Is there a limit to the SPSS random number generator? Will the random number generator in SPSS be serviceable if I need  250,000 random numbers, or will the randomness start to degenerate?
Asked another way, what practical limits are there to using the random number generator in SPSS to generate large numbers of random numbers?
 A: I think SPSS, like most modern software, uses the Mersenne Twister. Its period is $2^{19937} − 1$ so you’re pretty safe from this point of view.
Up to 623 successive outcomes are uncorrelated, so you can safely consider a few consecutive outcomes as independent (this would not be the case with a classical Linear congruential generator).
To summarize: modern random number generators are performant enough for all ordinary applications in statistics... don’t worry.
A: SPSS Statistics provides both the Mersenne Twister and, for compatibility, an older shift-congruential generator.  By default, the older generator is used.  Use SET RNG=MT or the Transform>Random Number Generators menu item to change this.  The MT should give you all the numbers you need.
There is also a user-contributed Python function that fetches truly random, not pseudo random numbers generated from atmospheric noise.  These are fetched from a website that has some rules about quantities that you should read.  The package is tr_rnd0.1.zip.  It can be downloaded from the SPSS Community website in the Python Modules collection.  Of course, this requires you to use Python programmability.  The tools for that can also be downloaded from the Community site.
A: I used the SPSS uniform function to create a random sample weekly for two years. Do not do this. They DO NOT generate random samples. The same dataset will generate the same random sample upon re-opening SPSS. Not all cases have the same probability to be selected (depends on sorting of your file).
My recommendation would be to use several methods of randomization sequentially. E.g. first randomize sorting, then use the select random sample function.
