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https://issues.apache.org/jira/browse/ARROW-2354?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16414170#comment-16414170
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ASF GitHub Bot commented on ARROW-2354:
---------------------------------------
pitrou commented on a change in pull request #1794: ARROW-2354: [C++] Make
PyDecimal_Check() faster
URL: https://github.com/apache/arrow/pull/1794#discussion_r177169733
##########
File path: cpp/src/arrow/python/helpers.cc
##########
@@ -227,12 +227,16 @@ Status UInt64FromPythonInt(PyObject* obj, uint64_t* out)
{
}
bool PyDecimal_Check(PyObject* obj) {
- // TODO(phillipc): Is this expensive?
- OwnedRef Decimal;
- Status status = ImportDecimalType(&Decimal);
- DCHECK_OK(status);
- const int32_t result = PyObject_IsInstance(obj, Decimal.obj());
- DCHECK_NE(result, -1) << " error during PyObject_IsInstance check";
+ static OwnedRef decimal_type;
Review comment:
Here is an alternative implementation. Which one do you prefer?
```c++
bool PyDecimal_Check(PyObject* obj) {
OwnedRef decimal_type;
PyTypeObject* obj_type = Py_TYPE(obj);
// Fast fail for most types other than Decimal, for speed
if (strcmp(obj_type->tp_name, "decimal.Decimal")) {
return false;
}
Status status = ImportDecimalType(&decimal_type);
DCHECK_OK(status);
DCHECK(PyType_Check(decimal_type.obj()));
// PyObject_IsInstance() is slower as it has to check for virtual
subclasses
const int result =
PyType_IsSubtype(obj_type,
reinterpret_cast<PyTypeObject*>(decimal_type.obj()));
DCHECK_NE(result, -1) << " error during PyType_IsSubtype check";
return result == 1;
}
```
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> [C++] PyDecimal_Check() is much too slow
> ----------------------------------------
>
> Key: ARROW-2354
> URL: https://issues.apache.org/jira/browse/ARROW-2354
> Project: Apache Arrow
> Issue Type: Bug
> Components: C++, Python
> Affects Versions: 0.9.0
> Reporter: Antoine Pitrou
> Assignee: Antoine Pitrou
> Priority: Major
> Labels: pull-request-available
>
> See https://github.com/apache/arrow/issues/1792
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