The last article demonstrated that a denormalized data model was a bit faster than a normalized data model when all the data fit into memory, but only by 20-30 percent or so, at least for the experiments I ran. This article deals with larger data volumes and shows a case where normalized data is faster than denormalized data and then details another case where a denormalized data model faster.
First, this is the what the tables in question look like. All the product tables have 10 million rows. The denormalized ProductAll table is 5.2 gig, and as innodb_buffer_pool_size is set to 4 gig, this table won't fit into memory. The filler column represents other product attributes without having to specify them in detail.
create table ProductAll (
productAllId int(11) not null,
productAllName varchar(32) not null,
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