AWS CloudFormation for AWS Glue - AWS Glue

AWS CloudFormation for AWS Glue

AWS CloudFormation is a service that can create many AWS resources. AWS Glue provides API operations to create objects in the AWS Glue Data Catalog. However, it might be more convenient to define and create AWS Glue objects and other related AWS resource objects in an AWS CloudFormation template file. Then you can automate the process of creating the objects.

AWS CloudFormation provides a simplified syntax—either JSON (JavaScript Object Notation) or YAML (YAML Ain't Markup Language)—to express the creation of AWS resources. You can use AWS CloudFormation templates to define Data Catalog objects such as databases, tables, partitions, crawlers, classifiers, and connections. You can also define ETL objects such as jobs, triggers, and development endpoints. You create a template that describes all the AWS resources you want, and AWS CloudFormation takes care of provisioning and configuring those resources for you.

For more information, see What Is AWS CloudFormation? and Working with AWS CloudFormation Templates in the AWS CloudFormation User Guide.

If you plan to use AWS CloudFormation templates that are compatible with AWS Glue, as an administrator, you must grant access to AWS CloudFormation and to the AWS services and actions on which it depends. To grant permissions to create AWS CloudFormation resources, attach the following policy to users that work with AWS CloudFormation:

{ "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": [ "cloudformation:*" ], "Resource": "*" } ] }

The following table contains the actions that an AWS CloudFormation template can perform on your behalf. It includes links to information about the AWS resource types and their property types that you can add to an AWS CloudFormation template.

To get started, use the following sample templates and customize them with your own metadata. Then use the AWS CloudFormation console to create an AWS CloudFormation stack to add objects to AWS Glue and any associated services. Many fields in an AWS Glue object are optional. These templates illustrate the fields that are required or are necessary for a working and functional AWS Glue object.

An AWS CloudFormation template can be in either JSON or YAML format. In these examples, YAML is used for easier readability. The examples contain comments (#) to describe the values that are defined in the templates.

AWS CloudFormation templates can include a Parameters section. This section can be changed in the sample text or when the YAML file is submitted to the AWS CloudFormation console to create a stack. The Resources section of the template contains the definition of AWS Glue and related objects. AWS CloudFormation template syntax definitions might contain properties that include more detailed property syntax. Not all properties might be required to create an AWS Glue object. These samples show example values for common properties to create an AWS Glue object.

Sample AWS CloudFormation template for an AWS Glue database

An AWS Glue database in the Data Catalog contains metadata tables. The database consists of very few properties and can be created in the Data Catalog with an AWS CloudFormation template. The following sample template is provided to get you started and to illustrate the use of AWS CloudFormation stacks with AWS Glue. The only resource created by the sample template is a database named cfn-mysampledatabase. You can change it by editing the text of the sample or changing the value on the AWS CloudFormation console when you submit the YAML.

The following shows example values for common properties to create an AWS Glue database. For more information about the AWS CloudFormation database template for AWS Glue, see AWS::Glue::Database.

--- AWSTemplateFormatVersion: '2010-09-09' # Sample CloudFormation template in YAML to demonstrate creating a database named mysampledatabase # The metadata created in the Data Catalog points to the flights public S3 bucket # # Parameters section contains names that are substituted in the Resources section # These parameters are the names the resources created in the Data Catalog Parameters: CFNDatabaseName: Type: String Default: cfn-mysampledatabse # Resources section defines metadata for the Data Catalog Resources: # Create an AWS Glue database CFNDatabaseFlights: Type: AWS::Glue::Database Properties: # The database is created in the Data Catalog for your account CatalogId: !Ref AWS::AccountId DatabaseInput: # The name of the database is defined in the Parameters section above Name: !Ref CFNDatabaseName Description: Database to hold tables for flights data LocationUri: s3://crawler-public-us-east-1/flight/2016/csv/ #Parameters: Leave AWS database parameters blank

Sample AWS CloudFormation template for an AWS Glue database, table, and partition

An AWS Glue table contains the metadata that defines the structure and location of data that you want to process with your ETL scripts. Within a table, you can define partitions to parallelize the processing of your data. A partition is a chunk of data that you defined with a key. For example, using month as a key, all the data for January is contained in the same partition. In AWS Glue, databases can contain tables, and tables can contain partitions.

The following sample shows how to populate a database, a table, and partitions using an AWS CloudFormation template. The base data format is csv and delimited by a comma (,). Because a database must exist before it can contain a table, and a table must exist before partitions can be created, the template uses the DependsOn statement to define the dependency of these objects when they are created.

The values in this sample define a table that contains flight data from a publicly available Amazon S3 bucket. For illustration, only a few columns of the data and one partitioning key are defined. Four partitions are also defined in the Data Catalog. Some fields to describe the storage of the base data are also shown in the StorageDescriptor fields.

