[GitHub] [arrow] bkietz commented on a change in pull request #7623: ARROW-9108: [C++][Dataset] Add supports for missing type in Statistics to Scalar conversion

[GitBox <gi...@apache.org>]

bkietz commented on a change in pull request #7623:
URL: https://github.com/apache/arrow/pull/7623#discussion_r451637966



##########
File path: python/pyarrow/_dataset.pyx
##########
@@ -881,10 +881,15 @@ cdef class RowGroupInfo:
             name = frombytes(c_statistics.type.get().field(i).get().name())
             c_minmax = <CStructScalar*> c_statistics.value[i].get()
 
-            statistics[name] = {
-                'min': pyarrow_wrap_scalar(c_minmax.value[0]).as_py(),
-                'max': pyarrow_wrap_scalar(c_minmax.value[1]).as_py(),
-            }
+            try:
+                statistics[name] = {
+                    'min': pyarrow_wrap_scalar(c_minmax.value[0]).as_py(),
+                    'max': pyarrow_wrap_scalar(c_minmax.value[1]).as_py(),
+                }
+            except ValueError:
+                # Don't treat failure to parse/convert a single Scalar as a
+                # failure. The min/max will simply be missing for this field.

Review comment:
       Should we add a test case for this? IIUC this will only arise when a parquet file has statistics of a type which `pyarrow_wrap_scalar` doesn't support; are we sure we want to hide that error?




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