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/*
* Copyright 2019-2024 Amazon.com, Inc. or its affiliates. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with
* the License. A copy of the License is located at
*
* http://aws.amazon.com/apache2.0
*
* or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
* CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions
* and limitations under the License.
*/
package com.amazonaws.services.neptunedata.model;
import java.io.Serializable;
import javax.annotation.Generated;
import com.amazonaws.AmazonWebServiceRequest;
/**
*
* @see AWS API Documentation
*/
@Generated("com.amazonaws:aws-java-sdk-code-generator")
public class StartMLDataProcessingJobRequest extends com.amazonaws.AmazonWebServiceRequest implements Serializable, Cloneable {
/**
*
* A unique identifier for the new job. The default is an autogenerated UUID.
*
*/
private String id;
/**
*
* The job ID of a completed data processing job run on an earlier version of the data.
*
*/
private String previousDataProcessingJobId;
/**
*
* The URI of the Amazon S3 location where you want SageMaker to download the data needed to run the data processing
* job.
*
*/
private String inputDataS3Location;
/**
*
* The URI of the Amazon S3 location where you want SageMaker to save the results of a data processing job.
*
*/
private String processedDataS3Location;
/**
*
* The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or an
* error will occur.
*
*/
private String sagemakerIamRoleArn;
/**
*
* The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf. This
* must be listed in your DB cluster parameter group or an error will occur.
*
*/
private String neptuneIamRoleArn;
/**
*
* The type of ML instance used during data processing. Its memory should be large enough to hold the processed
* dataset. The default is the smallest ml.r5 type whose memory is ten times larger than the size of the exported
* graph data on disk.
*
*/
private String processingInstanceType;
/**
*
* The disk volume size of the processing instance. Both input data and processed data are stored on disk, so the
* volume size must be large enough to hold both data sets. The default is 0. If not specified or 0, Neptune ML
* chooses the volume size automatically based on the data size.
*
*/
private Integer processingInstanceVolumeSizeInGB;
/**
*
* Timeout in seconds for the data processing job. The default is 86,400 (1 day).
*
*/
private Integer processingTimeOutInSeconds;
/**
*
* One of the two model types that Neptune ML currently supports: heterogeneous graph models (
* heterogeneous), and knowledge graph (kge). The default is none. If not specified,
* Neptune ML chooses the model type automatically based on the data.
*
*/
private String modelType;
/**
*
* A data specification file that describes how to load the exported graph data for training. The file is
* automatically generated by the Neptune export toolkit. The default is
* training-data-configuration.json.
*
*/
private String configFileName;
/**
*
* The IDs of the subnets in the Neptune VPC. The default is None.
*
*/
private java.util.List subnets;
/**
*
* The VPC security group IDs. The default is None.
*
*/
private java.util.List securityGroupIds;
/**
*
* The Amazon Key Management Service (Amazon KMS) key that SageMaker uses to encrypt data on the storage volume
* attached to the ML compute instances that run the training job. The default is None.
*
*/
private String volumeEncryptionKMSKey;
/**
*
* The Amazon Key Management Service (Amazon KMS) key that SageMaker uses to encrypt the output of the processing
* job. The default is none.
*
*/
private String s3OutputEncryptionKMSKey;
/**
*
* A unique identifier for the new job. The default is an autogenerated UUID.
*
*
* @param id
* A unique identifier for the new job. The default is an autogenerated UUID.
*/
public void setId(String id) {
this.id = id;
}
/**
*
* A unique identifier for the new job. The default is an autogenerated UUID.
*
*
* @return A unique identifier for the new job. The default is an autogenerated UUID.
*/
public String getId() {
return this.id;
}
/**
*
* A unique identifier for the new job. The default is an autogenerated UUID.
*
*
* @param id
* A unique identifier for the new job. The default is an autogenerated UUID.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withId(String id) {
setId(id);
return this;
}
/**
*
* The job ID of a completed data processing job run on an earlier version of the data.
*
*
* @param previousDataProcessingJobId
* The job ID of a completed data processing job run on an earlier version of the data.
*/
public void setPreviousDataProcessingJobId(String previousDataProcessingJobId) {
this.previousDataProcessingJobId = previousDataProcessingJobId;
}
/**
*
* The job ID of a completed data processing job run on an earlier version of the data.
*
*
* @return The job ID of a completed data processing job run on an earlier version of the data.
