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XWiki Platform / cid:jira-generated-image-avatar-ce720362-adb6-400e-91e7-5ac489ecb2d0 XWIKI-23081 Open

Fetching backlinks is slow and consumes a lot of memory on large instances

 
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Issue created

 
cid:jira-generated-image-avatar-15410278-22be-42af-ba9a-a59517d5ad69 Michael Hamann created this issue on 08/Apr/25 12:26
 
Summary: Fetching backlinks is slow and consumes a lot of memory on large instances
Issue Type: cid:jira-generated-image-avatar-ce720362-adb6-400e-91e7-5ac489ecb2d0 Bug
Affects Versions: 14.8-rc-1
Assignee: Unassigned
Components: Search - Solr
Created: 08/Apr/25 12:26
Labels: performance
Priority: cid:jira-generated-image-static-major-20edf7a2-3980-41ac-b418-2ac0d816e3a5 Major
Reporter: Michael Hamann
Description:

Steps to reproduce:

1. Create a lot of pages, or pages with lots of properties. 37 million indexed items (pages + objects + object properties + attachments) should make the problem noticeable.
2. View the backlinks of a document that has few backlinks.

Expected result:

Viewing the backlinks is fast.

Actual result:

Viewing the backlinks is relatively slow, requesting the backlinks many times in parallel leads to an OOM. With 37 million indexed items, I found that one requests consumes about 700MB of RAM in Solr, so with 5 GB of RAM, 10 parallel requests should lead to an OOM. Note that there are caches on the Solr side so you might need to try with different pages.

This also leads to slower than necessary refactoring operations.

 
 

2 updates

 
cid:jira-generated-image-avatar-15410278-22be-42af-ba9a-a59517d5ad69 Changes by Michael Hamann on 08/Apr/25 12:27
 
Description: *Steps to reproduce:*

1. Create a lot of pages, or pages with lots of
objects/object properties. 37 million indexed items (pages + objects + object properties + attachments) should make the problem noticeable.
2. View the backlinks of a document that has few backlinks.

*Expected result:*

Viewing the backlinks is fast.

*Actual result:*

Viewing the backlinks is relatively slow, requesting the backlinks many times in parallel leads to an OOM. With 37 million indexed items, I found that one requests consumes about 700MB of RAM in Solr, so with 5 GB of RAM, 10 parallel requests should lead to an OOM. Note that there are caches on the Solr side so you might need to try with different pages.

This also leads to slower than necessary refactoring operations.
Assignee: Michael Hamann