Abstract: A centralized datastore maintained by a service provider may maintain current versions of objects (e.g., applications, documents, websites, etc.). A local datastore residing on user devices of users may maintain local versions of the objects. A user may submit a modification to the object and, upon determining that a version of the local object is the same as the version of current version of the object, a current version of the object may be updated to include the modification. If the version and the current version are different, individual fields of the object may be analyzed to determine if the modification involves a change to data that conflicts with data within the same field in the current version of the object. If not, the objects may be merged and the current version of the object may be updated to include the modification. Otherwise, the modification will be rejected.

Abstract: Methods, systems, and computer-readable media for distributed computing with adaptive parallelization are disclosed. An execution time metric is determined based (at least in part) on execution of a batch of jobs. A quantity of partitions for an additional batch of jobs is determined based (at least in part) on the execution time metric and on a target metric. The additional batch of jobs is divided between a set of partitions of the determined quantity. Execution is initiated of the additional batch of jobs in the set of partitions. The set of partitions comprises at least a first partition and a second partition. A first subset of jobs in the first partition is executed in parallel with a second subset of jobs in the second partition.

Abstract: Methods, systems, and computer-readable media for distributed computing with adaptive parallelization are disclosed. An execution time metric is determined based (at least in part) on execution of a batch of jobs. A quantity of partitions for an additional batch of jobs is determined based (at least in part) on the execution time metric and on a target metric. The additional batch of jobs is divided between a set of partitions of the determined quantity. Execution is initiated of the additional batch of jobs in the set of partitions. The set of partitions comprises at least a first partition and a second partition. A first subset of jobs in the first partition is executed in parallel with a second subset of jobs in the second partition.