kou opened a new issue, #39695:
URL: https://github.com/apache/arrow/issues/39695
### Describe the bug, including details regarding any error messages,
version, and platform.
I'm not sure that this is a problem of Gandiva/PyArrow or my environment.
I'm verifying Apache Arrow 15.0.0 RC1. I got the following failures:
```text
=================================== FAILURES
===================================
____________________________ test_tree_exp_builder
_____________________________
@pytest.mark.gandiva
def test_tree_exp_builder():
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)
assert node_a.return_type() == field_a.type
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)
assert expr.result().type == pa.int32()
config = gandiva.Configuration(dump_ir=True)
> projector = gandiva.make_projector(
schema, [expr], pa.default_memory_pool(), "NONE", config)
pyarrow/tests/test_gandiva.py:51:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _
pyarrow/gandiva.pyx:625: in pyarrow.gandiva.make_projector
cpdef make_projector(Schema schema, children, MemoryPool pool,
pyarrow/gandiva.pyx:664: in pyarrow.gandiva.make_projector
check_status(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _
> raise convert_status(status)
E pyarrow.lib.ArrowException: CodeGenError in Gandiva: Could not create
LLJIT instance: Symbols not found: [ llvm_orc_registerEHFrameSectionWrapper ]
pyarrow/error.pxi:91: ArrowException
----------------------------- Captured stderr call
-----------------------------
/tmp/arrow-15.0.0.lJ9Vt/apache-arrow-15.0.0/cpp/src/gandiva/cache.cc:50:
Creating gandiva cache with capacity of 500
/tmp/arrow-15.0.0.lJ9Vt/apache-arrow-15.0.0/cpp/src/gandiva/engine.cc:265:
Detected CPU Name : znver2
/tmp/arrow-15.0.0.lJ9Vt/apache-arrow-15.0.0/cpp/src/gandiva/engine.cc:266:
Detected CPU Features: [ +prfchw -cldemote +avx +aes +sahf +pclmul -xop +crc32
+xsaves -avx512fp16 -sm4 +sse4.1 -avx512ifma +xsave -avx512pf +sse4.2 -tsxldtrk
-ptwrite -widekl -sm3 -invpcid +64bit +xsavec -avx512vpopcntdq +cmov
-avx512vp2intersect -avx512cd +movbe -avxvnniint8 -avx512er -amx-int8 -kl
-sha512 -avxvnni -rtm +adx +avx2 -hreset -movdiri -serialize -vpclmulqdq
-avx512vl -uintr +clflushopt -raoint -cmpccxadd +bmi -amx-tile +sse -gfni
-avxvnniint16 -amx-fp16 +xsaveopt +rdrnd -avx512f -amx-bf16 -avx512bf16
-avx512vnni +cx8 -avx512bw +sse3 -pku +fsgsbase +clzero +mwaitx -lwp +lzcnt
+sha -movdir64b +wbnoinvd -enqcmd -prefetchwt1 -avxneconvert -tbm -pconfig
-amx-complex +ssse3 +cx16 +bmi2 +fma +popcnt -avxifma +f16c -avx512bitalg
+rdpru +clwb +mmx +sse2 +rdseed -avx512vbmi2 -prefetchi +rdpid -fma4
-avx512vbmi -shstk -vaes -waitpkg -sgx +fxsr -avx512dq +sse4a]
__________________________________ test_table
__________________________________
@pytest.mark.gandiva
def test_table():
import pyarrow.gandiva as gandiva
table = pa.Table.from_arrays([pa.array([1.0, 2.0]), pa.array([3.0,
4.0])],
['a', 'b'])
builder = gandiva.TreeExprBuilder()
node_a = builder.make_field(table.schema.field("a"))
node_b = builder.make_field(table.schema.field("b"))
sum = builder.make_function("add", [node_a, node_b], pa.float64())
field_result = pa.field("c", pa.float64())
expr = builder.make_expression(sum, field_result)
> projector = gandiva.make_projector(
table.schema, [expr], pa.default_memory_pool())
pyarrow/tests/test_gandiva.py:82:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _
pyarrow/gandiva.pyx:625: in pyarrow.gandiva.make_projector
cpdef make_projector(Schema schema, children, MemoryPool pool,
pyarrow/gandiva.pyx:664: in pyarrow.gandiva.make_projector
