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http://opensource.atlassian.com/projects/hibernate/browse/HSEARCH-469?pag...
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Dobes Vandermeer commented on HSEARCH-469:
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Hi Sanne,
It's off-topic, yes. I think the most of the needed improvements are already in the
system but not yet implemented or released. At the same time, our use of lucene is simple
enough that it's easier to reimplement search using lucene directly than to patch
hibernate-search. Hope that makes sense ... especially I am changing the system to store
indexes in the database, and one set of indexes per tenant in our multi-tenant system.
Each tenant has a relatively small set of records to search and searching is never done
across tenants, so this reduces our memory footprint on a search considerably. Storing
the indexes in the DB reduces IT complexity for backups, database clones, transactions,
and unit tests and although performance may be slightly impacted, it seems worth the price
in simplifying a bunch of other things.
Filter caching using causes excessive memory use
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Key: HSEARCH-469
URL:
http://opensource.atlassian.com/projects/hibernate/browse/HSEARCH-469
Project: Hibernate Search
Issue Type: Bug
Components: query
Affects Versions: 3.1.1.GA
Environment: hibernate-core-3.3.2.GA
Reporter: Dobes Vandermeer
Assignee: Sanne Grinovero
Fix For: 3.2.0
The CachingWrapperFilter uses the reader instance (CacheableMultiReader) as a key for the
caching.
However, the reader instance keeps pointers to byte arrays in its "normsCache"
and in the "normsCache" of its sub-readers; each array has one byte for each
document in the index and in some cases there will be multiple of these arrays associated
with differet fields.
For an index with millions of records this can result in an apparent "leak" of
hundreds of megabytes of memory as those readers are not re-used and the MRU cache used by
default will keep up to 128 hard references to the readers by default.
The search system must either re-use or delete the normsCache, OR the cache key for these
filters should be tied to something else that doesn't keep references to potentially
huge data arrays. Otherwise the scalability of the search subsystem is significantly
impacted when using filters, as you must have enough heap to accommodate up to 128 times
as many copies of the norms arrays.
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