I have code like this:
public bool Set(IEnumerable<WhiteForest.Common.Entities.Projections.RequestProjection> requests)
{
var documentSession = _documentStore.OpenSession();
//{
try
{
foreach (var request in requests)
{
documentSession.Store(request);
}
//requests.AsParallel().ForAll(x => documentSession.Store(x));
documentSession.SaveChanges();
documentSession.Dispose();
return true;
}
catch (Exception e)
{
_log.LogDebug("Exception in RavenRequstRepository - Set. Exception is [{0}]", e.ToString());
return false;
}
//}
}
This code gets called many times. After i get to around 50,000 documents that have passed through it i get an OutOfMemoryException.
Any idea why ? perhaps after a while i need to declare a new DocumentStore ?
thank you
**
- UPDATE:
**
I ended up using the Batch/Patch API to perform the update I needed.
You can see the discussion here: https://groups.google.com/d/topic/ravendb/3wRT9c8Y-YE/discussion
Basically since i only needed to update 1 property on my objects, and after considering ayendes comments about re-serializing all the objects back to JSON, i did something like this:
internal void Patch()
{
List<string> docIds = new List<string>() { "596548a7-61ef-4465-95bc-b651079f4888", "cbbca8d5-be45-4e0d-91cf-f4129e13e65e" };
using (var session = _documentStore.OpenSession())
{
session.Advanced.DatabaseCommands.Batch(GenerateCommands(docIds));
}
}
private List<ICommandData> GenerateCommands(List<string> docIds )
{
List<ICommandData> retList = new List<ICommandData>();
foreach (var item in docIds)
{
retList.Add(new PatchCommandData()
{
Key = item,
Patches = new[] { new Raven.Abstractions.Data.PatchRequest () {
Name = "Processed",
Type = Raven.Abstractions.Data.PatchCommandType.Set,
Value = new RavenJValue(true)
}}});
}
return retList;
}
Hope this helps …
Thanks alot.
I just did this for my current project. I chunked the data into pieces and saved each chunk in a new session. This may work for you, too.
Note, this example shows chunking by 1024 documents at a time, but needing at least 2000 before we decide it’s worth chunking. So far, my inserts got the best performance with a chunk size of 4096. I think that’s because my documents are relatively small.