CN111338568B - Data logic position mapping method - Google Patents
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Abstract
The invention discloses a data logic position mapping method, which divides each logic volume into a plurality of logic nodes with the same space size; sequentially storing the data abstract values of the data objects to be stored into each logic node; generating a node abstract value of each logical node with the stored data abstract value; filling an upper parent node: filling node abstract values of n adjacent logic nodes with stored data abstract values into an empty logic node, and taking the filled logic node as an upper parent node of the n logic nodes with stored data abstract values; repeating the step of filling the upper father nodes until the number of the generated upper father nodes is 1, and generating a data logic position corresponding relation; the invention enables the metadata to be simplified and configured and deleted repeatedly by skillfully arranging the metadata organization mode, thereby improving the space utilization rate and the operation efficiency.
Description
[ technical field ] A method for producing a semiconductor device
The invention belongs to the technical field of computer data storage, and particularly relates to a data logic position mapping method.
[ background of the invention ]
With the advent of the big data era, business applications have increasingly large requirements on storage space and higher performance. The storage requirements of massive data are far beyond the range of traditional multi-control storage systems. No single set of storage can provide such a large data storage capacity. Storage systems are moving towards large-scale, distributed, virtualization.
The management of the distributed storage space is to organize scattered hard disk spaces scattered on a plurality of server nodes together by some means or software to form a logically continuous large storage space. Then, a plurality of storage servers cooperate with each other to present a uniform and virtual single space view for users.
In many aspects of cost, performance and the like, the current distributed storage usually uses a plurality of pieces of cheap commercial hardware, and a software management system is installed on the hardware to provide storage services as a unified system.
Existing solutions, such as open source CEPH, and related storage products for EMC and NETAPP, provide storage virtualization and distributed management functions.
CEPH provides distributed object and block storage, as well as the functionality of a file system. However, in the implementation of CEPH, a link of data de-duplication is lost, which results in low space utilization rate. If a complex cross-node erasure code is used, the space utilization rate can be properly improved. However, due to the complexity of the erasure code implementation process, performance is reduced and failure rates are increased.
Although related products of EMC and NETAPP provide a global deduplication function, due to the deficiency of metadata management in design, metadata itself cannot be deduplicated and reduced, so that the storage space is not efficiently used.
As can be seen from the above, the prior art has the disadvantage that either the data in storage cannot be deduplicated at all, or the metadata portion cannot be thin-provisioned and deduplicated. Meanwhile, the metadata and the user data are treated differently, so that the software logic becomes very complex and the scale is larger, the error probability is increased, and the operation efficiency is reduced.
[ summary of the invention ]
The invention aims to provide a data logic position mapping method, which is used for effectively managing metadata stored in a distributed mode and realizing the simplified configuration and repeated data deletion of the metadata.
The invention adopts the following technical scheme: a data logic position mapping method comprises the following steps:
dividing each logic volume into a plurality of logic nodes with the same space size; b is the space size of each logic node, n is a positive integer, and a is the space size occupied by the data abstract value of the data object;
sequentially storing the data abstract values of the data objects to be stored into each logic node;
generating a node abstract value of each logical node with the stored data abstract value;
filling an upper parent node: filling node abstract values of n adjacent logic nodes with stored data abstract values into an empty logic node, and taking the filled logic node as an upper parent node of the n logic nodes with stored data abstract values;
and repeating the step of filling the upper father nodes until the number of the generated upper father nodes is 1, and generating the data logic position corresponding relation by taking the upper father nodes as root nodes.
Further, when the logical volume needs to be cloned or snapshot, the node digest value of the root node is extracted, and the cloned or snapshot logical volume is generated.
Further, generating the logical volume of the clone or snapshot also includes incrementing the reference count for each node digest value by 1.
Further, in logical nodes that are not populated with data digest values or node digest values, all zero objects are referenced.
Further, the data digest values and the node digest values are generated using SHA1 or the CITYHASH algorithm.
The invention has the beneficial effects that: the technical scheme skillfully arranges the metadata organization mode, realizes that the user data and the metadata are viewed as the same entity and share the same storage pool, so that the metadata can be simply configured and deleted repeatedly.
[ description of the drawings ]
FIG. 1 is a schematic diagram of a logical space tree according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating a structure of a zero logical space tree according to an embodiment of the present invention.
[ detailed description ] embodiments
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
Generally, a storage system provides a user with a logical volume device, and the user reads and writes data through a logical address of the device. In a distributed storage system, real data objects are distributed on different hard disks of different nodes. Some means is required to associate a logical address with the data location to which the address corresponds.
The present embodiment uses a "LUN TREE" logical space TREE to manage the mapping of logical addresses of logical volumes to their corresponding data digest values. Furthermore, the distributed storage system can also request the corresponding data object from the lower module through the data abstract value.
In this embodiment, the metadata of the logical space tree is encapsulated into the same object as the user data, and the user data and the metadata are smartly stored in the same storage pool and processed according to the same logic. Thereby supporting the deduplication and compaction of metadata.
