Pc_relate error

I tried to do relatedness analysis but I’m facing a problem with large amount of comparison.

pc_rel = hl.pc_relate(mt.GT, min_individual_maf = 0.01, k=10, statistics='kin', min_kinship=0.2, block_size=512)
2020-02-28 12:43:06 Hail: INFO: hwe_normalized_pca: running PCA using 37119 variants.
2020-02-28 12:43:32 Hail: INFO: pca: running PCA with 10 components...
2020-02-28 12:50:20 Hail: INFO: Wrote all 942 blocks of 80285 x 2601 matrix with block size 512.

Py4JError: An error occurred while calling o130.executeJSON

# A fatal error has been detected by the Java Runtime Environment:
#  SIGSEGV (0xb) at pc=0x00007f9477a84b34, pid=27117, tid=0x00007f93ffcfc700
# JRE version: OpenJDK Runtime Environment (8.0_212-b03) (build 1.8.0_212-8u212-b03-0ubuntu1.18.04.1-b03)
# Java VM: OpenJDK 64-Bit Server VM (25.212-b03 mixed mode linux-amd64 compressed oops)
# Problematic frame:
# V  [libjvm.so+0x88cb34]
# Failed to write core dump. Core dumps have been disabled. To enable core dumping, try "ulimit -c unlimited" before starting Java again
# An error report file with more information is saved as:
# /mnt/tank/scratch/rskitchenko/FSGS/hs_err_pid27117.log
# If you would like to submit a bug report, please visit:
#   http://bugreport.java.com/bugreport/crash.jsp

is the problem related to a lack of memory?

Are you using Google Cloud Dataproc (e.g. hailctl dataproc start) or something else? If you’re using something else, you need to install hail from source. Moreover, this error sometimes occurs if you do not have LAPACK and BLAS installed, two high performance linear algebra libraries. The easiest BLAS/LAPACK library to install is probably OpenBLAS.