@Evolving public interface BatchWrite
The writing procedure is:
createBatchWriterFactory(PhysicalWriteInfo), serialize and send it to all the partitions of the input data(RDD).
DataWriter.commit(). If exception happens during the writing, call
commit(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 retry, or the Spark job fails with some unknown reasons, or
Commits this writing job with a list of commit messages.
Creates a writer factory which will be serialized and sent to executors.
Handles a commit message on receiving from a successful data writer.
Returns whether Spark should use the commit coordinator to ensure that at most one task for each partition commits.
DataWriterFactory createBatchWriterFactory(PhysicalWriteInfo info)
If this method fails (by throwing an exception), the action will fail and no Spark job will be submitted.
info- Physical information about the input data that will be written to this table.
default boolean useCommitCoordinator()
default void onDataWriterCommit(WriterCommitMessage message)
abort(WriterCommitMessage)would be called.
void commit(WriterCommitMessage messages)
DataWriter.commit(). If this method fails (by throwing an exception), this writing job is considered to to have been failed, and
abort(WriterCommitMessage)would be called. The state of the destination is undefined and @
abort(WriterCommitMessage)may not be able to deal with it. Note that speculative execution may cause multiple tasks to run for a partition. By default, Spark uses the commit coordinator to allow at most one task to commit. Implementations can disable this behavior by overriding
useCommitCoordinator(). If disabled, multiple tasks may have committed successfully and one successful commit message per task will be passed to this commit method. The remaining commit messages are ignored by Spark.
void abort(WriterCommitMessage messages)
commit(WriterCommitMessage)fails. 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 should have some null slots as there maybe only a few data writers that are 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.