JobPreparationTask Class
A Job Preparation Task to run before any Tasks of the Job on any given Compute Node.
You can use Job Preparation to prepare a Node to run Tasks for the Job. Activities commonly performed in Job Preparation include: Downloading common resource files used by all the Tasks in the Job. The Job Preparation Task can download these common resource files to the shared location on the Node. (AZ_BATCH_NODE_ROOT_DIRshared), or starting a local service on the Node so that all Tasks of that Job can communicate with it. If the Job Preparation Task fails (that is, exhausts its retry count before exiting with exit code 0), Batch will not run Tasks of this Job on the Node. The Compute Node remains ineligible to run Tasks of this Job until it is reimaged. The Compute Node remains active and can be used for other Jobs. The Job Preparation Task can run multiple times on the same Node. Therefore, you should write the Job Preparation Task to handle re-execution. If the Node is rebooted, the Job Preparation Task is run again on the Compute Node before scheduling any other Task of the Job, if rerunOnNodeRebootAfterSuccess is true or if the Job Preparation Task did not previously complete. If the Node is reimaged, the Job Preparation Task is run again before scheduling any Task of the Job. Batch will retry Tasks when a recovery operation is triggered on a Node. Examples of recovery operations include (but are not limited to) when an unhealthy Node is rebooted or a Compute Node disappeared due to host failure. Retries due to recovery operations are independent of and are not counted against the maxTaskRetryCount. Even if the maxTaskRetryCount is 0, an internal retry due to a recovery operation may occur. Because of this, all Tasks should be idempotent. This means Tasks need to tolerate being interrupted and restarted without causing any corruption or duplicate data. The best practice for long running Tasks is to use some form of checkpointing.
All required parameters must be populated in order to send to Azure.
- Inheritance
-
msrest.serialization.ModelJobPreparationTask
Constructor
JobPreparationTask(*, command_line: str, id: str = None, container_settings=None, resource_files=None, environment_settings=None, constraints=None, wait_for_success: bool = None, user_identity=None, rerun_on_node_reboot_after_success: bool = None, **kwargs)
Parameters
Name | Description |
---|---|
id
Required
|
The ID can contain any combination of alphanumeric characters including hyphens and underscores and cannot contain more than 64 characters. If you do not specify this property, the Batch service assigns a default value of 'jobpreparation'. No other Task in the Job can have the same ID as the Job Preparation Task. If you try to submit a Task with the same id, the Batch service rejects the request with error code TaskIdSameAsJobPreparationTask; if you are calling the REST API directly, the HTTP status code is 409 (Conflict). |
command_line
Required
|
Required. The command line does not run under a shell, and therefore cannot take advantage of shell features such as environment variable expansion. If you want to take advantage of such features, you should invoke the shell in the command line, for example using "cmd /c MyCommand" in Windows or "/bin/sh -c MyCommand" in Linux. If the command line refers to file paths, it should use a relative path (relative to the Task working directory), or use the Batch provided environment variable (https://docs.microsoft.com/en-us/azure/batch/batch-compute-node-environment-variables). |
container_settings
Required
|
The settings for the container under which the Job Preparation Task runs. When this is specified, all directories recursively below the AZ_BATCH_NODE_ROOT_DIR (the root of Azure Batch directories on the node) are mapped into the container, all Task environment variables are mapped into the container, and the Task command line is executed in the container. Files produced in the container outside of AZ_BATCH_NODE_ROOT_DIR might not be reflected to the host disk, meaning that Batch file APIs will not be able to access those files. |
resource_files
Required
|
Files listed under this element are located in the Task's working directory. There is a maximum size for the list of resource files. When the max size is exceeded, the request will fail and the response error code will be RequestEntityTooLarge. If this occurs, the collection of ResourceFiles must be reduced in size. This can be achieved using .zip files, Application Packages, or Docker Containers. |
environment_settings
Required
|
|
constraints
Required
|
Constraints that apply to the Job Preparation Task. |
wait_for_success
Required
|
