Zeyuan Shang created ARROW-5471:
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Summary: [C++][Gandiva]Array offset is ignored in Gandiva projector
Key: ARROW-5471
URL: https://issues.apache.org/jira/browse/ARROW-5471
Project: Apache Arrow
Issue Type: Bug
Reporter: Zeyuan Shang
I used the test case in
[https://github.com/apache/arrow/blob/master/python/pyarrow/tests/test_gandiva.py#L25],
and found an issue when I was using the slice operator {{input_batch[1:]}}. It
seems that the offset is ignored in the Gandiva projector.
{code:java}
import pyarrow as pa
import pyarrow.gandiva as gandiva
builder = gandiva.TreeExprBuilder()
field_a = pa.field('a', pa.int32())
field_b = pa.field('b', pa.int32())
schema = pa.schema([field_a, field_b])
field_result = pa.field('res', pa.int32())
node_a = builder.make_field(field_a)
node_b = builder.make_field(field_b)
condition = builder.make_function("greater_than", [node_a, node_b],
pa.bool_())
if_node = builder.make_if(condition, node_a, node_b, pa.int32())
expr = builder.make_expression(if_node, field_result)
projector = gandiva.make_projector(
schema, [expr], pa.default_memory_pool())
a = pa.array([10, 12, -20, 5], type=pa.int32())
b = pa.array([5, 15, 15, 17], type=pa.int32())
e = pa.array([10, 15, 15, 17], type=pa.int32())
input_batch = pa.RecordBatch.from_arrays([a, b], names=['a', 'b'])
r, = projector.evaluate(input_batch[1:])
print(r)
{code}
If we use the full record batch {{input_batch}}, the expected output is {{[10,
15, 15, 17]}}. So if we use {{input_batch[1:]}}, the expected output should be
{{[15, 15, 17]}}, however this script returned {{[10, 15, 15]}}. It seems that
the projector ignores the offset and always reads from 0.
A corresponding issue is created in GitHub as well
[https://github.com/apache/arrow/issues/4420]
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