT': 2.562020778656006, 'Stroman v.U.S.Treasury': 2.2744507789611816, 'United States v.Ainsworth': 3.354217290878296, 'Ballester v.State of Florida': 2.6577446460723877, 'Sharma v.Eyebrows': 1.5845091342926025, 'Search Warrant Issued in case as to Priority Mail Package addressed to': 6.618940830230713, '"all parties must sign their names on the attached Consent"': 6.413479328155518, 'proceedings': 5.880823850631714, 'held': 7.133835554122925, 'before': 6.008804082870483, 'Magistrate ': 5.767233848571777, 'Judge': 10.441797494888306, 'description:ORDER AND plain_text:Motion': 3.044948101043701, 'description:ORDER OR plain_text:Motion': 6.683403491973877, 'Levi Haywood': 1.828810453414917, 'EASTERN DISTRICT OF CALIFORNIA"EASTERN DISTRICT OF CALIFORNIA"': 15.047075271606445, 'Signed by Magistrate Judge': 10.302546262741089, 'shall': 4.491498231887817, 'file': 13.681512594223022, 'further': 4.3232457637786865, 'amended': 8.31783151626587, 'pleadings': 3.5336947441101074, 'without': 5.296891450881958, 'first': 7.023275375366211, 'MINUTE ORDER': 8.17717170715332, 'Motions deadline': 6.768023729324341, 'Continuance of Motions': 12.944596767425537, 'Detention and Identity': 2.3744993209838867, 'Case Management': 8.623630046844482, 'Scheduling Order': 12.879775047302246, 'New York State': 17.535990476608276, 'Supreme Court': 4.8432090282440186, 'MAGISTRATE CASE TERMINATED': 3.71307110786438, 'Detention and Identity Hearing': 2.9273197650909424, '"Detention and Identity Hearing"': 3.673309564590454, 'All pretrial motions': 4.464235782623291, 'Each': 4.568949222564697, 'party': 6.419445991516113, 'will': 5.719357013702393, 'bear': 2.8618102073669434, 'own': 4.45696496963501, 'Second Floor': 3.538938283920288, 'Plaintiff': 10.54492473602295}
Average response time: 9.52 seconds.
Search term with maximum request time: 'UNITED STATES' :182.78 seconds.
Search term with minimum request time: 'Sharma v.Eyebrows' :1.58 seconds.I'll say, subjectively, I think I've noticed it being snappier, but man, my human judgement can't be trusted.
You know, we could build timings into it properly and probably could even send them to grafana if we wanted...
blancoramiro
commented
3 months ago This is running with the new settings for the volumes: gp3, 6000 IOPS and 500 throughput:
Response Times: {'': 19.389137029647827, 'The Litigation Practice Group': 6.697393417358398, '"Alston v. Penn State Health"': 2.5720479488372803, 'Danny Ray Jackson': 2.361642360687256, '"MEMBER CASE OPENED:"': 3.8787882328033447, 'Parties to exchange Rule ': 5.985720872879028, 'BROOKS v. CITY': 3.315563917160034, 'UNITED STATES': 180.64219641685486, 'ALABAMA NORTHERN DIVISION': 4.218769788742065, 'ALSAIDI v.HUBERT': 3.5269417762756348, 'Stroman v.U.S.Treasury': 3.6733152866363525, 'United States v.Ainsworth': 8.48942232131958, 'Ballester v.State of Florida': 2.7759177684783936, 'Sharma v.Eyebrows': 6.5400567054748535, 'Search Warrant Issued in case as to Priority Mail Package addressed to': 5.7365806102752686, '"all parties must sign their names on the attached Consent"': 11.76836609840393, 'proceedings': 6.7141735553741455, 'held': 9.7101411819458, 'before': 6.182885646820068, 'Magistrate ': 6.528410911560059, 'Judge': 11.60857081413269, 'description:ORDER AND plain_text:Motion': 13.44865107536316, 'description:ORDER OR plain_text:Motion': 6.467121839523315, 'Levi Haywood': 1.424640417098999, 'EASTERN DISTRICT OF CALIFORNIA"EASTERN DISTRICT OF CALIFORNIA"': 18.95367455482483, 'Signed by Magistrate Judge': 12.410669326782227, 'shall': 6.154239177703857, 'file': 16.23836851119995, 'further': 38.335286378860474, 'amended': 7.098358869552612, 'pleadings': 4.35529351234436, 'without': 4.8390953540802, 'first': 6.629684686660767, 'MINUTE ORDER': 8.452007293701172, 'Motions deadline': 7.147292375564575, 'Continuance of Motions': 10.494942426681519, 'Detention and Identity': 2.8219213485717773, 'Case Management': 8.98738408088684, 'Scheduling Order': 15.09764313697815, 'New York State': 16.041921377182007, 'Supreme Court': 5.295551300048828, 'MAGISTRATE CASE TERMINATED': 4.588144063949585, 'Detention and Identity Hearing': 3.0284392833709717, '"Detention and Identity Hearing"': 3.539536952972412, 'All pretrial motions': 6.917094707489014, 'Each': 3.5133533477783203, 'party': 6.6951165199279785, 'will': 5.989624500274658, 'bear': 2.777287244796753, 'own': 3.466843843460083, 'Second Floor': 3.439796209335327, 'Plaintiff': 13.284327030181885}
Average response time: 11.16 seconds.
