They're mapped with the StructType/StructArray, which is also columnar representation, e.g. one buffer per field in the sub-object. If you have varying/incompatible types, a field will be promoted to a UnionType.
François On Thu, Apr 2, 2020 at 12:54 AM Micah Kornfield <emkornfi...@gmail.com> wrote: > > Hi Hasara, > There isn't current functionality in C++/Python to do this ( > https://issues.apache.org/jira/browse/ARROW-4630 is the issue tracking > this). > > Also how nested attributes in json format are mapped into buffers once > > converted in arrow format? > > I'm not sure I understand this question? > > Thanks, > Micah > > On Sun, Mar 22, 2020 at 10:09 PM Hasara Maithree < > hasaramaithreedesi...@gmail.com> wrote: > > > Hi all, > > > > Assume I have a json file named 'my_data.json' as below. > > > > *{"a": [1, 2], "b": {"c": true, "d": "1991-02-03"}} > > {"a": [3, 4, 5], "b": {"c": false, "d": "2019-04-01"**}}* > > > > If I need to do a join operation based on attribute d, can I do it > > directly from arrow structs? ( or are there any efficient alternatives?) > > Also how nested attributes in json format are mapped into buffers once > > converted in arrow format? (example taken from documentation) > > > > >>> table = json.read_json("my_data.json")>>> table > > pyarrow.Table > > a: list<item: int64> > > child 0, item: int64 > > b: struct<c: bool, d: timestamp[s]> > > child 0, c: bool > > child 1, d: timestamp[s]>>> table.to_pandas() > > a b0 [1, 2] > > {'c': True, 'd': 1991-02-03 00:00:00}1 [3, 4, 5] {'c': False, 'd': > > 2019-04-01 00:00:00} > > > > > > Thank You > >
