CN114185934B - Indexing and query method and system based on Tiandun database column storage - Google Patents
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Abstract
The invention discloses an index and query method based on storage of a Tiandun database column, which comprises the steps of preprocessing received data through a preposed database, setting a table segment containing a fixed amount in the preposed database, caching first data to be stored in a local database in the preposed database line by line, determining a first data sequence, sequencing data blocks of the received first data file according to the first data sequence by the preposed database, taking the first data file as standard data, receiving a second data file, and sequencing the second data file according to the first data sequence in the preposed database if the data amount of the second data file is judged to be smaller than that of the first data file; the local database stores the column values of the first data file and the record identifications of the data blocks as value data into the data blocks, sorts the data blocks according to the size of the column values, establishes indexes for the data blocks in the preposed database and the data blocks in the local database, and queries data according to the generated index data blocks when querying.
Description
Technical Field
The invention relates to the technical field of databases, in particular to an indexing and query method and system based on Tiandun database column storage.
Background
Databases are electronic filing systems that store data in a structured manner. The primary storage structure in the database is a table. The database may contain multiple tables, and each table may hold a particular type of information. Database tables store and organize data in horizontal rows and vertical columns. A row typically corresponds to a real-world entity or relationship that represents a single record in a table. Columns may indicate specific attributes of these entities or relationships, such as "name", "address", or "phone number". For example, company X may have a database containing a "customer" table listing the names, addresses and telephone numbers of its customers. Each row may represent a single customer and the columns may represent the name, address and telephone number of each customer.
Databases are typically stored in one-dimensional computer memory. Thus, a two-dimensional database table must be mapped into a one-dimensional data structure for storage in the database. One mapping approach involves storing tables in a database by rows (i.e., a row-oriented storage model). This approach may keep information about a single entity together. For example, storing by row may first store all information about a first customer, then all information about a second customer, and so on. Alternatively, the tables may be stored in the database by rows (i.e., column-oriented storage models). This approach may keep the same attributes of different entities together. For example, storing by column may first store the names of all customers, then store the addresses of all customers, and so on.
The writing of the row store is done once. If such a write is built on the file system of the operating system, success or failure of the write process can be guaranteed and the integrity of the data can be determined accordingly. Column storage requires splitting a row of records into single columns for storage, and the number of writes is significantly greater than row storage (meaning that the number of head schedules, which is time-consuming, typically 1ms to 10 ms), plus the time it takes for the head to move and position on the disk, which is more time consuming in practice. Therefore, row storage has a great advantage in writing.
In many column-oriented database systems, data for all columns of a single row is distributed across a storage disk or multiple storage disks. For example, data blocks of one column may be stored in a particular location on disk storage, while data blocks of other columns may be stored in other locations that are not physically adjacent. Thus, accessing a particular row will require accessing multiple disk blocks distributed across the storage disk or disks, which can result in significant latency. Unfortunately, many typical OLTP queries often request such operations.
Column storage is not as good as row storage in terms of writing efficiency and data integrity, and has the advantage that redundant data cannot be generated in the reading process, which is very important for the field of large data processing with low requirement on data integrity, such as the internet.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention discloses an indexing and query method based on storage of a Tiandun database column, which comprises the following steps:
step 1, establishing a transmission link from a cloud data file to a local, receiving the data file from a cloud database, preprocessing the received data by a pre-database, setting a table segment containing a fixed amount in the pre-database, caching first data to be stored in the local database in the pre-database line by line, determining a first data sequence, and sequencing data blocks of the received first data file by the pre-database according to the first data sequence, wherein the first data file consists of a plurality of data blocks;
step 2, taking the first data file as standard data, and directly storing the data file larger than the first data file by a local database;
step 3, after the preposed database finishes receiving the first data file, receiving a second data file, and if the data volume of the second data file is judged to be smaller than that of the first data file, sequencing the second data file in the preposed database according to the first data sequence;
step 4, the local database stores the column values of the first data file and the record marks of the data blocks as value data into the data blocks and sorts the data files according to the column values, and when the data files to be received are judged to be smaller than the first data file, the record marks and the serial numbers of the data blocks storing the value data are stored into new data blocks as connection data and sorted according to the size of the record marks;
and 5, establishing indexes for the data blocks in the preposed database and the data blocks in the local database, generating index data blocks, and inquiring the data according to the generated index data blocks during inquiry.
Furthermore, row storage is adopted in the preposed database, and column storage is adopted in the local database.
Furthermore, the preposed database simplifies the query operation steps through an index mechanism and table partitioning, and sends the index value of the query result to the local database for storage as the index data block of the preposed storage.
Furthermore, when data query is performed, the query instruction is executed in the pre-database and the local database at the same time.
Furthermore, when data query is performed, retrieval is performed in the local database, and the local database queries the pre-database according to the pre-stored index data block.
