CN115630063A - Method and device for optimizing storage space of b + tree - Google Patents

Method and device for optimizing storage space of b + tree Download PDF

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CN115630063A
CN115630063A CN202211233861.5A CN202211233861A CN115630063A CN 115630063 A CN115630063 A CN 115630063A CN 202211233861 A CN202211233861 A CN 202211233861A CN 115630063 A CN115630063 A CN 115630063A
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length
comparison unit
tree
comparing
hash
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陈柳泉
张群
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CLP Cloud Digital Intelligence Technology Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/22—Indexing; Data structures therefor; Storage structures
    • G06F16/2228—Indexing structures
    • G06F16/2246—Trees, e.g. B+trees
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/22—Indexing; Data structures therefor; Storage structures
    • G06F16/2228—Indexing structures
    • G06F16/2255—Hash tables
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2453—Query optimisation

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Abstract

The application discloses a b + tree storage space optimization method and device, which comprise the following steps: converting the key values of non-leaf nodes of the b + tree into hash keys with equal length through a hash algorithm, wherein the hash keys comprise a first comparison unit and a second comparison unit, the values recorded by the first comparison unit and the second comparison unit are different, and when searching and comparing, comparing the first comparison unit and the second comparison unit according to a preset sequence to realize internal sequencing; for the non-leaf nodes of the b + tree, the real key values are not stored, and only the addresses of the leaf nodes at the lower boundary of the range represented by the corresponding entry (rec) of the non-leaf nodes are stored. In the method of this embodiment, the non-leaf node key value of the b + tree is converted into a hash key with equal length through a hash algorithm, the hash key includes a first comparison unit and a second comparison unit, and for the non-leaf node of the b + tree, only the address of the leaf node at the lower bound of the range represented by the rec is stored, so that the data structure of the b + tree is optimized, and the metadata space consumption caused by the key value is reduced.

