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> Because the data is sampled every three seconds for
> several days, this data base could get large fast.
> However I'm more interested in speed than disk space.
> Tho I don't want have to take up all of the computer
> memory with the data file.

Use the filesystem as the database.  That is:

> a channel number in array format, to get the values.

The directory structure might look like:


Within the final directory, either have each sample as a separate file, or
bundle them into a single file.  I would probably make each a separate file.

I'm not going to do the real math here, but let's say you get back a sample
with the time stamp of 9876543210 (a made-up number).  Let's say this
decomposes down to:

Year: 2001
Month: 7
Day: 19
Hour: 2
Minute: 6
Second: 30

I would then create a file with the following path:


The file 9876543210 might contain something like this:

	return {1,2,3, ... ,16,17}

So to get back the table of sample values for a particular time:

	x = dofile("2001/7/19/2/6/9876543210")

The only downside to this is that Lua doesn't have any built-in functions to
deal with walking directory structures.  You could add that.  Extending Lua
is (somewhat) easy and even fun to do.

If dealing with individual files is too slow, you can create at each
directory level that summarizes information.  For example, if a common
request is to look at sample date per hour, you might create in each
Year/Month/Day/Hour directory a file named "summary" that predigests all the
samples for that hour's period.

> One of the other requirements is that I be able to
> delete the data, on a day/date range bases.
> Just put in NIL's?

Want to delete all data for July 19th, 2001?

	rm -rf 2001/7/19

Deleting more fine periods of data (say, between 2:34:20am and 6:26:50pm)
would require a bit more logic.  But if you know ahead of time the kinds of
ranges you'll want to delete data, you can build a directory structure to
take advantage of it.