| commit | author | age | ||
| 4783f2 | 1 | --- |
| LL | 2 | # Default variables that are defined by the playbook that will be deploying these roles |
| 3 | become_override: False | |
| 4 | ocp_username: opentlc-mgr | |
| 5 | silent: False | |
| 6 | ||
| 7 | # This workshop requires per user 10-12 CPU and 16GB of Memory | |
| 8 | # For a 50 person workshop, you'll need ~40 OCP worker nodes running on with m4.4xlarge instances | |
| 9 | _infra_node_replicas: 40 | |
| 10 | _infra_node_instance_type: m4.4xlarge | |
| 11 | ||
| 12 | user_name: null | |
| 13 | project_name: null | |
| 14 | ||
| 15 | # The first user number to start with when creating projects | |
| 16 | user_count_start: 1 | |
| 17 | # The last user number to start with when creating projects | |
| 852e52 | 18 | user_count_end: "{{user_count_start|int + num_users|int}}" |
| 4783f2 | 19 | |
| LL | 20 | # Rook Ceph Info |
| 21 | # These variables will be initialized by the role ocp4-workload-rhte-analytics_data_ocp_infra | |
| 22 | # The Rook Ceph RGW service ClusterIP in the rook-ceph namespace | |
| 23 | rgw_service_ip: null | |
| 24 | # The Rook Ceph RGW service port in the rook-ceph namespace | |
| 25 | rgw_service_port: null | |
| 26 | # Full RGW endpoint url that can be used as the S3 endpoint | |
| 27 | rgw_endpoint_url: "http://{{ rgw_service_ip }}:{{ rgw_service_port }}" | |
| 28 | ||
| 29 | # Open Data Hub | |
| 30 | # Deploy the Open Data Hub CustomResource in the user project space, | |
| 31 | # after the project is setup and ODH ClusterServiceVersion has finished | |
| 32 | deploy_odh_cr: false | |
| 33 | # Open Data Hub operator image | |
| 34 | odh_operator_image_repo: "quay.io/opendatahub/opendatahub-operator:v0.4.0" | |
| 35 | # Registry and repistory for AICoE-JupyterHub images | |
| 36 | # EXAMPLE: podman pull {{ jupyterhub_image_registry }}/{{ jupyterhub_image_repository }}:IMAGE:TAG | |
| 37 | jupyterhub_image_registry: 'quay.io' | |
| 38 | jupyterhub_image_repository: 'odh-jupyterhub' | |
| 39 | ||
| 40 | # Custom notebook image source that will be used for the workshop | |
| 41 | workshop_jupyter_notebook_imagestream_image: "quay.io/llasmith/spark-notebook:spark-2.3.2_hadoop-2.8.5" | |
| 42 | # Imagestream name for the custom workshop image | |
| 43 | workshop_jupyter_notebook_imagestream_name: s2i-spark-scipy-notebook | |
| 44 | # Imagestream tag for the custom workshop image | |
| 45 | workshop_jupyter_notebook_imagestream_tag: "3.6" | |
| 46 | ||
| 47 | # Command separated string list each git repo url to preload on the notebook pod when it spawns | |
| 712bd4 | 48 | workshop_preload_repos: "https://gitlab.com/opendatahub/data-engineering-and-machine-learning-workshop.git" |
| 4783f2 | 49 | |
| LL | 50 | # Amount of memory for the JupyterHub server |
| 51 | jupyterhub_memory: "1Gi" | |
| 52 | # Amount of memory for the spawned Jupyter Notebook pods | |
| 53 | jupyter_notebook_memory: "2Gi" | |
| 54 | ||
| 55 | # Image to use for the Spark Cluster | |
| 56 | spark_node_image: "quay.io/llasmith/openshift-spark:spark-2.3.2_hadoop-2.8.5" | |
| 57 | # Number of Spark master nodes | |
| 58 | spark_master_count: 1 | |
| 59 | # Number of Spark worker nodes | |
| 60 | spark_worker_count: 2 | |
| 61 | # Amount of memory to allocate to each Spark node. This amount will be used for master AND worker nodes | |
| 62 | spark_node_memory: "4Gi" | |
| 63 | # Amount of cpu to allocate to each Spark node. This amount will be used for master AND worker nodes | |
| 64 | spark_node_cpu: 1 | |
| 65 | ||
| 66 | # Path to append to env var PYTHONPATH for pyspark module | |
| 67 | spark_pythonpath: "/opt/app-root/lib/python3.6/site-packages/pyspark/python/:/opt/app-root/lib/python3.6/site-packages/pyspark/python/lib/py4j-0.10.7-src.zip" | |
| 68 | # PySpark submit args to be set as the env var SPARK_SUBMIT_ARGS | |
| 69 | spark_submit_args: "--conf spark.cores.max=1 --conf spark.executor.instances=1 --conf spark.executor.memory=4G --conf spark.executor.cores=1 --conf spark.driver.memory=2G --packages com.amazonaws:aws-java-sdk:1.8.0,org.apache.hadoop:hadoop-aws:2.8.5 pyspark-shell" | |
