Reduce function if concatenated intermediate results doesn't fit in memory

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I'm trying to decode a huge dataset of rougly 500k*10k size. What I'm doing is actually load the file into a datastore, replace the tall table variable names with a meaningful name, and decode the content of all columns with a meaningful sentences in my dictionary.
I have some wiered issues that didn't let my program go through using a tall table. So I'm now trying to use mapreduce.
I find an example here
function subsettingReducer(~, intermValList, outKVStore)
% get all intermediate results from the list
outVal = {};
while hasnext(intermValList)
outVal = [outVal; getnext(intermValList)];
% Note that this approach assumes the concatenated intermediate values (the
% subset of the whole data) fit in memory.
add(outKVStore, 'Null', outVal);
My question is, in this example, if the contanenated intermediate results doesn't fit in memory, is there a better workaround for this?

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