Furthermore, the local storage data is compressed through an increment compression and prefix compression algorithm so as to reduce the space occupied by the local storage data.
The invention further discloses an indexing and query system based on the storage of the Tiandun database column, which comprises: the method comprises the steps that a front database and a local database are established, a transmission link from a cloud data file to the local is established, the data file is received from the cloud database, the received data needs to be preprocessed through the front database, a table segment containing a fixed amount is arranged in the front database, first data to be stored in the local database are cached in the front database line by line, a first data sequence is determined, the front database sorts data blocks of the received first data file according to the first data sequence, and the first data file is composed of a plurality of data blocks; taking the first data file as standard data, and directly storing the data file larger than the first data file by a local database; after the front database finishes receiving the first data file, receiving a second data file, and if the data volume of the second data file is judged to be smaller than that of the first data file, sequencing the second data file in the front database according to a first data sequence; the local database stores the column values of the first data file and the record identifications of the data blocks as value data into the data blocks and sorts the data blocks according to the size of the column values, and stores the sequence numbers of the record identifications and the data blocks storing the value data into new data blocks as connection data and sorts the data blocks according to the size of the record identifications after judging that the data file to be received is smaller than the first data file; and establishing indexes for the data blocks in the preposed database and the data blocks in the local database to generate index data blocks, and inquiring the data according to the generated index data blocks during inquiry.
Furthermore, row storage is adopted in the preposed database, a column storage mode is adopted in the local database, the preposed database simplifies the query operation steps through an index mechanism and table partitioning, and the index value of the query result is sent to the local database for storage as the index data block of the preposed storage.
Furthermore, the retrieval is firstly carried out in the local database, the local database stores the preposed database according to the index data block which is stored in the preposed manner, the retrieval is firstly carried out in the local database when the data query is carried out, and the local database queries the preposed database according to the index data block which is stored in the preposed manner.
Furthermore, the local storage data is compressed through an increment compression and prefix compression algorithm so as to reduce the space occupied by the local storage data.
Compared with the prior art, the method has the advantages that the row storage is adopted by adding the preposed database, the column storage is adopted in the local database, the writing-in of the row storage is completed at one time, the success or failure of the writing-in process can be ensured for the data with large data volume, the integrity of the data can be determined, the preposed database is adopted for classifying the storage, the storage is respectively carried out according to the size and the importance of the file, and the double indexes are constructed, so that the query process is quicker.
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The invention will be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the embodiments. In the drawings, like reference numerals designate corresponding parts throughout the different views.
FIG. 1 is a flow chart of a method of indexing and querying based on a tiandune database column store of the present invention.
Detailed Description
Example one
As shown in fig. 1, the present embodiment discloses an indexing and querying method based on storage of a tiandun database column, which includes the following steps:
step 1, establishing a transmission link from a cloud data file to a local, receiving the data file from a cloud database, preprocessing the received data by a pre-database, setting a table segment containing a fixed amount in the pre-database, caching first data to be stored in the local database in the pre-database line by line, determining a first data sequence, and sequencing data blocks of the received first data file by the pre-database according to the first data sequence, wherein the first data file consists of a plurality of data blocks;
step 2, taking the first data file as standard data, and directly storing the data file larger than the first data file by a local database;
step 3, after the preposed database finishes receiving the first data file, receiving a second data file, and if the data volume of the second data file is judged to be smaller than that of the first data file, sequencing the second data file in the preposed database according to the first data sequence;
step 4, the local database stores the column values of the first data file and the record marks of the data blocks as value data into the data blocks and sorts the data blocks according to the column values, and when the data file to be received is judged to be smaller than the first data file, the sequence numbers of the record marks and the data blocks storing the value data are stored into a new data block as connection data and sorted according to the size of the record marks;
and 5, establishing indexes for the data blocks in the pre-database and the data blocks in the local database, generating index data blocks, and inquiring data according to the generated index data blocks during inquiry.
Furthermore, row storage is adopted in the preposed database, and column storage is adopted in the local database.
Furthermore, the preposed database simplifies the query operation steps through an index mechanism and table partitioning, and sends the index value of the query result to the local database for storage as the index data block of the preposed storage.
Furthermore, when data query is performed, the query instruction is executed in the pre-database and the local database at the same time.
Furthermore, when data query is performed, retrieval is performed in a local database, and the local database queries the pre-database according to the index data block stored in the pre-database.
Furthermore, the local storage data is compressed through an increment compression and prefix compression algorithm so as to reduce the space occupied by the local storage data.