*/
public String getPreviousDataProcessingJobId() {
return this.previousDataProcessingJobId;
}
/**
*
* The job ID of a completed data processing job run on an earlier version of the data.
*
*
* @param previousDataProcessingJobId
* The job ID of a completed data processing job run on an earlier version of the data.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withPreviousDataProcessingJobId(String previousDataProcessingJobId) {
setPreviousDataProcessingJobId(previousDataProcessingJobId);
return this;
}
/**
*
* The URI of the Amazon S3 location where you want SageMaker to download the data needed to run the data processing
* job.
*
*
* @param inputDataS3Location
* The URI of the Amazon S3 location where you want SageMaker to download the data needed to run the data
* processing job.
*/
public void setInputDataS3Location(String inputDataS3Location) {
this.inputDataS3Location = inputDataS3Location;
}
/**
*
* The URI of the Amazon S3 location where you want SageMaker to download the data needed to run the data processing
* job.
*
*
* @return The URI of the Amazon S3 location where you want SageMaker to download the data needed to run the data
* processing job.
*/
public String getInputDataS3Location() {
return this.inputDataS3Location;
}
/**
*
* The URI of the Amazon S3 location where you want SageMaker to download the data needed to run the data processing
* job.
*
*
* @param inputDataS3Location
* The URI of the Amazon S3 location where you want SageMaker to download the data needed to run the data
* processing job.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withInputDataS3Location(String inputDataS3Location) {
setInputDataS3Location(inputDataS3Location);
return this;
}
/**
*
* The URI of the Amazon S3 location where you want SageMaker to save the results of a data processing job.
*
*
* @param processedDataS3Location
* The URI of the Amazon S3 location where you want SageMaker to save the results of a data processing job.
*/
public void setProcessedDataS3Location(String processedDataS3Location) {
this.processedDataS3Location = processedDataS3Location;
}
/**
*
* The URI of the Amazon S3 location where you want SageMaker to save the results of a data processing job.
*
*
* @return The URI of the Amazon S3 location where you want SageMaker to save the results of a data processing job.
*/
public String getProcessedDataS3Location() {
return this.processedDataS3Location;
}
/**
*
* The URI of the Amazon S3 location where you want SageMaker to save the results of a data processing job.
*
*
* @param processedDataS3Location
* The URI of the Amazon S3 location where you want SageMaker to save the results of a data processing job.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withProcessedDataS3Location(String processedDataS3Location) {
setProcessedDataS3Location(processedDataS3Location);
return this;
}
/**
*
* The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or an
* error will occur.
*
*
* @param sagemakerIamRoleArn
* The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or
* an error will occur.
*/
public void setSagemakerIamRoleArn(String sagemakerIamRoleArn) {
this.sagemakerIamRoleArn = sagemakerIamRoleArn;
}
/**
*
* The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or an
* error will occur.
*
*
* @return The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or
* an error will occur.
*/
public String getSagemakerIamRoleArn() {
return this.sagemakerIamRoleArn;
}
/**
*
* The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or an
* error will occur.
*
*
* @param sagemakerIamRoleArn
* The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or
* an error will occur.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withSagemakerIamRoleArn(String sagemakerIamRoleArn) {
setSagemakerIamRoleArn(sagemakerIamRoleArn);
return this;
}
/**
*
* The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf. This
* must be listed in your DB cluster parameter group or an error will occur.
*
*
* @param neptuneIamRoleArn
* The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.
* This must be listed in your DB cluster parameter group or an error will occur.
*/
public void setNeptuneIamRoleArn(String neptuneIamRoleArn) {
this.neptuneIamRoleArn = neptuneIamRoleArn;
}
/**
*
* The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf. This
* must be listed in your DB cluster parameter group or an error will occur.
*
*
* @return The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.
* This must be listed in your DB cluster parameter group or an error will occur.
*/
public String getNeptuneIamRoleArn() {
return this.neptuneIamRoleArn;
}
/**
*
* The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf. This
* must be listed in your DB cluster parameter group or an error will occur.
*
*
* @param neptuneIamRoleArn
* The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.
* This must be listed in your DB cluster parameter group or an error will occur.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withNeptuneIamRoleArn(String neptuneIamRoleArn) {
setNeptuneIamRoleArn(neptuneIamRoleArn);
return this;
}
/**
*
* The type of ML instance used during data processing. Its memory should be large enough to hold the processed
* dataset. The default is the smallest ml.r5 type whose memory is ten times larger than the size of the exported
* graph data on disk.
