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object S3Steps

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@StepObject()
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  6. def createFileManager(region: String, bucket: String, accessKeyId: Option[String] = None, secretAccessKey: Option[String] = None, accountId: Option[String] = None, role: Option[String] = None, partition: Option[String] = None): Option[S3FileManager]

    Simple function to generate the S3FileManager for the local S3 file system.

    Simple function to generate the S3FileManager for the local S3 file system.

    region

    The AWS region this bucket should be accessed in

    bucket

    The bucket to use for this file system.

    accessKeyId

    The AWS access key to use when interacting with the S3 bucket

    secretAccessKey

    The AWS secret to use when interaction with the S3 bucket

    returns

    A FileManager that can interact with the specified S3 bucket.

    Annotations
    @StepFunction( ... , "Create S3 FileManager" , ... , "Pipeline" , "AWS" ) @StepParameters( ... ) @StepResults( ... , None )
  7. def createFileManagerWithClient(s3Client: AmazonS3, bucket: String): Option[S3FileManager]

    Simple function to generate the S3FileManager for the local S3 file system.

    Simple function to generate the S3FileManager for the local S3 file system.

    s3Client

    The existing AWS S3 client

    bucket

    The bucket to use for this file system.

    returns

    A FileManager that can interact with the specified S3 bucket.

    Annotations
    @StepFunction( ... , "Create S3 FileManager with Client" , ... , "Pipeline" , "AWS" ) @StepParameters( ... ) @StepResults( ... , None )
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  17. def readFromPath(path: String, accessKeyId: Option[String] = None, secretAccessKey: Option[String] = None, accountId: Option[String] = None, role: Option[String] = None, partition: Option[String] = None, options: Option[DataFrameReaderOptions] = None, pipelineContext: PipelineContext): DataFrame
    Annotations
    @StepFunction( ... , "Load DataFrame from S3 path" , ... , "Pipeline" , "AWS" ) @StepParameters( ... ) @StepResults( "org.apache.spark.sql.DataFrame" , None )
  18. def readFromPaths(paths: List[String], accessKeyId: Option[String] = None, secretAccessKey: Option[String] = None, accountId: Option[String] = None, role: Option[String] = None, partition: Option[String] = None, options: Option[DataFrameReaderOptions] = None, pipelineContext: PipelineContext): DataFrame
    Annotations
    @StepFunction( ... , "Load DataFrame from S3 paths" , ... , "Pipeline" , "AWS" ) @StepParameters( ... ) @StepResults( "org.apache.spark.sql.DataFrame" , None )
  19. def registerS3FileSystems(pipelineContext: PipelineContext): Unit
    Annotations
    @StepFunction( ... , "Register S3 FS Providers" , ... , "Pipeline" , "AWS" )
  20. def setupS3Authentication(accessKeyId: Option[String] = None, secretAccessKey: Option[String] = None, accountId: Option[String] = None, role: Option[String] = None, partition: Option[String] = None, pipelineContext: PipelineContext): Unit
    Annotations
    @StepFunction( ... , "Setup S3 Authentication" , ... , "Pipeline" , "AWS" ) @StepParameters( ... )
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  26. def writeToPath(dataFrame: DataFrame, path: String, accessKeyId: Option[String] = None, secretAccessKey: Option[String] = None, accountId: Option[String] = None, role: Option[String] = None, partition: Option[String] = None, options: Option[DataFrameWriterOptions] = None, pipelineContext: PipelineContext): Unit
    Annotations
    @StepFunction( ... , "Write DataFrame to S3" , ... , "Pipeline" , "AWS" ) @StepParameters( ... )

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