The embodiment of the invention provides a data logic position mapping method, which comprises the following steps:
dividing each logic volume into a plurality of logic nodes with the same space size; b is the space size of each logic node, n is a positive integer, and a is the space size occupied by the data abstract value of the data object; sequentially storing the data abstract values of the data objects to be stored into each logic node; generating a node abstract value of each logical node with the stored data abstract value; filling an upper parent node: filling node abstract values of n adjacent logic nodes with stored data abstract values into an empty logic node, and taking the filled logic node as an upper parent node of the n logic nodes with stored data abstract values; repeating the step of filling the upper parent nodes until the number of the generated upper parent nodes is 1, and generating the data logical position corresponding relation by using the upper parent nodes as root nodes as shown in fig. 1.
The technical scheme skillfully arranges the metadata organization mode, realizes that the user data and the metadata are viewed as the same entity and share the same storage pool, so that the metadata can be simply configured and deleted repeatedly.
The distributed management storage system organizes the scattered storage space of each server across nodes, and presents a uniform and continuous view to users. The continuous view seen by the user is a storage device, also called LUN (logical volume). A LUN (logical volume) is a virtual storage device emulated by software and presented to a user operating system in a conventional manner to be identified for use by underlying block devices.
In this embodiment, a logical space tree is used to represent the corresponding relationship between the data object and the logical position, and after the above steps are completed, the logical space tree shown in fig. 1 can be generated, where in the tree structure, n takes the value of 3 and includes the following nodes:
root node: 0;
intermediate nodes: 1,2,3
Leaf node: 4,5,6,7,8,9.
Each tree node stores a set of data, and the data stored within the tree node is a cryptographic digest value (i.e., a data digest value or a node digest value). Whenever new user data or metadata is written, the data is segmented into "data objects" of the same size. The size of the data object may be predefined, typically 4KB or 8 KB. The tree node object and the user data object have the same size and are processed according to the same logic.
The data object is subjected to digest calculation by some cryptographic hash algorithm to obtain a cryptographic digest value of the data object, i.e. a data digest value. The digest algorithm may use SHA1 or CITYHSH or other mature algorithms. The data digest values are then stored within the tree nodes.
The node size is predefined, and the number of the encryption digest values which can be contained is also determined according to the predefined node size. In practical storage systems, each node may contain as many as several hundred cryptographic digest values. For convenience of description, the present embodiment takes 3 cryptographic digest values as an example.
The internal data of the leaf node stores the data digest value of the user data, which represents the contents of different logical block numbers of the logical volume according to the position of the leaf node in the tree and the offset of the data digest value inside the node.
For example, the value at the 1 st position of the leaf node 4 is "dh 0", which represents that the encrypted digest value of the 1 st block of the logical volume, that is, the data whose Logical Block Number (LBN) is 0, is "dh 0"; the value at the 1 st position of the leaf node 5 is "dh 3", which represents that the encryption digest value of the 4 th block of the logical volume, that is, the data having a Logical Block Number (LBN) of 3, is "dh 3"; the value at the 2 nd position of the leaf node 8 is "dh 13", which represents that the cryptographic digest value of the 14 th block of the logical volume, that is, the data having a Logical Block Number (LBN) of 13, is "dh 13". And by analogy, the encryption digest value of the data corresponding to each logical block number is determined according to the positions of the leaf nodes in the tree and the offset of the data encryption digest value in the nodes.
The internal data of the root node and the intermediate node holds the cryptographic digest values of its child nodes, i.e., the cryptographic digest values of the metadata. For example, the 1 st position in node 1 has a value of "h 4", which represents its child node 4 with a cryptographic digest value of "h 4"; the 3 rd position in node 2 has a value of "h 9" which represents its child node 9 with cryptographic digest value of "h 9"; and by analogy, recalling to the root node from bottom to top.
The association between the parent and child nodes of the logical space tree is maintained by the cryptographic digest values. A cryptographic digest value in a parent node specifies the contents of its child node. The system finds and reads its child nodes from the underlying virtualization based on the cryptographic digest value of the parent node. When the system is started, the system is built layer by layer from the root node downwards, so that a complete logic space tree is built.
In implementation, the number of nodes of the logical space tree may be very large depending on the size of the logical volume. In order to implement metadata de-duplication, the node size of the logical space tree and the size of the user data block need to be defined to be the same. In this way, the nodes of the logical space tree as metadata and the user data can be processed according to the same logic, and the repeated data deletion is realized. In the case where a logical volume is written full, the logical space tree is a "full tree," the data of which is shown in FIG. 1. The disk space occupied by the full tree, which may reach 1/100 the size of the logical volume, is the largest metadata in the system.
In the embodiment of the invention, when the logical volume needs to be cloned or snapshot, the node digest value of the root node is extracted, and the cloned or snapshot logical volume is generated. Generating the logical volume of the clone or snapshot also includes incrementing the reference count for each node digest value by 1.
In this embodiment, the clone and the snapshot are almost the same structure, and the difference is that the clone allows reading and writing, and the snapshot is read-only. Traditional cloning and snapshot of metadata is in the form of copying metadata and copying user data, which makes the metadata larger and larger. Therefore, it is necessary to perform metadata deduplication on a logical space tree. In this embodiment, because the metadata deduplication is performed, the clone and snapshot take up little space, but share nodes of the logical space tree with the original logical volume. In addition, the method does not need copy-on-write (COW), so that cloning and snapshot have almost no influence on system performance.