--- AWSTemplateFormatVersion: '2010-09-09' # Sample CloudFormation template in YAML to demonstrate creating a database, a table, and partitions # The metadata created in the Data Catalog points to the flights public S3 bucket # # Parameters substituted in the Resources section # These parameters are names of the resources created in the Data Catalog Parameters: CFNDatabaseName: Type: String Default: cfn-database-flights-1 CFNTableName1: Type: String Default: cfn-manual-table-flights-1 # Resources to create metadata in the Data Catalog Resources: ### # Create an AWS Glue database CFNDatabaseFlights: Type: AWS::Glue::Database Properties: CatalogId: !Ref AWS::AccountId DatabaseInput: Name: !Ref CFNDatabaseName Description: Database to hold tables for flights data ### # Create an AWS Glue table CFNTableFlights: # Creating the table waits for the database to be created DependsOn: CFNDatabaseFlights Type: AWS::Glue::Table Properties: CatalogId: !Ref AWS::AccountId DatabaseName: !Ref CFNDatabaseName TableInput: Name: !Ref CFNTableName1 Description: Define the first few columns of the flights table TableType: EXTERNAL_TABLE Parameters: { "classification": "csv" } # ViewExpandedText: String PartitionKeys: # Data is partitioned by month - Name: mon Type: bigint StorageDescriptor: OutputFormat: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat Columns: - Name: year Type: bigint - Name: quarter Type: bigint - Name: month Type: bigint - Name: day_of_month Type: bigint InputFormat: org.apache.hadoop.mapred.TextInputFormat Location: s3://crawler-public-us-east-1/flight/2016/csv/ SerdeInfo: Parameters: field.delim: "," SerializationLibrary: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe # Partition 1 # Create an AWS Glue partition CFNPartitionMon1: DependsOn: CFNTableFlights Type: AWS::Glue::Partition Properties: CatalogId: !Ref AWS::AccountId DatabaseName: !Ref CFNDatabaseName TableName: !Ref CFNTableName1 PartitionInput: Values: - 1 StorageDescriptor: OutputFormat: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat Columns: - Name: mon Type: bigint InputFormat: org.apache.hadoop.mapred.TextInputFormat Location: s3://crawler-public-us-east-1/flight/2016/csv/mon=1/ SerdeInfo: Parameters: field.delim: "," SerializationLibrary: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe # Partition 2 # Create an AWS Glue partition CFNPartitionMon2: DependsOn: CFNTableFlights Type: AWS::Glue::Partition Properties: CatalogId: !Ref AWS::AccountId DatabaseName: !Ref CFNDatabaseName TableName: !Ref CFNTableName1 PartitionInput: Values: - 2 StorageDescriptor: OutputFormat: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat Columns: - Name: mon Type: bigint InputFormat: org.apache.hadoop.mapred.TextInputFormat Location: s3://crawler-public-us-east-1/flight/2016/csv/mon=2/ SerdeInfo: Parameters: field.delim: "," SerializationLibrary: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe # Partition 3 # Create an AWS Glue partition CFNPartitionMon3: DependsOn: CFNTableFlights Type: AWS::Glue::Partition Properties: CatalogId: !Ref AWS::AccountId DatabaseName: !Ref CFNDatabaseName TableName: !Ref CFNTableName1 PartitionInput: Values: - 3 StorageDescriptor: OutputFormat: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat Columns: - Name: mon Type: bigint InputFormat: org.apache.hadoop.mapred.TextInputFormat Location: s3://crawler-public-us-east-1/flight/2016/csv/mon=3/ SerdeInfo: Parameters: field.delim: "," SerializationLibrary: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe # Partition 4 # Create an AWS Glue partition CFNPartitionMon4: DependsOn: CFNTableFlights Type: AWS::Glue::Partition Properties: CatalogId: !Ref AWS::AccountId DatabaseName: !Ref CFNDatabaseName TableName: !Ref CFNTableName1 PartitionInput: Values: - 4 StorageDescriptor: OutputFormat: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat Columns: - Name: mon Type: bigint InputFormat: org.apache.hadoop.mapred.TextInputFormat Location: s3://crawler-public-us-east-1/flight/2016/csv/mon=4/ SerdeInfo: Parameters: field.delim: "," SerializationLibrary: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe

Sample AWS CloudFormation template for an AWS Glue grok classifier

An AWS Glue classifier determines the schema of your data. One type of custom classifier uses a grok pattern to match your data. If the pattern matches, then the custom classifier is used to create your table's schema and set the classification to the value set in the classifier definition.

This sample creates a classifier that creates a schema with one column named message and sets the classification to greedy.

