CN114185934A - Indexing and query method and system based on Tiandun database column storage - Google Patents
Indexing and query method and system based on Tiandun database column storage Download PDFInfo
- Publication number
- CN114185934A CN114185934A CN202111534161.5A CN202111534161A CN114185934A CN 114185934 A CN114185934 A CN 114185934A CN 202111534161 A CN202111534161 A CN 202111534161A CN 114185934 A CN114185934 A CN 114185934A
- Authority
- CN
- China
- Prior art keywords
- data
- database
- data file
- local
- storage
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 28
- 238000012163 sequencing technique Methods 0.000 claims abstract description 11
- 238000007781 pre-processing Methods 0.000 claims abstract description 4
- 230000006835 compression Effects 0.000 claims description 12
- 238000007906 compression Methods 0.000 claims description 12
- 230000005540 biological transmission Effects 0.000 claims description 6
- 238000000638 solvent extraction Methods 0.000 claims description 5
- 238000005192 partition Methods 0.000 claims 1
- 238000013459 approach Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000004590 computer program Methods 0.000 description 2
- 238000013507 mapping Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
Images
Classifications
-
- 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
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2474—Sequence data queries, e.g. querying versioned data
-
- 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
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Software Systems (AREA)
- Computational Linguistics (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Probability & Statistics with Applications (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
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 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 and the record identifications of the data blocks into the data blocks as value data, 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 10ms), 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 storage 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 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 larger than the first data file in 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 and the record marks of the data blocks into the data blocks as value data and sorts the data blocks according to the size of 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 are 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 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 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 larger than the first data file in 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 and the record identifications of the data blocks into the data blocks as value data and sorts the data blocks according to the size of the column values, and stores the sequence numbers of the data blocks of the record identifications and the stored value data into a new data block 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.
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.
Drawings
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 an 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 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 larger than the first data file in 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 and the record marks of the data blocks into the data blocks as value data and sorts the data blocks according to the size of 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 are 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 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 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 larger than the first data file in 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 and the record identifications of the data blocks into the data blocks as value data and sorts the data blocks according to the size of the column values, and stores the sequence numbers of the data blocks of the record identifications and the stored value data into a new data block 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 phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises 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 the like) 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 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 (10)
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 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 larger than the first data file in 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 and the record marks of the data blocks into the data blocks as value data and sorts the data blocks according to the size of 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 are 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 indexing and querying method based on tiandun database column storage as claimed in claim 1, wherein row storage is adopted in the pre-database, and column storage is adopted in the local database.
3. The method as claimed in claim 2, wherein the index and query operations of the front database are simplified by the index mechanism and the table partition, and the index value of the query result is sent to the local database as the index data block of the front database.
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 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 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 larger than the first data file in 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 and the record identifications of the data blocks into the data blocks as value data and sorts the data blocks according to the size of the column values, and stores the sequence numbers of the data blocks of the record identifications and the stored value data into a new data block 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 system of claim 7, wherein the index and query system based on the column storage of the tiandun database adopts row storage in the pre-database and column storage in the local database, the pre-database simplifies query operation steps through an index mechanism and table partitioning, and sends an index value of a query result as an index data block of the pre-storage to the local database for storage.
9. The system according to claim 7, wherein the search is performed in a local database, the local database stores the pre-database according to the index data block stored in the pre-database, the search is performed in the local database when the data search is performed, and the local database searches the pre-database according to the index data block stored in the pre-database.
