Telecom & Mnesia - Call Detail Record Collection

Per Bergqvist per@REDACTED
Thu Apr 11 11:22:28 CEST 2002

Hi Martin,                                                            
My experience is that disk_copies work extremely well until you run   
out of RAM.                                                           
disk_only_copies seem to consume memory relative the database size and
run out of steam far to early for really large databases.             
I have a similiar problem like your CDR problem and for this purpose I
 use Berkeley db which is performing well even with very large        
This however, does not give you a distributed database.               
My intention is to combine Berkeley db with mnesia transaction        
management, but this is really just an idea at this stage due to lack 
of time.                                                              
> Hello All,                                                          
>     I am working for a small telephony company here in the States.  
The only                                                              
> method that we have for billing our customers is via call detail    
records. The                                                          
> system that we are using now is a rather poor one. My boss and I    
propose that                                                          
> we can revolutionize the way that we do this by employing erlang and
> All of my past projects with it have been extremly succesfull. I    
have started                                                          
> running some preliminary stress/load tests with mnesia and I am     
encountering a                                                        
> few problems. Mnesia really seems to slow down at 120,000 small     
records stored                                                        
> as disk_only_copies and at 300,000 small records stored as          
ram_copies.  The                                                      
> requirements for this project could be in excess of 8 gig of data   
storage with                                                          
> 500,000 records comming in on a daily basis. I have always thought  
of mnesia                                                             
> as a real time db for storing smaller amounts of data. I would like 
to build                                                              
> this cdr collection and reporting system entirly in erlang though   
and remove                                                            
> the need for the sql db if possible. The more erlang the better off 
we all                                                                
> are.                                                                
> The quiestions I have are:                                          
> 1. Has anyone stored such a vast amount of data in mnesia? I could  
not find                                                              
> much on the list.                                                   
> 2. How does mnesia preform under large loads?  I need to do         
reporting on the                                                      
> data.                                                               
> 3. What are the most effective mnesia configurations for maxing out 
its data                                                              
> storage potential? What is its potential?                           
> 3. Has anyone out there used mnesia/erts/otp for call detail record 
> collection? If so can you give me any recomendations                
>     for my project?                                                 
>                     Thank you for any help in this matter,          
>                     Martin.                                         
Per Bergqvist                                                         
Synapse Systems AB                                                    
Phone: +46 709 686 685                                                
Email: per@REDACTED                                                   

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