Package software.amazon.awscdk.services.glue.alpha

@Stability(Experimental) package software.amazon.awscdk.services.glue.alpha

AWS Glue Construct Library

---

The APIs of higher level constructs in this module are experimental and under active development. They are subject to non-backward compatible changes or removal in any future version. These are not subject to the Semantic Versioning model and breaking changes will be announced in the release notes. This means that while you may use them, you may need to update your source code when upgrading to a newer version of this package.

This module is part of the AWS Cloud Development Kit project.

Job

A Job encapsulates a script that connects to data sources, processes them, and then writes output to a data target.

There are 3 types of jobs supported by AWS Glue: Spark ETL, Spark Streaming, and Python Shell jobs.

The glue.JobExecutable allows you to specify the type of job, the language to use and the code assets required by the job.

glue.Code allows you to refer to the different code assets required by the job, either from an existing S3 location or from a local file path.

glue.ExecutionClass allows you to specify FLEX or STANDARD. FLEX is appropriate for non-urgent jobs such as pre-production jobs, testing, and one-time data loads.

Spark Jobs

These jobs run in an Apache Spark environment managed by AWS Glue.

ETL Jobs

An ETL job processes data in batches using Apache Spark.

 Bucket bucket;
 
 Job.Builder.create(this, "ScalaSparkEtlJob")
         .executable(JobExecutable.scalaEtl(ScalaJobExecutableProps.builder()
                 .glueVersion(GlueVersion.V4_0)
                 .script(Code.fromBucket(bucket, "src/com/example/HelloWorld.scala"))
                 .className("com.example.HelloWorld")
                 .extraJars(List.of(Code.fromBucket(bucket, "jars/HelloWorld.jar")))
                 .build()))
         .workerType(WorkerType.G_8X)
         .description("an example Scala ETL job")
         .build();
 

Streaming Jobs

A Streaming job is similar to an ETL job, except that it performs ETL on data streams. It uses the Apache Spark Structured Streaming framework. Some Spark job features are not available to streaming ETL jobs.

 Job.Builder.create(this, "PythonSparkStreamingJob")
         .executable(JobExecutable.pythonStreaming(PythonSparkJobExecutableProps.builder()
                 .glueVersion(GlueVersion.V4_0)
                 .pythonVersion(PythonVersion.THREE)
                 .script(Code.fromAsset(join(__dirname, "job-script", "hello_world.py")))
                 .build()))
         .description("an example Python Streaming job")
         .build();
 

Python Shell Jobs

A Python shell job runs Python scripts as a shell and supports a Python version that depends on the AWS Glue version you are using. This can be used to schedule and run tasks that don't require an Apache Spark environment. Currently, three flavors are supported:

• PythonVersion.TWO (2.7; EOL)
• PythonVersion.THREE (3.6)
• PythonVersion.THREE_NINE (3.9)

 Bucket bucket;
 
 Job.Builder.create(this, "PythonShellJob")
         .executable(JobExecutable.pythonShell(PythonShellExecutableProps.builder()
                 .glueVersion(GlueVersion.V1_0)
                 .pythonVersion(PythonVersion.THREE)
                 .script(Code.fromBucket(bucket, "script.py"))
                 .build()))
         .description("an example Python Shell job")
         .build();
 

Ray Jobs

These jobs run in a Ray environment managed by AWS Glue.

 Job.Builder.create(this, "RayJob")
         .executable(JobExecutable.pythonRay(PythonRayExecutableProps.builder()
                 .glueVersion(GlueVersion.V4_0)
                 .pythonVersion(PythonVersion.THREE_NINE)
                 .runtime(Runtime.RAY_TWO_FOUR)
                 .script(Code.fromAsset(join(__dirname, "job-script", "hello_world.py")))
                 .build()))
         .workerType(WorkerType.Z_2X)
         .workerCount(2)
         .description("an example Ray job")
         .build();
 

Enable Spark UI

Enable Spark UI setting the sparkUI property.