--- AWSTemplateFormatVersion: '2010-09-09' # Sample CFN YAML to demonstrate creating a classifier # # Parameters section contains names that are substituted in the Resources section # These parameters are the names the resources created in the Data Catalog Parameters: # The name of the classifier to be created CFNClassifierName: Type: String Default: cfn-classifier-grok-one-column-1 # # # Resources section defines metadata for the Data Catalog Resources: # Create classifier that uses grok pattern to put all data in one column and classifies it as "greedy". CFNClassifierFlights: Type: AWS::Glue::Classifier Properties: GrokClassifier: #Grok classifier that puts all data in one column Name: !Ref CFNClassifierName Classification: greedy GrokPattern: "%{GREEDYDATA:message}" #CustomPatterns: none

Sample AWS CloudFormation template for an AWS Glue JSON classifier

An AWS Glue classifier determines the schema of your data. One type of custom classifier uses a JsonPath string defining the JSON data for the classifier to classify. AWS Glue supports a subset of the operators for JsonPath, as described in Writing JsonPath Custom Classifiers.

If the pattern matches, then the custom classifier is used to create your table's schema.

This sample creates a classifier that creates a schema with each record in the Records3 array in an object.

--- AWSTemplateFormatVersion: '2010-09-09' # Sample CFN YAML to demonstrate creating a JSON classifier # # Parameters section contains names that are substituted in the Resources section # These parameters are the names the resources created in the Data Catalog Parameters: # The name of the classifier to be created CFNClassifierName: Type: String Default: cfn-classifier-json-one-column-1 # # # Resources section defines metadata for the Data Catalog Resources: # Create classifier that uses a JSON pattern. CFNClassifierFlights: Type: AWS::Glue::Classifier Properties: JSONClassifier: #JSON classifier Name: !Ref CFNClassifierName JsonPath: $.Records3[*]

Sample AWS CloudFormation template for an AWS Glue XML classifier

An AWS Glue classifier determines the schema of your data. One type of custom classifier specifies an XML tag to designate the element that contains each record in an XML document that is being parsed. If the pattern matches, then the custom classifier is used to create your table's schema and set the classification to the value set in the classifier definition.

This sample creates a classifier that creates a schema with each record in the Record tag and sets the classification to XML.

--- AWSTemplateFormatVersion: '2010-09-09' # Sample CFN YAML to demonstrate creating an XML classifier # # Parameters section contains names that are substituted in the Resources section # These parameters are the names the resources created in the Data Catalog Parameters: # The name of the classifier to be created CFNClassifierName: Type: String Default: cfn-classifier-xml-one-column-1 # # # Resources section defines metadata for the Data Catalog Resources: # Create classifier that uses the XML pattern and classifies it as "XML". CFNClassifierFlights: Type: AWS::Glue::Classifier Properties: XMLClassifier: #XML classifier Name: !Ref CFNClassifierName Classification: XML RowTag: <Records>

Sample AWS CloudFormation template for an AWS Glue crawler for Amazon S3

An AWS Glue crawler creates metadata tables in your Data Catalog that correspond to your data. You can then use these table definitions as sources and targets in your ETL jobs.

This sample creates a crawler, the required IAM role, and an AWS Glue database in the Data Catalog. When this crawler is run, it assumes the IAM role and creates a table in the database for the public flights data. The table is created with the prefix "cfn_sample_1_". The IAM role created by this template allows global permissions; you might want to create a custom role. No custom classifiers are defined by this classifier. AWS Glue built-in classifiers are used by default.

When you submit this sample to the AWS CloudFormation console, you must confirm that you want to create the IAM role.

--- AWSTemplateFormatVersion: '2010-09-09' # Sample CFN YAML to demonstrate creating a crawler # # Parameters section contains names that are substituted in the Resources section # These parameters are the names the resources created in the Data Catalog Parameters: # The name of the crawler to be created CFNCrawlerName: Type: String Default: cfn-crawler-flights-1 CFNDatabaseName: Type: String Default: cfn-database-flights-1 CFNTablePrefixName: Type: String Default: cfn_sample_1_ # # # Resources section defines metadata for the Data Catalog Resources: #Create IAM Role assumed by the crawler. For demonstration, this role is given all permissions. CFNRoleFlights: Type: AWS::IAM::Role Properties: AssumeRolePolicyDocument: Version: "2012-10-17" Statement: - Effect: "Allow" Principal: Service: - "glue.amazonaws.com" Action: - "sts:AssumeRole" Path: "/" Policies: - PolicyName: "root" PolicyDocument: Version: "2012-10-17" Statement: - Effect: "Allow" Action: "*" Resource: "*" # Create a database to contain tables created by the crawler CFNDatabaseFlights: Type: AWS::Glue::Database Properties: CatalogId: !Ref AWS::AccountId DatabaseInput: Name: !Ref CFNDatabaseName Description: "AWS Glue container to hold metadata tables for the flights crawler" #Create a crawler to crawl the flights data on a public S3 bucket CFNCrawlerFlights: Type: AWS::Glue::Crawler Properties: Name: !Ref CFNCrawlerName Role: !GetAtt CFNRoleFlights.Arn #Classifiers: none, use the default classifier Description: AWS Glue crawler to crawl flights data #Schedule: none, use default run-on-demand DatabaseName: !Ref CFNDatabaseName Targets: S3Targets: # Public S3 bucket with the flights data - Path: "s3://crawler-public-us-east-1/flight/2016/csv" TablePrefix: !Ref CFNTablePrefixName SchemaChangePolicy: UpdateBehavior: "UPDATE_IN_DATABASE" DeleteBehavior: "LOG" Configuration: "{\"Version\":1.0,\"CrawlerOutput\":{\"Partitions\":{\"AddOrUpdateBehavior\":\"InheritFromTable\"},\"Tables\":{\"AddOrUpdateBehavior\":\"MergeNewColumns\"}}}"

