CN112115126B - Processing method and device for aggregate data types and database management system - Google Patents
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Abstract
The present disclosure relates to a method, an apparatus, and a database management system for processing an aggregate data type, in which a data object of the aggregate data type stored in a flattened data structure is obtained from an external memory, the data object is stored in a memory in an expandable data structure, the data object is processed in the memory in the expandable data structure, and the data object is transferred between modules of the memory in the expandable data structure, that is, the data object is stored in the memory in the expandable data structure, and the data object is transferred between modules of the memory in the expandable data structure, so that the data structure of the data object is not required to be converted by each module of the memory, thereby improving the processing efficiency of the aggregate data type, and the flattened data structure is stored in the external memory, saving the storage space, and improving the resource utilization.
Description
Technical Field
The disclosure relates to the field of computer technology, and in particular, to a method and a device for processing aggregate data types and a database management system.
Background
With the rapid development of computer technology, the application of databases is also becoming more and more widespread, and the diversity of data types is a very important index of the overall function of databases. The purpose of the different data types is to facilitate the computation and storage of the data objects, which may be stored in different data structures.
In a database management system, storage and computing power is provided for any data type of object, and thus, a corresponding data structure is required to store information for the data type of data object. For the aggregate data type, since the aggregate data type may contain a plurality of data objects, the data objects therein need to be conveniently stored, accessed, added and deleted, in the prior art, the same flattened data structure is generally adopted for both the memory and the external memory, when the data objects need to be operated on, the data objects stored in the flattened data structure are read from the external memory into the memory, when each module in the memory processes the data objects, the flattened data structure is converted into an expandable data structure, the data objects are processed, after the processing is finished, the data objects are repackaged into the flattened data structure, the data objects are transferred between the modules in the memory, and the final result of the processing is written into the external memory in the flattened data structure.
However, with prior art methods, the processing of aggregate data types is inefficient.
Disclosure of Invention
In order to solve the above technical problems or at least partially solve the above technical problems, the present disclosure provides a method, an apparatus, and a database management system for processing aggregate data types.
In a first aspect, the present disclosure provides a method for processing an aggregate data type, including:
Obtaining a data object from a memory, wherein the data object is of an aggregate data type, and the data object is stored in the memory in a flattened data structure;
storing the data object into a memory in an expandable data structure;
processing the data object in the memory in an expandable data structure, and transferring the data object in the expandable data structure among the modules of the memory.
Optionally, before the data object is stored in the memory in the expandable data structure, the method further includes:
Registering the expandable data structure in a database management system to enable each module in the memory to identify data objects communicated in the expandable data structure.
Optionally, the registering the extensible data structure in the database management system includes:
The extensible data structure is declared as a global variable in a database management system.
Optionally, the method further comprises:
determining keywords and grammar rules of the extensible data structure;
And adding the keywords and grammar rules into the definition of the aggregate data type.
Optionally, the storing the data object in the memory in the expandable data structure includes: searching in a name space according to the name of the data type;
acquiring an extensible data structure corresponding to the aggregate data type;
And storing the data object into the memory according to the expandable data structure.
Optionally, the method further comprises:
data objects stored in the memory in the expandable data structure are converted into flattened data structures and stored in the external memory.
In a second aspect, the present disclosure provides a processing apparatus for aggregating data types, including:
The system comprises an acquisition module, a data storage module and a data storage module, wherein the acquisition module is used for acquiring a data object from a memory, the data object is of an aggregate data type, and the data object is stored in the memory in a flattened data structure;
the storage module is used for storing the data object into a memory in an expandable data structure;
And the processing module is used for processing the data object in the memory in an expandable data structure and transmitting the data object in the expandable data structure among the modules of the memory.
Optionally, the processing module is further configured to register the expandable data structure in a database management system, so that each module in the memory can identify a data object transferred in the expandable data structure.
Optionally, the processing module is specifically configured to declare the extensible data structure as a global variable in a database management system.
Optionally, the processing module is further configured to determine keywords and grammar rules of the expandable data structure; and adding the keywords and grammar rules into the definition of the aggregate data type.
Optionally, the processing module is specifically configured to search in a namespace according to a name of the data type; acquiring an extensible data structure corresponding to the aggregate data type; and storing the data object into the memory according to the expandable data structure.
