Migrate knowledge from Google Cloud Storage to Amazon S3 utilizing AWS Glue

At this time, we’re happy to announce a brand new AWS Glue connector for Google Cloud Storage that lets you transfer knowledge bi-directionally between Google Cloud Storage and Amazon Easy Storage Service (Amazon S3).

We’ve seen that there’s a demand to design purposes that allow knowledge to be transportable throughout cloud environments and provide the capability to derive insights from a number of knowledge sources. One of many knowledge sources now you can shortly combine with is Google Cloud Storage, a managed service for storing each unstructured knowledge and structured knowledge. With this connector, you may carry the info from Google Cloud Storage to Amazon S3.

On this submit, we go over how the brand new connector works, introduce the connector’s features, and give you key steps to set it up. We give you stipulations, share learn how to subscribe to this connector in AWS Market, and describe learn how to create and run AWS Glue for Apache Spark jobs with it.

AWS Glue is a serverless knowledge integration service that makes it easy to find, put together, and mix knowledge for analytics, machine studying, and software improvement. AWS Glue natively integrates with varied knowledge shops akin to MySQL, PostgreSQL, MongoDB, and Apache Kafka, together with AWS knowledge shops akin to Amazon S3, Amazon Redshift, Amazon Relational Database Service (Amazon RDS), Amazon DynamoDB, and Amazon S3. AWS Glue Market connectors mean you can uncover and combine extra knowledge sources, akin to software program as a service (SaaS) purposes and your customized knowledge sources. With only a few clicks, you may search and choose connectors from AWS Market and start your knowledge preparation workflow in minutes.

How the connector works

This connector depends on the Spark DataSource API in AWS Glue and calls Hadoop’s FileSystem interface. The latter has applied libraries for studying and writing varied distributed or conventional storage. This connector additionally consists of the Google Cloud Storage Connector for Hadoop, which helps you to run Apache Hadoop or Apache Spark jobs straight on knowledge in Google Cloud Storage. AWS Glue masses the library from the Amazon Elastic Container Registry (Amazon ECR) repository throughout initialization (as a connector), reads the connection credentials utilizing AWS Secrets and techniques Supervisor, and reads knowledge supply configurations from enter parameters. When AWS Glue has web entry, the Spark job in AWS Glue can learn from and write to Google Cloud Storage.

Answer overview

The next structure diagram exhibits how AWS Glue connects to Google Cloud Storage for knowledge ingestion.

Within the following sections, we present you learn how to create a brand new secret for Google Cloud Storage in Secrets and techniques Supervisor, subscribe to the AWS Glue connector, and transfer knowledge from Google Cloud Storage to Amazon S3.

Stipulations

You want the next stipulations:

• An account in Google Cloud and your knowledge path in Google Cloud Storage. Put together the GCP account keys file prematurely and add them to the S3 bucket. For directions, seek advice from Create a service account key.
• A Secrets and techniques Supervisor secret to retailer a Google Cloud secret.
• An AWS Id and Entry Administration (IAM) position for the AWS Glue job with the next insurance policies:
  • AWSGlueServiceRole, which permits the AWS Glue service position entry to associated providers.
  • AmazonEC2ContainerRegistryReadOnly, which offers read-only entry to Amazon EC2 Container Registry repositories. This coverage is for utilizing AWS Market’s connector libraries.
  • A Secrets and techniques Supervisor coverage, which offers learn entry to the key in Secrets and techniques Supervisor.
  • An S3 bucket coverage for the S3 bucket that it’s essential to load ETL (extract, rework, and cargo) knowledge from Google Cloud Storage.

We assume that you’re already accustomed to the important thing ideas of Secrets and techniques Supervisor, IAM, and AWS Glue. Concerning IAM, these roles must be granted the permissions wanted to speak with AWS providers and nothing extra, in line with the precept of least privilege.

Create a brand new secret for Google Cloud Storage in Secrets and techniques Supervisor

Full the next steps to create a secret in Secrets and techniques Supervisor to retailer the Google Cloud Storage credentials:

1. On the Secrets and techniques Supervisor console, select Retailer a brand new secret.
2. For Secret kind, choose Different kind of secret.
3. Enter your key as keyS3Uri and the worth as your key file within the s3 bucket, for instance, s3://keys/project-gcs-connector **.json.
   
4. Go away the remainder of the choices at their default.
5. Select Subsequent.
6. Present a reputation for the key, akin to googlecloudstorage_credentials.
7. Observe the remainder of the steps to retailer the key.

Subscribe to the AWS Glue connector for Google Cloud Storage

To subscribe to the connector, full the next steps:

1. Navigate to the Google Cloud Storage Connector for AWS Glue on AWS Market.
2. On the product web page for the connector, use the tabs to view details about the connector. When you resolve to buy this connector, select Proceed to Subscribe.
   
3. Evaluate the pricing phrases and the vendor’s Finish Person License Settlement, then select Settle for Phrases.
   
4. Proceed to the following step by selecting Proceed to Configuration.
   
5. On the Configure this software program web page, select the success choices and the model of the connector to make use of. We now have offered two choices for the Google Cloud Storage Connector, AWS Glue 3.0 and AWS Glue 4.0. On this instance, we deal with AWS Glue 4.0. After choosing Glue 3.0 or Glue 4.0, choose corresponding AWS Glue model whenever you configure the AWS Glue job.
6. Select Proceed to Launch.
   
7. On the Launch this software program web page, you may evaluate the Utilization Directions offered by AWS. Once you’re able to proceed, select Activate the Glue connector in AWS Glue Studio.
   