10. 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.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111534161.5A CN114185934B (en) | 2021-12-15 | 2021-12-15 | Indexing and query method and system based on Tiandun database column storage |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111534161.5A CN114185934B (en) | 2021-12-15 | 2021-12-15 | Indexing and query method and system based on Tiandun database column storage |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114185934A true CN114185934A (en) | 2022-03-15 |
| CN114185934B CN114185934B (en) | 2022-10-14 |
Family
ID=80543928
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111534161.5A Active CN114185934B (en) | 2021-12-15 | 2021-12-15 | Indexing and query method and system based on Tiandun database column storage |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114185934B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116009775A (en) * | 2022-12-20 | 2023-04-25 | 广州辰创科技发展有限公司 | Database memory management system and method |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004110586A (en) * | 2002-09-19 | 2004-04-08 | Fujitsu Ltd | Retrieval method, retrieval device, and computer program |
| CN101727465A (en) * | 2008-11-03 | 2010-06-09 | ***通信集团公司 | Methods for establishing and inquiring index of distributed column storage database, device and system thereof |
| CN101751406A (en) * | 2008-12-18 | 2010-06-23 | 赵伟 | Method and device for realizing column storage based relational database |
| CN102156714A (en) * | 2011-03-22 | 2011-08-17 | 清华大学 | Method for realizing self-adaptive vertical divided relational database and system thereof |
| US20110252018A1 (en) * | 2010-04-13 | 2011-10-13 | Infosys Technologies Limited | System and method for creating search index on cloud database |
| CN102890721A (en) * | 2012-10-16 | 2013-01-23 | 苏州迈科网络安全技术股份有限公司 | Database establishment method and database establishment system based on column storage technology |
| CN104881481A (en) * | 2015-06-03 | 2015-09-02 | 安科智慧城市技术（中国）有限公司 | Method and device for accessing mass time sequence data |
| 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 |
| 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 |
| 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 |
| CN109086456A (en) * | 2018-08-31 | 2018-12-25 | 中国联合网络通信集团有限公司 | data index method and device |
| 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 |
| 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 |
-
2021
- 2021-12-15 CN CN202111534161.5A patent/CN114185934B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004110586A (en) * | 2002-09-19 | 2004-04-08 | Fujitsu Ltd | Retrieval method, retrieval device, and computer program |
| CN101727465A (en) * | 2008-11-03 | 2010-06-09 | ***通信集团公司 | Methods for establishing and inquiring index of distributed column storage database, device and system thereof |
| US20110314027A1 (en) * | 2008-11-03 | 2011-12-22 | China Mobile Communications Corporation | Index building, querying method, device, and system for distributed columnar database |
| CN101751406A (en) * | 2008-12-18 | 2010-06-23 | 赵伟 | Method and device for realizing column storage based relational database |
| US20110252018A1 (en) * | 2010-04-13 | 2011-10-13 | Infosys Technologies Limited | System and method for creating search index on cloud database |
| CN102156714A (en) * | 2011-03-22 | 2011-08-17 | 清华大学 | Method for realizing self-adaptive vertical divided relational database and system thereof |
| CN102890721A (en) * | 2012-10-16 | 2013-01-23 | 苏州迈科网络安全技术股份有限公司 | Database establishment method and database establishment system based on column storage 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 |
| 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 |
| CN104881481A (en) * | 2015-06-03 | 2015-09-02 | 安科智慧城市技术（中国）有限公司 | Method and device for accessing mass time sequence 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 |
| CN109086456A (en) * | 2018-08-31 | 2018-12-25 | 中国联合网络通信集团有限公司 | data index 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 |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116009775A (en) * | 2022-12-20 | 2023-04-25 | 广州辰创科技发展有限公司 | Database memory management system and method |
| CN116009775B (en) * | 2022-12-20 | 2024-04-02 | 广州辰创科技发展有限公司 | Database memory management system and method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114185934B (en) | 2022-10-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US5809494A (en) | Method for rapidly and efficiently hashing records of large databases | |
| US5560006A (en) | Entity-relation database | |
| JP5342958B2 (en) | How to query the structure of compressed data | |
| US8799229B2 (en) | Searchable archive | |
| US6049804A (en) | Method and apparatus for segmenting a database | |
| US7689574B2 (en) | Index and method for extending and querying index | |
| CN107491487B (en) | Full-text database architecture and bitmap index creation and data query method, server and medium | |
| US7263520B2 (en) | Fast aggregation of compressed data using full table scans | |
| WO2004104774A2 (en) | Limiting scans of loosely ordered and/or grouped relations using nearly ordered maps | |
| CN103218365A (en) | SS Table file data processing method and system | |
| US5742809A (en) | Database generic composite structure processing system | |
| CN114185934B (en) | Indexing and query method and system based on Tiandun database column storage | |
| EP0583108B1 (en) | Entity-relation database | |
| US7870138B2 (en) | File storage and retrieval method | |
| CN113157692B (en) | Relational memory database system | |
| CN114564501A (en) | Database data storage and query methods, devices, equipment and medium | |
| CN114416741A (en) | KV data writing and reading method and device based on multi-level index and storage medium | |
| CN100361088C (en) | Method for realizing device test | |
| CN104765656A (en) | Backup method and device for cold data | |
| CN104834664A (en) | Optical disc juke-box oriented full text retrieval system | |
| CN117290390B (en) | Method for memory mapping on big data retrieval based on special index | |
| CN115827653B (en) | Pure column type updating method and device for HTAP and mass data | |
| US20240193142A1 (en) | Method of processing data in a database | |
| JPH0962697A (en) | Merchandise code retrieving system | |
| CN115309742A (en) | Table building method and device, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
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. |
|
| EE01 | Entry into force of recordation of patent licensing contract | ||
| EE01 | Entry into force of recordation of patent licensing contract |
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 |