 Job.Builder.create(this, "EnableSparkUI")
         .jobName("EtlJobWithSparkUIPrefix")
         .sparkUI(SparkUIProps.builder()
                 .enabled(true)
                 .build())
         .executable(JobExecutable.pythonEtl(PythonSparkJobExecutableProps.builder()
                 .glueVersion(GlueVersion.V3_0)
                 .pythonVersion(PythonVersion.THREE)
                 .script(Code.fromAsset(join(__dirname, "job-script", "hello_world.py")))
                 .build()))
         .build();
 

The sparkUI property also allows the specification of an s3 bucket and a bucket prefix.

See documentation for more information on adding jobs in Glue.

Enable Job Run Queuing

AWS Glue job queuing monitors your account level quotas and limits. If quotas or limits are insufficient to start a Glue job run, AWS Glue will automatically queue the job and wait for limits to free up. Once limits become available, AWS Glue will retry the job run. Glue jobs will queue for limits like max concurrent job runs per account, max concurrent Data Processing Units (DPU), and resource unavailable due to IP address exhaustion in Amazon Virtual Private Cloud (Amazon VPC).

Enable job run queuing by setting the jobRunQueuingEnabled property to true.

 Job.Builder.create(this, "EnableRunQueuing")
         .jobName("EtlJobWithRunQueuing")
         .executable(JobExecutable.pythonEtl(PythonSparkJobExecutableProps.builder()
                 .glueVersion(GlueVersion.V4_0)
                 .pythonVersion(PythonVersion.THREE)
                 .script(Code.fromAsset(join(__dirname, "job-script", "hello_world.py")))
                 .build()))
         .jobRunQueuingEnabled(true)
         .build();
 

Connection

A Connection allows Glue jobs, crawlers and development endpoints to access certain types of data stores. For example, to create a network connection to connect to a data source within a VPC:

 SecurityGroup securityGroup;
 Subnet subnet;
 
 Connection.Builder.create(this, "MyConnection")
         .type(ConnectionType.NETWORK)
         // The security groups granting AWS Glue inbound access to the data source within the VPC
         .securityGroups(List.of(securityGroup))
         // The VPC subnet which contains the data source
         .subnet(subnet)
         .build();
 

For RDS Connection by JDBC, it is recommended to manage credentials using AWS Secrets Manager. To use Secret, specify SECRET_ID in properties like the following code. Note that in this case, the subnet must have a route to the AWS Secrets Manager VPC endpoint or to the AWS Secrets Manager endpoint through a NAT gateway.

 SecurityGroup securityGroup;
 Subnet subnet;
 DatabaseCluster db;
 
 Connection.Builder.create(this, "RdsConnection")
         .type(ConnectionType.JDBC)
         .securityGroups(List.of(securityGroup))
         .subnet(subnet)
         .properties(Map.of(
                 "JDBC_CONNECTION_URL", String.format("jdbc:mysql://%s/databasename", db.getClusterEndpoint().getSocketAddress()),
                 "JDBC_ENFORCE_SSL", "false",
                 "SECRET_ID", db.getSecret().getSecretName()))
         .build();
 

If you need to use a connection type that doesn't exist as a static member on ConnectionType, you can instantiate a ConnectionType object, e.g: new glue.ConnectionType('NEW_TYPE').

See Adding a Connection to Your Data Store and Connection Structure documentation for more information on the supported data stores and their configurations.

SecurityConfiguration

A SecurityConfiguration is a set of security properties that can be used by AWS Glue to encrypt data at rest.

 SecurityConfiguration.Builder.create(this, "MySecurityConfiguration")
         .cloudWatchEncryption(CloudWatchEncryption.builder()
                 .mode(CloudWatchEncryptionMode.KMS)
                 .build())
         .jobBookmarksEncryption(JobBookmarksEncryption.builder()
                 .mode(JobBookmarksEncryptionMode.CLIENT_SIDE_KMS)
                 .build())
         .s3Encryption(S3Encryption.builder()
                 .mode(S3EncryptionMode.KMS)
                 .build())
         .build();
 

By default, a shared KMS key is created for use with the encryption configurations that require one. You can also supply your own key for each encryption config, for example, for CloudWatch encryption:

 Key key;
 
 SecurityConfiguration.Builder.create(this, "MySecurityConfiguration")
         .cloudWatchEncryption(CloudWatchEncryption.builder()
                 .mode(CloudWatchEncryptionMode.KMS)
                 .kmsKey(key)
                 .build())
         .build();
 

See documentation for more info for Glue encrypting data written by Crawlers, Jobs, and Development Endpoints.