Clone and snapshot generation:
1. when the snapshot is just created, the system only needs to record the encryption digest value of the root node of the logical space tree of one source LUN and change the ID of the logical volume because the source LUN and the newly generated clone are completely the same as the data of the snapshot;
2. with the encryption digest value of the root node, the system can recursively construct a logical space tree which is completely the same as the source LUN;
3. because the node object is identical to the source LUN, under the action of deduplication, the nodes of the logical space tree do not need to be copied, and only the reference count of the logical space tree metadata object of the source LUN needs to be increased by one.
Clone and snapshot read-write:
1. the clone and the snapshot are read and written by the same method as the common LUN;
2. when new data is written, the clone and snapshot only need to change the leaf nodes corresponding to the affected LBAs and the subtrees thereof. Most other unaffected metadata remains shared with the source LUN;
3. this approach avoids the traditional copy-on-write of COW without affecting system performance.
In this embodiment, in the logical node not filled with the data digest value or the node digest value, all zero objects are referenced, that is, all 0 data are filled, so that the thin provisioning can be achieved.
Because of the support of the logic space tree structure, the scheme naturally realizes simplified configuration. In the process of creating a logical volume, the data on all logical blocks is initially 0. Therefore, a "zero tree" may be referenced. The zero tree can represent the largest logical volume only by a few tree nodes, occupies little space and realizes the simplified configuration of metadata.
The structure of the zero tree is shown in fig. 2, and the characteristics of the "zero tree" are as follows: the cryptographic digest values (dh0, dh1, dh2) stored in the leaf nodes are all equal, i.e.: dh0 ═ dh1 ═ dh2, which is obtained by calculating digests from all 0 data blocks; the cryptographic digest values (h4, h5, h6) held by the intermediate nodes are also equal, i.e.: h 4-h 5-h 6, which is obtained by calculating the abstract of the leaf node; each cryptographic digest value (h1, h2, h3) held in the root node is also equal, i.e.: h 1-h 2-h 3 is obtained by calculating the digest by the intermediate node.
With the user data being written continuously, the "zero tree" will be closer to the "full tree". Regardless of the size of the logical volume, all logical volumes have the same "zero tree" structure when initially created. Nodes of the zero tree are also data objects and can be deleted repeatedly. Therefore, the whole system shares the same zero tree structure and only occupies little space.
With the support of the above-described data logical relationship, the present embodiment achieves deduplication of data very elegantly. As can be seen from the following read-write flow, whether it is user data or logical space tree metadata, it is a data object in nature. All data objects in the system are treated equally, and the same data is stored in one copy.
The principle of implementing deduplication lies in:
all data in the system is divided into equally large data objects; each data object is encrypted and abstracted, and the encryption abstraction algorithm is as SHA1, and the essence of CITYHSH is to represent a longer data object by a string of abstract values, and the abstract values are the same, and the content of the data object is considered to be the same; and in the process of saving the data, the system calculates the node where the data object is located according to the abstract value and saves the data object to the corresponding computer node.
Due to the natural, uniform distribution of cryptographic digest values, data objects are evenly distributed across the multiple computer nodes that make up the system. When there is duplicate data written to the system again, the system does not save the data object again because the duplicate data object has the same digest value, but instead increments the reference count of the identical object that has already been saved in the system by one.
According to the design of the embodiment, the metadata objects of the data objects including the logical space tree are shared by each node. All nodes can build the same logical volume by reading the logical space tree metadata. When the owner node of the logical volume fails, other nodes can read the metadata of the logical volume, reconstruct the logical space tree, and become a new owner node. In this way, the owner node of the logical volume can be freely transformed, so that the logical volume can be freely moved among the nodes, and high availability of the logical volume is realized.
Claims (3)
1. A method for mapping a logical position of data, comprising:
dividing each logic volume into a plurality of logic nodes with the same space size; b is the space size of each logic node, n is a positive integer, and a is the space size occupied by the data abstract value of the data object;
sequentially storing the data abstract values of the data objects to be stored into each logic node;
generating a node abstract value of each logical node with the stored data abstract value;
filling an upper parent node: filling node abstract values of n adjacent logic nodes with data abstract values stored therein to an empty logic node, and taking the filled logic node as an upper parent node of the n logic nodes with the data abstract values stored therein;
repeatedly executing the step of filling the upper father nodes until the number of the generated upper father nodes is 1, and generating a data logic position corresponding relation by taking the upper father nodes as root nodes;
when the logical volume needs to be cloned or snapshot, extracting the node abstract value of the root node, and generating the cloned or snapshot logical volume;
generating the logical volume of the clone or snapshot also includes incrementing the reference count for each node digest value by 1.
2. A method for mapping a logical location of data according to claim 1, characterized in that all zero objects are referenced in logical nodes not filled with data digest values or node digest values.
3. The method of claim 1, wherein the data digest values and the node digest values are generated using SHA1 or a CITYHASH algorithm.
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