Output file mode

I'd like to follow-up on #628 and make sure we come up with something generic that will suit file-based outputs. Right now, I think the following outputs would be in scope: aws_s3, azure_blob_storage, file, gcp_cloud_storage, hdfs, sftp.

I think having a mode field for these is probably the way to go, such that the user can specify what behaviour they'd like to have when the output file already exists: error, overwrite, append, skip (anything else?).

From the comment you left here, I think setting the mode to error would let users implement the dead letter queue pattern with a try broker.

Looking at Go's io package, the following constants are provided:

const (
    // Exactly one of O_RDONLY, O_WRONLY, or O_RDWR must be specified.
    O_RDONLY int = syscall.O_RDONLY // open the file read-only.
    O_WRONLY int = syscall.O_WRONLY // open the file write-only.
    O_RDWR   int = syscall.O_RDWR   // open the file read-write.
    // The remaining values may be or'ed in to control behavior.
    O_APPEND int = syscall.O_APPEND // append data to the file when writing.
    O_CREATE int = syscall.O_CREAT  // create a new file if none exists.
    O_EXCL   int = syscall.O_EXCL   // used with O_CREATE, file must not exist.
    O_SYNC   int = syscall.O_SYNC   // open for synchronous I/O.
    O_TRUNC  int = syscall.O_TRUNC  // truncate regular writable file when opened.
)

As another example, Spark defines the following SaveMode constants:

Append - Append mode means that when saving a DataFrame to a data source, if data/table already exists, contents of the DataFrame are expected to be appended to existing data.
ErrorIfExists - ErrorIfExists mode means that when saving a DataFrame to a data source, if data already exists, an exception is expected to be thrown.
Ignore - Ignore mode means that when saving a DataFrame to a data source, if data already exists, the save operation is expected to not save the contents of the DataFrame and to not change the existing data.
Overwrite - Overwrite mode means that when saving a DataFrame to a data source, if data/table already exists, existing data is expected to be overwritten by the contents of the DataFrame.

WDYT?

Start by reading issue #628 and the linked comment, then compare the listed file-based outputs and the Go io and Spark mode references. The issue does not name implementation files or tests; done would require an agreed generic output-mode design and confirmed behavior across the in-scope outputs.