Whether the Batch service should wait for the Job Preparation Task to complete successfully before scheduling any other Tasks of the Job on the Compute Node. A Job Preparation Task has completed successfully if it exits with exit code 0. If true and the Job Preparation Task fails on a Node, the Batch service retries the Job Preparation Task up to its maximum retry count (as specified in the constraints element). If the Task has still not completed successfully after all retries, then the Batch service will not schedule Tasks of the Job to the Node. The Node remains active and eligible to run Tasks of other Jobs. If false, the Batch service will not wait for the Job Preparation Task to complete. In this case, other Tasks of the Job can start executing on the Compute Node while the Job Preparation Task is still running; and even if the Job Preparation Task fails, new Tasks will continue to be scheduled on the Compute Node. The default value is true. |
user_identity
Required
|
The user identity under which the Job Preparation Task runs. If omitted, the Task runs as a non-administrative user unique to the Task on Windows Compute Nodes, or a non-administrative user unique to the Pool on Linux Compute Nodes. |
rerun_on_node_reboot_after_success
Required
|
Whether the Batch service should rerun the Job Preparation Task after a Compute Node reboots. The Job Preparation Task is always rerun if a Compute Node is reimaged, or if the Job Preparation Task did not complete (e.g. because the reboot occurred while the Task was running). Therefore, you should always write a Job Preparation Task to be idempotent and to behave correctly if run multiple times. The default value is true. |
Keyword-Only Parameters
Name | Description |
---|---|
command_line
Required
|
|
id
Required
|
|
container_settings
Required
|
|
resource_files
Required
|
|
environment_settings
Required
|
|
constraints
Required
|
|
wait_for_success
Required
|
|
user_identity
Required
|
|
rerun_on_node_reboot_after_success
Required
|
|
Methods
as_dict |
Return a dict that can be JSONify using json.dump. Advanced usage might optionally use a callback as parameter: Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains 'type' with the msrest type and 'key' with the RestAPI encoded key. Value is the current value in this object. The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict. See the three examples in this file:
If you want XML serialization, you can pass the kwargs is_xml=True. |
deserialize |
Parse a str using the RestAPI syntax and return a model. |
enable_additional_properties_sending | |
from_dict |
Parse a dict using given key extractor return a model. By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor) |
is_xml_model | |
serialize |
Return the JSON that would be sent to azure from this model. This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False). If you want XML serialization, you can pass the kwargs is_xml=True. |
validate |
Validate this model recursively and return a list of ValidationError. |
as_dict
Return a dict that can be JSONify using json.dump.
Advanced usage might optionally use a callback as parameter:
Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains 'type' with the msrest type and 'key' with the RestAPI encoded key. Value is the current value in this object.
The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.
See the three examples in this file:
attribute_transformer
full_restapi_key_transformer
last_restapi_key_transformer
If you want XML serialization, you can pass the kwargs is_xml=True.
as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)
Parameters
Name | Description |
---|---|
key_transformer
|
<xref:function>
A key transformer function. |
keep_readonly
|
Default value: True
|
Returns
Type | Description |
---|---|
A dict JSON compatible object |
deserialize
Parse a str using the RestAPI syntax and return a model.
deserialize(data, content_type=None)
Parameters
Name | Description |
---|---|
data
Required
|
A str using RestAPI structure. JSON by default. |
content_type
|
JSON by default, set application/xml if XML. Default value: None
|
Returns
Type | Description |
---|---|
An instance of this model |
Exceptions
Type | Description |
---|---|
DeserializationError if something went wrong
|
enable_additional_properties_sending
enable_additional_properties_sending()
from_dict
Parse a dict using given key extractor return a model.
By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
from_dict(data, key_extractors=None, content_type=None)
Parameters
Name | Description |
---|---|
data
Required
|
A dict using RestAPI structure |
content_type
|
JSON by default, set application/xml if XML. Default value: None
|
key_extractors
|
Default value: None
|
Returns
Type | Description |
---|---|
An instance of this model |
Exceptions
Type | Description |
---|---|
DeserializationError if something went wrong
|
is_xml_model
is_xml_model()
serialize
Return the JSON that would be sent to azure from this model.
This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).
If you want XML serialization, you can pass the kwargs is_xml=True.
serialize(keep_readonly=False, **kwargs)
Parameters
Name | Description |
---|---|
keep_readonly
|
If you want to serialize the readonly attributes Default value: False
|
Returns
Type | Description |
---|---|
A dict JSON compatible object |
validate
Validate this model recursively and return a list of ValidationError.
validate()
Returns
Type | Description |
---|---|
A list of validation error |
Azure SDK for Python