Description

Method and device for optimizing storage space of b + tree
Technical Field
The present application relates to the field of storage technologies, and in particular, to a method and an apparatus for optimizing a b + tree storage space.
Background
In the traditional storage technology, a b + tree is often used in the organization form of disk data, the times of reading and writing a disk can be effectively reduced, and the storage system has stable reading and writing performance, for example, mysql and oracle are storage engines based on the b tree. The non-leaf nodes and the leaf nodes of the b + tree both store keys without actual data, so that the number of indexes is increased, and the hierarchy of the tree is reduced.
In a high-performance storage medium (such as SCM), due to the high cost per unit capacity, it is necessary to consider reducing the space occupation as much as possible. For a scene with longer keys, such as a b + tree structure needing to be sorted in a lexicographic order, the length of the key is a variable-length character string, so that the key value occupies more space.
Disclosure of Invention
The embodiment of the application provides a b + tree storage space optimization method and device, which are used for optimizing a data structure of a b + tree and reducing metadata space consumption brought by a key value.
The embodiment of the application provides a b + tree storage space optimization method, which comprises the following steps:
converting the key values of non-leaf nodes of the b + tree into hash keys with equal length through a hash algorithm, wherein the hash keys comprise a first comparison unit and a second comparison unit, the values recorded by the first comparison unit and the second comparison unit are different, and when searching and comparing, comparing the first comparison unit and the second comparison unit according to a preset sequence to realize internal sequencing;
for non-leaf nodes of the B + tree, the real key values are not stored, and only the addresses of the leaf nodes at the lower boundary of the range represented by the corresponding entry (rec) of the non-leaf nodes are stored.
Optionally, the first comparing unit and the second comparing unit have the same length, and the first comparing unit further includes a first comparing subunit and a second comparing subunit having the same length, where:
the first comparison subunit is used for recording the length of the character string;
the second comparison subunit is used for obtaining a first hash value by adopting a first hash algorithm;
the second comparison unit is a second hash value obtained by adopting a second hash algorithm;
when searching and comparing, the first comparison unit is compared firstly, and then the second comparison unit is compared, so as to realize internal sequencing.
Optionally, for a character string with a length smaller than the hash key length, storing the length of the character string by using a first length byte, and storing the character string by using a second length byte, wherein the sum of the first length and the second length is the same as the length of the hash key;
when searching and comparing, the first comparing unit compares the third length byte, and then compares the fourth length byte to realize internal sequencing, wherein the third length byte, the fourth length byte and the second comparing unit have the same length.
Optionally, the method further includes storing a real key in a leaf node, finding a corresponding leaf node through an address in a non-leaf node under the condition of searching the corresponding level of the b + tree, and obtaining a key value of the 0 th rec of the leaf node for comparison.
An embodiment of the present application further provides a terminal device, including a processor, configured to:
converting the key values of non-leaf nodes of the B + tree into hash keys with equal length through a hash algorithm, wherein each hash key comprises a first comparison unit and a second comparison unit, the values recorded by the first comparison unit and the second comparison unit are different, and when searching and comparing, comparing the first comparison unit and the second comparison unit according to a preset sequence to realize internal sequencing;
for non-leaf nodes of the B + tree, the real key values are not stored, and only the addresses of the leaf nodes at the lower boundary of the range represented by the corresponding entry (rec) of the non-leaf nodes are stored.
Optionally, the first comparing unit and the second comparing unit have the same length, and the first comparing unit further includes a first comparing subunit and a second comparing subunit having the same length, where:
the first comparison subunit is used for recording the length of the character string;
the second comparison subunit is used for obtaining a first hash value by adopting a first hash algorithm;
the second comparison unit is a second hash value obtained by adopting a second hash algorithm;
in looking up the comparison, the processor is further configured to: and comparing the first comparison unit and the second comparison unit to realize internal sequencing.
Optionally, the processor is further configured to:
for a character string with the length smaller than the hash key length, storing the length of the character string by using a first length byte, and storing the character string by using a second length byte, wherein the sum of the first length and the second length is the same as the length of the hash key;
when searching and comparing, the first comparing unit compares the third length byte, and then compares the fourth length byte to realize internal sequencing, wherein the third length byte, the fourth length byte and the second comparing unit have the same length.
Optionally, the processor is further configured to:
the method also comprises the steps of storing real keys in leaf nodes, finding out the corresponding leaf nodes through addresses in non-leaf nodes under the condition of searching the corresponding levels of the b + tree, and acquiring the key value of the 0 th rec of the leaf node for comparison.
An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the foregoing b + tree storage space optimization method are implemented.
In the method of this embodiment, the non-leaf node key value of the b + tree is converted into a hash key with equal length through a hash algorithm, the hash key includes a first comparing unit and a second comparing unit, and for the non-leaf node of the b + tree, only the address of the leaf node at the lower bound of the range represented by the rec is stored, so that the data structure of the b + tree is optimized, and the metadata space consumption caused by the key value is reduced.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
Various additional advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the application. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 is a hash key example of a b + tree storage space optimization method according to an embodiment of the present application;
FIG. 2 is a block diagram illustrating an exemplary b + tree memory space optimization according to an embodiment of the present disclosure;
fig. 3 is a storage example of a string smaller than 15 bytes for the b + tree storage space optimization method according to the embodiment of the present application.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The embodiment of the application provides a b + tree storage space optimization method, which comprises the following steps:
and converting the key values of the non-leaf nodes of the b + tree into hash keys with equal length through a hash algorithm. For the character string scene which does not need to be sorted according to the input key, the fixed length of the key value can be realized through a hash algorithm, so that the order of the middle layer of the tree is improved, and the aims of reducing the hierarchy and reducing the storage space of the non-leaf nodes are fulfilled. Meanwhile, the comparison efficiency of the key value can be improved, and the searching performance is improved.
The hash key comprises a first comparison unit and a second comparison unit, the values recorded by the first comparison unit and the second comparison unit are different, and when the hash key is searched and compared, the first comparison unit and the second comparison unit are compared according to a preset sequence so as to realize internal sequencing. In some specific examples, the first comparing unit and the second comparing unit have the same length, and the first comparing unit further includes a first comparing subunit and a second comparing subunit having the same length, where:
