This site is moving soon to become part of an integrated Appfire documentation and information site for our apps. This site will remain available during the transition to our new and improved site. Once this site is moved over, this banner will be updated with the new site link for easy access.
Take a look here! If you have any questions please email support@appfire.com
Performance characteristics
How tests were executed
The machine on which tests were executed contains 16GB of RAM memory (1600MHz), PLEXTOR PX-256M5 SSD drive and single Intel Core i7 4790K 4.00 GHz processor.
Tests were executed on Jira 7.4 version, running against Postgres 9.6. The instance has:
- issues 1,053,030
- issues that were moved 1,000,000
- comments 4,029,535
- projects 402
- worklogs 1,504,565
Each query present in the results was executed 50 times to collect min/max/avg values. There were 5 concurrent threads executing the query one after another (so at any given time Jira was running 5 searches concurrently).
Testing impact of jira.search.maxclause
Below tests measured the impact of raising jira.search.maxclause limit to a higher value than the default (65k). To better understand of what this limit is and how to raise it please check How to solve com.atlassian.jira.issue.search.ClauseTooComplexSearchException.
Query | jira.search.maxclause | Min | Max | Avg |
|---|---|---|---|---|
issue in movedIssues() | 65000 | 1.145sec | 2.555sec | 1.637sec |
issue in commentedAfter("2018-05-26") | 65000 | 0.721sec | 1.176sec | 0.921sec |
issue in commentsCountLessThan("10") | 65000 | 0.665sec | 1.604sec | 0.912sec |
Query | jira.search.maxclause | Min | Max | Avg |
|---|---|---|---|---|
issue in movedIssues() | 130000 | 1.790sec | 5.876sec | 2.724sec |
issue in commentedAfter("2018-05-26") | 130000 | 1.360sec | 3.069sec | 2.153sec |
issue in commentsCountLessThan("10") | 130000 | 1.170sec | 2.544sec | 1.874sec |
Query | jira.search.maxclause | Min | Max | Avg |
|---|---|---|---|---|
issue in movedIssues() | 260000 | 5.483sec | 10.201sec | 7.050sec |
issue in commentedAfter("2018-05-26") | 260000 | 4.388sec | 9.744sec | 6.254sec |
issue in commentsCountLessThan("10") | 260000 | 2.357sec | 7.571sec | 5.370sec |
Memory was raised to 4GB for 500k jira.search.maxclause, mostly due to stay within GC Overhead limit.
Query | jira.search.maxclause | Min | Max | Avg |
|---|---|---|---|---|
issue in movedIssues() | 500000 | 5.686sec | 11.345sec | 9.099sec |
issue in commentedAfter("2018-05-26") | 500000 | 5.316sec | 13.021sec | 10.422sec |
issue in commentsCountLessThan("10") | 500000 | 8.069sec | 12.272sec | 9.973sec |
Conclusions:
Raising the limit or jira.search.maxclause will require more CPU and Memory, it all depends on the machine that Jira is running on. Before raising the limit to big values, we recommend to first ensure that the server have still some CPU power left.
Performance of non-subquery based functions
Below tests were executed with jira.search.maxclause limit of 65000, not all of the functions returned the amount of the issues equal to the limit (for example issue in movedIssues() returned issues over the limit, but issue in movedIssues("ABII") returned around 6k issues which is more realistic than pessimistic scenario).
