CLI Configuration

Prerequisite

Setup default values for different options while running OCI Data Sciecne Jobs or OCI DataFlow. By setting defaults, you can avoid inputing compartment ocid, project ocid, etc.

To setup configuration run -

ads opctl configure

This will prompt you to setup default ADS CLI configurations for each OCI profile defined in your OCI config. By default, all the files are generated in the ~/.ads_ops folder.

~/.ads_ops/config.ini will contain OCI profile defaults and conda pack related information. For example:

[OCI]
oci_config = ~/.oci/config
oci_profile = ANOTHERPROF

[CONDA]
conda_pack_folder = </local/path/for/saving/condapack>
conda_pack_os_prefix = oci://my-bucket@mynamespace/conda_environments/

~/.ads_ops/ml_job_config.ini will contain defaults for running Data Science Job. Defaults are set for each profile listed in your oci config file. Here is a sample -

[DEFAULT]
compartment_id = oci.xxxx.<compartment_ocid>
project_id = oci.xxxx.<project_ocid>
subnet_id = oci.xxxx.<subnet-ocid>
log_group_id = oci.xxxx.<log_group_ocid>
log_id = oci.xxxx.<log_ocid>
shape_name = VM.Standard2.2
block_storage_size_in_GBs = 100

[ANOTHERPROF]
compartment_id = oci.xxxx.<compartment_ocid>
project_id = oci.xxxx.<project_ocid>
subnet_id = oci.xxxx.<subnet-ocid>
shape_name = VM.Standard2.1
log_group_id =ocid1.loggroup.oc1.xxx.xxxxx
log_id = oci.xxxx.<log_ocid>
block_storage_size_in_GBs = 50

~/.ads_ops/dataflow_config.ini will contain defaults for running Data Science Job. Defaults are set for each profile listed in your oci config file. Here is a sample -

[MYTENANCYPROF]
compartment_id = oci.xxxx.<compartment_ocid>
driver_shape = VM.Standard2.1
executor_shape = VM.Standard2.1
logs_bucket_uri = oci://mybucket@mytenancy/dataflow/logs
script_bucket = oci://mybucket@mytenancy/dataflow/mycode/
num_executors = 3
spark_version = 3.0.2
archive_bucket = oci://mybucket@mytenancy/dataflow/archive