the first comparison subunit is used for recording the length of the character string;
the second comparison subunit is used for obtaining a first hash value by adopting a first hash algorithm;
the second comparison unit is a second hash value obtained by adopting a second hash algorithm;
when searching and comparing, the first comparison unit is compared firstly, and then the second comparison unit is compared, so as to realize internal sorting.
As shown in fig. 1, in this example, a hash key of a 16-byte double-hash comparison mechanism may be designed, where the first 8 bytes are used as a first comparison unit, the first 4 bytes of the first comparison unit are used as a first comparison subunit for recording a length of a character string, the last 4 bytes of the first comparison subunit are used as a second comparison subunit, and a dbj2 hash algorithm is used to obtain a hash value of 4 bytes. Then 8 bytes are used as a second comparison unit, and a hash value of 8 bytes is obtained through a murmur hash algorithm. When searching and comparing, the internal sequencing is realized by comparing the first 8 bytes and the second 8 bytes.
For non-leaf nodes of the B + tree, the real key values are not stored, and only the addresses of the leaf nodes at the lower boundary of the range represented by the corresponding entry (rec) of the non-leaf nodes are stored.
In some examples, the method further includes storing a real key in a leaf node, and in the case of searching the corresponding level of the b + tree, finding a corresponding leaf node through an address in a non-leaf node, and obtaining a key value of the 0 th rec of the leaf node for comparison.
In this way, the length of the key of the non-leaf node can be effectively reduced, and only 8 bytes of the address of the corresponding leaf node need to be recorded, as shown in fig. 2, the number of the storage sub-nodes is increased from 4096/(64 + 8) =56 to 4096/(8 + 8) =256 in a 4096 page by calculating according to the 64-byte user key. Corresponding to the 3-layer tree, the kv which can be stored by 4096 is taken as the order, and the total number of the indexable kv is 56 3 =175,616 up to 256 3 =16,777,216, the required nodes are 56 respectively 2 +56+1=3193, 256 2 +256+1=65,793. The non-leaf node occupation ratio is reduced from 57/3193=0.017 (1.7%) to 257/65793=0.003 (0.3%), the same number kv of levels is greatly reduced, and the space occupation of the non-leaf nodes is reduced.
In some embodiments, for a character string with a length smaller than the hash key length, storing the length of the character string by using a first length byte, and storing the character string by using a second length byte, wherein the sum of the first length and the second length is the same as the length of the hash key;
when searching and comparing, the first comparing unit compares the third length byte, and then compares the fourth length byte to realize internal sequencing, wherein the third length byte, the fourth length byte and the second comparing unit have the same length.
As shown in fig. 3, in order to reduce the hash calculation consumption, in this example, the design logic of the hash key is further optimized, and for a character string smaller than 15 bytes, in this embodiment, hash calculation is not performed, and a key value is directly stored, for example, a first 1-byte storage length and a second 15-byte storage length may be used to store the character string. When searching for comparison, the comparison principle of the first 8 bytes and the last 8 bytes is still followed.
The embodiment converts the variable-length keys into 16-byte hash values for storage, and is suitable for kv storage with longer keys and without sorting in a lexicographic order. If the number of storage child nodes of a 4096 page is increased from 4096/(64 + 8) =56 to 4096/(16 + 8) =170 according to the user key of 64 bytes, corresponding to a 3-layer tree, and kv that can be stored in 4096 is taken as the order, the total number of indexable kv is 56 3 Lifting of =175,616 to 170 3 =4,913,000, required nodes are 56 respectively 2 +56+1=3193, 170 2 +170+1= 29071. The non-leaf node occupancy is reduced from 57/3193=0.017 (1.7%) to 171/29071=0.0058 (0.58%), effectively reducing the space and tree levels of the non-leaf nodes.
In the method of this embodiment, the non-leaf node key value of the B + tree is converted into a hash key with equal length through a hash algorithm, and the hash key includes a first comparing unit and a second comparing unit, and for the non-leaf node of the B + tree, only the address of the leaf node in the lower bound of the range represented by the rec is stored, so that the data structure of the B + tree is optimized, and the metadata space consumption caused by the key value is reduced.
An embodiment of the present application further provides a terminal device, which includes a processor configured to:
converting the key values of non-leaf nodes of the b + tree into hash keys with equal length through a hash algorithm, wherein the hash keys comprise a first comparison unit and a second comparison unit, the values recorded by the first comparison unit and the second comparison unit are different, and when searching and comparing, comparing the first comparison unit and the second comparison unit according to a preset sequence to realize internal sequencing;
for the non-leaf nodes of the b + tree, the real key values are not stored, and only the addresses of the leaf nodes at the lower boundary of the range represented by the corresponding entry (rec) of the non-leaf nodes are stored.
In some embodiments, the first and second comparison units are the same in length, the first comparison unit further comprising a first and second comparison sub-unit of equal length, wherein:
the first comparison subunit is used for recording the length of the character string;
the second comparison subunit is used for obtaining a first hash value by adopting a first hash algorithm;
the second comparison unit is a second hash value obtained by adopting a second hash algorithm;
in looking up the comparison, the processor is further configured to: the first comparison unit is compared first, and then the second comparison unit is compared to realize internal sorting.
In some embodiments, the processor is further configured to:
for a character string with the length smaller than the hash key length, storing the length of the character string by using a first length byte, and storing the character string by using a second length byte, wherein the sum of the first length and the second length is the same as the length of the hash key;
when searching and comparing, the first comparing unit compares the third length byte firstly, and then compares the fourth length byte to realize internal sequencing, wherein the third length byte and the fourth length byte have the same length as the second comparing unit.
In some embodiments, the processor is further configured to:
and storing the real key in a leaf node, finding the corresponding leaf node through the address in the non-leaf node under the condition of searching the corresponding hierarchy of the b + tree, and acquiring the key value of the 0 th rec of the leaf node for comparison.
An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the foregoing b + tree storage space optimization method are implemented.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one of 8230, and" comprising 8230does not exclude the presence of additional like elements in a process, method, article, or apparatus comprising the element.
The above-mentioned serial numbers of the embodiments of the present application are merely for description, and do not represent the advantages and disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application or portions thereof that contribute to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (such as a ROM/RAM, a magnetic disk, and an optical disk), and includes several instructions for enabling a terminal (which may be a mobile phone, a computer, a server, or a network device, etc.) to execute the method described in the embodiments of the present application.
While the present embodiments have been described with reference to the accompanying drawings, it is to be understood that the present embodiments are not limited to those precise embodiments, which are intended to be illustrative rather than restrictive, and that various changes and modifications may be effected therein by one skilled in the art without departing from the scope of the appended claims.

