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pub struct Input {
    pub input_parallelism: Option<InputParallelism>,
    pub input_processing_configuration: Option<InputProcessingConfiguration>,
    pub input_schema: SourceSchema,
    pub kinesis_firehose_input: Option<KinesisFirehoseInput>,
    pub kinesis_streams_input: Option<KinesisStreamsInput>,
    pub name_prefix: String,
}
Expand description

When you configure the application input for a SQL-based Kinesis Data Analytics application, you specify the streaming source, the in-application stream name that is created, and the mapping between the two.

Fields

input_parallelism: Option<InputParallelism>

Describes the number of in-application streams to create.

input_processing_configuration: Option<InputProcessingConfiguration>

The InputProcessingConfiguration for the input. An input processor transforms records as they are received from the stream, before the application's SQL code executes. Currently, the only input processing configuration available is InputLambdaProcessor.

input_schema: SourceSchema

Describes the format of the data in the streaming source, and how each data element maps to corresponding columns in the in-application stream that is being created.

Also used to describe the format of the reference data source.

kinesis_firehose_input: Option<KinesisFirehoseInput>

If the streaming source is an Amazon Kinesis Data Firehose delivery stream, identifies the delivery stream's ARN.

kinesis_streams_input: Option<KinesisStreamsInput>

If the streaming source is an Amazon Kinesis data stream, identifies the stream's Amazon Resource Name (ARN).

name_prefix: String

The name prefix to use when creating an in-application stream. Suppose that you specify a prefix "MyInApplicationStream." Kinesis Data Analytics then creates one or more (as per the InputParallelism count you specified) in-application streams with the names "MyInApplicationStream_001," "MyInApplicationStream_002," and so on.

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