Database

A Database is a logical grouping of Tables in the Glue Catalog.

 Database.Builder.create(this, "MyDatabase")
         .databaseName("my_database")
         .description("my_database_description")
         .build();
 

Table

A Glue table describes a table of data in S3: its structure (column names and types), location of data (S3 objects with a common prefix in a S3 bucket), and format for the files (Json, Avro, Parquet, etc.):

 Database myDatabase;
 
 S3Table.Builder.create(this, "MyTable")
         .database(myDatabase)
         .columns(List.of(Column.builder()
                 .name("col1")
                 .type(Schema.STRING)
                 .build(), Column.builder()
                 .name("col2")
                 .type(Schema.array(Schema.STRING))
                 .comment("col2 is an array of strings")
                 .build()))
         .dataFormat(DataFormat.JSON)
         .build();
 

By default, a S3 bucket will be created to store the table's data but you can manually pass the bucket and s3Prefix:

 Bucket myBucket;
 Database myDatabase;
 
 S3Table.Builder.create(this, "MyTable")
         .bucket(myBucket)
         .s3Prefix("my-table/")
         // ...
         .database(myDatabase)
         .columns(List.of(Column.builder()
                 .name("col1")
                 .type(Schema.STRING)
                 .build()))
         .dataFormat(DataFormat.JSON)
         .build();
 

Glue tables can be configured to contain user-defined properties, to describe the physical storage of table data, through the storageParameters property:

 Database myDatabase;
 
 S3Table.Builder.create(this, "MyTable")
         .storageParameters(List.of(StorageParameter.skipHeaderLineCount(1), StorageParameter.compressionType(CompressionType.GZIP), StorageParameter.custom("separatorChar", ",")))
         // ...
         .database(myDatabase)
         .columns(List.of(Column.builder()
                 .name("col1")
                 .type(Schema.STRING)
                 .build()))
         .dataFormat(DataFormat.JSON)
         .build();
 

Glue tables can also be configured to contain user-defined table properties through the parameters property:

 Database myDatabase;
 
 S3Table.Builder.create(this, "MyTable")
         .parameters(Map.of(
                 "key1", "val1",
                 "key2", "val2"))
         .database(myDatabase)
         .columns(List.of(Column.builder()
                 .name("col1")
                 .type(Schema.STRING)
                 .build()))
         .dataFormat(DataFormat.JSON)
         .build();
 

Partition Keys

To improve query performance, a table can specify partitionKeys on which data is stored and queried separately. For example, you might partition a table by year and month to optimize queries based on a time window:

 Database myDatabase;
 
 S3Table.Builder.create(this, "MyTable")
         .database(myDatabase)
         .columns(List.of(Column.builder()
                 .name("col1")
                 .type(Schema.STRING)
                 .build()))
         .partitionKeys(List.of(Column.builder()
                 .name("year")
                 .type(Schema.SMALL_INT)
                 .build(), Column.builder()
                 .name("month")
                 .type(Schema.SMALL_INT)
                 .build()))
         .dataFormat(DataFormat.JSON)
         .build();
 

Partition Indexes

Another way to improve query performance is to specify partition indexes. If no partition indexes are present on the table, AWS Glue loads all partitions of the table and filters the loaded partitions using the query expression. The query takes more time to run as the number of partitions increase. With an index, the query will try to fetch a subset of the partitions instead of loading all partitions of the table.

