Hi roberto,I have ever done some experiments on a dataset with 31960000 
transactions and 289154813 frequent itemsets. FPGrowth can finish the computing 
within 10 minutes. I can have a try if you could share the artificial dataset.

From: [email protected]
To: [email protected]
CC: [email protected]
Subject: Re: frequent itemsets
Date: Sun, 3 Jan 2016 01:20:07 +0000






Hi Lin,
From 1e-5 and below it crashes with me. I also developed my own program in C++ 
(single machine, no spark) and I was able to compute all itemsets, that is, 
support = 0. 



Stack overflow definitely occur when computing frequent itemset, before 
association rule even starts. If you want, I can try generate an artificial 
dataset to share. Did you ever try with hundreds of millions of frequent 
itemsets?



With small datasets it works, but it looks like there might be issues when the 
number of combination grows. 



Thanks, 





From: LinChen <[email protected]>

Date: Saturday, 2 January 2016 14:48

To: Roberto Pagliari <[email protected]>

Cc: "[email protected]" <[email protected]>

Subject: RE: frequent itemsets







Hi Roberto,
What is the minimum support threshold you set? 
Could you check which stage you ran into StackOverFlow exception?



Thanks.






From: [email protected]

To: [email protected]

CC: [email protected]

Subject: Re: frequent itemsets

Date: Sat, 2 Jan 2016 12:01:31 +0000



Hi Yanbo,
Unfortunately, I cannot share the data. I am using the code in the tutorial 



https://spark.apache.org/docs/latest/mllib-frequent-pattern-mining.html



Did you ever try run it when there are hundreds of millions of co-purchases of 
at least two products?
I suspect AR does not handle that very well. 



Thank you, 











From: Yanbo Liang <[email protected]>

Date: Saturday, 2 January 2016 09:03

To: Roberto Pagliari <[email protected]>

Cc: "[email protected]" <[email protected]>

Subject: Re: frequent itemsets







Hi Roberto,



Could you share your code snippet that others can help to diagnose your 
problems?









2016-01-02 7:51 GMT+08:00 Roberto Pagliari 
<[email protected]>:



When using the frequent itemsets APIs, I’m running into stackOverflow exception 
whenever there are too many combinations to deal with and/or too many 
transactions and/or too many items. 






Does anyone know how many transactions/items these APIs can deal with?






Thank you ,
















                                          

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