Question

I have a sharded cluster in 3 systems.
While inserting I get the error message:

cant map file memory-mongo requires 64 bit build for larger datasets

I know that 32 bit machine have a limit size of 2 gb.
I have two questions to ask.

1. The 2 gb limit is for 1 system, so the total data will be, 6gb as my sharding is done in 3 systems. So it would be only 2 gb or 6 gb?
2. While sharding is done properly, all the data are stored in single system in spite of distributing data in all the three sharded system?

Does Sharding play any role in increasing the datasize limit?
Does chunk size play any vital role in performance?

Answer 1

Sharding is all about scaling out your data set across multiple nodes so in answer to your question, yes you have increased the possible size of your data set. Remember though that namespaces and indexes also take up space.

You haven’t specified where your mongos resides??? Where are you seeing the error from – a mongod or the mongos? I suspect that it’s the mongod. I believe that you need to look at pre-splitting the chunks – http://docs.mongodb.org/manual/administration/sharding/#splitting-chunks.
which would seem to indicate that all your data is going to the one mongod.

If you have a mongos, what does sh.status() return? Are chunks spread across all mongod's?

For testing, I’d recommend a chunk size of 1mb. In production, it’s best to stick with the default of 64mb unless you’ve some really important reason why you don’t want the default and you really know what you are doing. If you have too small of a chunk size, then you will be performing splits far too often.