So, the cell table has 1 million rows. Each cell has (in the current study), a 7300 rows by 9 columns table of weather data. There are 400 sets of weather data, so there is some level of normalization.

I serialized and compressed the weather data (using Storable via Data::Serializer) and stored each set as a BLOB. Unfortunately, the speed of extracting the BLOB and de-serializing and uncompressing it is sufficiently high... about 28 ms per set, which is really slow. In fact, it is quicker to simply pull out 7300 rows from the table than to pull out one row of BLOB and unraveling it.

I will look at Cache::Memcached.

--

when small people start casting long shadows, it is time to go to bed

In reply to Re^4: speeding up row by row lookup in a large db by punkish
in thread speeding up row by row lookup in a large db by punkish

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