Could not initialize class com.nvidia.spark.ml.linalg.JniRAPIDSML

[pxLi]

ML JNI mvn build is OK, but when try test it w/ spark plugin in a fresh ENV (w/o conda env for build), it would throw error

[2022-05-31T03:28:40.517Z] 22/05/31 03:28:40 WARN TaskSetManager: 
Lost task 6.0 in stage 5.0 (TID 33) (10.233.109.181 executor 0): 
java.lang.UnsatisfiedLinkError: /tmp/librapidsml_jni.so5201224938898577270: 
libarrow_cuda.so.700: cannot open shared object file: 
No such file or directory

the only change we found is a new cmake option when build w/ conda cudf-22.06
previous (before 22.06.00a220530, e.g. 22.06.00a220519)

LINK_LIBRARIES = -Wl,-rpath,/usr/local/cuda/lib64:/root/miniconda3/lib  -Wl,-Bstatic  -lcudart_static  -lcusparse_static  
-lcusolver_static  -lculibos  -llapack_static  -Wl,-Bdynamic  /root/miniconda3/lib/libcudf.so  /usr/local/cuda/lib64/libcublas.so 
 /root/miniconda3/lib/libarrow.so.700.0.0  /root/miniconda3/lib/libarrow_cuda.so.700.0.0  -ldl  -lpthread  
/usr/local/cuda/lib64/libcudart.so  /usr/lib64/libcuda.so  -lcudadevrt  -lcudart_static  -lrt  -lpthread  -ldl

now (22.06.00a220530)

LINK_LIBRARIES = -Wl,-rpath,/usr/local/cuda/lib64:/root/miniconda3/lib  -Wl,-Bstatic  -lcudart_static  -lcusparse_static  
-lcusolver_static  -lculibos  -llapack_static  -Wl,-Bdynamic  /root/miniconda3/lib/libcudf.so  /usr/local/cuda/lib64/libcublas.so 
 /root/miniconda3/lib/libarrow.so.700.0.0  /root/miniconda3/lib/libarrow_cuda.so.700.0.0  -ldl  -lpthread 
/usr/local/cuda/lib64/libcudart.so /usr/lib64/libcuda.so -lcudadevrt  -lcudart_static  -lrt  -lpthread  -ldl  
-Wl,-rpath-link,/root/miniconda3/lib

which introduced -Wl,-rpath-link,/root/miniconda3/lib in

cudf                      22.06.00a220530 cuda_11_py38_gdcb04704b3_316    rapidsai-nightly
libcudf                   22.06.00a220530 cuda11_gdcb04704b3_316    rapidsai-nightly
arrow-cpp                 7.0.0           py38he106920_7_cuda    conda-forge
arrow-cpp-proc            3.0.0                      cuda    conda-forge
pyarrow                   7.0.0           py38h17143e8_7_cuda    conda-forge

Probably the dependeny tree mess up in latest cudf pkg on conda?
Test using ml JNI artifacts built against cudf packages before 22.06.00a220530 worked fine.