@Evolving public interface StreamingWrite
createStreamingWriterFactory(PhysicalWriteInfo), serialize and send it to all the partitions of the input data(RDD).
DataWriter.commit(). If exception happens during the writing, call
commit(long, WriterCommitMessage). If some writers are aborted, or the job failed with an unknown reason, call
While Spark will retry failed writing tasks, Spark won't retry failed writing jobs. Users should do it manually in their Spark applications if they want to retry.
Please refer to the documentation of commit/abort methods for detailed specifications.
|Modifier and Type||Method and Description|
Aborts this writing job because some data writers are failed and keep failing when retried, or the Spark job fails with some unknown reasons, or
Commits this writing job for the specified epoch with a list of commit messages.
Creates a writer factory which will be serialized and sent to executors.
StreamingDataWriterFactory createStreamingWriterFactory(PhysicalWriteInfo info)
If this method fails (by throwing an exception), the action will fail and no Spark job will be submitted.
info- Information about the RDD that will be written to this data writer
void commit(long epochId, WriterCommitMessage messages)
If this method fails (by throwing an exception), this writing job is considered to have been
failed, and the execution engine will attempt to call
The execution engine may call
commit multiple times for the same epoch in some
circumstances. To support exactly-once data semantics, implementations must ensure that
multiple commits for the same epoch are idempotent.
void abort(long epochId, WriterCommitMessage messages)
If this method fails (by throwing an exception), the underlying data source may require manual cleanup.
Unless the abort is triggered by the failure of commit, the given messages will have some null slots, as there may be only a few data writers that were committed before the abort happens, or some data writers were committed but their commit messages haven't reached the driver when the abort is triggered. So this is just a "best effort" for data sources to clean up the data left by data writers.