Serializer.Unpack Continuosly Stream of Data => High Memory Usage #356

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1. yfakariya commented on Apr 17, 2023

   

   yfakariya

   on Apr 17, 2023

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   Thank you for reporting, it looks a bug as you think.
   I will confirm few things to reproduce / investigate your condition:

   • Definition of MyType. I guess you use loosely typed collection (dictionary) in your type.
   • Content of myOpenStream.

   Could you give me above info?
2. yfakariya

   added

   need-more-infoNeed more information (error message, stack trace, repro code etc)Need more information (error message, stack trace, repro code etc)

   on Apr 17, 2023
3. rootfixxxer commented on Apr 19, 2023

   

   rootfixxxer

   on Apr 19, 2023

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   Hello

   After some more tests I found out the problem it's with the volume of data present in the stream (Network Stream), I don't know if the handling of the data can be optimized by the library, but I have this as MyType:

     public class MsgPackArray
       {
           [MessagePackMember(0)]
           public IList<List<MessagePackObject>> ListContents { get; set; }
           [MessagePackMember(1)]
           public ulong Location { get; set; }
       }

   By default, the List it's always a list with 3 items, first one it's a byte array with 16 bytes, the second one a Uint64 and the third one a MessagePackObjectDictionary, that has 4 keys and 4 values, all strings...

   When I receive objects with more than 100k of items in the ListContents that's when the memory starts to raise, and it never drops...

   Thanks
4. yfakariya

   removed

   need-more-infoNeed more information (error message, stack trace, repro code etc)Need more information (error message, stack trace, repro code etc)

   on Apr 23, 2023
5. yfakariya commented on Apr 23, 2023

   

   yfakariya

   on Apr 23, 2023

   Last edited by yfakariya

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   Sorry, I was busy to investigate this problem, but I want to know that 1)average size of each string keys and values in dictionary and 2) bit size of your process (32 bit or 64 bit).
   Because MessagePackObject must have both of byte array (un-decoded string) and string, so it requires double size for strings, and 100K sized dictionary with few kiro bytes string causes over 2GB memory size.

   You can avoid this "over sized" behavior using POCO for the list because it always has three items, like following:

   public class MsgPackArray
   {
       [MessagePackMember(0)]
       public IList<MsgPackInnerArray> ListContents { get; set; }
       [MessagePackMember(1)]
       public ulong Location { get; set; }
   }
   
   public class MsgPackInnerArray
   {
       [MessagePackMember(0)]
       public byte[] First { get; set; }
       [MessagePackMember(1)]
       public ulong Second { get; set; }
       [MessagePackMember(2)]
       public Dictionary<string, string> Third { get; set; }
   }

   This can deserialize following structure (represented as JSON for explanation):

   [
     [ // begin ListContents
       0123456789ABCDEF0123456789ABCDEF,
       123, 
       {"A": "1", "B": "2", ... },
     ], // end ListContents
     456, // Location
   ]

   Note that you still might face to OutOfMemoryException when you run in the 32bit process.

   Or, if you want to reduce memory size anyway, you can use streaming processing using Unpacker directly.

   using (var unpacker = Unpacker.Create(myStream))
   {
   	if (!unpacker.Read() || unpacker.LastReadData != 2 || !unpacker.IsArrayHeader) throw new Exception("Invalid input");
   
   	var msgPackArrayUnpacker = unpacker.ReadSubtree();
   
   	if (!msgPackArrayUnpacker.Read() || msgPackArrayUnpacker.LastReadData != 3 || !msgPackArrayUnpacker.IsArrayHeader) throw new Exception("Invalid input");
   
   	var first = msgPackArrayUnpacker.ReadItemData().AsBinary();
   	var second = msgPackArrayUnpacker.ReadItemData().AsUInt64();
   
   	if (!msgPackArrayUnpacker.Read() || !msgPackArrayUnpacker.IsMapHeader) throw new Exception( "Invalid input" );
   
   	var mapSize = msgPackArrayUnpacker.LastReadData.AsInt32();
   	using (var mapUnpacker = msgPackArrayUnpacker.ReadSubtree())
   	{
   		for (var i = 0; i < mapSize; i++)
   		{
   			var key = mapUnpacker.ReadItemData().AsString();
   			var value = mapUnpacker.ReadItemData().AsString();
   			// Process key and value here...
   		}
   	}
   
   	var location = msgPackArrayUnpacker.ReadItemData().AsUInt64();
   }