Comments (2)
I tried the following for the problem I'm facing -
I have a large pipe, with 2 columns - say the columns are 'advertiser_id, 'bids
Say I limit to 100 rows
Now I will have a datafile that has 100 rows & 2 columns
I want each row to go into its own Tsv whose name is the entry in 'advertiser_id of that row.
I try writing to 100 files in a map & its fails with npe because flowdef is null.
But how about I put the datafile in a matrix, transpose to get a 2 row 100 column matrix.
Now run a map & filter on the column-name, and return a pipe that contains the bids for that advertiser.
Since there are exactly 100 pipes, just iterate over the pipes in a regular for loop & write to the sinks.
This works locally for small number of columns...without needing PailSource or TemplateTap.
Is this a scalable solution ?
from scalding.
I think this is going to be much more computationally expensive, but I don't really know.
This is exactly the problem that Pail is supposed to solve, so I really think we should investigate it.
By the way, next year, we will start sharding our processed logs more by column data, so we have to start using Pail more, as far as I can see. I think now is the time to adopt it more widely.
PS: Sam Ritchie can help you get started on your first Pail source.
from scalding.
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