Query | Min | Max | Avg |
|---|---|---|---|
issue in movedIssues() | 1.219sec | 5.733sec | 1.851sec |
issue in movedIssues("ABII") | 0.394sec | 0.960sec | 0.528sec |
issue in commentedAfter("2018-05-26") | 0.715sec | 1.434sec | 0.889sec |
issue in commentedAfter("2019-06-26") | 1.946sec | 5.860sec | 2.911sec |
issue in commentedBefore("2018-10-26") | 0.906sec | 1.520sec | 1.102sec |
issue in commentedByUser("admin") | 0.708sec | 5.846sec | 4.242sec |
issue in commentedByUser(taahonmrs) | 1.967sec | 3.082sec | 2.812sec |
issue in commentsCountLessThan("10") | 0.655sec | 0.933sec | 0.743sec |
issue in commentsCountGreaterThan(4) | 0.733sec | 1.383sec | 0.931sec |
issue in linksCountLessThan(1) | 1.441sec | 1.826sec | 1.592sec |
issue in linksCountGreaterThan(1) | 1.685sec | 2.238sec | 1.845sec |
issue in subtaskCountGreaterThan("1") | 0.911sec | 1.677sec | 1.088sec |
issue in subtaskCountLessThan("2") | 0.670sec | 1.017sec | 0.824sec |
issue in subTaskPriority("low") | 1.118sec | 2.027sec | 1.343sec |
issue in subTaskPriority("low", "high", "highest", "lowest", "medium") | 1.661sec | 2.134sec | 1.894sec |
issue in subTaskType("Sub-Task", "SubtaskType2", "SubtaskType3", "SubtaskType4", "SubtaskType5", "SubtaskType6", "SubtaskType7", "SubtaskType8", "SubtaskType9", "SubtaskType10", "SubtaskType11", "SubtaskType12", "SubtaskType13", "SubtaskType14", "SubtaskType15", "SubtaskType16", "SubtaskType17", "SubtaskType18", "SubtaskType19", "SubtaskType20", "SubtaskType21") | 1.729sec | 2.539sec | 2.032sec |
issue in subTaskStatus("In Progress", "To Do", "Done", "Reopened", "Closed", "Resolved") | 1.684sec | 2.162sec | 1.918sec |
issue in subTaskStatusCategory("To Do", "In Progress", "Done") | 1.754sec | 2.249sec | 1.953sec |
Below chart show the CPU and Memory footprint on the JVM that Jira was running on.
Testing impact of subQuery limit
Below we present timings of execution of JQL functions which accept subQueries. To prevent instances from running out of memory or to become unstable due to the impact generated on the Lucene index we developed the protection which will load no more issues than the specified by limit. The default value is 10,000 which may be to low for bigger instances, this limit can be raised by setting a systemProperty called com.digitaltoucan.jqlextensions.subquery.limit (this, however, comes with a performance impact). To raise the limit please check SubQuery Limits. Instead of increasing the limit to big numbers, we recommend to narrow down the number of issues with a help of the query (for example instead of loading all issues in the subquery, try to load only issues from a given project, or only issues that are still open).
Query | SubQuery limit | Min | Max | Avg |
|---|---|---|---|---|
issue in allIssuesInEpic("") | 5000 | 0.669sec | 1.587sec | 0.855sec |
issue in allIssuesInEpic("") | 10000 | 1.172sec | 1.449sec | 1.287sec |
issue in allIssuesInEpic("") | 20000 | 2.264sec | 2.702sec | 2.416sec |
issue in allIssuesInEpic("") | 30000 | 3.215sec | 4.634sec | 3.514sec |
issue in allIssuesInEpic("resolution is Empty") | 5000 | 0.687sec | 0.911sec | 0.777sec |
issue in allIssuesInEpic("resolution is Empty") | 10000 | 1.212sec | 1.477sec | 1.322sec |
issue in allIssuesInEpic("resolution is Empty") | 20000 | 2.322sec | 2.892sec | 2.496sec |
