System and method for machine learning-driven cache flushing
A method, computer program product, and computing system for receiving, at a cache memory system, a write request for writing data to a storage system. A data reduction rate may be predicted for the write request. One or more portions of memory within the storage system may be allocated based upon, at least in part, the predicted data reduction rate for the write request. The write request may be flushed from the cache memory system to the allocated one or more portions of memory within the storage system.
1. A computer-implemented method, executed on a computing device, comprising:
receiving, at a cache memory system, a write request for writing data to a storage system;
predicting a data reduction rate for the write request;
allocating one or more portions of memory within the storage system based upon, at least in part, the predicted data reduction rate for the write request; and
flushing the write request from the cache memory system to the allocated one or more portions of memory within the storage system.
2. The computer-implemented method of claim 1 , wherein receiving the write request for writing data to the storage system includes storing the write request within the cache memory system without performing data compression or data deduplication.
3. The computer-implemented method of claim 1 , wherein predicting the data reduction rate for the write request includes training a machine learning model to predict the data reduction rate for the write request.
4. The computer-implemented method of claim 3 , wherein training the machine learning model to predict the data reduction rate for the write request includes weighting a plurality of data reduction factors for the write request.
5. The computer-implemented method of claim 1 , wherein allocating the one or more portions of memory within the storage system based upon, at least in part, the predicted data reduction rate for the write request includes allocating one or more partially utilized memory blocks within the storage system based upon, at least in part, the predicted data reduction rate for the write request.
6. The computer-implemented method of claim 1 , wherein flushing the write request from the cache memory system to the allocated one or more portions of memory within the storage system includes performing one or more data reduction operations on the write request based upon, at least in part, the predicted data reduction rate for the write request.
7. The computer-implemented method of claim 3 , further comprising:
in response to flushing the write request from the cache memory system to the allocated one or more portions of memory within the storage system, determining an actual data reduction rate for the write request; and
updating the machine learning model with the actual data reduction rate for the write request.
8. A computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising:
receiving, at a cache memory system, a write request for writing data to a storage system;
predicting a data reduction rate for the write request;
allocating one or more portions of memory within the storage system based upon, at least in part, the predicted data reduction rate for the write request; and
flushing the write request from the cache memory system to the allocated one or more portions of memory within the storage system.
9. The computer program product of claim 8 , wherein receiving the write request for writing data to the storage system includes storing the write request within the cache memory system without performing data compression or data deduplication.
10. The computer program product of claim 8 , wherein predicting the data reduction rate for the write request includes training a machine learning model to predict the data reduction rate for the write request.
11. The computer program product of claim 10 , wherein training the machine learning model to predict the data reduction rate for the write request includes weighting a plurality of data reduction factors for the write request.
12. The computer program product of claim 8 , wherein allocating the one or more portions of memory within the storage system based upon, at least in part, the predicted data reduction rate for the write request includes allocating one or more partially utilized memory blocks within the storage system based upon, at least in part, the predicted data reduction rate for the write request.
13. The computer program product of claim 8 , wherein flushing the write request from the cache memory system to the allocated one or more portions of memory within the storage system includes performing one or more data reduction operations on the write request based upon, at least in part, the predicted data reduction rate for the write request.
14. The computer program product of claim 10 , wherein the operations further comprise:
in response to flushing the write request from the cache memory system to the allocated one or more portions of memory within the storage system, determining an actual data reduction rate for the write request; and
updating the machine learning model with the actual data reduction rate for the write request.
15. A computing system comprising:
a memory; and
a processor configured to receive, at a cache memory system, a write request for writing data to a storage system, wherein the processor is further configured to predict a data reduction rate for the write request, wherein the processor is further configured to allocate one or more portions of memory within the storage system based upon, at least in part, the predicted data reduction rate for the write request, and wherein the processor is further configured to flush the write request from the cache memory system to the allocated one or more portions of memory within the storage system.
16. The computing system of claim 15 , wherein receiving the write request for writing data to the storage system includes storing the write request within the cache memory system without performing data compression or data deduplication.
17. The computing system of claim 15 , wherein predicting the data reduction rate for the write request includes training a machine learning model to predict the data reduction rate for the write request.
18. The computing system of claim 17 , wherein training the machine learning model to predict the data reduction rate for the write request includes weighting a plurality of data reduction factors for the write request.
19. The computing system of claim 15 , wherein allocating the one or more portions of memory within the storage system based upon, at least in part, the predicted data reduction rate for the write request includes allocating one or more partially utilized memory blocks within the storage system based upon, at least in part, the predicted data reduction rate for the write request.
20. The computing system of claim 15 , wherein flushing the write request from the cache memory system to the allocated one or more portions of memory within the storage system includes performing one or more data reduction operations on the write request based upon, at least in part, the predicted data reduction rate for the write request.