*
*
* @param processingInstanceType
* The type of ML instance used during data processing. Its memory should be large enough to hold the
* processed dataset. The default is the smallest ml.r5 type whose memory is ten times larger than the size
* of the exported graph data on disk.
*/
public void setProcessingInstanceType(String processingInstanceType) {
this.processingInstanceType = processingInstanceType;
}
/**
*
* The type of ML instance used during data processing. Its memory should be large enough to hold the processed
* dataset. The default is the smallest ml.r5 type whose memory is ten times larger than the size of the exported
* graph data on disk.
*
*
* @return The type of ML instance used during data processing. Its memory should be large enough to hold the
* processed dataset. The default is the smallest ml.r5 type whose memory is ten times larger than the size
* of the exported graph data on disk.
*/
public String getProcessingInstanceType() {
return this.processingInstanceType;
}
/**
*
* The type of ML instance used during data processing. Its memory should be large enough to hold the processed
* dataset. The default is the smallest ml.r5 type whose memory is ten times larger than the size of the exported
* graph data on disk.
*
*
* @param processingInstanceType
* The type of ML instance used during data processing. Its memory should be large enough to hold the
* processed dataset. The default is the smallest ml.r5 type whose memory is ten times larger than the size
* of the exported graph data on disk.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withProcessingInstanceType(String processingInstanceType) {
setProcessingInstanceType(processingInstanceType);
return this;
}
/**
*
* The disk volume size of the processing instance. Both input data and processed data are stored on disk, so the
* volume size must be large enough to hold both data sets. The default is 0. If not specified or 0, Neptune ML
* chooses the volume size automatically based on the data size.
*
*
* @param processingInstanceVolumeSizeInGB
* The disk volume size of the processing instance. Both input data and processed data are stored on disk, so
* the volume size must be large enough to hold both data sets. The default is 0. If not specified or 0,
* Neptune ML chooses the volume size automatically based on the data size.
*/
public void setProcessingInstanceVolumeSizeInGB(Integer processingInstanceVolumeSizeInGB) {
this.processingInstanceVolumeSizeInGB = processingInstanceVolumeSizeInGB;
}
/**
*
* The disk volume size of the processing instance. Both input data and processed data are stored on disk, so the
* volume size must be large enough to hold both data sets. The default is 0. If not specified or 0, Neptune ML
* chooses the volume size automatically based on the data size.
*
*
* @return The disk volume size of the processing instance. Both input data and processed data are stored on disk,
* so the volume size must be large enough to hold both data sets. The default is 0. If not specified or 0,
* Neptune ML chooses the volume size automatically based on the data size.
*/
public Integer getProcessingInstanceVolumeSizeInGB() {
return this.processingInstanceVolumeSizeInGB;
}
/**
*
* The disk volume size of the processing instance. Both input data and processed data are stored on disk, so the
* volume size must be large enough to hold both data sets. The default is 0. If not specified or 0, Neptune ML
* chooses the volume size automatically based on the data size.
*
*
* @param processingInstanceVolumeSizeInGB
* The disk volume size of the processing instance. Both input data and processed data are stored on disk, so
* the volume size must be large enough to hold both data sets. The default is 0. If not specified or 0,
* Neptune ML chooses the volume size automatically based on the data size.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withProcessingInstanceVolumeSizeInGB(Integer processingInstanceVolumeSizeInGB) {
setProcessingInstanceVolumeSizeInGB(processingInstanceVolumeSizeInGB);
return this;
}
/**
*
* Timeout in seconds for the data processing job. The default is 86,400 (1 day).
*
*
* @param processingTimeOutInSeconds
* Timeout in seconds for the data processing job. The default is 86,400 (1 day).
*/
public void setProcessingTimeOutInSeconds(Integer processingTimeOutInSeconds) {
this.processingTimeOutInSeconds = processingTimeOutInSeconds;
}
/**
*
* Timeout in seconds for the data processing job. The default is 86,400 (1 day).
*
*
* @return Timeout in seconds for the data processing job. The default is 86,400 (1 day).
*/
public Integer getProcessingTimeOutInSeconds() {
return this.processingTimeOutInSeconds;
}
/**
*
* Timeout in seconds for the data processing job. The default is 86,400 (1 day).
*
*
* @param processingTimeOutInSeconds
* Timeout in seconds for the data processing job. The default is 86,400 (1 day).