The keys of a partition index must be a subset of the partition keys of the table. You can have a maximum of 3 partition indexes per table. To specify a partition index, you can use the partitionIndexes property:

 Database myDatabase;
 
 S3Table.Builder.create(this, "MyTable")
         .database(myDatabase)
         .columns(List.of(Column.builder()
                 .name("col1")
                 .type(Schema.STRING)
                 .build()))
         .partitionKeys(List.of(Column.builder()
                 .name("year")
                 .type(Schema.SMALL_INT)
                 .build(), Column.builder()
                 .name("month")
                 .type(Schema.SMALL_INT)
                 .build()))
         .partitionIndexes(List.of(PartitionIndex.builder()
                 .indexName("my-index") // optional
                 .keyNames(List.of("year"))
                 .build())) // supply up to 3 indexes
         .dataFormat(DataFormat.JSON)
         .build();
 

Alternatively, you can call the addPartitionIndex() function on a table:

 Table myTable;
 
 myTable.addPartitionIndex(PartitionIndex.builder()
         .indexName("my-index")
         .keyNames(List.of("year"))
         .build());
 

Partition Filtering

If you have a table with a large number of partitions that grows over time, consider using AWS Glue partition indexing and filtering.

 Database myDatabase;
 
 S3Table.Builder.create(this, "MyTable")
         .database(myDatabase)
         .columns(List.of(Column.builder()
                 .name("col1")
                 .type(Schema.STRING)
                 .build()))
         .partitionKeys(List.of(Column.builder()
                 .name("year")
                 .type(Schema.SMALL_INT)
                 .build(), Column.builder()
                 .name("month")
                 .type(Schema.SMALL_INT)
                 .build()))
         .dataFormat(DataFormat.JSON)
         .enablePartitionFiltering(true)
         .build();
 

Glue Connections

Glue connections allow external data connections to third party databases and data warehouses. However, these connections can also be assigned to Glue Tables, allowing you to query external data sources using the Glue Data Catalog.

Whereas S3Table will point to (and if needed, create) a bucket to store the tables' data, ExternalTable will point to an existing table in a data source. For example, to create a table in Glue that points to a table in Redshift:

 Connection myConnection;
 Database myDatabase;
 
 ExternalTable.Builder.create(this, "MyTable")
         .connection(myConnection)
         .externalDataLocation("default_db_public_example") // A table in Redshift
         // ...
         .database(myDatabase)
         .columns(List.of(Column.builder()
                 .name("col1")
                 .type(Schema.STRING)
                 .build()))
         .dataFormat(DataFormat.JSON)
         .build();
 

Encryption

You can enable encryption on a Table's data:

• S3Managed - (default) Server side encryption (SSE-S3) with an Amazon S3-managed key.

 Database myDatabase;
 
 S3Table.Builder.create(this, "MyTable")
         .encryption(TableEncryption.S3_MANAGED)
         // ...
         .database(myDatabase)
         .columns(List.of(Column.builder()
                 .name("col1")
                 .type(Schema.STRING)
                 .build()))
         .dataFormat(DataFormat.JSON)
         .build();
 

• Kms - Server-side encryption (SSE-KMS) with an AWS KMS Key managed by the account owner.

 Database myDatabase;
 
 // KMS key is created automatically
 // KMS key is created automatically
 S3Table.Builder.create(this, "MyTable")
         .encryption(TableEncryption.KMS)
         // ...
         .database(myDatabase)
         .columns(List.of(Column.builder()
                 .name("col1")
                 .type(Schema.STRING)
                 .build()))
         .dataFormat(DataFormat.JSON)
         .build();
 
 // with an explicit KMS key
 // with an explicit KMS key
 S3Table.Builder.create(this, "MyTable")
         .encryption(TableEncryption.KMS)
         .encryptionKey(new Key(this, "MyKey"))
         // ...
         .database(myDatabase)
         .columns(List.of(Column.builder()
                 .name("col1")
                 .type(Schema.STRING)
                 .build()))
         .dataFormat(DataFormat.JSON)
         .build();
 

• KmsManaged - Server-side encryption (SSE-KMS), like Kms, except with an AWS KMS Key managed by the AWS Key Management Service.

 Database myDatabase;
 
 S3Table.Builder.create(this, "MyTable")
         .encryption(TableEncryption.KMS_MANAGED)
         // ...
         .database(myDatabase)
         .columns(List.of(Column.builder()
                 .name("col1")
                 .type(Schema.STRING)
                 .build()))
         .dataFormat(DataFormat.JSON)
         .build();
 

• ClientSideKms - Client-side encryption (CSE-KMS) with an AWS KMS Key managed by the account owner.