Optionally, the storage module is further configured to convert the data objects stored in the memory in the expandable data structure into flattened data structures and store the flattened data structures in the external memory.
In a third aspect, the present disclosure provides a database management system comprising: a processor for executing a computer program stored in a memory, which when executed by the processor implements the steps of the method according to any of the first aspects.
In a fourth aspect, the present disclosure provides a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to the first aspect.
Compared with the prior art, the technical scheme provided by the embodiment of the disclosure has the following advantages:
The method comprises the steps of obtaining data objects of the aggregate data type stored in the flattened data structure from the external memory, storing the data objects in the internal memory in the expandable data structure, processing the data objects in the internal memory in the expandable data structure, and transmitting the data objects in the expandable data structure among the modules of the internal memory, namely, transmitting the data objects in the expandable data structure among the modules of the internal memory by adopting the expandable data structure in the internal memory, and converting the data structures of the data objects in the modules of the internal memory without the need of the data structures of the modules of the internal memory, so that the processing efficiency of the aggregate data type is improved, and storing the data objects in the flattened data structure in the external memory, the storage space is saved, and the resource utilization rate is improved.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.
In order to more clearly illustrate the embodiments of the present disclosure or the solutions in the prior art, the drawings that are required for the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a flow chart of an embodiment of a method for processing aggregate data types provided in the present disclosure;
FIG. 2 is a flow chart of another embodiment of a method for processing aggregate data types provided by the present disclosure;
FIG. 3 is a schematic diagram of a memory structure of a flattened data structure provided by the present disclosure;
FIG. 4 is a flowchart illustrating an embodiment of a method for processing aggregate data types according to the present disclosure;
FIG. 5 is a schematic diagram of a processing apparatus for aggregating data types provided in the present disclosure;
Fig. 6 is a schematic structural diagram of a database management system provided in the present disclosure.
Detailed Description
In order that the above objects, features and advantages of the present disclosure may be more clearly understood, a further description of aspects of the present disclosure will be provided below. It should be noted that, without conflict, the embodiments of the present disclosure and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced otherwise than as described herein; it will be apparent that the embodiments in the specification are only some, but not all, embodiments of the disclosure.
A collection is a composite data type in a database, elements with the same data type are combined in a certain sequence, the elements can be operated through unique indexes of the elements, and the elements in the collection can be increased or decreased. The aggregate data type is characterized by comprising a plurality of elements of the same data type.
Aiming at the aggregate data type, the method and the device have the advantages that the flattened data structure is favorable for saving storage space and reading data objects, the expandable data structure is favorable for operating the data objects, the data objects of the aggregate data type are processed in a mode of combining the flattened data structure and the expandable data structure, and particularly, the data objects are stored in an external memory in the flattened data structure, and are processed and transferred in an internal memory in the expandable data structure, so that the purposes of convenient calculation of the aggregate data type in the internal memory and convenient storage in the external memory are realized, and the processing efficiency of the data objects of the aggregate type is improved.
The following description of the technical solutions of the present disclosure is made in several specific embodiments, and for the same or similar concepts, reference may be made to each other, and each location will not be described in detail.
Fig. 1 is a flow chart of an embodiment of a method for processing aggregate data types, as shown in fig. 1, where the method in this embodiment includes:
s101: the data object is retrieved from the external memory.
The data objects are of an aggregate data type, and are stored in the external memory in a flattened data structure.
Storing in a flattened data structure means storing data objects in a continuous and compact data storage space, which is advantageous for saving storage space.
When the data object needs to be processed, the data object needs to be read from the external memory into the internal memory, and the data object needs to be processed in the internal memory, for example, the data object in the internal memory is accessed, added, deleted, and the like.
S102: and storing the data object into a memory in an extensible data structure.
Because flattened data structures do not facilitate processing of data objects, expandable data structures facilitate processing of data objects, data objects are stored in memory in an expandable data structure after the data objects are read to the memory.
In particular, the flattened data structure may be converted into an extensible data structure by an extension function.
