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https://issues.apache.org/jira/browse/ARROW-3765?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Siyuan Zhuang updated ARROW-3765:
---------------------------------
Summary: [Gandiva] Segfault when the validity bitmap has not been allocated
(was: [Gandiva] Segfault when validity bitmap has not been allocated)
> [Gandiva] Segfault when the validity bitmap has not been allocated
> ------------------------------------------------------------------
>
> Key: ARROW-3765
> URL: https://issues.apache.org/jira/browse/ARROW-3765
> Project: Apache Arrow
> Issue Type: Bug
> Components: C++, Gandiva
> Reporter: Siyuan Zhuang
> Priority: Major
> Labels: pull-request-available
>
> This is because the `validity buffer` could be `None`:
> {code}
> >>> df = pd.DataFrame(np.random.randint(0, 100, size=(2**12, 10)))
> >>> pa.Table.from_pandas(df).to_batches()[0].column(0).buffers()
> [None, <pyarrow.lib.Buffer object at 0x110c1a228>]
> >>> df = pd.DataFrame(np.random.randint(0, 100, size=(2**12, 10))*1.0)
> >>> pa.Table.from_pandas(df).to_batches()[0].column(0).buffers()
> [<pyarrow.lib.Buffer object at 0x11a2b3030>, <pyarrow.lib.Buffer object at
> 0x11a2b3228>]{code}
> But Gandiva has not implemented it yet, thus accessing a nullptr:
> {code}
> void Annotator::PrepareBuffersForField(const FieldDescriptor& desc, const
> arrow::ArrayData& array_data, EvalBatch* eval_batch) {
> int buffer_idx = 0;
> // TODO:
> // - validity is optional
> uint8_t* validity_buf =
> const_cast<uint8_t*>(array_data.buffers[buffer_idx]->data());
> eval_batch->SetBuffer(desc.validity_idx(), validity_buf);
> ++buffer_idx;
> {code}
>
> Reproduce code:
> {code:java}
> frame_data = np.random.randint(0, 100, size=(2**22, 10))
> table = pa.Table.from_pandas(df)
> filt = ... # Create any gandiva filter
> r = filt.evaluate(table.to_batches()[0], pa.default_memory_pool()) #
> segfault{code}
> Backtrace:
> {code:java}
> * thread #2, queue = 'com.apple.main-thread', stop reason = EXC_BAD_ACCESS
> (code=1, address=0x10)
> * frame #0: 0x00000001060184fc
> libarrow.12.dylib`arrow::Buffer::data(this=0x0000000000000000) const at
> buffer.h:162
> frame #1: 0x0000000106fbed78
> libgandiva.12.dylib`gandiva::Annotator::PrepareBuffersForField(this=0x0000000100624dc8,
> desc=0x000000010101e138, array_data=0x000000010061f8e8,
> eval_batch=0x0000000100796848) at annotator.cc:65
> frame #2: 0x0000000106fbf4ed
> libgandiva.12.dylib`gandiva::Annotator::PrepareEvalBatch(this=0x0000000100624dc8,
> record_batch=0x00000001007a45b8, out_vector=size=1) at annotator.cc:94
> frame #3: 0x00000001071449b7
> libgandiva.12.dylib`gandiva::LLVMGenerator::Execute(this=0x0000000100624da0,
> record_batch=0x00000001007a45b8, output_vector=size=1) at
> llvm_generator.cc:102
> frame #4: 0x0000000107059a4f
> libgandiva.12.dylib`gandiva::Filter::Evaluate(this=0x000000010079c668,
> batch=0x00000001007a45b8,
> out_selection=std::__1::shared_ptr<gandiva::SelectionVector>::element_type @
> 0x00000001007a43e8 strong=2 weak=1) at filter.cc:106
> frame #5: 0x000000010948e002
> gandiva.cpython-36m-darwin.so`__pyx_pw_7pyarrow_7gandiva_6Filter_3evaluate(_object*,
> _object*, _object*) + 1986
> frame #6: 0x0000000100140e8b Python`_PyCFunction_FastCallDict + 475
> frame #7: 0x00000001001d28ca Python`call_function + 602
> frame #8: 0x00000001001cf798 Python`_PyEval_EvalFrameDefault + 24616
> frame #9: 0x00000001001d3cf9 Python`fast_function + 569
> frame #10: 0x00000001001d2899 Python`call_function + 553
> frame #11: 0x00000001001cf798 Python`_PyEval_EvalFrameDefault + 24616
> frame #12: 0x00000001001d34c6 Python`_PyEval_EvalCodeWithName + 2902
> frame #13: 0x00000001001c96e0 Python`PyEval_EvalCode + 48
> frame #14: 0x00000001002029ae Python`PyRun_FileExFlags + 174
> frame #15: 0x0000000100201f75 Python`PyRun_SimpleFileExFlags + 277
> frame #16: 0x000000010021ef46 Python`Py_Main + 3558
> frame #17: 0x0000000100000e08 Python`___lldb_unnamed_symbol1$$Python + 248
> frame #18: 0x00007fff6ea72085 libdyld.dylib`start + 1{code}
>
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