 Database myDatabase;
 
 // KMS key is created automatically
 // KMS key is created automatically
 S3Table.Builder.create(this, "MyTable")
         .encryption(TableEncryption.CLIENT_SIDE_KMS)
         // ...
         .database(myDatabase)
         .columns(List.of(Column.builder()
                 .name("col1")
                 .type(Schema.STRING)
                 .build()))
         .dataFormat(DataFormat.JSON)
         .build();
 
 // with an explicit KMS key
 // with an explicit KMS key
 S3Table.Builder.create(this, "MyTable")
         .encryption(TableEncryption.CLIENT_SIDE_KMS)
         .encryptionKey(new Key(this, "MyKey"))
         // ...
         .database(myDatabase)
         .columns(List.of(Column.builder()
                 .name("col1")
                 .type(Schema.STRING)
                 .build()))
         .dataFormat(DataFormat.JSON)
         .build();
 

Note: you cannot provide a Bucket when creating the S3Table if you wish to use server-side encryption (KMS, KMS_MANAGED or S3_MANAGED).

Types

A table's schema is a collection of columns, each of which have a name and a type. Types are recursive structures, consisting of primitive and complex types:

 Database myDatabase;
 
 S3Table.Builder.create(this, "MyTable")
         .columns(List.of(Column.builder()
                 .name("primitive_column")
                 .type(Schema.STRING)
                 .build(), Column.builder()
                 .name("array_column")
                 .type(Schema.array(Schema.INTEGER))
                 .comment("array<integer>")
                 .build(), Column.builder()
                 .name("map_column")
                 .type(Schema.map(Schema.STRING, Schema.TIMESTAMP))
                 .comment("map<string,string>")
                 .build(), Column.builder()
                 .name("struct_column")
                 .type(Schema.struct(List.of(Column.builder()
                         .name("nested_column")
                         .type(Schema.DATE)
                         .comment("nested comment")
                         .build())))
                 .comment("struct<nested_column:date COMMENT 'nested comment'>")
                 .build()))
         // ...
         .database(myDatabase)
         .dataFormat(DataFormat.JSON)
         .build();
 

Primitives

Numeric

| Name | Type | Comments | |----------- |---------- |------------------------------------------------------------------------------------------------------------------ | | FLOAT | Constant | A 32-bit single-precision floating point number | | INTEGER | Constant | A 32-bit signed value in two's complement format, with a minimum value of -2^31 and a maximum value of 2^31-1 | | DOUBLE | Constant | A 64-bit double-precision floating point number | | BIG_INT | Constant | A 64-bit signed INTEGER in two’s complement format, with a minimum value of -2^63 and a maximum value of 2^63 -1 | | SMALL_INT | Constant | A 16-bit signed INTEGER in two’s complement format, with a minimum value of -2^15 and a maximum value of 2^15-1 | | TINY_INT | Constant | A 8-bit signed INTEGER in two’s complement format, with a minimum value of -2^7 and a maximum value of 2^7-1 |

Date and time

| Name | Type | Comments | |----------- |---------- |------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | DATE | Constant | A date in UNIX format, such as YYYY-MM-DD. | | TIMESTAMP | Constant | Date and time instant in the UNiX format, such as yyyy-mm-dd hh:mm:ss[.f...]. For example, TIMESTAMP '2008-09-15 03:04:05.324'. This format uses the session time zone. |

String

| Name | Type | Comments | |-------------------------------------------- |---------- |--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | STRING | Constant | A string literal enclosed in single or double quotes | | decimal(precision: number, scale?: number) | Function | precision is the total number of digits. scale (optional) is the number of digits in fractional part with a default of 0. For example, use these type definitions: decimal(11,5), decimal(15) | | char(length: number) | Function | Fixed length character data, with a specified length between 1 and 255, such as char(10) | | varchar(length: number) | Function | Variable length character data, with a specified length between 1 and 65535, such as varchar(10) |

Miscellaneous

| Name | Type | Comments | |--------- |---------- |------------------------------- | | BOOLEAN | Constant | Values are true and false | | BINARY | Constant | Value is in binary |

Complex

| Name | Type | Comments | |------------------------------------- |---------- |------------------------------------------------------------------- | | array(itemType: Type) | Function | An array of some other type | | map(keyType: Type, valueType: Type) | Function | A map of some primitive key type to any value type | | struct(collumns: Column[]) | Function | Nested structure containing individually named and typed collumns |

