Disclosed are a method and a device for browsing network data, and a storage medium, and the method is operable on a device for browsing network data and includes: requesting for acquisition of network data, which includes thumbnail media data used for the thumbnail display of original media data; acquiring the thumbnail media data and data amount information of the original media data corresponding to the thumbnail media data; and displaying the thumbnail media data and the data amount information. By the disclosure, a user of an Internet terminal may obtain the relevant information of the original media data, so that unnecessary data acquiring operations by the user may be reduced, the waste of network traffic is reduced and the standby time of the Internet terminal is prolonged.

This technique improves energy efficiency of MapReduce system by using system performance model without changing any component of the MapReduce system. This involves determining presence of any hardware bottleneck in any node of MapReduce system based on a system performance model and if any hardware bottleneck is present in any node, then the maximum bandwidth value of hardware associated with the bottleneck of each node is determined. Thereafter, an energy efficient value of Central Processing Unit (CPU) frequency of each node having the bottleneck is determined by using the system performance model and the maximum bandwidth value of hardware associated with the bottleneck. Further, the CPU frequency of each node having the bottleneck is set at the energy efficient value determined in the earlier step.

A multi-level cache system may include a server with a processor and memory. The memory may include a database cache system for use with a distributed database system. The server may also include a Solid State Drive that may include a key-value store and a second storage device that may store a backend database. The key-value store may act as a second level cache to the database cache system.

In a multi-level cache system, a logic may be responsible for calculating the appropriate sizes for a database cache and a key-value store. Reception circuitry may receive a hit rate for the database cache, a reuse distance for the key-value store, and a user-selected quality of server. An adaption calculator may then calculate a target size for the database cache and a target size for the key-value store. Transmission circuitry may then transmit the target size for the database cache and the target size for the key-value store for use in the multi-level cache system.

In a multi-level cache system, a logic (360) may be responsible for calculating the appropriate sizes for a database cache (140) and a key-value store (320, 325, 330, 335). Reception circuitry (1005) may receive a hit rate (1020) for the database cache (140), a reuse distance (1025) for the key-value store (320, 325, 330, 335), and a user-selected quality of server (1030). An adaption calculator (1010) may then calculate a target size (505, 510) for the database cache (140) and a target size (515, 520) for the key-value store (320, 325, 330, 335). Transmission circuitry (1015) may then transmit the target size (505, 510) for the database cache (140) and the target size (515, 520) for the key-value store (320, 325, 330, 335) for use in the multi-level cache system.

A multi-level cache system may include a server (105) with a processor (110) and memory (115). The memory (115) may include a database cache system (140) for use with a distributed database system. The server (105) may also include a Solid State Drive (130, 135) that may include a key-value store (320, 325, 330, 335) and a second storage device (120) that may store a backend database (125). The key-value store (320, 325, 330, 335) may act as a second level cache to the database cache system (140).

Described herein is a technology for providing enhanced transactional caching. In accordance with one aspect, a transactional cache associated with a database is configured. The enhanced cache may support write operation by partial key or index. Execution of a write operation on the database is delayed until a flush is determined to be necessary. The write operation is delayed by performing the write operation on the transactional cache. The flush is invoked by performing a row-wise bulk operation that updates the database based on the transactional cache.

A data storage system is operable to perform a power supply strategy selection function based on first energy utilization-based operation optimizer input data to generate first energy utilization-based power supply strategy data that includes first power supply resource type proportion data denoting, for each power supply type of a plurality of power supply types, a corresponding first proportion of power supply resources that be implemented as the each power supply type. Based on the first energy utilization-based power supply strategy data, a first set of power supply resources is selected to execute a first operation is selected. The power supply strategy selection function is performed based on second energy utilization-based operation optimizer input data to generate second energy utilization-based power supply strategy data. Based on the second energy utilization-based power supply strategy data, a second set of power supply resources is selected to execute a second operation.