Sample AWS CloudFormation template for an AWS Glue connection

An AWS Glue connection in the Data Catalog contains the JDBC and network information that is required to connect to a JDBC database. This information is used when you connect to a JDBC database to crawl or run ETL jobs.

This sample creates a connection to an Amazon RDS MySQL database named devdb. When this connection is used, an IAM role, database credentials, and network connection values must also be supplied. See the details of necessary fields in the template.

--- AWSTemplateFormatVersion: '2010-09-09' # Sample CFN YAML to demonstrate creating a connection # # Parameters section contains names that are substituted in the Resources section # These parameters are the names the resources created in the Data Catalog Parameters: # The name of the connection to be created CFNConnectionName: Type: String Default: cfn-connection-mysql-flights-1 CFNJDBCString: Type: String Default: "jdbc:mysql://xxx-mysql.yyyyyyyyyyyyyy.us-east-1.rds.amazonaws.com:3306/devdb" CFNJDBCUser: Type: String Default: "master" CFNJDBCPassword: Type: String Default: "12345678" NoEcho: true # # # Resources section defines metadata for the Data Catalog Resources: CFNConnectionMySQL: Type: AWS::Glue::Connection Properties: CatalogId: !Ref AWS::AccountId ConnectionInput: Description: "Connect to MySQL database." ConnectionType: "JDBC" #MatchCriteria: none PhysicalConnectionRequirements: AvailabilityZone: "us-east-1d" SecurityGroupIdList: - "sg-7d52b812" SubnetId: "subnet-84f326ee" ConnectionProperties: { "JDBC_CONNECTION_URL": !Ref CFNJDBCString, "USERNAME": !Ref CFNJDBCUser, "PASSWORD": !Ref CFNJDBCPassword } Name: !Ref CFNConnectionName

Sample AWS CloudFormation template for an AWS Glue crawler for JDBC

An AWS Glue crawler creates metadata tables in your Data Catalog that correspond to your data. You can then use these table definitions as sources and targets in your ETL jobs.

This sample creates a crawler, required IAM role, and an AWS Glue database in the Data Catalog. When this crawler is run, it assumes the IAM role and creates a table in the database for the public flights data that has been stored in a MySQL database. The table is created with the prefix "cfn_jdbc_1_". The IAM role created by this template allows global permissions; you might want to create a custom role. No custom classifiers can be defined for JDBC data. AWS Glue built-in classifiers are used by default.

When you submit this sample to the AWS CloudFormation console, you must confirm that you want to create the IAM role.

