Patent Application
20070266108
The present invention relates to data storage, and more particularly to an architecture and approach for a high performance, highly scaleable storage accelerator for computer networks.
In computing architectures that use externally attached storage such as Network Attached Storage (NAS) or Storage Area Networks (SANs), there is a growing mismatch between the increasing speed of compute servers and the ability of these storage systems to deliver data in a timely fashion. This inability for storage systems to keep up with fast compute servers causes applications to stall and overall throughput of the system to plateau or even regress under significant load.
When looking more closely at the root causes of this scalability problem, one common factor is latency of fetching data from a disk drive, in particular the rotation and seek time. While drives can deliver large contiguous amounts of data with an initial latency of 1-5 ms in seek time (moving the drive heads to the correct location on disk) frequent access to non-contiguous data can be of the order of ˜40 ms per access. For datasets that involve a lot of randomly accessed data (such as relational databases), the drive seek time becomes a major bottleneck in delivering data in a timely fashion.
Traditional attempts to solve this problem include adding a hierarchy of RAM-based data caches in the data path. This conventional approach is illustrated in
While such caches are generally beneficial, certain drawbacks remain. For example, the performance problems mentioned above still occur when the active data set is being accessed randomly or is too large to fit into the caches normally present.
There have been a number of companies that have created caching products which try to attack this problem through custom hardware solutions. Examples of this include RAMSAN from Texas Memory Systems (http://www.superssd.com/default.asp) and e and n-series products from Solid Data (http://www.soliddata.com/). These products are inadequate because they rely on solid-state disk technology which tends to be both expensive and limited in maximum storage size.
The present invention is related to providing a high performance, highly scalable and cost-effective storage accelerator. According to one aspect, an additional extremely large and scaleable RAM-based cache is introduced into the storage hierarchy between the Storage Array/NAS Filer and the compute servers. While external caching devices are not new and several established products exist, the architecture and approach of the present invention are unique. In one example, the system architecture is based on a parallel computing cluster design which yields an extraordinarily large scaleable cache at a very attractive price point.
In furtherance of these and other aspects, an apparatus that accelerates an access between a storage server and a client over a network according to the invention includes a plurality of computing elements each having an available portion of system memory, a memory pool being comprised of the combined available system memory of the computing elements, and programs respectively executing on the computing elements that cause the access to be intercepted and determine whether data corresponding to the access should be provided from the memory pool rather than the storage server.
In additional furtherance of these and other aspects, a storage system according to the invention comprises a scaleable RAM-based cache system separate from, and in a network path between, a storage server and a compute server.
In additional furtherance of these and other aspects, a method of accelerating storage access, comprises providing a scaleable RAM-based cache system separate from, and in a network path between, a storage server and a compute server.
These and other aspects and features of the present invention will become apparent to those ordinarily skilled in the art upon review of the following description of specific embodiments of the invention in conjunction with the accompanying figures, wherein:
The present invention will now be described in detail with reference to the drawings, which are provided as illustrative examples of the invention so as to enable those skilled in the art to practice the invention. Notably, the figures and examples below are not meant to limit the scope of the present invention to a single embodiment, but other embodiments are possible by way of interchange of some or all of the described or illustrated elements. Moreover, where certain elements of the present invention can be partially or fully implemented using known components, only those portions of such known components that are necessary for an understanding of the present invention will be described, and detailed descriptions of other portions of such known components will be omitted so as not to obscure the invention. In the present specification, an embodiment showing a singular component should not be considered limiting; rather, the invention is intended to encompass other embodiments including a plurality of the same component, and vice-versa, unless explicitly stated otherwise herein. Moreover, applicants do not intend for any term in the specification or claims to be ascribed an uncommon or special meaning unless explicitly set forth as such. Further, the present invention encompasses present and future known equivalents to the known components referred to herein by way of illustration.
In general, the present invention greatly improves storage scalability by introducing an additional extremely large and scaleable RAM-based cache into the storage hierarchy between the Storage Array/NAS Filer and the compute servers.
A block diagram illustrating an example architecture in accordance with some aspects of the invention is shown in
Storage servers 202 are in one example NAS filers such as the FAS 900 series from Network Appliance. In another example storage servers 202 are comprised of SAN products such as the Symmetrix DMX series from EMC Corporation. It should be noted that although a plurality of servers are shown, there may only be one. It should be further noted that servers 202 may comprise combinations of different types of servers (e.g. some of both NAS and SAN).
Compute servers 210 are typically high-performance servers running OLTP, batch processing, and other intensive operations under Apple OS X, AIX, Solaris, Linux, and Windows environments, for example. One example of compute servers 210 that can be used include the DL145 from Hewlett Packard.
Network 220 is an Ethernet in a NAS example, or a Fibre Channel in a SAN example. Hardware from Fibre Channel vendors including Cisco, Emulex, Brocade, McData, QLogic, LSI Logic, and Vixel can be used in a Fibre Channel example. Other types of wired and wireless networks and connections, as well as combinations of disparate types of networks, are possible.
CRD 230, as will be described in more detail below, preferably contains a large pool of RAM or other type of semiconductor memory, and contains functionality for recognizing and fulfilling requests for reading and writing data between stores 202 and servers 210.
