The Frontline Support team will be slow to respond December 17-18 due to an institute-wide retreat and offline December 22- January 1, while the institute is closed. Thank you for your patience during these next few weeks. Happy Holidays!
Jar caching and enabling it
When running GATK4 Spark jobs, we see in the standard output a message about caching the jar file.
Using GATK jar /Applications/genomicstools/gatk/gatk-4.latest/gatk-package-4.beta.2-spark.jar jar caching is disabled because GATK_GCS_STAGING is not set please set GATK_GCS_STAGING to a bucket you have write access too in order to enable jar caching add the following line to you .bashrc or equivalent startup script export GATK_GCS_STAGING=gs://<my_bucket>/
Instead of uploading the local jar each time you run a command, it is possible to cache the jar in a run to a cloud bucket. To enable this, you will have to export, i.e. add to your bashrc,
GATK_GCS_STAGING=gs://your_bucket_name/some_folder_name/. Gatk-launch will check if the jar you are invoking matches the jar in this folder and, if they match, will copy this jar from google storage to the google cluster instead of your local system. Here is an example export command.
Uploads to Google cloud buckets are free though. So this feature is advantageous for situations in which you have limited or slow network connections. And we know uploads are generally much slower than downloads.
Remember to include the forward slash at the end of the bucket path and use a dedicated directory, e.g. gatk4. Because each GATK4 release’s jar will have a different identifying hash, as you upgrade to each latest release, different versioned jars will start to accumulate and otherwise litter your bucket.