--- AWSTemplateFormatVersion: '2010-09-09' # Sample CFN YAML to demonstrate creating a crawler # # Parameters section contains names that are substituted in the Resources section # These parameters are the names the resources created in the Data Catalog Parameters: # The name of the crawler to be created CFNCrawlerName: Type: String Default: cfn-crawler-jdbc-flights-1 # The name of the database to be created to contain tables CFNDatabaseName: Type: String Default: cfn-database-jdbc-flights-1 # The prefix for all tables crawled and created CFNTablePrefixName: Type: String Default: cfn_jdbc_1_ # The name of the existing connection to the MySQL database CFNConnectionName: Type: String Default: cfn-connection-mysql-flights-1 # The name of the JDBC path (database/schema/table) with wildcard (%) to crawl CFNJDBCPath: Type: String Default: saldev/% # # # Resources section defines metadata for the Data Catalog Resources: #Create IAM Role assumed by the crawler. For demonstration, this role is given all permissions. CFNRoleFlights: Type: AWS::IAM::Role Properties: AssumeRolePolicyDocument: Version: "2012-10-17" Statement: - Effect: "Allow" Principal: Service: - "glue.amazonaws.com" Action: - "sts:AssumeRole" Path: "/" Policies: - PolicyName: "root" PolicyDocument: Version: "2012-10-17" Statement: - Effect: "Allow" Action: "*" Resource: "*" # Create a database to contain tables created by the crawler CFNDatabaseFlights: Type: AWS::Glue::Database Properties: CatalogId: !Ref AWS::AccountId DatabaseInput: Name: !Ref CFNDatabaseName Description: "AWS Glue container to hold metadata tables for the flights crawler" #Create a crawler to crawl the flights data in MySQL database CFNCrawlerFlights: Type: AWS::Glue::Crawler Properties: Name: !Ref CFNCrawlerName Role: !GetAtt CFNRoleFlights.Arn #Classifiers: none, use the default classifier Description: AWS Glue crawler to crawl flights data #Schedule: none, use default run-on-demand DatabaseName: !Ref CFNDatabaseName Targets: JdbcTargets: # JDBC MySQL database with the flights data - ConnectionName: !Ref CFNConnectionName Path: !Ref CFNJDBCPath #Exclusions: none TablePrefix: !Ref CFNTablePrefixName SchemaChangePolicy: UpdateBehavior: "UPDATE_IN_DATABASE" DeleteBehavior: "LOG" Configuration: "{\"Version\":1.0,\"CrawlerOutput\":{\"Partitions\":{\"AddOrUpdateBehavior\":\"InheritFromTable\"},\"Tables\":{\"AddOrUpdateBehavior\":\"MergeNewColumns\"}}}"

Sample AWS CloudFormation template for an AWS Glue job for Amazon S3 to Amazon S3

An AWS Glue job in the Data Catalog contains the parameter values that are required to run a script in AWS Glue.

This sample creates a job that reads flight data from an Amazon S3 bucket in csv format and writes it to an Amazon S3 Parquet file. The script that is run by this job must already exist. You can generate an ETL script for your environment with the AWS Glue console. When this job is run, an IAM role with the correct permissions must also be supplied.

Common parameter values are shown in the template. For example, AllocatedCapacity (DPUs) defaults to 5.

--- AWSTemplateFormatVersion: '2010-09-09' # Sample CFN YAML to demonstrate creating a job using the public flights S3 table in a public bucket # # Parameters section contains names that are substituted in the Resources section # These parameters are the names the resources created in the Data Catalog Parameters: # The name of the job to be created CFNJobName: Type: String Default: cfn-job-S3-to-S3-2 # The name of the IAM role that the job assumes. It must have access to data, script, temporary directory CFNIAMRoleName: Type: String Default: AWSGlueServiceRoleGA # The S3 path where the script for this job is located CFNScriptLocation: Type: String Default: s3://aws-glue-scripts-123456789012-us-east-1/myid/sal-job-test2 # # # Resources section defines metadata for the Data Catalog Resources: # Create job to run script which accesses flightscsv table and write to S3 file as parquet. # The script already exists and is called by this job CFNJobFlights: Type: AWS::Glue::Job Properties: Role: !Ref CFNIAMRoleName #DefaultArguments: JSON object # If script written in Scala, then set DefaultArguments={'--job-language'; 'scala', '--class': 'your scala class'} #Connections: No connection needed for S3 to S3 job # ConnectionsList #MaxRetries: Double Description: Job created with CloudFormation #LogUri: String Command: Name: glueetl ScriptLocation: !Ref CFNScriptLocation # for access to directories use proper IAM role with permission to buckets and folders that begin with "aws-glue-" # script uses temp directory from job definition if required (temp directory not used S3 to S3) # script defines target for output as s3://aws-glue-target/sal AllocatedCapacity: 5 ExecutionProperty: MaxConcurrentRuns: 1 Name: !Ref CFNJobName

Sample AWS CloudFormation template for an AWS Glue job for JDBC to Amazon S3

An AWS Glue job in the Data Catalog contains the parameter values that are required to run a script in AWS Glue.

This sample creates a job that reads flight data from a MySQL JDBC database as defined by the connection named cfn-connection-mysql-flights-1 and writes it to an Amazon S3 Parquet file. The script that is run by this job must already exist. You can generate an ETL script for your environment with the AWS Glue console. When this job is run, an IAM role with the correct permissions must also be supplied.

Common parameter values are shown in the template. For example, AllocatedCapacity (DPUs) defaults to 5.

