A mechanism is provided in a data processing system for distributed tree learning. A source processing instance distributes data record instances to a plurality of model update processing items. The plurality of model update processing items determine candidate leaf splitting actions in a decision tree in parallel based on the data record instances. The plurality of model update processing items send the candidate leaf splitting actions to a plurality of conflict resolve processing items. The plurality of conflict resolve processing items identifies conflict leaf splitting actions. The plurality of conflict resolve processing items applies tree structure changes to the decision tree in the plurality of model update processing items.
Please help me write a proper abstract based on the patent claims. CLAIM: 1-10. (canceled) 11. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: distribute, by a source processing instance, data record instances to a plurality of model update processing items; determine, by the plurality of model update processing items, candidate leaf splitting actions in a decision tree in parallel based on the data record instances; send, by the plurality of model update processing items, the candidate leaf splitting actions to a plurality of conflict resolve processing items; identify, by the plurality of conflict resolve processing items, conflict leaf splitting actions; and apply, by the plurality of conflict resolve processing items, tree structure changes to the decision tree in the plurality of model update processing items. 12. The computer program product of claim 11, wherein determining candidate leaf splitting actions comprises computing information gain for candidate leaf splitting actions. 13. The computer program product of claim 12, wherein determining candidate leaf splitting actions further comprises determining a first attribute having a highest information gain and a second attribute having a second highest information gain. 14. The computer program product of claim 11, wherein each of the plurality of model update processing items has access to a replica of the decision tree. 15. The computer program product of claim 11, wherein each of the plurality of model update processing items has access to the decision, tree in shared memory. 16. The computer program product of claim 11, wherein sending the candidate leaf splitting actions comprises sending a leaf identifier, an attribute identifier for an attribute causing a leaf split, a split point at which the leaf splits, local statistical information, and an identifier of fee model update processing item. 17. The computer program product of claim 11, wherein the computer readable program causes the computing device to: determine, by the plurality of conflict resolve processing items for a given candidate leaf split, whether to take the given candidate leaf split or to block the given candidate leaf split. 18. The computer program product of claim 11, wherein the computer readable program causes the computing device to: aggregate, by the plurality of conflict resolve processing items, local statistical information for each candidate leaf split from the first plurality of model update processing items. 19. The computer program product of claim 11, wherein the computer readable program causes the computing device to: communicate, by the plurality of conflict resolve processing items, blocked candidate leaf split actions. 20. The computer program product of claim 19, wherein a given model update processing item matching an identifier of a blocked candidate leaf split action does not read new data in a next cycle. 21. An apparatus comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: distribute, by a source processing instance, data record instances to a plurality of model update processing items; determine, by the plurality of model update processing items, candidate leaf splitting actions in a decision tree in parallel based on the data record instances; send, by the plurality of model update processing items, the candidate leaf splitting actions to a plurality of conflict resolve processing items; identify, by the plurality of conflict resolve processing items, conflict leaf spitting actions; and apply, by the plurality of conflict resolve processing items, tree structure changes to the decision tree in the first plurality of model update processing items.