[ARROW-5471] [C++][Gandiva]Array offset is ignored in Gandiva projector

• Type: Bug
• Status: Resolved
• Priority: Major
• Resolution: Fixed
• Fix Version/s: 0.15.0
• Component/s: C++ - Gandiva
• Labels: pull-request-available
• External issue URL: https://github.com/apache/arrow/issues/21921
• Assignee: Zeyuan Shang
• Reporter: Zeyuan Shang
• Created: 31/May/19 17:07
• Updated: 11/Jan/23 07:40
• Resolved: 10/Sep/19 01:40

Description

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.

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)

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

Issue Links

• links to: GitHub Pull Request #5255