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https://issues.apache.org/jira/browse/ARROW-47?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16719205#comment-16719205
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Benjamin Kietzman edited comment on ARROW-47 at 12/12/18 5:06 PM:
------------------------------------------------------------------
One alternative to using `vector<shared_ptr<Scalar>>` would be a flatbuffer:
{code:title=struct_scalar.h}
struct StructScalar {
template <typename T>
T GetFieldAs(int field_index);
flatbuffers::Table *root_;
std::vector<flatbuffers::reflection::Field*> fields_;
std::shared_ptr<Buffer> storage_;
};
{code}
In any case, the main challenge I see is the amount of fragile unboxing
boilerplate that StructScalar would require to be user friendly. That can be
mitigated with good metaprogramming, but it's still a bit verbose:
{code:title=unbox_styles.cc}
StructScalar* obj = get();
Status s = Unbox1<int, string, ignore, bool>(obj, [](vector<bool> is_valid, int
id, string_view name, ignore, bool admin) {
// ...
});
vector<bool> is_valid;
tuple<int, string_view, ignore, bool> employee;
RETURN_NOT_OK(Unbox2(obj, &employee, &is_valid));
pair<bool, int> id;
pair<bool, string_view> name;
pair<bool, bool> admin;
RETURN_NOT_OK(Unbox3<int>(obj, 0, &id));
RETURN_NOT_OK(Unbox3<int>(obj, 1, &name));
RETURN_NOT_OK(Unbox3<int>(obj, 3, &admin));
// more options available beyond c++11
{code}
was (Author: bkietz):
One alternative to using `vector<shared_ptr<Scalar>>` would be a flatbuffer:
```
struct StructScalar {
template <typename T>
T GetFieldAs(int field_index);
flatbuffers::Table *root_;
std::vector<flatbuffers::reflection::Field*> fields_;
std::shared_ptr<Buffer> storage_;
};
```
In any case, the main challenge I see is the amount of fragile unboxing
boilerplate that StructScalar would require to be user friendly. That can be
mitigated with good metaprogramming, but it's still a bit verbose:
{{
StructScalar* obj = get();
Status s = Unbox1<int, string, ignore, bool>(obj, [](vector<bool> is_valid, int
id, string_view name, ignore, bool admin) {
// ...
});
vector<bool> is_valid;
tuple<int, string_view, ignore, bool> employee;
RETURN_NOT_OK(Unbox2(obj, &employee, &is_valid));
pair<bool, int> id;
pair<bool, string_view> name;
pair<bool, bool> admin;
RETURN_NOT_OK(Unbox3<int>(obj, 0, &id));
RETURN_NOT_OK(Unbox3<int>(obj, 1, &name));
RETURN_NOT_OK(Unbox3<int>(obj, 3, &admin));
// more options available beyond c++11
}}
> [C++] Consider adding a scalar type object model
> ------------------------------------------------
>
> Key: ARROW-47
> URL: https://issues.apache.org/jira/browse/ARROW-47
> Project: Apache Arrow
> Issue Type: New Feature
> Components: C++
> Reporter: Wes McKinney
> Assignee: Uwe L. Korn
> Priority: Major
> Labels: Analytics
> Fix For: 0.13.0
>
>
> Just did this on the Python side. In later analytics routines, passing in
> scalar values (example: Array + Scalar) requires some kind of container. Some
> systems, like the R language, solve this problem with length-1 arrays, but we
> should do some analysis of use cases and figure out what will work best for
> Arrow.
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