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Invalid maximum heap size: -Xmx0m
What happened?
while trying to run the following code I get the error mention in the title (Invalid maximum heap size: -Xmx0m).
import hail as hl hl.init(default_reference="GRCh38")
However I tried to resolve the issue with overloading the default setting with new values for spark configuration (command below), unfortunately the error still exists hl.init(driver_memory='1024m’)
Version
latest version used in allOfUs research workbench platform
Relevant log output
Invalid maximum heap size: -Xmx0m
Error: Could not create the Java Virtual Machine.
Error: A fatal exception has occurred. Program will exit.
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
Cell In[14], line 2
1 #hl.init(default_reference="GRCh38")
----> 2 hl.init(driver_memory='1024m')
File <decorator-gen-1756>:2, in init(sc, app_name, master, local, log, quiet, append, min_block_size, branching_factor, tmp_dir, default_reference, idempotent, global_seed, spark_conf, skip_logging_configuration, local_tmpdir, _optimizer_iterations, backend, driver_cores, driver_memory, worker_cores, worker_memory, gcs_requester_pays_configuration, regions, gcs_bucket_allow_list)
File /opt/conda/lib/python3.10/site-packages/hail/typecheck/check.py:587, in _make_dec.<locals>.wrapper(__original_func, *args, **kwargs)
584 @decorator
585 def wrapper(__original_func: Callable[..., T], *args, **kwargs) -> T:
586 args_, kwargs_ = check_all(__original_func, args, kwargs, checkers, is_method=is_method)
--> 587 return __original_func(*args_, **kwargs_)
File /opt/conda/lib/python3.10/site-packages/hail/context.py:364, in init(sc, app_name, master, local, log, quiet, append, min_block_size, branching_factor, tmp_dir, default_reference, idempotent, global_seed, spark_conf, skip_logging_configuration, local_tmpdir, _optimizer_iterations, backend, driver_cores, driver_memory, worker_cores, worker_memory, gcs_requester_pays_configuration, regions, gcs_bucket_allow_list)
346 return hail_event_loop().run_until_complete(init_batch(