hi Korry, On Mon, Dec 3, 2018 at 3:56 PM Korry Douglas <[email protected]> wrote: > > I’ve been working on this project for a few weeks now and it’s going well (at > least, I think it is). > > I’m using the Parquet cpp API. As I mentioned earlier, I have used AWS Glue > to build some sample files - I can read those files now and even make sense > of them :-) > > Now I’m working on writing large batches to a parquet file. I can read/write > a few data types (strings, UUID’s, fixed-length strings, booleans), but I’m > having trouble with DECIMALs. If I understand correctly, I can store a > DECIMAL as an INT32, an INT64, or an FLBA (source: > https://github.com/apache/parquet-format/blob/master/LogicalTypes.md#decimal). > > So a few questions: > > 1) Is the decimal position (scale) fixed for a given column? Or can I mix > scales within the same column? If I can mix them, how do I store the actual > scale with each value?
Yes, it's fixed > > 2) Can anyone point me to an example of how to build a DECIMAL value based on > an FLBA? Are there any classes that would help me build such (and then > deconstruct) such a value? Have a look at the Arrow write paths for decimals under src/parquet/arrow. If using Arrow directly is not an option then you could reuse the ideas from this code > > Thanks in advance. > > > — Korry > > > > On Nov 15, 2018, at 12:56 PM, Korry Douglas <[email protected]> wrote: > > Hi all, I’m exploring the idea of adding a foreign data wrapper (FDW) that > will let PostgreSQL read Parquet-format files. > > I have just a few questions for now: > > 1) I have created a few sample Parquet data files using AWS Glue. Glue split > my CSV input into many (48) smaller xxx.snappy.parquet files, each about > 30MB. When I open one of these files using > gparquet_arrow_file_reader_new_path(), I can then call > gparquet_arrow_file_reader_read_table() (and then access the content of the > table). However, …_read_table() seems to read the entire file into memory > all at once (I say that based on the amount of time it takes for > gparquet_arrow_file_reader_read_table() to return). That’s not the behavior > I need. > > I have tried to use garrow_memory_mappend_input_stream_new() to open the > file, followed by garrow_record_batch_stream_reader_new(). The call to > garrow_record_batch_stream_reader_new() fails with the message: > > [record-batch-stream-reader][open]: Invalid: Expected to read 827474256 > metadata bytes, but only read 30284162 > > Does this error occur because Glue split the input data? Or because Glue > compressed the data using snappy? Do I need to uncompress before I can > read/open the file? Do I need to merge the files before I can open/read the > data? > > > > 2) If I use garrow_record_batch_stream_reader_new() instead of > gparquet_arrow_file_reader_new_path(), will I avoid the overhead of reading > the entire into memory before I fetch the first row? > > > Thanks in advance for help and any advice. > > > — Korry > >
