Struct aws_sdk_glue::model::JobUpdate

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#[non_exhaustive]
pub struct JobUpdate { /* private fields */ }

Expand description

Specifies information used to update an existing job definition. The previous job definition is completely overwritten by this information.

Implementations§

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impl JobUpdate

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pub fn description(&self) -> Option<&str>

Description of the job being defined.

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pub fn log_uri(&self) -> Option<&str>

This field is reserved for future use.

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pub fn role(&self) -> Option<&str>

The name or Amazon Resource Name (ARN) of the IAM role associated with this job (required).

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pub fn execution_property(&self) -> Option<&ExecutionProperty>

An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.

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pub fn command(&self) -> Option<&JobCommand>

The JobCommand that runs this job (required).

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pub fn default_arguments(&self) -> Option<&HashMap<String, String>>

The default arguments for this job.

You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.

For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.

For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.

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pub fn non_overridable_arguments(&self) -> Option<&HashMap<String, String>>

Non-overridable arguments for this job, specified as name-value pairs.

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pub fn connections(&self) -> Option<&ConnectionsList>

The connections used for this job.

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pub fn max_retries(&self) -> i32

The maximum number of times to retry this job if it fails.

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pub fn allocated_capacity(&self) -> i32

👎Deprecated: This property is deprecated, use MaxCapacity instead.

This field is deprecated. Use MaxCapacity instead.

The number of Glue data processing units (DPUs) to allocate to this job. You can allocate a minimum of 2 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.

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pub fn timeout(&self) -> Option<i32>

The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).

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pub fn max_capacity(&self) -> Option<f64>

For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.

Do not set Max Capacity if using WorkerType and NumberOfWorkers.

The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job or an Apache Spark ETL job:

When you specify a Python shell job (JobCommand.Name="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.
When you specify an Apache Spark ETL job (JobCommand.Name="glueetl") or Apache Spark streaming ETL job (JobCommand.Name="gluestreaming"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.

For Glue version 2.0 jobs, you cannot instead specify a Maximum capacity. Instead, you should specify a Worker type and the Number of workers.

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pub fn worker_type(&self) -> Option<&WorkerType>

The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.

For the Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.
For the G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.

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pub fn number_of_workers(&self) -> Option<i32>

The number of workers of a defined workerType that are allocated when a job runs.

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pub fn security_configuration(&self) -> Option<&str>

The name of the SecurityConfiguration structure to be used with this job.

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pub fn notification_property(&self) -> Option<&NotificationProperty>

Specifies the configuration properties of a job notification.

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pub fn glue_version(&self) -> Option<&str>

Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.

For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.

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pub fn code_gen_configuration_nodes(
&self
) -> Option<&HashMap<String, CodeGenConfigurationNode>>

The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.

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pub fn execution_class(&self) -> Option<&ExecutionClass>

Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.

The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.

Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX. The flexible execution class is available for Spark jobs.

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