CfnDevEndpointProps Struct
Properties for defining a CfnDevEndpoint.
Example
// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import { aws_glue as glue } from 'aws-cdk-lib';
declare const arguments_: any;
declare const tags: any;
const cfnDevEndpointProps: glue.CfnDevEndpointProps = {
roleArn: 'roleArn',
// the properties below are optional
arguments: arguments_,
endpointName: 'endpointName',
extraJarsS3Path: 'extraJarsS3Path',
extraPythonLibsS3Path: 'extraPythonLibsS3Path',
glueVersion: 'glueVersion',
numberOfNodes: 123,
numberOfWorkers: 123,
publicKey: 'publicKey',
publicKeys: ['publicKeys'],
securityConfiguration: 'securityConfiguration',
securityGroupIds: ['securityGroupIds'],
subnetId: 'subnetId',
tags: tags,
workerType: 'workerType',
};
Properties
notes
Valid arguments are:
"--enable-glue-datacatalog": """GLUE_PYTHON_VERSION": "3""GLUE_PYTHON_VERSION": "2"
You can specify a version of Python support for development endpoints by using the Arguments parameter in the CreateDevEndpoint or UpdateDevEndpoint APIs. If no arguments are provided, the version defaults to Python 2.
extraJarsS3Pathstringextra_jars_s3_pathstrextraJarsS3PathStringExtraJarsS3PathstringExtraJarsS3Path*string#You can only use pure Java/Scala libraries with a
DevEndpoint.
extraPythonLibsS3Pathstringextra_python_libs_s3_pathstrextraPythonLibsS3PathStringExtraPythonLibsS3PathstringExtraPythonLibsS3Path*string#notes
Multiple values must be complete paths separated by a comma.
You can only use pure Python libraries with a
DevEndpoint. Libraries that rely on C extensions, such as the pandas Python data analysis library, are not currently supported.
notes
The Python version indicates the version supported for running your ETL scripts on development endpoints.
For more information about the available AWS Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Development endpoints that are created without specifying a Glue version default to Glue 0.9.
You can specify a version of Python support for development endpoints by using the Arguments parameter in the CreateDevEndpoint or UpdateDevEndpoint APIs. If no arguments are provided, the version defaults to Python 2.
numberOfNodesnumbernumber_of_nodesint | floatnumberOfNodesNumberNumberOfNodesdoubleNumberOfNodes*float64#numberOfWorkersnumbernumber_of_workersint | floatnumberOfWorkersNumberNumberOfWorkersdoubleNumberOfWorkers*float64#The maximum number of workers you can define are 299 for G.1X , and 149 for G.2X .
This attribute is provided for backward compatibility because the recommended attribute to use is public keys.
publicKeysstring[]public_keystyping.List[str]publicKeysList<String>PublicKeysstring[]PublicKeys*[]*string#notes
Using this attribute is preferred over a single public key because the public keys allow you to have a different private key per client.
If you previously created an endpoint with a public key, you must remove that key to be able to set a list of public keys. Call the
UpdateDevEndpointAPI operation with the public key content in thedeletePublicKeysattribute, and the list of new keys in theaddPublicKeysattribute.
securityConfigurationstringsecurity_configurationstrsecurityConfigurationStringSecurityConfigurationstringSecurityConfiguration*string#securityGroupIdsstring[]security_group_idstyping.List[str]securityGroupIdsList<String>SecurityGroupIdsstring[]SecurityGroupIds*[]*string#notes
Accepts a value of Standard, G.1X, or G.2X.
- For the
Standardworker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker. - For the
G.1Xworker 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.2Xworker 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.
Known issue: when a development endpoint is created with the G.2X WorkerType configuration, the Spark drivers for the development endpoint will run on 4 vCPU, 16 GB of memory, and a 64 GB disk.