Abstract: A data storage method includes: in response to a stream ID carried by an IO write request of a host satisfying a first preset condition, writing data corresponding to the IO write request into a first storage unit; and in response to the stream ID carried by the IO write request satisfying a second preset condition, writing the data corresponding to the IO write request into a second storage unit, wherein the stream ID indicates write latency requirement information of the data corresponding to the IO write request, wherein a data write latency indicated by the stream ID satisfying the first preset condition is less than the data write latency indicated by the stream ID satisfying the second preset condition, wherein a read and write performance of the first storage unit is higher than the read and write performance of the second storage unit.

Abstract: A data storage method includes: in response to a stream ID carried by an IO write request of a host satisfying a first preset condition, writing data corresponding to the IO write request into a first storage unit; and in response to the stream ID carried by the IO write request satisfying a second preset condition, writing the data corresponding to the IO write request into a second storage unit, wherein the stream ID indicates write latency requirement information of the data corresponding to the IO write request, wherein a data write latency indicated by the stream ID satisfying the first preset condition is less than the data write latency indicated by the stream ID satisfying the second preset condition, wherein a read and write performance of the first storage unit is higher than the read and write performance of the second storage unit.

Abstract: A data storage method includes: in response to a stream ID carried by an IO write request of a host satisfying a first preset condition, writing data corresponding to the IO write request into a first storage unit; and in response to the stream ID carried by the IO write request satisfying a second preset condition, writing the data corresponding to the IO write request into a second storage unit, wherein the stream ID indicates write latency requirement information of the data corresponding to the IO write request, wherein a data write latency indicated by the stream ID satisfying the first preset condition is less than the data write latency indicated by the stream ID satisfying the second preset condition, wherein a read and write performance of the first storage unit is higher than the read and write performance of the second storage unit.

Abstract: A log-structured merge-tree (LSM-Tree) based key-value (KV) data storage method includes writing KV data into a NAND flash memory. The KV data includes a key-value pair including a key and a corresponding value. The KV data is stored in a key-value solid state drive (KVSSD), which includes a storage class memory (SCM) and the NAND flash memory. The method further includes storing metadata of the KV data in the SCM. The metadata of the KV data includes the key and index information of the corresponding value of the KV data, and the index information of the corresponding value of the KV data indicates address information of the KV data in the NAND flash memory.

Abstract: The present application discloses optical frame glasses, comprising lens. The lens has a circular central area and a plurality of annular focus-increasing compensation areas surrounding the central area, the center of the circular central area coincides with the optical center of the lens, wherein focal powers of the central area and the plurality of focus-increasing compensation areas progressively increase in a radially outward direction. The optical frame glasses in the present application can eliminate high-order aberrations of eyes, thereby limiting the occurrence and development of myopia. In addition, the optical frame glasses of the present application do not touch the eyeballs, the wearing method is simple, no discomfort is caused after worn, the maintenance method is simple, and the manufacturing cost is low.

Abstract: A data processing method for a log structured merge (LSM) tree includes selecting SST files to be compressed and merged in a current layer and a next layer, sequentially reading the SST files to be compressed and merged in the current layer and the next layer from a first storage device and sequentially writing the SST files in a second storage device, randomly reading the SST files to be compressed and merged from the second storage device into a memory according to key sequence numbers of data blocks included in the SST files to be compressed and merged, and performing compression and merge processing on the SST files to be compressed and merged. Sequential and random read and write speed of the second storage device is higher than that of the first storage device.

Abstract: A log-structured merge-tree (LSM-Tree) based key-value (KV) data storage method includes writing KV data into a NAND flash memory. The KV data includes a key-value pair including a key and a corresponding value. The KV data is stored in a key-value solid state drive (KVSSD), which includes a storage class memory (SCM) and the NAND flash memory. The method further includes storing metadata of the KV data in the SCM. The metadata of the KV data includes the key and index information of the corresponding value of the KV data, and the index information of the corresponding value of the KV data indicates address information of the KV data in the NAND flash memory.

Abstract: A data storage method includes: in response to a stream ID carried by an IO write request of a host satisfying a first preset condition, writing data corresponding to the IO write request into a first storage unit; and in response to the stream ID carried by the IO write request satisfying a second preset condition, writing the data corresponding to the IO write request into a second storage unit, wherein the stream ID indicates write latency requirement information of the data corresponding to the IO write request, wherein a data write latency indicated by the stream ID satisfying the first preset condition is less than the data write latency indicated by the stream ID satisfying the second preset condition, wherein a read and write performance of the first storage unit is higher than the read and write performance of the second storage unit.

Abstract: A data processing method for a log structured merge (LSM) tree includes selecting SST files to be compressed and merged in a current layer and a next layer, sequentially reading the SST files to be compressed and merged in the current layer and the next layer from a first storage device and sequentially writing the SST files in a second storage device, randomly reading the SST files to be compressed and merged from the second storage device into a memory according to key sequence numbers of data blocks included in the SST files to be compressed and merged, and performing compression and merge processing on the SST files to be compressed and merged.

Abstract: The present application discloses optical frame glasses, comprising lens. The lens has a circular central area and a plurality of annular focus-increasing compensation areas surrounding the central area, the center of the circular central area coincides with the optical center of the lens, wherein focal powers of the central area and the plurality of focus-increasing compensation areas progressively increase in a radially outward direction. The optical frame glasses in the present application can eliminate high-order aberrations of eyes, thereby limiting the occurrence and development of myopia. In addition, the optical frame glasses of the present application do not touch the eyeballs, the wearing method is simple, no discomfort is caused after worn, the maintenance method is simple, and the manufacturing cost is low.