If you run out of RAM during or at the end of a reload you can in order of priority:
1) Reduce the data you loading
2) Make sure that the footprint of the data you are loading becomes less in QlikView
3) Buy more RAM
For 1 and 2 you should first of all find the real culprit of the problem. Is it a single table? If so analyze this table in the context of the points in 1 and 2.
1) Reduce the data or the footprint of the data you are loading:
a) Do you need all the rows you are loading in every table? Could you analysis application really be split into
several apps with different year-spans or quarters or something similar.
b) Do you need the full granularity of the rows? Could you summarize from minutes into hours or days instead?
c) Do you need all the columns of every table?
2) Make sure that the footprint of the data you are loading becomes less in QlikView
a) For every column that will be turned into fields could you decrease the number of distinct values. By
for instance rounding of a sales transaction date from full resolution into a day-resolution? It is a
similar operation as b in point 1 but not the same. Here you would reduce the cardinality of the field
itself whereas in b you would reduce the number of rows for a table. This could have a tremenduous
impact on reducing the footprint of this field alone. It is due to the fact that you would allow QlikView
to use it's behind the scenes symbol tables to store way less data - a form of compression that often
saves a lot of RAM and consequently also speeds up any calculations.
b) Make sure that you don't allow for synthetic keys that are not necessary. In most situations synthetic
keys are unnecessary - so try to avoid them at all costs. They can consume a lot of RAM and be very
costly when it comes to performance.
c) Analyze the number of tables and how they relate to each other. Is it a simpler way of getting them to
relate? Will it have an impact on the footprint? Do you really need all of the tables? Could some of them
be merged or joined together.
3) Buy more RAM:
This might not even solve your problem. So at least before doing such a thing make sure that you load half the data and see how much RAM you have left after that. If you don't get to load even the half it seems to suggest that even doubling your RAM will still leave you in trouble....
Mind you this is not an exhaustive list of what you can do when you run into these kind of issues. I wrote this out of the top of my head...