Data Quality Ruleset

A DataQualityRuleset specifies a data quality ruleset with DQDL rules applied to a specified AWS Glue table. For example, to create a data quality ruleset for a given table:

 DataQualityRuleset.Builder.create(this, "MyDataQualityRuleset")
         .clientToken("client_token")
         .description("description")
         .rulesetName("ruleset_name")
         .rulesetDqdl("ruleset_dqdl")
         .tags(Map.of(
                 "key1", "value1",
                 "key2", "value2"))
         .targetTable(new DataQualityTargetTable("database_name", "table_name"))
         .build();
 

For more information, see AWS Glue Data Quality.

Related Packages

Package	Description
software.amazon.awscdk.services.glue	AWS Glue Construct Library

Class	Description
$Module
AssetCode	(experimental) Job Code from a local file.
ClassificationString	(experimental) Classification string given to tables with this data format.
CloudWatchEncryption	(experimental) CloudWatch Logs encryption configuration.
CloudWatchEncryption.Builder	A builder for CloudWatchEncryption
CloudWatchEncryption.Jsii$Proxy	An implementation for CloudWatchEncryption
CloudWatchEncryptionMode	(experimental) Encryption mode for CloudWatch Logs.
Code	(experimental) Represents a Glue Job's Code assets (an asset can be a scripts, a jar, a python file or any other file).
CodeConfig	(experimental) Result of binding Code into a Job.
CodeConfig.Builder	A builder for CodeConfig
CodeConfig.Jsii$Proxy	An implementation for CodeConfig
Column	(experimental) A column of a table.
Column.Builder	A builder for Column
Column.Jsii$Proxy	An implementation for Column
ColumnCountMismatchHandlingAction	(experimental) Identifies if the file contains less or more values for a row than the number of columns specified in the external table definition.
CompressionType	(experimental) The compression type.
Connection	(experimental) An AWS Glue connection to a data source.
Connection.Builder	(experimental) A fluent builder for Connection.
ConnectionOptions	(experimental) Base Connection Options.
ConnectionOptions.Builder	A builder for ConnectionOptions
ConnectionOptions.Jsii$Proxy	An implementation for ConnectionOptions
ConnectionProps	(experimental) Construction properties for Connection.
ConnectionProps.Builder	A builder for ConnectionProps
ConnectionProps.Jsii$Proxy	An implementation for ConnectionProps
ConnectionType	(experimental) The type of the glue connection.
ContinuousLoggingProps	(experimental) Properties for enabling Continuous Logging for Glue Jobs.
ContinuousLoggingProps.Builder	A builder for ContinuousLoggingProps
ContinuousLoggingProps.Jsii$Proxy	An implementation for ContinuousLoggingProps
Database	(experimental) A Glue database.
Database.Builder	(experimental) A fluent builder for Database.
DatabaseProps	Example:
DatabaseProps.Builder	A builder for DatabaseProps
DatabaseProps.Jsii$Proxy	An implementation for DatabaseProps
DataFormat	(experimental) Defines the input/output formats and ser/de for a single DataFormat.
DataFormat.Builder	(experimental) A fluent builder for DataFormat.
DataFormatProps	(experimental) Properties of a DataFormat instance.
DataFormatProps.Builder	A builder for DataFormatProps
DataFormatProps.Jsii$Proxy	An implementation for DataFormatProps
DataQualityRuleset	(experimental) A Glue Data Quality ruleset.
DataQualityRuleset.Builder	(experimental) A fluent builder for DataQualityRuleset.
DataQualityRulesetProps	(experimental) Construction properties for DataQualityRuleset.
DataQualityRulesetProps.Builder	A builder for DataQualityRulesetProps
DataQualityRulesetProps.Jsii$Proxy	An implementation for DataQualityRulesetProps
DataQualityTargetTable	(experimental) Properties of a DataQualityTargetTable.
ExecutionClass	(experimental) The ExecutionClass whether the job is run with a standard or flexible execution class.
ExternalTable	(experimental) A Glue table that targets an external data location (e.g.
ExternalTable.Builder	(experimental) A fluent builder for ExternalTable.
