I was running the JointDiscovery pipeline as a part of the GATK Best Practices pipeline. I am running this on many vcf files (~150) called by the HaplotypeCaller. I am getting this error:

23:32:16.900 INFO  ProgressMeter - Traversal complete. Processed 19816687 total variants in 613.7 minutes.
23:32:17.434 INFO  VariantDataManager - QD:      mean = 22.14    standard deviation = 6.21
23:32:18.366 INFO  VariantDataManager - MQRankSum:   mean = -0.01    standard deviation = 0.25
23:32:19.385 INFO  VariantDataManager - ReadPosRankSum:      mean = 0.08     standard deviation = 0.47
23:32:20.172 INFO  VariantDataManager - FS:      mean = 1.38     standard deviation = 3.42
23:32:20.947 INFO  VariantDataManager - MQ:      mean = 59.89    standard deviation = 2.23
23:32:21.711 INFO  VariantDataManager - SOR:     mean = 0.70     standard deviation = 0.22
23:32:22.473 INFO  VariantDataManager - DP:      mean = 6835.64  standard deviation = 3532.38
01:01:24.432 INFO  VariantDataManager - Annotations are now ordered by their information content: [DP, MQ, QD, SOR, MQRankSum, FS, ReadPosRankSum]
01:02:53.662 INFO  VariantDataManager - Training with 6999956 variants after standard deviation thresholding.
01:02:53.662 WARN  VariantDataManager - WARNING: Very large training set detected. Downsampling to 2500000 training variants.
01:05:04.968 INFO  VariantRecalibrator - Shutting down engine
[September 18, 2019 1:05:04 AM EDT] org.broadinstitute.hellbender.tools.walkers.vqsr.VariantRecalibrator done. Elapsed time: 706.54 minutes.
Runtime.totalMemory()=3208118272
Exception in thread "main" java.lang.OutOfMemoryError: Java heap space
    at org.broadinstitute.hellbender.tools.walkers.vqsr.MultivariateGaussian.<init>(MultivariateGaussian.java:31)
    at org.broadinstitute.hellbender.tools.walkers.vqsr.GaussianMixtureModel.<init>(GaussianMixtureModel.java:34)
    at org.broadinstitute.hellbender.tools.walkers.vqsr.VariantRecalibratorEngine.generateModel(VariantRecalibratorEngine.java:43)
    at org.broadinstitute.hellbender.tools.walkers.vqsr.VariantRecalibrator.onTraversalSuccess(VariantRecalibrator.java:625)
    at org.broadinstitute.hellbender.engine.GATKTool.doWork(GATKTool.java:895)
    at org.broadinstitute.hellbender.cmdline.CommandLineProgram.runTool(CommandLineProgram.java:134)
    at org.broadinstitute.hellbender.cmdline.CommandLineProgram.instanceMainPostParseArgs(CommandLineProgram.java:179)
    at org.broadinstitute.hellbender.cmdline.CommandLineProgram.instanceMain(CommandLineProgram.java:198)
    at org.broadinstitute.hellbender.Main.runCommandLineProgram(Main.java:160)
    at org.broadinstitute.hellbender.Main.mainEntry(Main.java:203)
    at org.broadinstitute.hellbender.Main.main(Main.java:289)

I believe this is derived from an error earlier in the log, since the stderr gives the same Java heap space error:

[2019-09-16 19:05:59,50] [error] WorkflowManagerActor Workflow 9f7a01a4-0632-4817-8622-aa51e520abf1 failed (during ExecutingWorkflowState): Job JointGenotyping.SNPsVariantRecalibratorClassic:NA:1 exited with return code 1 which has not been declared as a valid return code. See 'continueOnReturnCode' runtime attribute for more details.
Check the content of stderr for potential additional information: /path/to/stderr.

I have read past issues (https://gatkforums.broadinstitute.org/gatk/discussion/23880/java-heap-space) regarding this that may suggest it is a bug. It has pointed me to increasing the available heap memory through the primary command of -Xmx. Is this the way to do it? java -Xmx600G -Dconfig.file=' + re.sub('input.json', 'overrides.conf', input_json) + ' -jar ' + args.cromwell_path + ' run ' + re.sub('input.json', 'joint-discovery-gatk4.wdl', input_json) + ' -i ' + input_json

where I substitute in the corresponding config, json, and wdl files. Is 600G enough? Each vcf is around 6G large and since I have 150, does that mean I should be allocating more than 900G (6G x 150)?

By the way, I would post this to the GATK forums but it's taking too long to get a verified account.