def execute(args: typing.NamedTuple):
spark_client = aztk.spark.Client(config.load_aztk_secrets())
if args.tail:
utils.stream_logs(client=spark_client,
cluster_id=args.cluster_id,
application_name=args.app_name)
else:
app_logs = spark_client.get_application_log(
cluster_id=args.cluster_id, application_name=args.app_name)
print(app_logs.log)
def execute(args: typing.NamedTuple):
spark_client = aztk.spark.Client(config.load_aztk_secrets())
if args.tail:
utils.stream_logs(client=spark_client, cluster_id=args.cluster_id, application_name=args.app_name)
else:
app_log = spark_client.cluster.get_application_log(id=args.cluster_id, application_name=args.app_name)
if args.output:
with utils.Spinner():
with open(os.path.abspath(os.path.expanduser(args.output)), "w", encoding="UTF-8") as f:
f.write(app_log.log)
else:
log.print(app_log.log)
def execute(args: typing.NamedTuple):
if not args.wait and args.output:
raise aztk.error.AztkError("--output flag requires --wait flag")
spark_client = aztk.spark.Client(config.load_aztk_secrets())
jars = []
py_files = []
files = []
if args.jars is not None:
jars = args.jars.replace(" ", "").split(",")
if args.py_files is not None:
py_files = args.py_files.replace(" ", "").split(",")
if args.files is not None:
files = args.files.replace(" ", "").split(",")
log_application(args, jars, py_files, files)
spark_client.cluster.submit(
id=args.cluster_id,
application=aztk.spark.models.ApplicationConfiguration(
name=args.name,
application=args.app,
application_args=args.app_args,
main_class=args.main_class,
jars=jars,
py_files=py_files,
files=files,
driver_java_options=args.driver_java_options,
driver_library_path=args.driver_library_path,
driver_class_path=args.driver_class_path,
driver_memory=args.driver_memory,
executor_memory=args.executor_memory,
driver_cores=args.driver_cores,
executor_cores=args.executor_cores,
max_retry_count=args.max_retry_count,
),
remote=args.remote,
internal=args.internal,
wait=False,
)
if args.wait:
if not args.output:
exit_code = utils.stream_logs(client=spark_client, cluster_id=args.cluster_id, application_name=args.name)
else:
with utils.Spinner():
spark_client.cluster.wait(id=args.cluster_id, application_name=args.name)
application_log = spark_client.cluster.get_application_log(
id=args.cluster_id, application_name=args.name)
with open(os.path.abspath(os.path.expanduser(args.output)), "w", encoding="UTF-8") as f:
f.write(application_log.log)
exit_code = application_log.exit_code
sys.exit(exit_code)
def execute(args: typing.NamedTuple):
if not args.wait and args.output:
raise aztk.error.AztkError("--output flag requires --wait flag")
spark_client = aztk.spark.Client(config.load_aztk_secrets())
jars = []
py_files = []
files = []
if args.jars is not None:
jars = args.jars.replace(' ', '').split(',')
if args.py_files is not None:
py_files = args.py_files.replace(' ', '').split(',')
if args.files is not None:
files = args.files.replace(' ', '').split(',')
log.info("-------------------------------------------")
log.info("Spark cluster id: %s", args.cluster_id)
log.info("Spark app name: %s", args.name)
log.info("Wait for app completion: %s", args.wait)
if args.main_class is not None:
log.info("Entry point class: %s", args.main_class)
if jars:
log.info("JARS: %s", jars)
if py_files:
log.info("PY_Files: %s", py_files)
if files:
log.info("Files: %s", files)
if args.driver_java_options is not None:
log.info("Driver java options: %s", args.driver_java_options)
if args.driver_library_path is not None:
log.info("Driver library path: %s", args.driver_library_path)
if args.driver_class_path is not None:
log.info("Driver class path: %s", args.driver_class_path)
if args.driver_memory is not None:
log.info("Driver memory: %s", args.driver_memory)
if args.executor_memory is not None:
log.info("Executor memory: %s", args.executor_memory)
if args.driver_cores is not None:
log.info("Driver cores: %s", args.driver_cores)
if args.executor_cores is not None:
log.info("Executor cores: %s", args.executor_cores)
log.info("Application: %s", args.app)
log.info("Application arguments: %s", args.app_args)
log.info("-------------------------------------------")
spark_client.submit(cluster_id=args.cluster_id,
application=aztk.spark.models.ApplicationConfiguration(
name=args.name,
application=args.app,
application_args=args.app_args,
main_class=args.main_class,
jars=jars,
py_files=py_files,
files=files,
driver_java_options=args.driver_java_options,
driver_library_path=args.driver_library_path,
driver_class_path=args.driver_class_path,
driver_memory=args.driver_memory,
executor_memory=args.executor_memory,
driver_cores=args.driver_cores,
executor_cores=args.executor_cores,
max_retry_count=args.max_retry_count),
remote=args.remote,
wait=False)
if args.wait:
if not args.output:
exit_code = utils.stream_logs(client=spark_client,
cluster_id=args.cluster_id,
application_name=args.name)
else:
with utils.Spinner():
spark_client.wait_until_application_done(
cluster_id=args.cluster_id, task_id=args.name)
application_log = spark_client.get_application_log(
cluster_id=args.cluster_id, application_name=args.name)
with open(os.path.abspath(os.path.expanduser(args.output)),
"w",
encoding="UTF-8") as f:
f.write(application_log.log)
exit_code = application_log.exit_code
sys.exit(exit_code)