--- AWSTemplateFormatVersion: '2010-09-09' # Sample CFN YAML to demonstrate creating a job using a MySQL JDBC DB with the flights data to an S3 file # # Parameters section contains names that are substituted in the Resources section # These parameters are the names the resources created in the Data Catalog Parameters: # The name of the job to be created CFNJobName: Type: String Default: cfn-job-JDBC-to-S3-1 # The name of the IAM role that the job assumes. It must have access to data, script, temporary directory CFNIAMRoleName: Type: String Default: AWSGlueServiceRoleGA # The S3 path where the script for this job is located CFNScriptLocation: Type: String Default: s3://aws-glue-scripts-123456789012-us-east-1/myid/sal-job-dec4a # The name of the connection used for JDBC data source CFNConnectionName: Type: String Default: cfn-connection-mysql-flights-1 # # # Resources section defines metadata for the Data Catalog Resources: # Create job to run script which accesses JDBC flights table via a connection and write to S3 file as parquet. # The script already exists and is called by this job CFNJobFlights: Type: AWS::Glue::Job Properties: Role: !Ref CFNIAMRoleName #DefaultArguments: JSON object # For example, if required by script, set temporary directory as DefaultArguments={'--TempDir'; 's3://aws-glue-temporary-xyc/sal'} Connections: Connections: - !Ref CFNConnectionName #MaxRetries: Double Description: Job created with CloudFormation using existing script #LogUri: String Command: Name: glueetl ScriptLocation: !Ref CFNScriptLocation # for access to directories use proper IAM role with permission to buckets and folders that begin with "aws-glue-" # if required, script defines temp directory as argument TempDir and used in script like redshift_tmp_dir = args["TempDir"] # script defines target for output as s3://aws-glue-target/sal AllocatedCapacity: 5 ExecutionProperty: MaxConcurrentRuns: 1 Name: !Ref CFNJobName

Sample AWS CloudFormation template for an AWS Glue on-demand trigger

An AWS Glue trigger in the Data Catalog contains the parameter values that are required to start a job run when the trigger fires. An on-demand trigger fires when you enable it.

This sample creates an on-demand trigger that starts one job named cfn-job-S3-to-S3-1.

--- AWSTemplateFormatVersion: '2010-09-09' # Sample CFN YAML to demonstrate creating an on-demand trigger # # Parameters section contains names that are substituted in the Resources section # These parameters are the names the resources created in the Data Catalog Parameters: # The existing job to be started by this trigger CFNJobName: Type: String Default: cfn-job-S3-to-S3-1 # The name of the trigger to be created CFNTriggerName: Type: String Default: cfn-trigger-ondemand-flights-1 # # Resources section defines metadata for the Data Catalog # Sample CFN YAML to demonstrate creating an on-demand trigger for a job Resources: # Create trigger to run an existing job (CFNJobName) on an on-demand schedule. CFNTriggerSample: Type: AWS::Glue::Trigger Properties: Name: Ref: CFNTriggerName Description: Trigger created with CloudFormation Type: ON_DEMAND Actions: - JobName: !Ref CFNJobName # Arguments: JSON object #Schedule: #Predicate:

Sample AWS CloudFormation template for an AWS Glue scheduled trigger

An AWS Glue trigger in the Data Catalog contains the parameter values that are required to start a job run when the trigger fires. A scheduled trigger fires when it is enabled and the cron timer pops.

This sample creates a scheduled trigger that starts one job named cfn-job-S3-to-S3-1. The timer is a cron expression to run the job every 10 minutes on weekdays.

--- AWSTemplateFormatVersion: '2010-09-09' # Sample CFN YAML to demonstrate creating a scheduled trigger # # Parameters section contains names that are substituted in the Resources section # These parameters are the names the resources created in the Data Catalog Parameters: # The existing job to be started by this trigger CFNJobName: Type: String Default: cfn-job-S3-to-S3-1 # The name of the trigger to be created CFNTriggerName: Type: String Default: cfn-trigger-scheduled-flights-1 # # Resources section defines metadata for the Data Catalog # Sample CFN YAML to demonstrate creating a scheduled trigger for a job # Resources: # Create trigger to run an existing job (CFNJobName) on a cron schedule. TriggerSample1CFN: Type: AWS::Glue::Trigger Properties: Name: Ref: CFNTriggerName Description: Trigger created with CloudFormation Type: SCHEDULED Actions: - JobName: !Ref CFNJobName # Arguments: JSON object # # Run the trigger every 10 minutes on Monday to Friday Schedule: cron(0/10 * ? * MON-FRI *) #Predicate:

Sample AWS CloudFormation template for an AWS Glue conditional trigger

An AWS Glue trigger in the Data Catalog contains the parameter values that are required to start a job run when the trigger fires. A conditional trigger fires when it is enabled and its conditions are met, such as a job completing successfully.

This sample creates a conditional trigger that starts one job named cfn-job-S3-to-S3-1. This job starts when the job named cfn-job-S3-to-S3-2 completes successfully.