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withProcessingTimeOutInSeconds(Integer processingTimeOutInSeconds) {
setProcessingTimeOutInSeconds(processingTimeOutInSeconds);
return this;
}
/**
*
* One of the two model types that Neptune ML currently supports: heterogeneous graph models (
* heterogeneous), and knowledge graph (kge). The default is none. If not specified,
* Neptune ML chooses the model type automatically based on the data.
*
*
* @param modelType
* One of the two model types that Neptune ML currently supports: heterogeneous graph models (
* heterogeneous), and knowledge graph (kge). The default is none. If not
* specified, Neptune ML chooses the model type automatically based on the data.
*/
public void setModelType(String modelType) {
this.modelType = modelType;
}
/**
*
* One of the two model types that Neptune ML currently supports: heterogeneous graph models (
* heterogeneous), and knowledge graph (kge). The default is none. If not specified,
* Neptune ML chooses the model type automatically based on the data.
*
*
* @return One of the two model types that Neptune ML currently supports: heterogeneous graph models (
* heterogeneous), and knowledge graph (kge). The default is none. If not
* specified, Neptune ML chooses the model type automatically based on the data.
*/
public String getModelType() {
return this.modelType;
}
/**
*
* One of the two model types that Neptune ML currently supports: heterogeneous graph models (
* heterogeneous), and knowledge graph (kge). The default is none. If not specified,
* Neptune ML chooses the model type automatically based on the data.
*
*
* @param modelType
* One of the two model types that Neptune ML currently supports: heterogeneous graph models (
* heterogeneous), and knowledge graph (kge). The default is none. If not
* specified, Neptune ML chooses the model type automatically based on the data.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withModelType(String modelType) {
setModelType(modelType);
return this;
}
/**
*
* A data specification file that describes how to load the exported graph data for training. The file is
* automatically generated by the Neptune export toolkit. The default is
* training-data-configuration.json.
*
*
* @param configFileName
* A data specification file that describes how to load the exported graph data for training. The file is
* automatically generated by the Neptune export toolkit. The default is
* training-data-configuration.json.
*/
public void setConfigFileName(String configFileName) {
this.configFileName = configFileName;
}
/**
*
* A data specification file that describes how to load the exported graph data for training. The file is
* automatically generated by the Neptune export toolkit. The default is
* training-data-configuration.json.
*
*
* @return A data specification file that describes how to load the exported graph data for training. The file is
* automatically generated by the Neptune export toolkit. The default is
* training-data-configuration.json.
*/
public String getConfigFileName() {
return this.configFileName;
}
/**
*
* A data specification file that describes how to load the exported graph data for training. The file is
* automatically generated by the Neptune export toolkit. The default is
* training-data-configuration.json.
*
*
* @param configFileName
* A data specification file that describes how to load the exported graph data for training. The file is
* automatically generated by the Neptune export toolkit. The default is
* training-data-configuration.json.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withConfigFileName(String configFileName) {
setConfigFileName(configFileName);
return this;
}
/**
*
* The IDs of the subnets in the Neptune VPC. The default is None.
*
*
* @return The IDs of the subnets in the Neptune VPC. The default is None.
*/
public java.util.List getSubnets() {
return subnets;
}
/**
*
* The IDs of the subnets in the Neptune VPC. The default is None.
*
*
* @param subnets
* The IDs of the subnets in the Neptune VPC. The default is None.
*/
public void setSubnets(java.util.Collection subnets) {
if (subnets == null) {
this.subnets = null;
return;
}
this.subnets = new java.util.ArrayList(subnets);
}
/**
*
* The IDs of the subnets in the Neptune VPC. The default is None.
*
*
* NOTE: This method appends the values to the existing list (if any). Use
* {@link #setSubnets(java.util.Collection)} or {@link #withSubnets(java.util.Collection)} if you want to override
* the existing values.
*
*
* @param subnets
* The IDs of the subnets in the Neptune VPC. The default is None.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withSubnets(String... subnets) {
if (this.subnets == null) {
setSubnets(new java.util.ArrayList(subnets.length));
}
for (String ele : subnets) {
this.subnets.add(ele);
}
return this;
}
/**
*
* The IDs of the subnets in the Neptune VPC. The default is None.
*
*
* @param subnets
* The IDs of the subnets in the Neptune VPC. The default is None.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withSubnets(java.util.Collection subnets) {
setSubnets(subnets);
return this;
}
/**
*
* The VPC security group IDs. The default is None.
