JobRun - AWS Glue

JobRun

Contains information about a job run.

Contents

AllocatedCapacity

This field is deprecated. Use MaxCapacity instead.

The number of AWS Glue data processing units (DPUs) allocated to this JobRun. From 2 to 100 DPUs can be allocated; 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 AWS Glue pricing page.

Type: Integer

Required: No

Arguments

The job arguments associated with this run. For this job run, they replace the default arguments set in the job definition itself.

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

Job arguments may be logged. Do not pass plaintext secrets as arguments. Retrieve secrets from a AWS Glue Connection, AWS Secrets Manager or other secret management mechanism if you intend to keep them within the Job.

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

For information about the arguments you can provide to this field when configuring Spark jobs, see the Special Parameters Used by AWS Glue topic in the developer guide.

For information about the arguments you can provide to this field when configuring Ray jobs, see Using job parameters in Ray jobs in the developer guide.

Type: String to string map

Required: No

Attempt

The number of the attempt to run this job.

Type: Integer

Required: No

CompletedOn

The date and time that this job run completed.

Type: Timestamp

Required: No

DPUSeconds

This field populates only for Auto Scaling job runs, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for G.1X, 2 for G.2X, or 0.25 for G.025X workers). This value may be different than the executionEngineRuntime * MaxCapacity as in the case of Auto Scaling jobs, as the number of executors running at a given time may be less than the MaxCapacity. Therefore, it is possible that the value of DPUSeconds is less than executionEngineRuntime * MaxCapacity.

Type: Double

Required: No

ErrorMessage

An error message associated with this job run.

Type: String

Required: No

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 AWS 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.

Type: String

Length Constraints: Maximum length of 16.

Valid Values: FLEX | STANDARD

Required: No

ExecutionTime

The amount of time (in seconds) that the job run consumed resources.

Type: Integer

Required: No

GlueVersion

In Spark jobs, GlueVersion determines the versions of Apache Spark and Python that AWS Glue available in a job. The Python version indicates the version supported for jobs of type Spark.

Ray jobs should set GlueVersion to 4.0 or greater. However, the versions of Ray, Python and additional libraries available in your Ray job are determined by the Runtime parameter of the Job command.

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

Jobs that are created without specifying a Glue version default to Glue 0.9.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 255.

Pattern: ^\w+\.\w+$

Required: No

Id

The ID of this job run.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 255.

Pattern: [\u0020-\uD7FF\uE000-\uFFFD\uD800\uDC00-\uDBFF\uDFFF\t]*

Required: No

JobName

The name of the job definition being used in this run.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 255.

Pattern: [\u0020-\uD7FF\uE000-\uFFFD\uD800\uDC00-\uDBFF\uDFFF\t]*

Required: No

JobRunState

The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see AWS Glue Job Run Statuses.

Type: String

Valid Values: STARTING | RUNNING | STOPPING | STOPPED | SUCCEEDED | FAILED | TIMEOUT | ERROR | WAITING

Required: No

LastModifiedOn

The last time that this job run was modified.

Type: Timestamp

Required: No

LogGroupName

The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using AWS KMS. This name can be /aws-glue/jobs/, in which case the default encryption is NONE. If you add a role name and SecurityConfiguration name (in other words, /aws-glue/jobs-yourRoleName-yourSecurityConfigurationName/), then that security configuration is used to encrypt the log group.

Type: String

Required: No

MaxCapacity

For Glue version 1.0 or earlier jobs, using the standard worker type, the number of AWS 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 AWS Glue pricing page.

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

Do not set MaxCapacity if using WorkerType and NumberOfWorkers.

The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job, an Apache Spark ETL job, or an Apache Spark streaming 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 from 2 to 100 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.

Type: Double

Required: No

NotificationProperty

Specifies configuration properties of a job run notification.

Type: NotificationProperty object

Required: No

NumberOfWorkers

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

Type: Integer

Required: No

PredecessorRuns

A list of predecessors to this job run.

Type: Array of Predecessor objects

Required: No

PreviousRunId

The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 255.

Pattern: [\u0020-\uD7FF\uE000-\uFFFD\uD800\uDC00-\uDBFF\uDFFF\t]*

Required: No

SecurityConfiguration

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

Type: String

Length Constraints: Minimum length of 1. Maximum length of 255.

Pattern: [\u0020-\uD7FF\uE000-\uFFFD\uD800\uDC00-\uDBFF\uDFFF\t]*

Required: No

StartedOn

The date and time at which this job run was started.

Type: Timestamp

Required: No

Timeout

The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.

Streaming jobs do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).

Type: Integer

Valid Range: Minimum value of 1.

Required: No

TriggerName

The name of the trigger that started this job run.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 255.

Pattern: [\u0020-\uD7FF\uE000-\uFFFD\uD800\uDC00-\uDBFF\uDFFF\t]*

Required: No

WorkerType

The type of predefined worker that is allocated when a job runs. Accepts a value of G.1X, G.2X, G.4X, G.8X or G.025X for Spark jobs. Accepts the value Z.2X for Ray jobs.

  • For the G.1X worker type, each worker maps to 1 DPU (4 vCPUs, 16 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.

  • For the G.2X worker type, each worker maps to 2 DPU (8 vCPUs, 32 GB of memory) with 128GB disk (approximately 77GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.

  • For the G.4X worker type, each worker maps to 4 DPU (16 vCPUs, 64 GB of memory) with 256GB disk (approximately 235GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for AWS Glue version 3.0 or later Spark ETL jobs in the following AWS Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), and Europe (Stockholm).

  • For the G.8X worker type, each worker maps to 8 DPU (32 vCPUs, 128 GB of memory) with 512GB disk (approximately 487GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for AWS Glue version 3.0 or later Spark ETL jobs, in the same AWS Regions as supported for the G.4X worker type.

  • For the G.025X worker type, each worker maps to 0.25 DPU (2 vCPUs, 4 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for AWS Glue version 3.0 streaming jobs.

  • For the Z.2X worker type, each worker maps to 2 M-DPU (8vCPUs, 64 GB of memory) with 128 GB disk (approximately 120GB free), and provides up to 8 Ray workers based on the autoscaler.

Type: String

Valid Values: Standard | G.1X | G.2X | G.025X | G.4X | G.8X | Z.2X

Required: No

See Also

For more information about using this API in one of the language-specific AWS SDKs, see the following: