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From Gang Wu <ust...@gmail.com>
Subject Re: access entire column in ORC files
Date Sun, 20 Jan 2019 17:52:47 GMT
To read the desired type of each column, you just need to cast the base
orc::ColumnVectorBatch, which you get from rowReader->next(), to its
desired type. You can dynamic_cast to orc::LongVectorBatch for int64 and
orc::StringVectorBatch for char *, check the API here:


On Sun, Jan 20, 2019 at 9:36 AM Zhiyuan Dong <zhiyuan.dong@gmail.com> wrote:

> Hi Owen,
> Let me follow the github example link you provided.
> Appreciate the prompt response. Many thanks!
> Best,
> Zhiyuan
> On Sun, Jan 20, 2019 at 11:09 AM Owen O'Malley <owen.omalley@gmail.com>
> wrote:
>> Yes, ORC files are set up so that reading individual columns is much
>> faster (and reads less data) than reading the entire row.
>> You need to call RowReaderOptions::include or includeType depending on
>> whether you want to select by name or id.
>> Look at the tool code for file contents about how to do this.
>> https://github.com/apache/orc/blob/4e7d9c2e126cebd075f51b9d6ab2c30f4c8943c0/tools/src/FileContents.cc#L77
>> .. Owen
>> On Sun, Jan 20, 2019 at 7:16 AM Zhiyuan Dong <zhiyuan.dong@gmail.com>
>> wrote:
>>> Hi
>>> 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!
>>> Best,
>>> Zhiyuan
> --
> Zhiyuan Dong, Ph.D.

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