*
*
* @return The VPC security group IDs. The default is None.
*/
public java.util.List getSecurityGroupIds() {
return securityGroupIds;
}
/**
*
* The VPC security group IDs. The default is None.
*
*
* @param securityGroupIds
* The VPC security group IDs. The default is None.
*/
public void setSecurityGroupIds(java.util.Collection securityGroupIds) {
if (securityGroupIds == null) {
this.securityGroupIds = null;
return;
}
this.securityGroupIds = new java.util.ArrayList(securityGroupIds);
}
/**
*
* The VPC security group IDs. The default is None.
*
*
* NOTE: This method appends the values to the existing list (if any). Use
* {@link #setSecurityGroupIds(java.util.Collection)} or {@link #withSecurityGroupIds(java.util.Collection)} if you
* want to override the existing values.
*
*
* @param securityGroupIds
* The VPC security group IDs. The default is None.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withSecurityGroupIds(String... securityGroupIds) {
if (this.securityGroupIds == null) {
setSecurityGroupIds(new java.util.ArrayList(securityGroupIds.length));
}
for (String ele : securityGroupIds) {
this.securityGroupIds.add(ele);
}
return this;
}
/**
*
* The VPC security group IDs. The default is None.
*
*
* @param securityGroupIds
* The VPC security group IDs. The default is None.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withSecurityGroupIds(java.util.Collection securityGroupIds) {
setSecurityGroupIds(securityGroupIds);
return this;
}
/**
*
* The Amazon Key Management Service (Amazon KMS) key that SageMaker uses to encrypt data on the storage volume
* attached to the ML compute instances that run the training job. The default is None.
*
*
* @param volumeEncryptionKMSKey
* The Amazon Key Management Service (Amazon KMS) key that SageMaker uses to encrypt data on the storage
* volume attached to the ML compute instances that run the training job. The default is None.
*/
public void setVolumeEncryptionKMSKey(String volumeEncryptionKMSKey) {
this.volumeEncryptionKMSKey = volumeEncryptionKMSKey;
}
/**
*
* The Amazon Key Management Service (Amazon KMS) key that SageMaker uses to encrypt data on the storage volume
* attached to the ML compute instances that run the training job. The default is None.
*
*
* @return The Amazon Key Management Service (Amazon KMS) key that SageMaker uses to encrypt data on the storage
* volume attached to the ML compute instances that run the training job. The default is None.
*/
public String getVolumeEncryptionKMSKey() {
return this.volumeEncryptionKMSKey;
}
/**
*
* The Amazon Key Management Service (Amazon KMS) key that SageMaker uses to encrypt data on the storage volume
* attached to the ML compute instances that run the training job. The default is None.
*
*
* @param volumeEncryptionKMSKey
* The Amazon Key Management Service (Amazon KMS) key that SageMaker uses to encrypt data on the storage
* volume attached to the ML compute instances that run the training job. The default is None.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withVolumeEncryptionKMSKey(String volumeEncryptionKMSKey) {
setVolumeEncryptionKMSKey(volumeEncryptionKMSKey);
return this;
}
/**
*
* The Amazon Key Management Service (Amazon KMS) key that SageMaker uses to encrypt the output of the processing
* job. The default is none.
*
*
* @param s3OutputEncryptionKMSKey
* The Amazon Key Management Service (Amazon KMS) key that SageMaker uses to encrypt the output of the
* processing job. The default is none.
*/
public void setS3OutputEncryptionKMSKey(String s3OutputEncryptionKMSKey) {
this.s3OutputEncryptionKMSKey = s3OutputEncryptionKMSKey;
}
/**
*
* The Amazon Key Management Service (Amazon KMS) key that SageMaker uses to encrypt the output of the processing
* job. The default is none.
*
*
* @return The Amazon Key Management Service (Amazon KMS) key that SageMaker uses to encrypt the output of the
* processing job. The default is none.
*/
public String getS3OutputEncryptionKMSKey() {
return this.s3OutputEncryptionKMSKey;
}
/**
*
* The Amazon Key Management Service (Amazon KMS) key that SageMaker uses to encrypt the output of the processing
* job. The default is none.
*
*
* @param s3OutputEncryptionKMSKey
* The Amazon Key Management Service (Amazon KMS) key that SageMaker uses to encrypt the output of the
* processing job. The default is none.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public StartMLDataProcessingJobRequest withS3OutputEncryptionKMSKey(String s3OutputEncryptionKMSKey) {
setS3OutputEncryptionKMSKey(s3OutputEncryptionKMSKey);
return this;
}
/**
* Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be
* redacted from this string using a placeholder value.
