[GitHub] [arrow] wjones1 edited a comment on pull request #6979: ARROW-7800 [Python] implement iter_batches() method for ParquetFile and ParquetReader

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wjones1 edited a comment on pull request #6979:
URL: https://github.com/apache/arrow/pull/6979#issuecomment-650474759


   RE: @jorisvandenbossche 
   > Same question as in the other PR: does setting the batch size also influence existing methods like `read` or `read_row_group` ? Should we add that keyword there as well?
   
   My one hesitation to adding them is that it's not clear to me what the effect would be on the execution. For `iter_batches()` the effect of `batch_size` is quite obvious, but I'm not sure about these other methods. 
   
   After quick search of the Apache Arrow docs the only explanation I saw on the batch size parameter was this:
   
   >  [The maximum row count for scanned record batches. If scanned record batches are overflowing memory then this method can be called to reduce their size.](https://arrow.apache.org/docs/python/generated/pyarrow.dataset.Scanner.html?highlight=batch_size)
   
   If I can find a good explanation for it or if you have one, I'd be happy to add the `batch_size` parameter to the `read()` and `read_row_group()` methods and include that explanation in the docstring.


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