[jira] [Updated] (ARROW-6157) [Python][C++] UnionArray with invalid data passes validation / leads to segfaults
[ https://issues.apache.org/jira/browse/ARROW-6157?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] ASF GitHub Bot updated ARROW-6157: -- Labels: pull-request-available (was: ) > [Python][C++] UnionArray with invalid data passes validation / leads to > segfaults > - > > Key: ARROW-6157 > URL: https://issues.apache.org/jira/browse/ARROW-6157 > Project: Apache Arrow > Issue Type: Bug > Components: C++, Python >Reporter: Joris Van den Bossche >Assignee: Antoine Pitrou >Priority: Major > Labels: pull-request-available > Fix For: 1.0.0 > > > From the Python side, you can create an "invalid" UnionArray: > {code} > binary = pa.array([b'a', b'b', b'c', b'd'], type='binary') > int64 = pa.array([1, 2, 3], type='int64') > types = pa.array([0, 1, 0, 0, 2, 1, 0], type='int8') # <- value of 2 is out > of bound for number of childs > value_offsets = pa.array([0, 0, 2, 1, 1, 2, 3], type='int32') > a = pa.UnionArray.from_dense(types, value_offsets, [binary, int64]) > {code} > Eg on conversion to python this leads to a segfault: > {code} > In [7]: a.to_pylist() > Segmentation fault (core dumped) > {code} > On the other hand, doing an explicit validation does not give an error: > {code} > In [8]: a.validate() > {code} > Should the validation raise errors for this case? (the C++ > {{ValidateVisitor}} for UnionArray does nothing) > (so that this can be called from the Python API to avoid creating invalid > arrays / segfaults there) -- This message was sent by Atlassian Jira (v8.3.4#803005)
[jira] [Updated] (ARROW-6157) [Python][C++] UnionArray with invalid data passes validation / leads to segfaults
[ https://issues.apache.org/jira/browse/ARROW-6157?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Antoine Pitrou updated ARROW-6157: -- Fix Version/s: 1.0.0 > [Python][C++] UnionArray with invalid data passes validation / leads to > segfaults > - > > Key: ARROW-6157 > URL: https://issues.apache.org/jira/browse/ARROW-6157 > Project: Apache Arrow > Issue Type: Bug > Components: C++, Python >Reporter: Joris Van den Bossche >Priority: Major > Fix For: 1.0.0 > > > From the Python side, you can create an "invalid" UnionArray: > {code} > binary = pa.array([b'a', b'b', b'c', b'd'], type='binary') > int64 = pa.array([1, 2, 3], type='int64') > types = pa.array([0, 1, 0, 0, 2, 1, 0], type='int8') # <- value of 2 is out > of bound for number of childs > value_offsets = pa.array([0, 0, 2, 1, 1, 2, 3], type='int32') > a = pa.UnionArray.from_dense(types, value_offsets, [binary, int64]) > {code} > Eg on conversion to python this leads to a segfault: > {code} > In [7]: a.to_pylist() > Segmentation fault (core dumped) > {code} > On the other hand, doing an explicit validation does not give an error: > {code} > In [8]: a.validate() > {code} > Should the validation raise errors for this case? (the C++ > {{ValidateVisitor}} for UnionArray does nothing) > (so that this can be called from the Python API to avoid creating invalid > arrays / segfaults there) -- This message was sent by Atlassian Jira (v8.3.4#803005)
[jira] [Updated] (ARROW-6157) [Python][C++] UnionArray with invalid data passes validation / leads to segfaults
[ https://issues.apache.org/jira/browse/ARROW-6157?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joris Van den Bossche updated ARROW-6157: - Description: >From the Python side, you can create an "invalid" UnionArray: {code} binary = pa.array([b'a', b'b', b'c', b'd'], type='binary') int64 = pa.array([1, 2, 3], type='int64') types = pa.array([0, 1, 0, 0, 2, 1, 0], type='int8') # <- value of 2 is out of bound for number of childs value_offsets = pa.array([0, 0, 2, 1, 1, 2, 3], type='int32') a = pa.UnionArray.from_dense(types, value_offsets, [binary, int64]) {code} Eg on conversion to python this leads to a segfault: {code} In [7]: a.to_pylist() Segmentation fault (core dumped) {code} On the other hand, doing an explicit validation does not give an error: {code} In [8]: a.validate() {code} Should the validation raise errors for this case? (the C++ {{ValidateVisitor}} for UnionArray does nothing) (so that this can be called from the Python API to avoid creating invalid arrays / segfaults there) was: >From the Python side, you can create an "invalid" UnionArray: {code} binary = pa.array([b'a', b'b', b'c', b'd'], type='binary') int64 = pa.array([1, 2, 3], type='int64') types = pa.array([0, 1, 0, 0, 2, 1, 0], type='int8') # <- value of 2 is out of bound for number of childs value_offsets = pa.array([0, 0, 2, 1, 1, 2, 3], type='int32') a = pa.UnionArray.from_dense(types, value_offsets, [binary, int64]) {code} Eg on conversion to python this leads to a segfault: {code} In [7]: a.to_pylist() Segmentation fault (core dumped) {code} On the other hand, doing an explicit validation does not give an error: {code} In [8]: a.validate() {code} Should the validation raise errors for this case? (the C++ {{ValidateVisitor}} for UnionArray does nothing) > [Python][C++] UnionArray with invalid data passes validation / leads to > segfaults > - > > Key: ARROW-6157 > URL: https://issues.apache.org/jira/browse/ARROW-6157 > Project: Apache Arrow > Issue Type: Bug > Components: C++, Python >Reporter: Joris Van den Bossche >Priority: Major > > From the Python side, you can create an "invalid" UnionArray: > {code} > binary = pa.array([b'a', b'b', b'c', b'd'], type='binary') > int64 = pa.array([1, 2, 3], type='int64') > types = pa.array([0, 1, 0, 0, 2, 1, 0], type='int8') # <- value of 2 is out > of bound for number of childs > value_offsets = pa.array([0, 0, 2, 1, 1, 2, 3], type='int32') > a = pa.UnionArray.from_dense(types, value_offsets, [binary, int64]) > {code} > Eg on conversion to python this leads to a segfault: > {code} > In [7]: a.to_pylist() > Segmentation fault (core dumped) > {code} > On the other hand, doing an explicit validation does not give an error: > {code} > In [8]: a.validate() > {code} > Should the validation raise errors for this case? (the C++ > {{ValidateVisitor}} for UnionArray does nothing) > (so that this can be called from the Python API to avoid creating invalid > arrays / segfaults there) -- This message was sent by Atlassian JIRA (v7.6.14#76016)