--- AWSTemplateFormatVersion: '2010-09-09' # Sample CFN YAML to demonstrate creating a conditional trigger for a job, which starts when another job completes # # Parameters section contains names that are substituted in the Resources section # These parameters are the names the resources created in the Data Catalog Parameters: # The existing job to be started by this trigger CFNJobName: Type: String Default: cfn-job-S3-to-S3-1 # The existing job that when it finishes causes trigger to fire CFNJobName2: Type: String Default: cfn-job-S3-to-S3-2 # The name of the trigger to be created CFNTriggerName: Type: String Default: cfn-trigger-conditional-1 # Resources: # Create trigger to run an existing job (CFNJobName) when another job completes (CFNJobName2). CFNTriggerSample: Type: AWS::Glue::Trigger Properties: Name: Ref: CFNTriggerName Description: Trigger created with CloudFormation Type: CONDITIONAL Actions: - JobName: !Ref CFNJobName # Arguments: JSON object #Schedule: none Predicate: #Value for Logical is required if more than 1 job listed in Conditions Logical: AND Conditions: - LogicalOperator: EQUALS JobName: !Ref CFNJobName2 State: SUCCEEDED

Sample AWS CloudFormation template for an AWS Glue development endpoint

An AWS Glue machine learning transform is a custom transform to cleanse your data. There is currently one available transform named FindMatches. The FindMatches transform enables you to identify duplicate or matching records in your dataset, even when the records do not have a common unique identifier and no fields match exactly.

This sample creates a machine learning transform. For more information about the parameters that you need to create a machine learning transform, see Record matching with AWS Lake Formation FindMatches.

--- AWSTemplateFormatVersion: '2010-09-09' # Sample CFN YAML to demonstrate creating a machine learning transform # # Resources section defines metadata for the machine learning transform Resources: MyMLTransform: Type: "AWS::Glue::MLTransform" Condition: "isGlueMLGARegion" Properties: Name: !Sub "MyTransform" Description: "The bestest transform ever" Role: !ImportValue MyMLTransformUserRole GlueVersion: "1.0" WorkerType: "Standard" NumberOfWorkers: 5 Timeout: 120 MaxRetries: 1 InputRecordTables: GlueTables: - DatabaseName: !ImportValue MyMLTransformDatabase TableName: !ImportValue MyMLTransformTable TransformParameters: TransformType: "FIND_MATCHES" FindMatchesParameters: PrimaryKeyColumnName: "testcolumn" PrecisionRecallTradeoff: 0.5 AccuracyCostTradeoff: 0.5 EnforceProvidedLabels: True Tags: key1: "value1" key2: "value2" TransformEncryption: TaskRunSecurityConfigurationName: !ImportValue MyMLTransformSecurityConfiguration MLUserDataEncryption: MLUserDataEncryptionMode: "SSE-KMS" KmsKeyId: !ImportValue MyMLTransformEncryptionKey

Sample AWS CloudFormation template for an AWS Glue Data Quality ruleset

An AWS Glue Data Quality ruleset contains rules that can be evaluated on a table within the Data Catalog. Once the ruleset is placed on your targeted table you can go into the Data Catalog and run an evaluation which runs your data against those rules within the ruleset. These rules can vary from evaluating the row count to evaluating referential integrity on your data.

The following sample is a CloudFormation template which creates a ruleset with a variety of rules on the specified target table.

AWSTemplateFormatVersion: '2010-09-09' # Sample CFN YAML to demonstrate creating a DataQualityRuleset # # Parameters section contains names that are substituted in the Resources section # These parameters are the names the resources created in the Data Catalog Parameters: # The name of the ruleset to be created RulesetName: Type: String Default: "CFNRulesetName" RulesetDescription: Type: String Default: "CFN DataQualityRuleset" # Rules that will be associated with this ruleset Rules: Type: String Default: 'Rules = [ RowCount > 100, IsUnique "id", IsComplete "nametype" ]' # Name of database and table within Data Catalog which the ruleset will # be applied too DatabaseName: Type: String Default: "ExampleDatabaseName" TableName: Type: String Default: "ExampleTableName" # Resources section defines metadata for the Data Catalog Resources: # Creates a Data Quality ruleset under specified rules DQRuleset: Type: AWS::Glue::DataQualityRuleset Properties: Name: !Ref RulesetName Description: !Ref RulesetDescription # The String within rules must be formatted in DQDL, a language # used specifically to make rules Ruleset: !Ref Rules # The targeted table must exist within Data Catalog alongside # the correct database TargetTable: DatabaseName: !Ref DatabaseName TableName: !Ref TableName

Sample AWS CloudFormation template for an AWS Glue Data Quality ruleset with EventBridge scheduler

An AWS Glue Data Quality ruleset contains rules that can be evaluated on a table within the Data Catalog. Once the ruleset is placed on your targeted table you can go into the Data Catalog and run an evaluation which runs your data against those rules within the ruleset. Instead of having to manually go into the Data Catalog to evaluate the ruleset, you can also add an EventBridge Scheduler within our CloudFormation template to schedule these ruleset evaluations for you on a timed interval.