The invention further discloses an indexing and query system based on the storage of the Tiandun database column, which comprises: the method comprises the steps that a preposed database and a local database are established, a transmission link from a cloud data file to the local is established, the data file is received from the cloud database, the received data needs to be preprocessed through the preposed database, a table segment containing a fixed amount is arranged in the preposed database, first data to be stored in the local database are cached in the preposed database line by line, a first data sequence is determined, the preposed database sequences data blocks of the received first data file according to the first data sequence, and the first data file is composed of a plurality of data blocks; taking the first data file as standard data, and directly storing the data file larger than the first data file by a local database; after the front database finishes receiving the first data file, receiving a second data file, and if the data volume of the second data file is judged to be smaller than that of the first data file, sequencing the second data file in the front database according to a first data sequence; the local database stores the column values of the first data file and the record identifications of the data blocks as value data into the data blocks and sorts the data blocks according to the size of the column values, and stores the sequence numbers of the record identifications and the data blocks storing the value data into new data blocks as connection data and sorts the data blocks according to the size of the record identifications after judging that the data file to be received is smaller than the first data file; and establishing indexes for the data blocks in the preposed database and the data blocks in the local database to generate index data blocks, and inquiring the data according to the generated index data blocks when inquiring.
Furthermore, row storage is adopted in the preposed database, a column storage mode is adopted in the local database, the preposed database simplifies the query operation steps through an index mechanism and table partitioning, and the index value of the query result is sent to the local database for storage as the index data block of the preposed storage.
Furthermore, the retrieval is firstly carried out in the local database, the local database stores the preposed database according to the index data block which is stored in the preposed manner, the retrieval is firstly carried out in the local database when the data query is carried out, and the local database queries the preposed database according to the index data block which is stored in the preposed manner.
Furthermore, the local storage data is compressed through an increment compression and prefix compression algorithm so as to reduce the space occupied by the local storage data.
It should also be noted that 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 phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of other like elements in a process, method, article, or apparatus comprising the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.
Although the invention has been described above with reference to various embodiments, it should be understood that many changes and modifications may be made without departing from the scope of the invention. It is therefore intended that the foregoing detailed description be regarded as illustrative rather than limiting, and that it be understood that it is the following claims, including all equivalents, that are intended to define the spirit and scope of this invention. The above examples are to be construed as merely illustrative and not limitative of the remainder of the disclosure. After reading the description of the present invention, the skilled person can make various changes or modifications to the invention, and these equivalent changes and modifications also fall into the scope of the invention defined by the claims.
Claims (9)
1. An indexing and query method based on storage of a Tiandun database column is characterized by comprising the following steps:
step 1, establishing a transmission link from a cloud data file to a local, receiving the data file from a cloud database, preprocessing the received data by a pre-database, setting a table segment containing a fixed amount in the pre-database, caching first data to be stored in the local database in the pre-database line by line, determining a first data sequence, and sequencing data blocks of the received first data file by the pre-database according to the first data sequence, wherein the first data file consists of a plurality of data blocks;
step 2, taking the first data file as standard data, and directly storing the data file larger than the first data file by a local database;
step 3, after the front database finishes receiving the first data file, receiving a second data file, and if the data volume of the second data file is judged to be smaller than that of the first data file, sequencing the second data file in the front database according to the first data sequence;
step 4, the local database stores the column values of the first data file and the record marks of the data blocks as value data into the data blocks and sorts the data files according to the column values, and when the data files to be received are judged to be smaller than the first data file, the record marks and the serial numbers of the data blocks storing the value data are stored into new data blocks as connection data and sorted according to the size of the record marks;
and 5, establishing indexes for the data blocks in the pre-database and the data blocks in the local database, generating index data blocks, and inquiring data according to the generated index data blocks during inquiry.
2. The method for indexing and querying on the basis of the column storage of the tiandune database as claimed in claim 1, wherein the row storage is adopted in the pre-database, and the column storage is adopted in the local database.
3. The method for indexing and querying on the basis of the paradox database column storage as claimed in claim 2, wherein the pre-database simplifies the query operation steps through an indexing mechanism and table partitioning, and sends the index value of the query result to the local database storage as the index data block of the pre-database storage.
4. The method as claimed in claim 1, wherein the query command is executed in both the pre-database and the local database during the data query.
5. The method for indexing and querying based on tiandun database column storage as claimed in claim 1, wherein when data query is performed, the data is firstly retrieved from the local database, and the local database queries the pre-database according to the index data block of the pre-storage.
6. The indexing and querying method based on tiandun database column storage according to claim 1, wherein the local storage data is compressed by an incremental compression and prefix compression algorithm to reduce the space occupied by the local storage data.
