CN108052599A - A kind of method and apparatus of the time series data storage of supported feature inquiry - Google Patents
A kind of method and apparatus of the time series data storage of supported feature inquiry Download PDFInfo
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- G06F16/245—Query processing
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Abstract
The present invention provides a kind of method and apparatus of the time series data storage of supported feature inquiry, including:Time series data to be stored is divided into several set of data points for including multiple continuous data points, the characteristic value of each set of data points is calculated by default characteristic function, using the timestamp of data point in each set of data points and data value as the initial data of corresponding data point set, by the information of characteristic function, characteristic information of the period information and characteristic value of each set of data points as corresponding data point set, using an original data block as the memory space of the initial data of a set of data points, the initial data of each set of data points is stored, using a characteristic block as the memory space of the characteristic information of a set of data points, the characteristic information of each set of data points is stored;The time series data stored by above-mentioned storage method had not only supported the inquiry to original time series data, but also has supported the inquiry to characteristic value.
Description
Technical field
The present invention relates to technical field of data processing, are deposited more particularly, to a kind of time series data of supported feature inquiry
The method and apparatus of storage.
Background technology
With the fast development of internet and Internet of Things, the acquisition and use of time series data (referred to as time series data)
Become more and more extensive, such as:In wind power industry, the sensor on wind turbine can be constantly be generated substantial amounts of time series data,
By can be adjusted to the real-time analysis of these data to fan condition, wind power generation efficiency is improved;It is looked forward in complex equipment
In industry, by the statistics of the history time series data to acquisition, the operating status of available each equipment.
Time series data has the characteristics that following:(1) data volume is big:One equipment enterprise often has thousands of or even up to ten thousand
Equipment, the sensor in each equipment is gathered at a time interval according to the demand used and return data, therefore, when
Ordinal number increases according to meeting is constantly quick.(2) there is unique feature:In different application fields, can be adopted for time series data
It is described with different features, for emphasizing the different characteristic of time series data.Such as:Ordinal number when Fourier transformation obtains may be employed
According to frequency domain character, and then characterize time series data by the use of frequency domain information as feature;Using piece wire approximation (PLA) by sequential
Data are divided into multiple continuous set of data points, and then characterize corresponding data point set using a plurality of straight line as feature
It closes;Basic statistical nature (average, variance, extreme value etc.) can also be considered as simple feature, for characterizing time series data.It is right
In time series data, user may need to be inquired about and analyzed by original time series data, it is also possible to when only needing certain section
Some features of interior data.Such as:The maxima and minima in a period of time is focused more in abnormal monitoring.
Existing storage system is general that only original time series data is stored when storing time series data, therefore mesh
Before lack it is a kind of can not only support to inquire about original time series data, but also can support the feature to original time series data
The storage method for the time series data inquired about.
The content of the invention
In order to overcome the above problem or solve the above problems at least partly, the present invention provides a kind of supported feature inquiry
Time series data storage method and apparatus.
According to an aspect of the present invention, a kind of method of the time series data storage of supported feature inquiry is provided, including:It will
Time series data to be stored is divided into several set of data points, and each set of data points includes multiple continuous data points, each
Data point includes a timestamp and a data value, for any data point set, by number in any data point set
Initial data of the timestamp and data value at strong point as set of data points;By data point in any data point set most
Early timestamp and latest time stab the period information as any data point set, and institute is obtained according to default characteristic function
The characteristic value of any data point set is stated, by the period information of any data point set, the information of characteristic function and described
Characteristic information of the characteristic value of any data point set as any data point set;Create original data block and spy
Data block is levied, using an original data block as the memory space of the initial data of a set of data points, to each data point
The initial data of set is stored, using a characteristic block as the storage of the characteristic information of a set of data points
Space stores the characteristic information of each set of data points.
Wherein, time series data to be stored is divided into several set of data points, including:By the elder generation of the timestamp of data point
The continuous data point for often presetting quantity is divided into a set of data points by order afterwards.
Wherein, the characteristic value of any data point set is obtained according to default characteristic function, including:Call feature letter
Number, deals with the initial data of any data point set, obtains the characteristic value of any data point set.
Wherein, the initial data of each set of data points is stored, including:For any data point set,
The timestamp of each data point and data value in any data point set are sequentially stored in an original data block, and
For any data point in any data point set, the timestamp of any data point is made to associate to any data
The data value of point, to store the initial data of any data point set;The original number of each set of data points is stored successively
According to.
Wherein, the characteristic information of each set of data points is stored, including:For any data point set
It closes, by the characteristic value of the period information of any data point set, the information of characteristic function and any data point set
It is sequentially stored in a characteristic block, to store the characteristic information of any data point set;Storage is every successively
The characteristic information of one set of data points.
Wherein, original data block and characteristic block are created, using an original data block as set of data points
The memory space of initial data stores the initial data of each set of data points, using a characteristic block as one
The memory space of the characteristic information of a set of data points carries out storing it to the characteristic information of each set of data points
Afterwards, further include:Incidence relation is established between original data block and characteristic block, wherein, for storing a data point set
The original data block of the initial data of conjunction is associated to for storing the characteristic of the characteristic information of same set of data points
According to block.
