Remove LLVM IR API from Gandiva's pyarrow binding since the configura…

…tion is not exposed so LLVM IR cannot be called.

python/pyarrow/gandiva.pyx

@@ -186,10 +186,6 @@ cdef class Projector(_Weakrefable):
         self.pool = pool
         return self
 
-    @property
-    def llvm_ir(self):
-        return self.projector.get().DumpIR().decode()
-
     def evaluate(self, RecordBatch batch, SelectionVector selection=None):
         """
         Evaluate the specified record batch and return the arrays at the
@@ -235,10 +231,6 @@ cdef class Filter(_Weakrefable):
         self.filter = filter
         return self
 
-    @property
-    def llvm_ir(self):
-        return self.filter.get().DumpIR().decode()
-
     def evaluate(self, RecordBatch batch, MemoryPool pool, dtype='int32'):
         """
         Evaluate the specified record batch and return a selection vector.

python/pyarrow/tests/test_gandiva.py

@@ -50,9 +50,6 @@ def test_tree_exp_builder():
     projector = gandiva.make_projector(
         schema, [expr], pa.default_memory_pool())
 
-    # Gandiva generates compute kernel function named `@expr_X`
-    assert projector.llvm_ir.find("@expr_") != -1
-
     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())
@@ -105,8 +102,6 @@ def test_filter():
     assert condition.result().type == pa.bool_()
 
     filter = gandiva.make_filter(table.schema, condition)
-    # Gandiva generates compute kernel function named `@expr_X`
-    assert filter.llvm_ir.find("@expr_") != -1
 
     result = filter.evaluate(table.to_batches()[0], pa.default_memory_pool())
     assert result.to_array().equals(pa.array(range(1000), type=pa.uint32()))