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To customize compression encoding for specific columns when creating a table, the connector provides a way to set the
encoding column metadata field. Please refer to the available encodings in the Amazon Redshift documentation.
Redshift allows descriptions to be attached to columns, which can be viewed in most query tools. You can specify a description for individual columns by setting the description column metadata field. This can be done using the COMMENT command.

IV) Datatype Mapping

V) Source Design

Flink connector redshift will offer 2 modes to read from the source:-

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1. Configuration:
   
   

   Source Connector Options

   Option	Required	Default	Type	Description
   hostname	required	none	String	Redshift connection hostname
   port	required	5439	Integer	Redshift connection port
   username	required	none	String	Redshift user username
   password	required	none	String	Redshift user password
   database.name	required	dev	String	Redshift database to connect
   table.name	required	none	String	Reshift table name
   source.batch.size	optional	1000	Integer	The max flush size, over this will flush data.
   source.flush.interval	optional	1s	Duration	Over this flush interval mills, asynchronous threads will flush data.
   source.max.retries	optional	3	Integer	The max retry times when writing records to the database failed.
   scan.read.mode	required	false	Boolean	Using Redshift UNLOAD command.
   unload.temp.s3.path	conditional required	none	String	If the unload-mode=true then then Redshift UNLOAD command must need a S3 URI.
   iam-role-arn	conditional required	none	String	If the unload.mode=true then then Redshift UNLOAD command must need a IAM role. And this role must have the privilege and attache to the Redshift cluser

   
   

VI) Sink Design

      Flink connector Redshift will offer 2 modes to write to Redshift:-

1. Directly writing to redshift using JDBC driver.
   
2. Flink stream write to a specified s3 path in the format and schema accepted by Redshift then use COPY command to write data into the redshift table.
   
   Flink connector redshift will provide users with the ability to configure different modes for the connector sink by utilizing the sink.write.mode  option in the source configuration. This configuration flexibility allows users to tailor the behaviour of the connector sink to their specific needs. Internally, the flink-connector-redshift module will intelligently select and integrate with the appropriate connectors based on the chosen write mode. If the user specifies the write mode as "jdbc" in the source configuration, the flink-connector-redshift will use custom redshift JDBC driver. This integration will enable seamless interaction with Redshift using the JDBC protocol, ensuring efficient data transfer from Flink to the Redshift database. Similarly, when the write mode is selected as a file-based operation, the flink-connector-redshift module will utilize the flink-connector-filesystem. This connector will facilitate writing data to an S3 bucket, adhering to the specific format and schema requirements outlined by Redshift's COPY command. By utilizing this connector, the flink-connector-redshift module will ensure that data is written in a manner compatible with Redshift's expectations. To provide a streamlined sink solution for Flink and Redshift integration, the flink-connector-redshift module will orchestrate and use flink-filesystem, behind the scenes. It preprocesses the data and seamlessly wraps these connectors to offer a unified sink interface for transferring data from Flink to Redshift.
   

Sink Connector Options

Update/Delete Data Considerations: The data is updated and deleted by the primary key.

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1. 1. 1. Flink to Redshift: The Flink connects to Redshift via JDBC using a username and password.
         Redshift does not support the use of IAM roles to authenticate this connection.
         This connection can be secured using SSL; for more details, see the Encryption section below.
      2. Flink to S3: S3 acts as a middleman to store bulk data when reading from or writing to Redshift.
         Flink connects to S3 using both the Hadoop FileSystem interfaces and directly using the Amazon Java SDK's S3 client.
         This connection can be authenticated using either AWS keys or IAM roles.
      3. Default Authentication: Flink-connector-aws provides different modes of Authentication redshift connectors will use CredentialProvider.
         AWS credentials will automatically be retrieved through the DefaultAWSCredentialsProviderChain.
         Users can use IAM instance roles to authenticate to S3 (e.g. on EMR, or EC2).

Proof Of Concept POC : https://github.com/Samrat002/flink-connector-aws/tree/redshift-connector

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