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https://issues.apache.org/jira/browse/ARROW-6830?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16948713#comment-16948713
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Anthony Abate edited comment on ARROW-6830 at 10/10/19 3:48 PM:
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I was using *RecordBatchFileReader* since it seemed to be the only to limit 
memory usage (I thought *read_arrow* was my only alternative)    We are 
indexing our data by record batch so we could be more efficient in filtering by 
passing the batch ids into the RecordBatchFileReader to avoid a 'full table 
scan' 

FYI - It was not clear to me from the name that *read_table* has anything to do 
with arrow files. 

Is read_table aware of underlying record batches so rows can be filtered out 
more efficiently?

 


was (Author: abbot):
I was using *RecordBatchFileReader* since it seemed to be the only to limit 
memory usage (I thought *read_arrow* was my only alternative)    We are 
effectively indexing our data by record batch so we could be more efficient in 
filtering and would want to pass down to avoid a 'full table scan' 

FYI - It was not clear to me from the name that *read_table* has anything to do 
with arrow files. 

Is read_table aware of underlying record batches so rows can be filtered out 
more effeciently?

 

> [R] Select Subset of Columns in read_arrow
> ------------------------------------------
>
>                 Key: ARROW-6830
>                 URL: https://issues.apache.org/jira/browse/ARROW-6830
>             Project: Apache Arrow
>          Issue Type: New Feature
>          Components: R
>            Reporter: Anthony Abate
>            Priority: Minor
>
> *Note:*  Not sure if this is a limitation of the R library or the underlying 
> C++ code:
> I have a ~30 gig arrow file with almost 1000 columns - it has 12,000 record 
> batches of varying row sizes
> 1. Is it possible at to use *read_arrow* to filter out columns?  (similar to 
> how *read_feather* has a (col_select =... )
> 2. Or is it possible using *RecordBatchFileReader* to filter columns?
>  
> The only thing I seem to be able to do (please confirm if this is my only 
> option) is loop over all record batches, select a single column at a time, 
> and construct the data I need to pull out manually.  ie like the following:
> {code:java}
> for(i in 0:data_rbfr$num_record_batches) {
>     rbn <- data_rbfr$get_batch(i)
>   
>   if (i == 0) 
>   {
>     merged <- as.data.frame(rbn$column(5)$as_vector())
>   }
>   else 
>   {
>     dfn <- as.data.frame(rbn$column(5)$as_vector())
>     merged <- rbind(merged,dfn)
>   }
>     
>   print(paste(i, nrow(merged)))
> } {code}
>  
>  



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