The console will show the Create market connection web page in AWS Glue Studio.

Transfer knowledge from Google Cloud Storage to Amazon S3

To maneuver your knowledge to Amazon S3, it’s essential to configure the customized connection after which arrange an AWS Glue job.

Create a customized connection in AWS Glue

An AWS Glue connection shops connection info for a selected knowledge retailer, together with login credentials, URI strings, digital personal cloud (VPC) info, and extra. Full the next steps to create your connection:

1. On the AWS Glue console, select Connectors within the navigation pane.
2. Select Create connection.
3. For Connector, select Google Cloud Storage Connector for AWS Glue.
4. For Identify, enter a reputation for the connection (for instance, GCSConnection).
5. Enter an optionally available description.
6. For AWS secret, enter the key you created (googlecloudstorage_credentials).
7. Select Create connection and activate connector.
   

The connector and connection info is now seen on the Connectors web page.

Create an AWS Glue job and configure connection choices

Full the next steps:

1. On the AWS Glue console, select Connectors within the navigation pane.
2. Select the connection you created (GCSConnection).
3. Select Create job.
   
4. On the Node properties tab within the node particulars pane, enter the next info:
   • For Identify, enter Google Cloud Storage Connector for AWS Glue. This title must be distinctive amongst all of the nodes for this job.
   • For Node kind, select the Google Cloud Storage Connector.
     
5. On the Information supply properties tab, present the next info:
   • For Connection, select the connection you created (GCSConnection).
   • For Key, enter path, and for Worth, enter your Google Cloud Storage URI (for instance, gs://bucket/covid-csv-data/).
   • Enter one other key-value pair. For Key, enter fileFormat. For Worth, enter csv, as a result of our pattern knowledge is that this format.
     
6. On the Job particulars tab, for IAM Function, select the IAM position talked about within the stipulations.
7. For Glue model, select your AWS Glue model.
8. Proceed to create your ETL job. For directions, seek advice from Creating ETL jobs with AWS Glue Studio.
9. Select Run to run your job.
   

After the job succeeds, we will examine the logs in Amazon CloudWatch.

The info is ingested into Amazon S3, as proven within the following screenshot.                        

We at the moment are in a position to import knowledge from Google Cloud Storage to Amazon S3.

Scaling issues

On this instance, we set the AWS Glue capability as 10 DPU (Information Processing Models). A DPU is a relative measure of processing energy that consists of 4 vCPUs of compute capability and 16 GB of reminiscence. To scale your AWS Glue job, you may improve the variety of DPU, and in addition benefit from Auto Scaling. With Auto Scaling enabled, AWS Glue routinely provides and removes employees from the cluster relying on the workload. This removes the necessity so that you can experiment and resolve on the variety of employees to assign on your AWS Glue ETL jobs. When you select the utmost variety of employees, AWS Glue will adapt the proper measurement of sources for the workload.

Clear up

To wash up your sources, full the next steps:

1. Take away the AWS Glue job and secret in Secrets and techniques Supervisor with the next command:

   aws glue delete-job —job-name <your_job_name> aws glue delete-connection —connection-name <your_connection_name>
   aws secretsmanager delete-secret —secret-id <your_secretsmanager_id> 

2. Cancel the Google Cloud Storage Connector for AWS Glue’s subscription:
   • On the AWS Market console, go to the Handle subscriptions web page.
   • Choose the subscription for the product that you just need to cancel.
   • On the Actions menu, select Cancel subscription.
   • Learn the data offered and choose the acknowledgement examine field.
   • Select Sure, cancel subscription.
3. Delete the info within the S3 buckets.

Conclusion

On this submit, we confirmed learn how to use AWS Glue and the brand new connector for ingesting knowledge from Google Cloud Storage to Amazon S3. This connector offers entry to Google Cloud Storage, facilitating cloud ETL processes for operational reporting, backup and catastrophe restoration, knowledge governance, and extra.

This connector permits your knowledge to be transportable throughout Google Cloud Storage and Amazon S3. We welcome any suggestions or questions within the feedback part.

References

In regards to the authors

Qiushuang Feng is a Options Architect at AWS, accountable for Enterprise prospects’ technical structure design, consulting, and design optimization on AWS Cloud providers. Earlier than becoming a member of AWS, Qiushuang labored in IT corporations akin to IBM and Oracle, and gathered wealthy sensible expertise in improvement and analytics.

Noritaka Sekiyama is a Principal Large Information Architect on the AWS Glue crew. He’s enthusiastic about architecting fast-growing knowledge environments, diving deep into distributed huge knowledge software program like Apache Spark, constructing reusable software program artifacts for knowledge lakes, and sharing data in AWS Large Information weblog posts.

 Greg Huang is a Senior Options Architect at AWS with experience in technical structure design and consulting for the China G1000 crew. He’s devoted to deploying and using enterprise-level purposes on AWS Cloud providers. He possesses almost 20 years of wealthy expertise in large-scale enterprise software improvement and implementation, having labored within the cloud computing discipline for a few years. He has in depth expertise in serving to varied varieties of enterprises migrate to the cloud. Previous to becoming a member of AWS, he labored for well-known IT enterprises akin to Baidu and Oracle.

Maciej Torbus is a Principal Buyer Options Supervisor inside Strategic Accounts at Amazon Internet Companies. With in depth expertise in large-scale migrations, he focuses on serving to prospects transfer their purposes and methods to extremely dependable and scalable architectures in AWS. Exterior of labor, he enjoys crusing, touring, and restoring classic mechanical watches.