The execution logic of the extended function is as follows:
creating a flattened data structure stored data object;
Initializing a data object stored in an extensible data structure, comprising: initializing a function in a data object of the expandable data structure storage, and creating a structure in the data object of the expandable data structure storage;
copying the data object stored in the flattened data structure obtained from the external memory to the created data object stored in the flattened data structure;
inserting data of the flattened data structure stored data object into the expandable data structure stored data object;
the data object stored according to the expandable data structure returns a pointer to the expandable data structure that is readable and writable.
S103: the data objects are processed in the memory in an expandable data structure, and are transferred between the modules of the memory in an expandable data structure.
Because the expandable data structure is convenient for processing the data object, the expandable data structure is used for processing the data object in the memory, and the expandable data structure is used for transferring among the modules of the memory, namely the expandable data structure is used for transferring and processing all the time in the memory, so that the transformation of the data structure in the transferring process and the transformation of the data structure again in the processing process are avoided.
In this embodiment, the data objects of the aggregate data type stored in the flattened data structure are obtained from the external memory, the data objects are stored in the internal memory in the expandable data structure, the data objects are processed in the internal memory in the expandable data structure, and the data objects are transferred in the expandable data structure between the modules of the internal memory, that is, the data objects are stored in the expandable data structure in the internal memory, and the data structures of the data objects are transferred in the expandable data structure between the modules of the internal memory, so that the data structure of the data objects is not required to be converted by the modules of the internal memory, and the processing efficiency of the aggregate data type is improved.
Fig. 2 is a flow chart of another embodiment of a method for processing aggregate data types provided in the present disclosure, and fig. 2 is a flowchart of an embodiment shown in fig. 1, further including, before S101:
s100: registering the expandable data structure in a database management system to enable each module in the memory to identify data objects communicated in the expandable data structure.
Alternatively, the extensible data structure may be declared as a global variable in the database management system.
Before declaring the expandable data structure as a global variable, aggregate data types can be defined first, and keywords and grammar rules of the expandable data structure can be determined; and adding the keywords and grammar rules into the definition of the aggregate data type.
Two data structures defining aggregate data types:
Wherein the flattened data structure points to a contiguous block of memory space, comprising the following fields: the method comprises the steps of obtaining the size of a whole memory occupied by a data object of a set data type from a memory, the first address offset of non-null data in the data object of the set data type and the data object of a flattened data structure, and the first address offset of null data in the data object of the set data type and the data object of the flattened data structure. The flattened data structure defines only header information of data objects of the aggregate data type, followed by a type information table, non-null data information and a null mapping information table of data objects of the aggregate data type. Flattened data structures can stretch complex aggregate data types into flat structures.
The extensible data structure includes the following fields: the existing data structure 'ExpandObjectHeader', the type information of the aggregate data type, the nesting layer number of the aggregate data type, the real storage space of the data object of the aggregate data type, the value of the element actually stored by the data object of the aggregate data type and the flattened data structure corresponding to the data object of the aggregate data type. Wherein the type information of the aggregate data type includes the type information of the key and the type information of the value, the key-value of the data object of the aggregate data type can be stored by using an array or an associated container in a standard template Library (STANDARD TEMPLATE Library, STL), and the real storage space of the data object of the aggregate data type is an address pointing to the array or the associated container. The extensible data structure may be considered a subclass of the existing data structure "ExpandObjectHeader" and may inherit the properties and methods of "ExpandObjectHeader".
The definition of a flattened data structure may be achieved as follows:
The flattened data structures "CollectionType", "CollectionType" are defined to point to a block of contiguous memory space, where the "v1_len" field indicates the size of the entire memory space, the "max_index" field indicates the next key of the nested table, the "limit_idx" field indicates the constraint index of the array, the "ndims" field indicates the dimension of the aggregate data, the "dataoffset" field indicates the address offset of non-null data, and the "nuloffset" field indicates the address offset of null data. The data structure "CollectionType" defines only header information of the aggregate data object, followed by a null mapping information table of "ndim x sizeof (int)" size and non-null data information. The structure can stretch complex aggregate data types into a flat structure as shown in fig. 3.
