Lucene nightly benchmarks
Each night, an automated Python tool checks out the Lucene/Solr trunk source code and runs multiple benchmarks: indexing the entire Wikipedia English export three times (with different settings / document sizes); running a near-real-time latency test; running a set of "hardish" auto-generated queries and tasks. The tests take around 2.5 hours to run, and the results are verified against the previous run and then added to the graphs linked below.The goal is to spot any long-term regressions (or, gains!) in Lucene's performance that might otherwise accidentally slip past the committers, hopefully avoiding the fate of the boiling frog.
See more details in this blog post.
Indexing:
Indexing throughput
Analyzers throughput
Near-real-time refresh latency
BooleanQuery:
+high-freq +high-freq
+high-freq +medium-freq
high-freq high-freq
high-freq medium-freq
+high-freq +(medium-freq medium-freq)
+medium-freq +(high-freq high-freq)
Proximity queries:
Exact phrase
Sloppy (~4) phrase
Span near (~10)
Ordered intervals (MAXWIDTH/10)
FuzzyQuery:
Edit distance 1
Edit distance 2
Other queries:
TermQuery
Respell (DirectSpellChecker)
Primary key lookup
WildcardQuery
PrefixQuery (3 leading characters)
Numeric range filtering on last-modified-datetime
Faceting:
Term query + date hierarchy
All dates hierarchy
All months
All months (doc values)
All dayOfYear
All dayOfYear (doc values)
Sorting (on TermQuery):
Date/time (long, high cardinality)
Title (string, high cardinality)
Month (string, low cardinality)
Day of year (int, medium cardinality)
Grouping (on TermQuery):
100 groups
10K groups
1M groups
1M groups (two pass block grouping)
1M groups (single pass block grouping)
Others:
Geo spatial benchmarks
Sparse vs dense doc values performance on NYC taxi ride corpus
"ant clean test" time in lucene
CheckIndex time
[last updated: 2019-04-25 00:53:35.757396; send questions to Mike McCandless]