check_status(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _
> raise convert_status(status)
E pyarrow.lib.ArrowException: CodeGenError in Gandiva: Could not create
LLJIT instance: Symbols not found: [ llvm_orc_registerEHFrameSectionWrapper ]
pyarrow/error.pxi:91: ArrowException
_________________________________ test_filter
__________________________________
@pytest.mark.gandiva
def test_filter():
import pyarrow.gandiva as gandiva
table = pa.Table.from_arrays([pa.array([1.0 * i for i in
range(10000)])],
['a'])
builder = gandiva.TreeExprBuilder()
node_a = builder.make_field(table.schema.field("a"))
thousand = builder.make_literal(1000.0, pa.float64())
cond = builder.make_function("less_than", [node_a, thousand],
pa.bool_())
condition = builder.make_condition(cond)
assert condition.result().type == pa.bool_()
config = gandiva.Configuration(dump_ir=True)
> filter = gandiva.make_filter(table.schema, condition, config)
pyarrow/tests/test_gandiva.py:109:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _
pyarrow/gandiva.pyx:672: in pyarrow.gandiva.make_filter
cpdef make_filter(Schema schema, Condition condition,
pyarrow/gandiva.pyx:700: in pyarrow.gandiva.make_filter
check_status(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _
> raise convert_status(status)
E pyarrow.lib.ArrowException: CodeGenError in Gandiva: Could not create
LLJIT instance: Symbols not found: [ llvm_orc_registerEHFrameSectionWrapper ]
pyarrow/error.pxi:91: ArrowException
_________________________________ test_in_expr
_________________________________
@pytest.mark.gandiva
def test_in_expr():
import pyarrow.gandiva as gandiva
arr = pa.array(["ga", "an", "nd", "di", "iv", "va"])
table = pa.Table.from_arrays([arr], ["a"])
# string
builder = gandiva.TreeExprBuilder()
node_a = builder.make_field(table.schema.field("a"))
cond = builder.make_in_expression(node_a, ["an", "nd"], pa.string())
condition = builder.make_condition(cond)
> filter = gandiva.make_filter(table.schema, condition)
pyarrow/tests/test_gandiva.py:129:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _
pyarrow/gandiva.pyx:672: in pyarrow.gandiva.make_filter
cpdef make_filter(Schema schema, Condition condition,
pyarrow/gandiva.pyx:700: in pyarrow.gandiva.make_filter
check_status(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _
> raise convert_status(status)
E pyarrow.lib.ArrowException: CodeGenError in Gandiva: Could not create
LLJIT instance: Symbols not found: [ llvm_orc_registerEHFrameSectionWrapper ]
pyarrow/error.pxi:91: ArrowException
_________________________________ test_boolean
_________________________________
@pytest.mark.gandiva
def test_boolean():
import pyarrow.gandiva as gandiva
table = pa.Table.from_arrays([
pa.array([1., 31., 46., 3., 57., 44., 22.]),
pa.array([5., 45., 36., 73., 83., 23., 76.])],
['a', 'b'])
builder = gandiva.TreeExprBuilder()
node_a = builder.make_field(table.schema.field("a"))
node_b = builder.make_field(table.schema.field("b"))
fifty = builder.make_literal(50.0, pa.float64())
eleven = builder.make_literal(11.0, pa.float64())
cond_1 = builder.make_function("less_than", [node_a, fifty],
pa.bool_())
cond_2 = builder.make_function("greater_than", [node_a, node_b],
pa.bool_())
cond_3 = builder.make_function("less_than", [node_b, eleven],
pa.bool_())
cond = builder.make_or([builder.make_and([cond_1, cond_2]), cond_3])
condition = builder.make_condition(cond)
> filter = gandiva.make_filter(table.schema, condition)
pyarrow/tests/test_gandiva.py:250:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _
