def setup_node():
client = config.batch_client
create_user.create_user(batch_client=client)
spark.setup_conf()
if os.environ['AZ_BATCH_NODE_IS_DEDICATED'] == "true" or os.environ[
'MIXED_MODE'] == "False":
is_master = pick_master.find_master(client)
else:
is_master = False
wait_until_master_selected.main()
master_node_id = pick_master.get_master_node_id(
config.batch_client.pool.get(config.pool_id))
master_node = config.batch_client.compute_node.get(config.pool_id,
master_node_id)
os.environ["MASTER_IP"] = master_node.ip_address
if is_master:
setup_as_master()
scripts.run_custom_scripts(is_master=True, is_worker=True)
else:
setup_as_worker()
scripts.run_custom_scripts(is_master=False, is_worker=True)
open("/tmp/setup_complete", 'a').close()
def setup_node():
client = config.batch_client
spark.setup_conf()
is_master = pick_master.find_master(client)
if is_master:
setup_as_master()
scripts.run_custom_scripts(is_master=True)
else:
setup_as_worker()
scripts.run_custom_scripts(is_master=False)
def setup_host(docker_repo: str, docker_run_options: str):
"""
Code to be run on the node (NOT in a container)
:param docker_repo: location of the Docker image to use
:param docker_run_options: additional command-line options to pass to docker run
"""
client = config.batch_client
create_user.create_user(batch_client=client)
if os.environ["AZ_BATCH_NODE_IS_DEDICATED"] == "true" or os.environ[
"AZTK_MIXED_MODE"] == "false":
is_master = pick_master.find_master(client)
else:
is_master = False
wait_until_master_selected.main()
is_worker = not is_master or os.environ.get(
"AZTK_WORKER_ON_MASTER") == "true"
master_node_id = pick_master.get_master_node_id(
config.batch_client.pool.get(config.pool_id))
master_node = config.batch_client.compute_node.get(config.pool_id,
master_node_id)
if is_master:
os.environ["AZTK_IS_MASTER"] = "true"
else:
os.environ["AZTK_IS_MASTER"] = "false"
if is_worker:
os.environ["AZTK_IS_WORKER"] = "true"
else:
os.environ["AZTK_IS_WORKER"] = "false"
os.environ["AZTK_MASTER_IP"] = master_node.ip_address
cluster_conf = read_cluster_config()
# setup_node_scheduling(client, cluster_conf, is_master)
# TODO pass azure file shares
spark_container.start_spark_container(
docker_repo=docker_repo,
docker_run_options=docker_run_options,
gpu_enabled=os.environ.get("AZTK_GPU_ENABLED") == "true",
plugins=cluster_conf.plugins,
)
plugins.setup_plugins(target=PluginTarget.Host,
is_master=is_master,
is_worker=is_worker)
def setup_node():
client = config.batch_client
spark.setup_conf()
is_master = pick_master.find_master(client)
master_node_id = pick_master.get_master_node_id(
config.batch_client.pool.get(config.pool_id))
master_node = config.batch_client.compute_node.get(config.pool_id,
master_node_id)
os.environ["MASTER_IP"] = master_node.ip_address
if is_master:
setup_as_master()
scripts.run_custom_scripts(is_master=True, is_worker=True)
else:
setup_as_worker()
scripts.run_custom_scripts(is_master=False, is_worker=True)