7. An indexing and querying system based on storage of a tiandun database column, the system comprising: the method comprises the steps that a preposed database and a local database are established, a transmission link from a cloud data file to the local is established, the data file is received from the cloud database, the received data needs to be preprocessed through the preposed database, a table segment containing a fixed amount is arranged in the preposed database, first data to be stored in the local database are cached in the preposed database line by line, a first data sequence is determined, the preposed database sequences data blocks of the received first data file according to the first data sequence, and the first data file is composed of a plurality of data blocks; taking the first data file as standard data, and directly storing the data file larger than the first data file by a local database; after the front database finishes receiving the first data file, receiving a second data file, and if the data volume of the second data file is judged to be smaller than that of the first data file, sequencing the second data file in the front database according to a first data sequence; the local database stores the column values of the first data file and the record identifications of the data blocks as value data into the data blocks and sorts the data blocks according to the size of the column values, and stores the sequence numbers of the record identifications and the data blocks storing the value data into new data blocks as connection data and sorts the data blocks according to the size of the record identifications after judging that the data file to be received is smaller than the first data file; and establishing indexes for the data blocks in the preposed database and the data blocks in the local database to generate index data blocks, and inquiring the data according to the generated index data blocks when inquiring.
8. The indexing and querying system based on the tiandune database column storage as claimed in claim 7, wherein the pre-database adopts row storage in the pre-database and column storage in the local database, the pre-database simplifies the query operation steps through the indexing mechanism and table partitioning, and sends the index value of the query result as the index data block of the pre-storage to the local database storage.
9. The system of claim 7, wherein the locally stored data is compressed by an incremental compression and prefix compression algorithm to reduce the space occupied by the locally stored data.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102156714A (en) * | 2011-03-22 | 2011-08-17 | 清华大学 | Method for realizing self-adaptive vertical divided relational database and system thereof |
| CN107077480A (en) * | 2014-09-17 | 2017-08-18 | 华为技术有限公司 | The method and system of column storage database is adaptively built from the row data storage storehouse of current time based on query demand |
Family Cites Families (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4076415B2 (en) * | 2002-09-19 | 2008-04-16 | 富士通株式会社 | SEARCH METHOD, SEARCH DEVICE, AND COMPUTER PROGRAM |
| CN101727465B (en) * | 2008-11-03 | 2011-12-21 | 中国移动通信集团公司 | Methods for establishing and inquiring index of distributed column storage database, device and system thereof |
| CN101751406B (en) * | 2008-12-18 | 2012-01-04 | 赵伟 | Method and device for realizing column storage based relational database |
| US8468146B2 (en) * | 2010-04-13 | 2013-06-18 | Infosys Limited | System and method for creating search index on cloud database |
| CN102890721B (en) * | 2012-10-16 | 2016-03-30 | 苏州迈科网络安全技术股份有限公司 | Based on database building method and the system of row memory technology |
| CN105468642A (en) * | 2014-09-09 | 2016-04-06 | 杭州海康威视数字技术股份有限公司 | Data storage method and apparatus |
| CN104881481B (en) * | 2015-06-03 | 2018-05-01 | 广东省机电设备招标有限公司 | A kind of method and device for accessing magnanimity time series data |
| CN108427748A (en) * | 2018-03-12 | 2018-08-21 | 北京奇艺世纪科技有限公司 | Distributed data base secondary index querying method, device and server |
| KR20190134115A (en) * | 2018-05-25 | 2019-12-04 | 주식회사 티맥스데이터 | Method and apparatus for providing efficient indexing and computer program included in computer readable medium therefor |
| CN109086456B (en) * | 2018-08-31 | 2020-11-03 | 中国联合网络通信集团有限公司 | Data indexing method and device |
| CN111078705A (en) * | 2019-12-20 | 2020-04-28 | 南京聚力云成电子科技有限公司 | Spark platform based data index establishing method and data query method |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102156714A (en) * | 2011-03-22 | 2011-08-17 | 清华大学 | Method for realizing self-adaptive vertical divided relational database and system thereof |
| CN107077480A (en) * | 2014-09-17 | 2017-08-18 | 华为技术有限公司 | The method and system of column storage database is adaptively built from the row data storage storehouse of current time based on query demand |
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Effective date of registration: 20231009 Address after: 300000 Tianjin Binhai New Area Tianjin Pilot Free Trade Zone (Dongjiang Bonded Port Area), No. 6975 Asia Road, Financial and Trade Center South Zone, 1-1-2019 Patentee after: Haitong Hengxin International Finance Leasing (Tianjin) Co.,Ltd. Address before: 510640 0601, building 07, No. 235, Gaotang Road, Tianhe District, Guangzhou City, Guangdong Province (only for office use, not for plant) Patentee before: GUANGZHOU CHENCHUANG TECHNOLOGY DEVELOPMENT Co.,Ltd. |
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Application publication date: 20220315 Assignee: GUANGZHOU CHENCHUANG TECHNOLOGY DEVELOPMENT Co.,Ltd. Assignor: Haitong Hengxin International Finance Leasing (Tianjin) Co.,Ltd. Contract record no.: X2024980000618 Denomination of invention: A method and system for indexing and querying based on column storage in the Tiandun database Granted publication date: 20221014 License type: Exclusive License Record date: 20240112 |
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