According to one aspect of the invention illustrated in
Further details of how a CRD 230 can be implemented to intercept and process read and write flows in various example embodiments will be provided below.
One example implementation of CRD 230 is further illustrated in
In one example, elements 502 are comprised of 64-bit blade servers such as ScaleOut series blades from Rackable Systems, each having 16 GBytes of system memory (e.g. RAM) 504. The memories of the individual blades are combined together in a manner to be described in more detail below to form a single very large and scalable memory pool 512. According to an aspect of the invention, therefore, the system offers an exceptionally large cache at an attractive price compared to conventional approaches which require expensive custom hardware designs which make the cost of a large cache (>320 GBytes at the time of writing) prohibitive. It should be noted that elements 502 or clusters of elements need not be implemented using exactly the same type of blade server or other computing element, as long as they are capable of supporting an application 506 as described below.
As further shown in
In one example, proxy 508 implements well-known virtual IP addresses and proxy server techniques to intercept and, if possible, fulfill data requests from clients to servers. However, according to an aspect of the invention as will be described in more detail below, the physical blade 502 that handles any given request (or any portion thereof) is determined by a connection handoff mechanism. According to another aspect, proxy 508 includes support for one or more industry standard storage protocols (such as NFS, CIFS, Fibre Channel) and is implemented as a “bump in the wire” tee. Proxy 508 also handles communications from servers back to clients.
Global directory 510 maps the cached files to the physical blade(s) 502 on which they reside. According to an aspect of the invention, a single file can be distributed across multiple blades 502. To be able to locate file content system wide by means of a Global Directory system (i.e. how one blade can determine which other blade has the content it needs to fulfill a particular request), application 506 preferably includes an efficient update mechanism where all blades see a consistent view of the Global Directory, and those skilled in the art will understand various ways to implement such an update mechanism.
Memory pool 512 is comprised of the aggregate of free system memory in RAM 504 of each of blades 502 in one example implementation. According to an aspect of the invention, this allows the total size of the memory pool 512 to be scalable depending on the number of blades 502 that are added or removed from CRD 230, either physically or through any number of software or hardware configuration methods known to those skilled in the art. In this regard, applications 506 preferably communicate with each other to determine the number of blades 502 that are available at any given moment, thus allowing the memory pool to be freely scaled.
As each blade 502 operates as an independent system, one or more of applications 506 further implement algorithms to decide on how best to distribute file content which is too big to fit in a single blade's memory across multiple blades. In one example, the algorithms consider: Placement of file data onto cluster blades based on a static round-robin algorithm, and/or Placement of data onto the next “least loaded blade” with a computed metric of the load factor of each blade. This computed metric can be a combination of one or more of: Total amount of memory in use; Input/Output rate of the blade; Cache activity—how often Cache Reclaim operations are taking place; and other considerations.
In one example, one of blades 502 is designated a default blade for initially intercepting and, if further processing is required, opening a socket in its corresponding application 506 to handle the request. A TCP connection handoff mechanism is then used to allow cloned sockets to be opened by applications 506 in other blades 502 to service a client request for data which it has in its own physical memory.
For example, application 506 in all blades 502 share a single virtual IP address for use of the CRD as a proxy server, and clients 302 are configured to send data requests destined for one of servers 304 to this IP address. The proxy 508 distributed across all blades 502 monitors the requested connection between the specific client 302 and server 304 associated with this connection. When one of blades 502 starts communicating with a client 302 using the virtual IP address, and it is determined that another blade 502 should handle communications (e.g. when the other blade 502 contains data in its physical memory corresponding to a data request from the client), that blade takes over the network connection (e.g. by transparently migrating the connected TCP endpoint from one blade 502 to another blade 502 without interaction on behalf of the client). This allows the other blade to directly deliver its data into the network stream. It should be noted that, in this example, applications 506 may communicate among themselves to determine the default blade at any given point in time.
According to one aspect, CRD 230 also provides for parallel data delivery. This means that many blades can operate in parallel delivering data to clients. An example might be when a single large file is distributed across all the blades in the system, each blade in turn can deliver its portion of the file to clients requesting data. This compares with a single file server where such requests are typically serialized and hence delivered one-by-one.
In some example implementations, application 506 can include a high speed lossless compress/decompress function which doubles or triples the effective size of the memory pool 512 versus the combined size of physically present RAM 504 on the blades. Many compress/decompress functions that are known in the art can be used, such as Lempel-Ziv or Run Length Encoding. Application 506 in other example implementations can further include a high speed checksum function which acts as in integrity check for data going into the memory pool 512 and coming out of it. Application 506 can still further include efficient and scalable file and block level lookup functions.
Further aspects of a CRD as described above and in accordance with the principles of the invention will become apparent from an example read operation illustrated in
As shown in
As further shown in
As more file F data is requested by the NAS client in
Although the present invention has been particularly described with reference to the preferred embodiments thereof, it should be readily apparent to those of ordinary skill in the art that changes and modifications in the form and details may be made without departing from the spirit and scope of the invention. It is intended that the appended claims encompass such changes and modifications.