*
* @return A string representation of this object.
*
* @see java.lang.Object#toString()
*/
@Override
public String toString() {
StringBuilder sb = new StringBuilder();
sb.append("{");
if (getId() != null)
sb.append("Id: ").append(getId()).append(",");
if (getPreviousDataProcessingJobId() != null)
sb.append("PreviousDataProcessingJobId: ").append(getPreviousDataProcessingJobId()).append(",");
if (getInputDataS3Location() != null)
sb.append("InputDataS3Location: ").append(getInputDataS3Location()).append(",");
if (getProcessedDataS3Location() != null)
sb.append("ProcessedDataS3Location: ").append(getProcessedDataS3Location()).append(",");
if (getSagemakerIamRoleArn() != null)
sb.append("SagemakerIamRoleArn: ").append(getSagemakerIamRoleArn()).append(",");
if (getNeptuneIamRoleArn() != null)
sb.append("NeptuneIamRoleArn: ").append(getNeptuneIamRoleArn()).append(",");
if (getProcessingInstanceType() != null)
sb.append("ProcessingInstanceType: ").append(getProcessingInstanceType()).append(",");
if (getProcessingInstanceVolumeSizeInGB() != null)
sb.append("ProcessingInstanceVolumeSizeInGB: ").append(getProcessingInstanceVolumeSizeInGB()).append(",");
if (getProcessingTimeOutInSeconds() != null)
sb.append("ProcessingTimeOutInSeconds: ").append(getProcessingTimeOutInSeconds()).append(",");
if (getModelType() != null)
sb.append("ModelType: ").append(getModelType()).append(",");
if (getConfigFileName() != null)
sb.append("ConfigFileName: ").append(getConfigFileName()).append(",");
if (getSubnets() != null)
sb.append("Subnets: ").append(getSubnets()).append(",");
if (getSecurityGroupIds() != null)
sb.append("SecurityGroupIds: ").append(getSecurityGroupIds()).append(",");
if (getVolumeEncryptionKMSKey() != null)
sb.append("VolumeEncryptionKMSKey: ").append(getVolumeEncryptionKMSKey()).append(",");
if (getS3OutputEncryptionKMSKey() != null)
sb.append("S3OutputEncryptionKMSKey: ").append(getS3OutputEncryptionKMSKey());
sb.append("}");
return sb.toString();
}
@Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (obj instanceof StartMLDataProcessingJobRequest == false)
return false;
StartMLDataProcessingJobRequest other = (StartMLDataProcessingJobRequest) obj;
if (other.getId() == null ^ this.getId() == null)
return false;
if (other.getId() != null && other.getId().equals(this.getId()) == false)
return false;
if (other.getPreviousDataProcessingJobId() == null ^ this.getPreviousDataProcessingJobId() == null)
return false;
if (other.getPreviousDataProcessingJobId() != null && other.getPreviousDataProcessingJobId().equals(this.getPreviousDataProcessingJobId()) == false)
return false;
if (other.getInputDataS3Location() == null ^ this.getInputDataS3Location() == null)
return false;
if (other.getInputDataS3Location() != null && other.getInputDataS3Location().equals(this.getInputDataS3Location()) == false)
return false;
if (other.getProcessedDataS3Location() == null ^ this.getProcessedDataS3Location() == null)
return false;
if (other.getProcessedDataS3Location() != null && other.getProcessedDataS3Location().equals(this.getProcessedDataS3Location()) == false)
return false;
if (other.getSagemakerIamRoleArn() == null ^ this.getSagemakerIamRoleArn() == null)
return false;
if (other.getSagemakerIamRoleArn() != null && other.getSagemakerIamRoleArn().equals(this.getSagemakerIamRoleArn()) == false)
return false;
if (other.getNeptuneIamRoleArn() == null ^ this.getNeptuneIamRoleArn() == null)
return false;
if (other.getNeptuneIamRoleArn() != null && other.getNeptuneIamRoleArn().equals(this.getNeptuneIamRoleArn()) == false)
return false;
if (other.getProcessingInstanceType() == null ^ this.getProcessingInstanceType() == null)
return false;
if (other.getProcessingInstanceType() != null && other.getProcessingInstanceType().equals(this.getProcessingInstanceType()) == false)
