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denominator cohort build drill out the ram #5
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Thanks for reporting this @rfherrerac, can you share the settings you used with the function and I will investigate this? |
Thanks @edward-burn |
Thanks @rfherrerac, let me take a look and get back to you. I'm actually preparing a new release so hopefully we can get this fixed in that. I only have a got access to a small redshift test database, so it would be great if you could test this new release on your data if that would be ok? |
For sure! happy to do so. |
@rfherrerac I'm not seeing anything obvious that I've changed that would of caused this (but I'll keep looking). Can I just check what versions of dbplyr and RPostgres you have installed? I'm just wondering if it might relate to r-dbi/RPostgres#457 |
Hi @edward-burn I have RPostgres 1.4.6. and dbplyr 2.4.0 |
Hi @rfherrerac, could you please try with the 0.7 version of IncidencePrevalence that is now out on cran? I realised that a dependency I was using was collecting data into R, and so with this fixed I´m hoping your issue will be solved but would be great if you could confirm |
Hi @edward-burn, it worked perfectly. Thanks a lot! |
Describe the bug
When running generateDenominatorCohortSet in a US large dataset in redshift, the memory ram is consumed vastly. And takes forever
R version 4.2.3 (2023-03-15)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux 8.7 (Ootpa)
Matrix products: default
BLAS/LAPACK: /usr/lib64/libopenblasp-r0.3.15.so
Version 0.4.1 did not have that issue ran pretty fast.
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