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https://issues.apache.org/jira/browse/MADLIB-1340?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Frank McQuillan updated MADLIB-1340:
------------------------------------
Fix Version/s: (was: v1.16)
v2.0
> minibatch_preprocessor_dl crashes with default batch size
> ---------------------------------------------------------
>
> Key: MADLIB-1340
> URL: https://issues.apache.org/jira/browse/MADLIB-1340
> Project: Apache MADlib
> Issue Type: Bug
> Components: Deep Learning
> Affects Versions: v1.16
> Reporter: Domino Valdano
> Priority: Minor
> Fix For: v2.0
>
>
> The minibatcher's internal logic for picking a default batch size isn't
> strict enough. It can crash for arrays of datatypes which are less than
> 32-bits. I tried to come up with a simple repro, but it still needs some
> work. Here's what I have now, for 16-bit type REAL[], haven't had a chance
> to test it yet:
> madlib=# CREATE TABLE foo AS SELECT ARRAY[i,i,i,i,i] AS x, 1 as y FROM
> (SELECT ARRAY[i,i,i,i,i] AS i FROM (SELECT GENERATE_SERIES(1,6*1024*1024) AS
> i) a1 ) a;
> madlib=# \d foo;
> Table "public.foo"
> Column | Type | Modifiers
> --------+---------+-----------
> x | integer[] |
> y | integer |
> Distributed randomly
> madlib=# SELECT madlib.minibatch_preprocessor_dl('foo','foo_batched', 'y',
> 'x');
> TODO: above example doesn't actually work, because it only has 6-million
> rows. Generate an example with at least 150-million rows, and it should work
> (ie, crash).
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