aws-cdk.aws-glue 1.87.1

The CDK Construct Library for AWS::Glue

AWS Glue Construct Library

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All classes with the Cfn prefix in this module (CFN Resources) are always stable and safe to use.

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 This means that while you may use them, you may need to update your source code when upgrading to a newer version of this package.

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

Database

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

# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
glue.Database(stack, "MyDatabase",
    database_name="my_database"
)

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.):

# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
glue.Table(stack, "MyTable",
    database=my_database,
    table_name="my_table",
    columns=[{
        "name": "col1",
        "type": glue.Schema.STRING
    }, {
        "name": "col2",
        "type": glue.Schema.array(Schema.STRING),
        "comment": "col2 is an array of strings"
    }],
    data_format=glue.DataFormat.JSON
)

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

# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
glue.Table(stack, "MyTable",
    bucket=my_bucket,
    s3_prefix="my-table/", ...
)

By default, an S3 bucket will be created to store the table's data and stored in the bucket root. You can also manually pass the bucket and s3Prefix:

Partitions

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:

# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
glue.Table(stack, "MyTable",
    database=my_database,
    table_name="my_table",
    columns=[{
        "name": "col1",
        "type": glue.Schema.STRING
    }],
    partition_keys=[{
        "name": "year",
        "type": glue.Schema.SMALL_INT
    }, {
        "name": "month",
        "type": glue.Schema.SMALL_INT
    }],
    data_format=glue.DataFormat.JSON
)

Encryption

You can enable encryption on a Table's data:

• Unencrypted - files are not encrypted. The default encryption setting.
• S3Managed - Server side encryption (SSE-S3) with an Amazon S3-managed key.

# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
glue.Table(stack, "MyTable",
    encryption=glue.TableEncryption.S3_MANAGED, ...
)

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

# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
# KMS key is created automatically
glue.Table(stack, "MyTable",
    encryption=glue.TableEncryption.KMS, ...
)

# with an explicit KMS key
glue.Table(stack, "MyTable",
    encryption=glue.TableEncryption.KMS,
    encryption_key=kms.Key(stack, "MyKey"), ...
)

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

# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
glue.Table(stack, "MyTable",
    encryption=glue.TableEncryption.KMS_MANAGED, ...
)

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

# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
# KMS key is created automatically
glue.Table(stack, "MyTable",
    encryption=glue.TableEncryption.CLIENT_SIDE_KMS, ...
)

# with an explicit KMS key
glue.Table(stack, "MyTable",
    encryption=glue.TableEncryption.CLIENT_SIDE_KMS,
    encryption_key=kms.Key(stack, "MyKey"), ...
)

Note: you cannot provide a Bucket when creating the Table 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:

# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
glue.Table(stack, "MyTable",
    columns=[{
        "name": "primitive_column",
        "type": glue.Schema.STRING
    }, {
        "name": "array_column",
        "type": glue.Schema.array(glue.Schema.INTEGER),
        "comment": "array<integer>"
    }, {
        "name": "map_column",
        "type": glue.Schema.map(glue.Schema.STRING, glue.Schema.TIMESTAMP),
        "comment": "map<string,string>"
    }, {
        "name": "struct_column",
        "type": glue.Schema.struct([
            name="nested_column",
            type=glue.Schema.DATE,
            comment="nested comment"
        ]),
        "comment": "struct<nested_column:date COMMENT 'nested comment'>"
    }], ...
)

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