ExternalTableProps	Example:
ExternalTableProps.Builder	A builder for ExternalTableProps
ExternalTableProps.Jsii$Proxy	An implementation for ExternalTableProps
GlueVersion	(experimental) AWS Glue version determines the versions of Apache Spark and Python that are available to the job.
IConnection	(experimental) Interface representing a created or an imported Connection.
IConnection.Jsii$Default	Internal default implementation for IConnection.
IConnection.Jsii$Proxy	A proxy class which represents a concrete javascript instance of this type.
IDatabase
IDatabase.Jsii$Default	Internal default implementation for IDatabase.
IDatabase.Jsii$Proxy	A proxy class which represents a concrete javascript instance of this type.
IDataQualityRuleset
IDataQualityRuleset.Jsii$Default	Internal default implementation for IDataQualityRuleset.
IDataQualityRuleset.Jsii$Proxy	A proxy class which represents a concrete javascript instance of this type.
IJob	(experimental) Interface representing a created or an imported Job.
IJob.Jsii$Default	Internal default implementation for IJob.
IJob.Jsii$Proxy	A proxy class which represents a concrete javascript instance of this type.
InputFormat	(experimental) Absolute class name of the Hadoop InputFormat to use when reading table files.
InvalidCharHandlingAction	(experimental) Specifies the action to perform when query results contain invalid UTF-8 character values.
ISecurityConfiguration	(experimental) Interface representing a created or an imported SecurityConfiguration.
ISecurityConfiguration.Jsii$Default	Internal default implementation for ISecurityConfiguration.
ISecurityConfiguration.Jsii$Proxy	A proxy class which represents a concrete javascript instance of this type.
ITable
ITable.Jsii$Default	Internal default implementation for ITable.
ITable.Jsii$Proxy	A proxy class which represents a concrete javascript instance of this type.
Job	(experimental) A Glue Job.
Job.Builder	(experimental) A fluent builder for Job.
JobAttributes	(experimental) Attributes for importing Job.
JobAttributes.Builder	A builder for JobAttributes
JobAttributes.Jsii$Proxy	An implementation for JobAttributes
JobBookmarksEncryption	(experimental) Job bookmarks encryption configuration.
JobBookmarksEncryption.Builder	A builder for JobBookmarksEncryption
JobBookmarksEncryption.Jsii$Proxy	An implementation for JobBookmarksEncryption
JobBookmarksEncryptionMode	(experimental) Encryption mode for Job Bookmarks.
JobExecutable	(experimental) The executable properties related to the Glue job's GlueVersion, JobType and code.
JobExecutableConfig	(experimental) Result of binding a JobExecutable into a Job.
JobExecutableConfig.Builder	A builder for JobExecutableConfig
JobExecutableConfig.Jsii$Proxy	An implementation for JobExecutableConfig
JobLanguage	(experimental) Runtime language of the Glue job.
JobProps	(experimental) Construction properties for Job.
JobProps.Builder	A builder for JobProps
JobProps.Jsii$Proxy	An implementation for JobProps
JobState	(experimental) Job states emitted by Glue to CloudWatch Events.
JobType	(experimental) The job type.
MetricType	(experimental) The Glue CloudWatch metric type.
NumericOverflowHandlingAction	(experimental) Specifies the action to perform when ORC data contains an integer (for example, BIGINT or int64) that is larger than the column definition (for example, SMALLINT or int16).
OrcColumnMappingType	(experimental) Specifies how to map columns when the table uses ORC data format.
OutputFormat	(experimental) Absolute class name of the Hadoop OutputFormat to use when writing table files.
PartitionIndex	(experimental) Properties of a Partition Index.
PartitionIndex.Builder	A builder for PartitionIndex
PartitionIndex.Jsii$Proxy	An implementation for PartitionIndex
PythonRayExecutableProps	(experimental) Props for creating a Python Ray job executable.
PythonRayExecutableProps.Builder	A builder for PythonRayExecutableProps
PythonRayExecutableProps.Jsii$Proxy	An implementation for PythonRayExecutableProps