The following sample is a CloudFormation template which creates a Data Quality ruleset and a EventBridge Scheduler to evaluate the aforementioned ruleset every five minutes.

AWSTemplateFormatVersion: '2010-09-09' # Sample CFN YAML to demonstrate creating a DataQualityRuleset # # Parameters section contains names that are substituted in the Resources section # These parameters are the names the resources created in the Data Catalog Parameters: # The name of the ruleset to be created RulesetName: Type: String Default: "CFNRulesetName" # Rules that will be associated with this Ruleset Rules: Type: String Default: 'Rules = [ RowCount > 100, IsUnique "id", IsComplete "nametype" ]' # The name of the Schedule to be created ScheduleName: Type: String Default: "ScheduleDQRulsetEvaluation" # This expression determines the rate at which the Schedule will evaluate # your data using the above ruleset ScheduleRate: Type: String Default: "rate(5 minutes)" # The Request that being sent must match the details of the Data Quality Ruleset ScheduleRequest: Type: String Default: ' { "DataSource": { "GlueTable": { "DatabaseName": "ExampleDatabaseName", "TableName": "ExampleTableName" } }, "Role": "role/AWSGlueServiceRoleDefault", "RulesetNames": [ ""CFNRulesetName"" ] } ' # Resources section defines metadata for the Data Catalog Resources: # Creates a Data Quality ruleset under specified rules DQRuleset: Type: AWS::Glue::DataQualityRuleset Properties: Name: !Ref RulesetName Description: "CFN DataQualityRuleset" # The String within rules must be formatted in DQDL, a language # used specifically to make rules Ruleset: !Ref Rules # The targeted table must exist within Data Catalog alongside # the correct database TargetTable: DatabaseName: "ExampleDatabaseName" TableName: "ExampleTableName" # Create a Scheduler to schedule evaluation runs on the above ruleset ScheduleDQEval: Type: AWS::Scheduler::Schedule Properties: Name: !Ref ScheduleName Description: "Schedule DataQualityRuleset Evaluations" FlexibleTimeWindow: Mode: "OFF" ScheduleExpression: !Ref ScheduleRate ScheduleExpressionTimezone: "America/New_York" State: "ENABLED" Target: # The ARN is the API that will be run, since we want to evaluate our ruleset # we want this specific ARN Arn: "arn:aws:scheduler:::aws-sdk:glue:startDataQualityRulesetEvaluationRun" # Your RoleArn must have approval to schedule RoleArn: "arn:aws:iam::123456789012:role/AWSGlueServiceRoleDefault" # This is the Request that is being sent to the Arn Input: ' { "DataSource": { "GlueTable": { "DatabaseName": "sampledb", "TableName": "meteorite" } }, "Role": "role/AWSGlueServiceRoleDefault", "RulesetNames": [ "TestCFN" ] } '

Sample AWS CloudFormation template for an AWS Glue development endpoint

An AWS Glue development endpoint is an environment that you can use to develop and test your AWS Glue scripts.

This sample creates a development endpoint with the minimal network parameter values required to successfully create it. For more information about the parameters that you need to set up a development endpoint, see Setting up networking for development for AWS Glue.

You provide an existing IAM role ARN (Amazon Resource Name) to create the development endpoint. Supply a valid RSA public key and keep the corresponding private key available if you plan to create a notebook server on the development endpoint.

Note

For any notebook server that you create that is associated with a development endpoint, you manage it. Therefore, if you delete the development endpoint, to delete the notebook server, you must delete the AWS CloudFormation stack on the AWS CloudFormation console.

--- AWSTemplateFormatVersion: '2010-09-09' # Sample CFN YAML to demonstrate creating a development endpoint # # Parameters section contains names that are substituted in the Resources section # These parameters are the names the resources created in the Data Catalog Parameters: # The name of the crawler to be created CFNEndpointName: Type: String Default: cfn-devendpoint-1 CFNIAMRoleArn: Type: String Default: arn:aws:iam::123456789012/role/AWSGlueServiceRoleGA # # # Resources section defines metadata for the Data Catalog Resources: CFNDevEndpoint: Type: AWS::Glue::DevEndpoint Properties: EndpointName: !Ref CFNEndpointName #ExtraJarsS3Path: String #ExtraPythonLibsS3Path: String NumberOfNodes: 5 PublicKey: ssh-rsa public.....key myuserid-key RoleArn: !Ref CFNIAMRoleArn SecurityGroupIds: - sg-64986c0b SubnetId: subnet-c67cccac