Claims (9)

1. A b + tree storage space optimization method is characterized by comprising the following steps:
converting the key values of non-leaf nodes of the b + tree into hash keys with equal length through a hash algorithm, wherein each hash key comprises a first comparison unit and a second comparison unit, the values recorded by the first comparison unit and the second comparison unit are different, and when searching and comparing, comparing the first comparison unit and the second comparison unit according to a preset sequence to realize internal sequencing;
for the non-leaf nodes of the b + tree, the real key values are not stored, and only the addresses of the leaf nodes at the lower boundary of the range represented by the corresponding entry (rec) of the non-leaf nodes are stored.
2. The b + tree storage space optimization method of claim 1, wherein the first comparison unit and the second comparison unit have the same length, the first comparison unit further comprises a first comparison subunit and a second comparison subunit having the same length, wherein:
the first comparison subunit is used for recording the length of the character string;
the second comparison subunit is used for obtaining a first hash value by adopting a first hash algorithm;
the second comparison unit is a second hash value obtained by adopting a second hash algorithm;
when searching and comparing, the first comparison unit is compared firstly, and then the second comparison unit is compared, so as to realize internal sequencing.
3. The b + tree storage space optimization method of claim 2, wherein for a string having a length smaller than the hashkey length, the length of the string is stored by a first length byte, and the string is stored by a second length byte, wherein the sum of the first length and the second length is the same as the length of the hashkey;
when searching and comparing, the first comparing unit compares the third length byte, and then compares the fourth length byte to realize internal sequencing, wherein the third length byte, the fourth length byte and the second comparing unit have the same length.
4. The method for optimizing the storage space of the b + tree of claim 1, further comprising storing a real key in a leaf node, finding a corresponding leaf node through an address in a non-leaf node when searching for a corresponding level of the b + tree, and obtaining a key value of the 0 th rec of the leaf node for comparison.
5. A terminal device, comprising a processor configured to:
converting the key values of non-leaf nodes of the b + tree into hash keys with equal length through a hash algorithm, wherein each hash key comprises a first comparison unit and a second comparison unit, the values recorded by the first comparison unit and the second comparison unit are different, and when searching and comparing, comparing the first comparison unit and the second comparison unit according to a preset sequence to realize internal sequencing;
for the non-leaf nodes of the b + tree, the real key values are not stored, and only the addresses of the leaf nodes at the lower boundary of the range represented by the corresponding entry (rec) of the non-leaf nodes are stored.
6. The terminal device of claim 5, wherein the first comparing unit and the second comparing unit are the same in length, the first comparing unit further comprising a first comparing subunit and a second comparing subunit which are equal in length, wherein:
the first comparison subunit is used for recording the length of the character string;
the second comparison subunit is used for obtaining a first hash value by adopting a first hash algorithm;
the second comparison unit is a second hash value obtained by adopting a second hash algorithm;
in looking up the comparison, the processor is further configured to: the first comparison unit is compared first, and then the second comparison unit is compared to realize internal sorting.
7. The terminal device of claim 6, wherein the processor is further configured to:
for a character string with the length smaller than the hash key length, storing the length of the character string by using a first length byte, and storing the character string by using a second length byte, wherein the sum of the first length and the second length is the same as the length of the hash key;
when searching and comparing, the first comparing unit compares the third length byte firstly, and then compares the fourth length byte to realize internal sequencing, wherein the third length byte and the fourth length byte have the same length as the second comparing unit.
8. The terminal device of claim 5, wherein the processor is further configured to:
the method also comprises the steps of storing real keys in leaf nodes, finding out the corresponding leaf nodes through addresses in non-leaf nodes under the condition of searching the corresponding levels of the b + tree, and acquiring the key value of the 0 th rec of the leaf node for comparison.
9. A computer-readable storage medium, characterized in that a computer program is stored thereon, which computer program, when being executed by a processor, carries out the steps of the b + tree storage space optimization method according to any one of claims 1 to 4.
CN202211233861.5A 2022-10-10 2022-10-10 Method and device for optimizing storage space of b + tree Pending CN115630063A (en)

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