PythonShellExecutableProps	(experimental) Props for creating a Python shell job executable.
PythonShellExecutableProps.Builder	A builder for PythonShellExecutableProps
PythonShellExecutableProps.Jsii$Proxy	An implementation for PythonShellExecutableProps
PythonSparkJobExecutableProps	(experimental) Props for creating a Python Spark (ETL or Streaming) job executable.
PythonSparkJobExecutableProps.Builder	A builder for PythonSparkJobExecutableProps
PythonSparkJobExecutableProps.Jsii$Proxy	An implementation for PythonSparkJobExecutableProps
PythonVersion	(experimental) Python version.
Runtime	(experimental) AWS Glue runtime determines the runtime engine of the job.
S3Code	(experimental) Glue job Code from an S3 bucket.
S3Encryption	(experimental) S3 encryption configuration.
S3Encryption.Builder	A builder for S3Encryption
S3Encryption.Jsii$Proxy	An implementation for S3Encryption
S3EncryptionMode	(experimental) Encryption mode for S3.
S3Table	(experimental) A Glue table that targets a S3 dataset.
S3Table.Builder	(experimental) A fluent builder for S3Table.
S3TableProps	Example:
S3TableProps.Builder	A builder for S3TableProps
S3TableProps.Jsii$Proxy	An implementation for S3TableProps
ScalaJobExecutableProps	(experimental) Props for creating a Scala Spark (ETL or Streaming) job executable.
ScalaJobExecutableProps.Builder	A builder for ScalaJobExecutableProps
ScalaJobExecutableProps.Jsii$Proxy	An implementation for ScalaJobExecutableProps
Schema	Example:
SecurityConfiguration	(experimental) A security configuration is a set of security properties that can be used by AWS Glue to encrypt data at rest.
SecurityConfiguration.Builder	(experimental) A fluent builder for SecurityConfiguration.
SecurityConfigurationProps	(experimental) Constructions properties of SecurityConfiguration.
SecurityConfigurationProps.Builder	A builder for SecurityConfigurationProps
SecurityConfigurationProps.Jsii$Proxy	An implementation for SecurityConfigurationProps
SerializationLibrary	(experimental) Serialization library to use when serializing/deserializing (SerDe) table records.
SparkUILoggingLocation	(experimental) The Spark UI logging location.
SparkUILoggingLocation.Builder	A builder for SparkUILoggingLocation
SparkUILoggingLocation.Jsii$Proxy	An implementation for SparkUILoggingLocation
SparkUIProps	(experimental) Properties for enabling Spark UI monitoring feature for Spark-based Glue jobs.
SparkUIProps.Builder	A builder for SparkUIProps
SparkUIProps.Jsii$Proxy	An implementation for SparkUIProps
StorageParameter	(experimental) A storage parameter.
StorageParameters	(experimental) The storage parameter keys that are currently known, this list is not exhaustive and other keys may be used.
SurplusBytesHandlingAction	(experimental) Specifies how to handle data being loaded that exceeds the length of the data type defined for columns containing VARBYTE data.
SurplusCharHandlingAction	(experimental) Specifies how to handle data being loaded that exceeds the length of the data type defined for columns containing VARCHAR, CHAR, or string data.
Table	Deprecated. Use S3Table instead.
Table.Builder	(experimental) A fluent builder for Table.
TableAttributes	Example:
TableAttributes.Builder	A builder for TableAttributes
TableAttributes.Jsii$Proxy	An implementation for TableAttributes
TableBase	(experimental) A Glue table.
TableBaseProps	Example:
TableBaseProps.Builder	A builder for TableBaseProps
TableBaseProps.Jsii$Proxy	An implementation for TableBaseProps
TableEncryption	(experimental) Encryption options for a Table.
TableProps	Example:
TableProps.Builder	A builder for TableProps
TableProps.Jsii$Proxy	An implementation for TableProps
Type	(experimental) Represents a type of a column in a table schema.
Type.Builder	A builder for Type
Type.Jsii$Proxy	An implementation for Type
WorkerType	(experimental) The type of predefined worker that is allocated when a job runs.
WriteParallel	(experimental) Specifies how to handle data being loaded that exceeds the length of the data type defined for columns containing VARCHAR, CHAR, or string data.