The definition of the extensible data structure may be achieved by:
The elements in the definition extensible data structures "ExpandCollectionHeader", "ExpandCollectionHeader" record type information for the aggregate data type, including key-value (key-values) type information, the number of nesting levels for the aggregate type, the actual storage space for the aggregate type, and the value of the element that the aggregate type actually stores. Therefore, the extensible data structure can be conveniently subjected to calculation and assignment operations. The "hdr" field in "ExpandCollectionHeader" represents the existing data structure ExpandObjectHeader, the "ct_magic" field represents the size of the scalable data structure, the "type" field represents the information of the aggregate data, the "max_index" field represents the next key of the nested table, the "limit_idx" field represents the constraint index of the array, the "ndims" field represents the dimension of the aggregate data, the "valcxt" field represents a data structure object describing the memory information, the "Values" field represents an object of the Datum data structure using STL graphs or arrays to store key-value data, the "flat_size" field represents the size of the flattened data structure "CollectionType", the "fvalue" field represents the address of the flattened data structure "CollectionType", and the "null_size" field represents the storage space required for the hollow data of the aggregate data object. "ExpandCollectionHeader" can be considered as a subclass of the existing data structure "ExpandObjectHeader", with the front field of the "ExpandCollectionHeader" structure containing all the fields of "ExpandObjectHeader" and the rear field being "CollectionType". Thus, it can be pointed to by a pointer of the base class "ExpandObjectHeader" and can be used as parameter transfer, etc. The entire data structure "ExpandCollectionHeader" is used to store the type information of the collection, and its basic information is mainly defined generic type information, such as type information exemplified by a generic type nested table. The field typkey is used to store the type of key of the set type, which is always a4 byte integer for nested tables and variable arrays, while the key type of the associated array depends on the user-defined type, and the field typdatatype is used to store the type of element the set type stores.
Optionally, one possible implementation of S102 is:
searching in a name space according to the name of the data type;
acquiring an extensible data structure corresponding to the aggregate data type;
the data object is stored to the memory according to the extensible data structure.
Fig. 4 is a flow chart of an embodiment of a method for processing aggregate data types provided in the present disclosure, and fig. 4 is a flowchart of an embodiment shown in fig. 1 or fig. 2, further including:
S1004: data objects stored in the memory in the expandable data structure are converted into flattened data structures and stored in the external memory.
Since the flattened data structure can save storage space, the data objects are stored in the flattened data structure in the external memory.
In particular, the extensible data structure may be translated into a flattened data structure by a flattening function.
The execution logic of the flattening function is as follows:
calculating the required storage space according to the data objects stored in the expandable data structure;
distributing corresponding storage space according to the calculated size of the storage space;
And adding the data of the data object stored in the expandable data structure into the data object of the flattened data structure, so as to realize flattening of the data object stored in the expandable data structure.
According to the embodiment, the flattened data structure is stored in the external memory, so that the storage space is saved, and the resource utilization rate is improved.
Fig. 5 is a schematic structural diagram of a processing apparatus for aggregating data types provided in the present disclosure, where the apparatus in this embodiment includes: an acquisition module 501, a storage module 502 and a processing module 503.
The acquiring module 501 is configured to acquire a data object from a memory, where the data object is of an aggregate data type, and the data object is stored in the memory in a flattened data structure;
a storage module 502, configured to store the data object into a memory in an expandable data structure;
A processing module 503, configured to process the data object in the memory in an expandable data structure, and transfer the data object in the expandable data structure between the modules in the memory.
Optionally, the processing module 503 is further configured to register the expandable data structure in a database management system, so that each module in the memory can identify a data object transferred in the expandable data structure.
Optionally, the processing module 503 is specifically configured to declare the extensible data structure as a global variable in the database management system.
Optionally, the processing module 503 is further configured to determine keywords and grammar rules of the expandable data structure; and adding the keywords and grammar rules into the definition of the aggregate data type.
Optionally, the processing module 503 is specifically configured to search in a namespace according to a name of a data type; acquiring an extensible data structure corresponding to the aggregate data type; and storing the data object into the memory according to the expandable data structure.
Optionally, the storage module 502 is further configured to convert the data objects stored in the memory with the expandable data structure into a flattened data structure and store the flattened data structure into the external memory.
The foregoing apparatus embodiments, corresponding to the technical solutions that may be used to execute any of the method embodiments shown in fig. 1, fig. 2 or fig. 4, have similar implementation principles and technical effects, and are not repeated herein.
