ParallelSimpleCopy copies incoming data records to all output CloverDX Cluster workers. The algorithm of the component is derived from the regular SimpleCopy component.

ParallelSimpleCopy propagates metadata in both directions. The component does not change priorities of propagated metadata.

The component has no metadata template.

ParallelSimpleCopy does not require any specific metadata fields.

ParallelSimpleCopy copies incoming data records to all output CloverDX Cluster workers. Each incoming record is duplicated and sent to all output partitions.

This component is useful whenever you need to have data available for all workers. For example, you decide to process a large number of your business transactions in a parallel way. ParallelPartition is the right component to split your data among several workers. Then you need to join your transactions for example with country codes, where the transactions have been performed. You need to have the list of all country codes available on all workers. Each worker can acquire the country codes individually, but if the data reading is very expensive, for example reading from a slow web service, it could be favorable to read them once and copy them among all workers using CloverDX functions. So you can read the country codes from a slow data source just once on a single worker and copy them to all workers using ParallelSimpleCopy, where they can be used to join with your transactions.

The algorithm of this component is derived from the regular SimpleCopy component. For more details, see the documentation of the SimpleCopy component.

This component belongs to a group of Cluster components that allows the change from a single-worker allocation to a multiple-worker allocation. So the allocation of the component preceding the ParallelSimpleCopy component has to provide just a single worker. The allocation of the component following the ParallelSimpleCopy component can provide multiple workers.

	Note
	For more information about this component, see Chapter 42, Data Partitioning in Cluster.