I am working in marketing research field, and find that at times I need to extract contents of ORC files into analytical packages like R, Julia, etc, without using tools like JDBC, etc ( which offers ability to access ORC files )
I have been using C++ to access ORC file contents, following examples provided in the ORC file C++ distribution example, e.g. meta info, contents, etc. My datasets are basic 2d tables, with rows and columns, each column has very basic data types : int64, or double. I have found the ORC file C++ access APIs very helpful and handy!
Since R or Julia has column major storage format in their matrix, and I would like to extract the contents of ORC files column by column. In the example that gets the file contents made available on the ORC file C++ official website, the C++ code reads the entire ORC file contents by batches, and within each batch, it reads the contents row by row, creating a string version of the data, JSON like.
My question is : ( since I don't know how ORC file structure details ), Can the user read ORC file contents column by column using the C++ APIs you guys published ? is there speed advantage of doing this ( as opposed to read in batches, and within each batch parse contents row by row ).
if possible : Is there an example that I can follow to read contents column by column?
Is it possible that the example C++ codes can give a (char*) type pointer to the user , each time it reads a row element within a column, so that users can read that into desired data type, e.g. int64, double, etc, directly without building the JSON like text output rows ? Or there are even more there already to read a ORC file column directly into a in-memory T* that stores the data with corresponding data type, e.g. int64, double, etc. ?
Many many thanks!