return false;
if (other.getProcessingInstanceVolumeSizeInGB() == null ^ this.getProcessingInstanceVolumeSizeInGB() == null)
return false;
if (other.getProcessingInstanceVolumeSizeInGB() != null
&& other.getProcessingInstanceVolumeSizeInGB().equals(this.getProcessingInstanceVolumeSizeInGB()) == false)
return false;
if (other.getProcessingTimeOutInSeconds() == null ^ this.getProcessingTimeOutInSeconds() == null)
return false;
if (other.getProcessingTimeOutInSeconds() != null && other.getProcessingTimeOutInSeconds().equals(this.getProcessingTimeOutInSeconds()) == false)
return false;
if (other.getModelType() == null ^ this.getModelType() == null)
return false;
if (other.getModelType() != null && other.getModelType().equals(this.getModelType()) == false)
return false;
if (other.getConfigFileName() == null ^ this.getConfigFileName() == null)
return false;
if (other.getConfigFileName() != null && other.getConfigFileName().equals(this.getConfigFileName()) == false)
return false;
if (other.getSubnets() == null ^ this.getSubnets() == null)
return false;
if (other.getSubnets() != null && other.getSubnets().equals(this.getSubnets()) == false)
return false;
if (other.getSecurityGroupIds() == null ^ this.getSecurityGroupIds() == null)
return false;
if (other.getSecurityGroupIds() != null && other.getSecurityGroupIds().equals(this.getSecurityGroupIds()) == false)
return false;
if (other.getVolumeEncryptionKMSKey() == null ^ this.getVolumeEncryptionKMSKey() == null)
return false;
if (other.getVolumeEncryptionKMSKey() != null && other.getVolumeEncryptionKMSKey().equals(this.getVolumeEncryptionKMSKey()) == false)
return false;
if (other.getS3OutputEncryptionKMSKey() == null ^ this.getS3OutputEncryptionKMSKey() == null)
return false;
if (other.getS3OutputEncryptionKMSKey() != null && other.getS3OutputEncryptionKMSKey().equals(this.getS3OutputEncryptionKMSKey()) == false)
return false;
return true;
}
@Override
public int hashCode() {
final int prime = 31;
int hashCode = 1;
hashCode = prime * hashCode + ((getId() == null) ? 0 : getId().hashCode());
hashCode = prime * hashCode + ((getPreviousDataProcessingJobId() == null) ? 0 : getPreviousDataProcessingJobId().hashCode());
hashCode = prime * hashCode + ((getInputDataS3Location() == null) ? 0 : getInputDataS3Location().hashCode());
hashCode = prime * hashCode + ((getProcessedDataS3Location() == null) ? 0 : getProcessedDataS3Location().hashCode());
hashCode = prime * hashCode + ((getSagemakerIamRoleArn() == null) ? 0 : getSagemakerIamRoleArn().hashCode());
hashCode = prime * hashCode + ((getNeptuneIamRoleArn() == null) ? 0 : getNeptuneIamRoleArn().hashCode());
hashCode = prime * hashCode + ((getProcessingInstanceType() == null) ? 0 : getProcessingInstanceType().hashCode());
hashCode = prime * hashCode + ((getProcessingInstanceVolumeSizeInGB() == null) ? 0 : getProcessingInstanceVolumeSizeInGB().hashCode());
hashCode = prime * hashCode + ((getProcessingTimeOutInSeconds() == null) ? 0 : getProcessingTimeOutInSeconds().hashCode());
hashCode = prime * hashCode + ((getModelType() == null) ? 0 : getModelType().hashCode());
hashCode = prime * hashCode + ((getConfigFileName() == null) ? 0 : getConfigFileName().hashCode());
hashCode = prime * hashCode + ((getSubnets() == null) ? 0 : getSubnets().hashCode());
hashCode = prime * hashCode + ((getSecurityGroupIds() == null) ? 0 : getSecurityGroupIds().hashCode());
hashCode = prime * hashCode + ((getVolumeEncryptionKMSKey() == null) ? 0 : getVolumeEncryptionKMSKey().hashCode());
hashCode = prime * hashCode + ((getS3OutputEncryptionKMSKey() == null) ? 0 : getS3OutputEncryptionKMSKey().hashCode());
return hashCode;
}
@Override
public StartMLDataProcessingJobRequest clone() {
return (StartMLDataProcessingJobRequest) super.clone();
}
}