issue in allIssuesInEpic("resolution is Empty") | 30000 | 3.302sec | 4.002sec | 3.552sec |
issue in epicOf("") | 5000 | 0.804sec | 0.986sec | 0.868sec |
issue in epicOf("") | 10000 | 1.594sec | 1.727sec | 1.653sec |
issue in epicOf("") | 20000 | 2.997sec | 3.811sec | 3.188sec |
issue in epicOf("") | 30000 | 4.558sec | 5.436sec | 5.031sec |
issue in epicOf("\"Epic Link\" is not Empty") | 5000 | 0.538sec | 0.700sec | 0.600sec |
issue in epicOf("\"Epic Link\" is not Empty") | 10000 | 0.538sec | 0.684sec | 0.594sec |
issue in epicOf("\"Epic Link\" is not Empty") | 20000 | 0.528sec | 0.654sec | 0.586sec |
issue in epicOf("\"Epic Link\" is not Empty") | 30000 | 0.472sec | 0.755sec | 0.576sec |
issue in fieldMatch("", "summary", ".*") | 5000 | 0.333sec | 0.633sec | 0.424sec |
issue in fieldMatch("", "summary", ".*") | 10000 | 0.523sec | 0.689sec | 0.579sec |
issue in fieldMatch("", "summary", ".*") | 20000 | 0.879sec | 1.058sec | 0.966sec |
issue in fieldMatch("", "summary", ".*") | 30000 | 1.239sec | 1.880sec | 1.384sec |
issue in fieldMatch("project = SFTSFTS", "summary", ".*") | 5000 | 0.236sec | 0.585sec | 0.324sec |
issue in fieldMatch("project = SFTSFTS", "summary", ".*") | 10000 | 0.415sec | 0.686sec | 0.477sec |
issue in fieldMatch("project = SFTSFTS", "summary", ".*") | 20000 | 0.715sec | 1.194sec | 0.826sec |
issue in fieldMatch("project = SFTSFTS", "summary", ".*") | 30000 | 1.026sec | 1.558sec | 1.123sec |
issue in fieldsHaveSameValue("fixVersion", "affectedVersion") | 5000 | 0.358sec | 0.462sec | 0.399sec |
issue in fieldsHaveSameValue("fixVersion", "affectedVersion") | 10000 | 0.508sec | 0.666sec | 0.566sec |
issue in fieldsHaveSameValue("fixVersion", "affectedVersion") | 20000 | 0.864sec | 1.322sec | 0.959sec |
issue in fieldsHaveSameValue("fixVersion", "affectedVersion") | 30000 | 1.203sec | 1.701sec | 1.349sec |
issue in parentOf("") | 5000 | 0.241sec | 0.385sec | 0.298sec |
issue in parentOf("") | 10000 | 0.374sec | 0.539sec | 0.431sec |
issue in parentOf("") | 20000 | 0.697sec | 0.806sec | 0.743sec |
issue in parentOf("") | 30000 | 0.931sec | 1.134sec | 1.030sec |
issue in parentOf("issuetype in subTaskIssueTypes()") | 5000 | 0.299sec | 0.507sec | 0.354sec |
issue in parentOf("issuetype in subTaskIssueTypes()") | 10000 | 0.462sec | 0.600sec | 0.512sec |
issue in parentOf("issuetype in subTaskIssueTypes()") | 20000 | 0.739sec | 1.276sec | 0.854sec |
issue in parentOf("issuetype in subTaskIssueTypes()") | 30000 | 0.985sec | 1.659sec | 1.144sec |
issue in subtaskOf("") | 5000 | 0.403sec | 0.761sec | 0.574sec |
issue in subtaskOf("") | 10000 | 0.648sec | 1.006sec | 0.864sec |
issue in subtaskOf("") | 20000 | 1.405sec | 1.740sec | 1.540sec |
issue in subtaskOf("") | 30000 | 2.180sec | 3.043sec | 2.617sec |
issue in links("", "blocks") | 5000 | 0.314sec | 0.781sec | 0.421sec |
issue in links("", "blocks") | 10000 | 0.529sec | 0.793sec | 0.627sec |
issue in links("", "blocks") | 20000 | 1.094sec | 1.843sec | 1.293sec |
issue in links("", "blocks") | 30000 | 1.475sec | 2.487sec | 1.979sec |
issue in linkedBy("", "is blocked by") | 5000 | 0.320sec | 0.650sec | 0.392sec |
issue in linkedBy("", "is blocked by") | 10000 | 0.524sec | 0.676sec | 0.606sec |
issue in linkedBy("", "is blocked by") | 20000 | 1.070sec | 2.112sec | 1.262sec |
issue in linkedBy("", "is blocked by") | 30000 | 1.658sec | 2.359sec | 2.031sec |