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java - Advice on handling large data volumes

So I have a "large" number of "very large" ASCII files of numerical data (gigabytes altogether), and my program will need to process the entirety of it sequentially at least once.

Any advice on storing/loading the data? I've thought of converting the files to binary to make them smaller and for faster loading.

Should I load everything into memory all at once?
If not, is opening what's a good way of loading the data partially?
What are some Java-relevant efficiency tips?

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So then what if the processing requires jumping around in the data for multiple files and multiple buffers? Is constant opening and closing of binary files going to become expensive?

I'm a big fan of 'memory mapped i/o', aka 'direct byte buffers'. In Java they are called Mapped Byte Buffers are are part of java.nio. (Basically, this mechanism uses the OS's virtual memory paging system to 'map' your files and present them programmatically as byte buffers. The OS will manage moving the bytes to/from disk and memory auto-magically and very quickly.

I suggest this approach because a) it works for me, and b) it will let you focus on your algorithm and let the JVM, OS and hardware deal with the performance optimization. All to frequently, they know what is best more so than us lowly programmers. ;)

How would you use MBBs in your context? Just create an MBB for each of your files and read them as you see fit. You will only need to store your results. .

BTW: How much data are you dealing with, in GB? If it is more than 3-4GB, then this won't work for you on a 32-bit machine as the MBB implementation is defendant on the addressable memory space by the platform architecture. A 64-bit machine & OS will take you to 1TB or 128TB of mappable data.

If you are thinking about performance, then know Kirk Pepperdine (a somewhat famous Java performance guru.) He is involved with a website, www.JavaPerformanceTuning.com, that has some more MBB details: NIO Performance Tips and other Java performance related things.


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