We have a moderate sized repository with roughly the following size:
* Around 1M total objects
* Around 100K documents (PDFs, office docs, text, xml etc)
* Around 3TB of data in datastore (majority of which are non-indexable
Recently we had to re-index the repository as the search index got out of
sync with the rest of the data. During that we encountered out-of-memory
issue several times. We had to increase the heap size to 64GB before the
re-indexing finally finished. The total RAM taken up by the Java process
during re-indexing steadily climbed to 60GB and stayed there till the
We are using pretty standard search configuration as shown below:
We tried playing with a few configuration settings such as
extractorPoolSize, maxMergeDocs etc without any appreciable impact on RAM
Some questions that we have are:
1) Is this high memory usage expected during indexing?
2) Can we make any configuration change to manage it?
3) Are there any improvements expected in Jackrabbit 3 (Project Oak)?
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