Abstract: Embodiments of the present disclosure relate to a data backup method, a data backup device, and a computer program product. The method includes: determining delta data based on previous data and current data of a storage system; determining a delta data block subset in a delta data block set; sending delta index information and delta reference information associated with delta data blocks in the delta data block subset to a backup storage system; and sending, to the backup storage system, a further delta data block subset including delta data blocks in the delta data block set other than the delta data block subset. With the technical solution of the present disclosure, the amount of data transmission, the amount of computation, and the usage of a processing unit and a memory when backing up data can be reduced.

Abstract: A load balancing method for use in conjunction with an application or service provided by a distributed computing system may begin by electing, from a group of participants, a leader for each of a plurality of tasks associated with the application or service. Responsive to detecting a signal or some other indication to run a particular task, the elected leader of the particular task may delegate responsibility to run the particular task to a particular participant. The particular participant, upon subsequently discovering that responsibility for the particular task has been delegated to it, responds by running the particular task. In some embodiments, the elected leader for a task may delegate responsibility for running the task to a least-loaded participant.

Abstract: An apparatus in an illustrative embodiment comprises at least one processing device that includes a processor coupled to a memory. The at least one processing device is configured to establish with a coordination service for one or more distributed applications a participant identifier for a given participant in a multi-leader election algorithm implemented in a distributed computing system comprising multiple compute nodes, the compute nodes corresponding to participants having respective participant identifiers, and to interact with the coordination service in performing an iteration of the multi-leader election algorithm to determine a current assignment of respective ones of the participants as leaders for respective processing tasks of the distributed computing system. In some embodiments, the at least one processing device comprises at least a portion of a particular one of the compute nodes of the distributed computing system, and the coordination service comprises one or more external servers.

Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for model training and duration prediction. The method includes acquiring a first set of parameter values related to a first snapshot of a data object, the first snapshot being deleted from a storage system through a first deletion operation. The method further includes acquiring a first duration during which the first deletion operation is performed. The method further includes generating a prediction model based on at least the first set of parameter values and the first duration, the prediction model being used for determining a predicted duration required for deleting the snapshot from the storage system.

Abstract: Techniques provide for data synchronization. For example, such a technique may involve: obtaining respective synchronization characteristics of a group of synchronization jobs to be processed, each synchronization characteristic indicating at least one of an expected completion time instant and an amount of data to be synchronized of a corresponding synchronization job; prioritizing the group of the synchronization jobs based on the synchronization characteristics; and controlling execution of the group of the synchronization jobs based on a result of the prioritizing. Accordingly, high priority is given to the synchronization jobs which can be rapidly completed thereby improving the Recovery Point Objective (RPO) achievement rate before occurrence of a failure.

Abstract: Techniques for data transmission involve obtaining respective data transmission characteristics of a set of to-be-processed data transmission jobs, the data transmission characteristics of each data transmission job indicating at least one of an expected transmission time and a data size of the data transmission job; determining corresponding weights of the set of data transmission jobs based on the data transmission characteristics of the set of data transmission jobs; and determining a transmission rate of each data transmission job based on the weights and a total transmission rate used for the set of data transmission. Accordingly, different transmission rates may be assigned to different data transmission jobs, thereby increasing a recovery point objective (RPO) completion rate before a failure occurs.

Abstract: Techniques involve storing data. In particular, such techniques involve: obtaining first data to be stored; determining whether the first data is able to be compressed in a compression ratio exceeding a predetermined threshold; and storing, based on the determined result, the first data into a storage device. Accordingly, such techniques can execute corresponding processing for data in a predicted compression ratio, so as to store the data into a storage device. In this manner, such techniques can significantly cut down the overheads for processing data while minimizing a storage space required for storing data.

Abstract: Techniques test a storage system. Such techniques involve: acquiring a result of performing a first test on the storage system using a test case; if the result indicates that the storage system fails the first test, performing a second test on the storage system based on a problem of the storage system; and if the result indicates that the storage system passes the first test, determining a security level of the test case based on the result. Such techniques can effectively enhance test performance and system reliability of the storage system.

Abstract: Techniques test a storage system. Such techniques involve: acquiring a result of performing a first test on the storage system using a test case; if the result indicates that the storage system fails the first test, performing a second test on the storage system based on a problem of the storage system; and if the result indicates that the storage system passes the first test, determining a security level of the test case based on the result. Such techniques can effectively enhance test performance and system reliability of the storage system.

Abstract: Techniques perform data input and output. For example, there is provided a technique for updating a data pattern table. The technique involves: during a time period for establishing or updating the data pattern table: receiving a data write request; making statistics of a frequency of data being written; and writing data frequently used and an identification of the data to a corresponding entry of the data pattern table based on a result of the statistics. Using such a technique, a data pattern table can be customized and data storage efficiency can be improved.

Abstract: Techniques provide for data synchronization. For example, such a technique may involve: obtaining respective synchronization characteristics of a group of synchronization jobs to be processed, each synchronization characteristic indicating at least one of an expected completion time instant and an amount of data to be synchronized of a corresponding synchronization job; prioritizing the group of the synchronization jobs based on the synchronization characteristics; and controlling execution of the group of the synchronization jobs based on a result of the prioritizing. Accordingly, high priority is given to the synchronization jobs which can be rapidly completed thereby improving the Recovery Point Objective (RPO) achievement rate before occurrence of a failure.

Abstract: Techniques involve storing data. In particular, such techniques involve: obtaining first data to be stored; determining whether the first data is able to be compressed in a compression ratio exceeding a predetermined threshold; and storing, based on the determined result, the first data into a storage device. Accordingly, such techniques can execute corresponding processing for data in a predicted compression ratio, so as to store the data into a storage device. In this manner, such techniques can significantly cut down the overheads for processing data while minimizing a storage space required for storing data.

Abstract: Techniques perform data input and output. For example, there is provided a technique for updating a data pattern table. The technique involves: during a time period for establishing or updating the data pattern table: receiving a data write request; making statistics of a frequency of data being written; and writing data frequently used and an identification of the data to a corresponding entry of the data pattern table based on a result of the statistics. Using such a technique, a data pattern table can be customized and data storage efficiency can be improved.

Abstract: There is disclosed a method, a system, and a computer program product suitable for backing up data on a computer system. In at least one embodiment, the method comprises monitoring activity in connection with a plurality of data objects. The method also comprises determining a level of activity in connection with each data object. The method further comprises evaluating the level of activity in connection with each data object. The method still further comprises scheduling a data protection process in connection with at least one of the data objects based on the said evaluation.