pyarrow/gandiva.pyx:672: in pyarrow.gandiva.make_filter
cpdef make_filter(Schema schema, Condition condition,
pyarrow/gandiva.pyx:700: in pyarrow.gandiva.make_filter
check_status(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _
> raise convert_status(status)
E pyarrow.lib.ArrowException: CodeGenError in Gandiva: Could not create
LLJIT instance: Symbols not found: [ llvm_orc_registerEHFrameSectionWrapper ]
pyarrow/error.pxi:91: ArrowException
__________________________________ test_regex
__________________________________
@pytest.mark.gandiva
def test_regex():
import pyarrow.gandiva as gandiva
elements = ["park", "sparkle", "bright spark and fire", "spark"]
data = pa.array(elements, type=pa.string())
table = pa.Table.from_arrays([data], names=['a'])
builder = gandiva.TreeExprBuilder()
node_a = builder.make_field(table.schema.field("a"))
regex = builder.make_literal("%spark%", pa.string())
like = builder.make_function("like", [node_a, regex], pa.bool_())
field_result = pa.field("b", pa.bool_())
expr = builder.make_expression(like, field_result)
> projector = gandiva.make_projector(
table.schema, [expr], pa.default_memory_pool())
pyarrow/tests/test_gandiva.py:311:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _
pyarrow/gandiva.pyx:625: in pyarrow.gandiva.make_projector
cpdef make_projector(Schema schema, children, MemoryPool pool,
pyarrow/gandiva.pyx:664: in pyarrow.gandiva.make_projector
check_status(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _
> raise convert_status(status)
E pyarrow.lib.ArrowException: CodeGenError in Gandiva: Could not create
LLJIT instance: Symbols not found: [ llvm_orc_registerEHFrameSectionWrapper ]
pyarrow/error.pxi:91: ArrowException
_____________________________ test_filter_project
______________________________
@pytest.mark.gandiva
def test_filter_project():
import pyarrow.gandiva as gandiva
mpool = pa.default_memory_pool()
# Create a table with some sample data
array0 = pa.array([10, 12, -20, 5, 21, 29], pa.int32())
array1 = pa.array([5, 15, 15, 17, 12, 3], pa.int32())
array2 = pa.array([1, 25, 11, 30, -21, None], pa.int32())
table = pa.Table.from_arrays([array0, array1, array2], ['a', 'b',
'c'])
field_result = pa.field("res", pa.int32())
builder = gandiva.TreeExprBuilder()
node_a = builder.make_field(table.schema.field("a"))
node_b = builder.make_field(table.schema.field("b"))
node_c = builder.make_field(table.schema.field("c"))
greater_than_function = builder.make_function("greater_than",
[node_a, node_b],
pa.bool_())
filter_condition = builder.make_condition(
greater_than_function)
project_condition = builder.make_function("less_than",
[node_b, node_c],
pa.bool_())
if_node = builder.make_if(project_condition,
node_b, node_c, pa.int32())
expr = builder.make_expression(if_node, field_result)
# Build a filter for the expressions.
> filter = gandiva.make_filter(table.schema, filter_condition)
pyarrow/tests/test_gandiva.py:359:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _
pyarrow/gandiva.pyx:672: in pyarrow.gandiva.make_filter
cpdef make_filter(Schema schema, Condition condition,
pyarrow/gandiva.pyx:700: in pyarrow.gandiva.make_filter
check_status(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _
> raise convert_status(status)
E pyarrow.lib.ArrowException: CodeGenError in Gandiva: Could not create
LLJIT instance: Symbols not found: [ llvm_orc_registerEHFrameSectionWrapper ]
pyarrow/error.pxi:91: ArrowException
```
Note that Gandiva tests written in C++ were passed.
### Component(s)
C++ - Gandiva, Python
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