Fig. 6 is a schematic structural diagram of a database management system provided in the present disclosure, including: a processor 601, where the processor 601 is configured to execute a computer program stored in a memory 602, where the computer program when executed by the processor 601 implements a technical solution of any one of the method embodiments shown in fig. 1, 2 or 4.
The present disclosure also provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the technical solution of any of the method embodiments shown in fig. 1, 2 or 4.
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, 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 … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing is merely a specific embodiment of the disclosure to enable one skilled in the art to understand or practice the disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown and described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method for processing aggregate data types, comprising:
Obtaining a data object from a memory, wherein the data object is of an aggregate data type, and the data object is stored in the memory in a flattened data structure;
storing the data object into a memory in an expandable data structure;
processing the data object in the memory by using an expandable data structure, and transmitting the data object between modules of the memory by using the expandable data structure;
Wherein, v1_len field in the flattened data structure represents the size of the whole storage space, max_index field represents the next key word of the nested table, limit_idx field represents the limit index of the array, ndims field represents the dimension of the aggregate data, dataoffset field represents the address offset of non-null data, and nuloffset field represents the address offset of null data;
The hdr field in the expandable data structure represents the existing data structure ExpandObjectHeader, the ct_magic field represents the size of the expandable data structure, the type field represents the information of the aggregate data, the max_index field represents the next key of the nested table, the limit_idx field represents the constraint index of the array, the ndims field represents the dimension of the aggregate data, the valcxt field represents a data structure object describing the memory information, the Values represents an object of the Datum data structure using STL graphs or arrays to store keyvalue data, the flat_size field represents the size of the flattened data structure, the fvalue field represents the address of the flattened data structure, and the nullsize field represents the storage space required for the data in the aggregate data object.
2. The method of claim 1, wherein prior to storing the data object in the memory in the expandable data structure, further comprising:
Registering the expandable data structure in a database management system to enable each module in the memory to identify data objects communicated in the expandable data structure.
3. The method of claim 2, wherein the registering the extensible data structure in a database management system comprises:
The extensible data structure is declared as a global variable in a database management system.
4. A method according to claim 3, characterized in that the method further comprises:
determining keywords and grammar rules of the extensible data structure;
And adding the keywords and grammar rules into the definition of the aggregate data type.
5. The method of claim 4, wherein the step of determining the position of the first electrode is performed,
The storing the data object in the memory in the expandable data structure comprises:
searching in a name space according to the name of the data type;
acquiring an extensible data structure corresponding to the aggregate data type;
And storing the data object into the memory according to the expandable data structure.
6. The method of any one of claims 1-5, further comprising:
data objects stored in the memory in the expandable data structure are converted into flattened data structures and stored in the external memory.
7. A processing apparatus for aggregating data types, comprising:
The system comprises an acquisition module, a data storage module and a data storage module, wherein the acquisition module is used for acquiring a data object from a memory, the data object is of an aggregate data type, and the data object is stored in the memory in a flattened data structure;
the storage module is used for storing the data object into a memory in an expandable data structure;
the processing module is used for processing the data object in the memory by using an expandable data structure and transmitting the data object among the modules of the memory by using the expandable data structure;
Wherein, v1_len field in the flattened data structure represents the size of the whole storage space, max_index field represents the next key word of the nested table, limit_idx field represents the limit index of the array, ndims field represents the dimension of the aggregate data, dataoffset field represents the address offset of non-null data, and nuloffset field represents the address offset of null data;
The hdr field in the expandable data structure represents the existing data structure ExpandObjectHeader, the ct_magic field represents the size of the expandable data structure, the type field represents the information of the aggregate data, the max_index field represents the next key of the nested table, the limit_idx field represents the constraint index of the array, the ndims field represents the dimension of the aggregate data, the valcxt field represents a data structure object describing the memory information, the Values represents an object of the Datum data structure using STL graphs or arrays to store keyvalue data, the flat_size field represents the size of the flattened data structure, the fvalue field represents the address of the flattened data structure, and the nullsize field represents the storage space required for the data in the aggregate data object.
8. The apparatus of claim 7, wherein the storage module is further configured to convert data objects stored in the memory in the scalable data structure into flattened data structures for storage in the external memory.
9. A database management system, comprising: a processor for executing a computer program stored in a memory, which when executed by the processor carries out the steps of the method according to any one of claims 1-6.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1-6.
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