Search term with maximum request time: 'UNITED STATES' :180.64 seconds.
Search term with minimum request time: 'Levi Haywood' :1.42 seconds.So is it fair to say that basically no change was created by doubling the disk speed?
albertisfu
commented
3 months ago I think this is not the most reliable method to measure the performance in the cluster. I tested some of the queries from the list and got better results:
Match all query:
from the benchmark 19.38
from the benchmark 6.69
from the benchmark 2.57
from the benchmark 2.361
from the benchmark 13.44
from the benchmark 18.95
from the benchmark 12.41
Since this benchmark is tied to a single sample, it can vary a lot. I think it would be better to use Rally to perform a more statistically robust benchmark so we can compare performance across different IOPS and throughput levels.
mlissner
commented
3 months ago Yeah, and we should prioritize #4230 too, so that we can get the real world data.
mlissner
commented
1 month ago @legaltextai, can you provide some average timings here now that we have saved queries? (Don't forget to remove cached=True!)
legaltextai
commented
1 month ago SELECT avg(query_time_ms) FROM search_searchquery where hit_cache is FALSE
776 Well, that's sub-1s, which is nice. Better than I expected, honestly. Can you break it down by the different object types though?
legaltextai
commented
1 month ago there are so many variations. are you interested in any specific categories? should i ignore the filters?
e.g. Search by citation: Count: 56403 Average Time (non-cached): 99.51 ms Time Range (non-cached): 13.0 - 75065.0 ms Sample Query: q=cites%3A%281525098+OR+9857490+OR+9857491%29
Keyword search with some filters: Count: 105590 Average Time (non-cached): 402.46 ms Time Range (non-cached): 0.0 - 686190.0 ms Sample Query: q=temporary+total+disability&type=o&order_by=score+desc&stat_Precedential=on&court=tennworkcompcl+tennworkcompapp
Case Name Search: Count: 26090 Average Time (non-cached): 746.90 ms Time Range (non-cached): 0.0 - 221040.0 ms Sample Query: q=Burrows+Vs+Combs&type=o&order_by=score+desc&stat_Precedential=on
Nature of Suit Search: Count: 8559 Average Time (non-cached): 1735.29 ms Time Range (non-cached): 54.0 - 105375.0 ms Sample Query: type=r&nature_of_suit=%22Civilian+Pay+-+Other%22
ps. i am not sure why min time range shows 0 in some cases since this is for non-cached only.
mlissner
commented
1 month ago I'm interested in performance by the type parameter. That's the one that determines the object type I was referring to.
legaltextai
commented
1 month ago If this is the correct definition of types:
o | Case law opinions
r | List of Federal cases (dockets) with up to three nested documents.
rd | Federal filing documents from PACER
d | Federal cases (dockets) from PACER
p | Judges
oa | Oral argument audio files
here are some results:
mlissner
commented
1 month ago That's great. We finally have a starting point to compare against. Once again, this issue has gotten too long, so I'm going to peel this off into a optimizations round 3, which we can resume when Alberto is back and we have a replacement for Ramiro.
Thanks all!
Back in https://github.com/freelawproject/courtlistener/issues/3536#issuecomment-1992789591, we talked about and did a lot of work on performance enhancements, and then we concluded:
I think playing with the query counts is probably our best low hanging fruit, and that we should get Ramiro to look into the performance metrics.
For now I just wanted to spin this off because that older issues is just too long!