Another aspect of the present invention provides a kind of device of the time series data storage of supported feature inquiry, including:At least one
A processor;And at least one processor being connected with processor communication, wherein:Memory storage has and can be executed by processor
Program instruction, the instruction of processor caller is to perform above-mentioned method.
Another aspect of the present invention provides a kind of computer program product, which includes being stored in non-
Computer program in transitory computer readable storage medium, which includes program instruction, when the program instruction quilt
When computer performs, computer is made to perform above-mentioned method.
Another aspect of the present invention, provides a kind of non-transient computer readable storage medium storing program for executing, and the non-transient computer is readable
Storage medium stores computer program, which makes computer perform above-mentioned method.
A kind of method and apparatus of the time series data storage of supported feature inquiry provided by the invention, including:It will be to be stored
Time series data be divided into several set of data points for including multiple continuous data points, calculated by default characteristic function every
The characteristic value of a set of data points, using the timestamp of data point in each set of data points and data value as corresponding data point set
The initial data of conjunction, using the period information and characteristic value of the information of characteristic function and each set of data points as corresponding data point
The characteristic information of set is right using an original data block as the memory space of the initial data of a set of data points
The initial data of each set of data points is stored, using a characteristic block as the characteristic of a set of data points
The memory space of information stores the characteristic information of each set of data points;It is stored by above-mentioned storage method
Time series data can not only support the inquiry to original time series data, but also can support to the feature of original time series data
Inquiry.
Description of the drawings
It, below will be to embodiment or the prior art in order to illustrate more clearly of technical solution of the invention or of the prior art
Attached drawing is briefly described needed in description, it should be apparent that, the accompanying drawings in the following description is the one of the present invention
A little embodiments, for those of ordinary skill in the art, without creative efforts, can also be according to these
Attached drawing obtains other attached drawings.
Fig. 1 is the flow chart for the method that the time series data inquired about according to the supported feature of the embodiment of the present invention stores;
Fig. 2 is the schematic diagram according to the storage format of the original data block of the embodiment of the present invention;
Fig. 3 is the schematic diagram according to the storage format of the characteristic block of the embodiment of the present invention.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with attached in the embodiment of the present invention
Figure, is clearly and completely described the technical solution in the present invention, it is clear that described embodiment is a part of the invention
Embodiment, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not making wound
All other embodiments obtained under the premise of the property made work, belong to the scope of protection of the invention.
In one embodiment of the invention, with reference to figure 1, a kind of side of the time series data storage of supported feature inquiry is provided
Method, including:Time series data to be stored is divided into several set of data points by S11, and each set of data points includes multiple continuous
Data point, each data point include a timestamp and a data value, for any data point set, by any number
Initial data of the timestamp and data value of data point as any data point set in the set of strong point;S12 described will appoint
The earliest time stamp of data point and latest time stab the period information as any data point set in one set of data points,
The characteristic value of any data point set is obtained according to default characteristic function, the period of any data point set is believed
Characteristic of the characteristic value of breath, the information of characteristic function and any data point set as any data point set
Information;S13 creates original data block and characteristic block, using an original data block as the original of set of data points
The memory space of data stores the initial data of each set of data points, using a characteristic block as a number
The memory space of the characteristic information of strong point set, stores the characteristic information of each set of data points.
Specifically, time series data be it is a series of with timestamp, arrange and come from same according to ascending order according to the time
The data of one target, a data point of each timestamp data value composition time series data corresponding with the timestamp.Use S
Represent time series, in S one section of continuous data point uses P={ p1, p2...pnRepresent, wherein pi=(ti, di) represent P
In i-th point, tiRepresent timestamp, diRepresent data value.Such as the data point in time series data is adopted according to every five seconds for example
The data of collection, wherein containing 10 data points, then corresponding time series data is as shown in table 1 below:
Table 1 contains the time series data of 10 data points
Data point | P1 | P2 | P3 | P4 | P5 | P6 | P7 | P8 | P9 | P10 |
Timestamp | 5 | 10 | 15 | 20 | 25 | 30 | 35 | 40 | 45 | 50 |
Data value | 1 | 2 | 3.1 | 4 | 5.2 | 10 | 9 | 8 | 7 | 6 |
For time series data to be stored, time series data to be stored is divided into several set of data points, each data
Point set includes multiple continuous data points, will be each for the timestamp and data value of data point in each set of data points
The initial data of the timestamp of data point and data value as corresponding set of data points in set of data points, for example, by table 1
p1、p2、p3、p4And p5Be divided into first set of data points, then the initial data of the set of data points be (5,1), (10,2),
(15,3.1), (20,4) and (25,5.2);For the initial data of each set of data points, by data in each set of data points
Period information of morning yesterday timestamp and the latest time stamp of point as fixed each set of data points, such as first set of data points
Middle earliest time stamp is " 5 ", and latest time stamp is " 25 ", then the period information of first set of data points is [5,25], each
The period information of set of data points includes the time range of the timestamp of all data points in corresponding data point set;Using default
Characteristic function, obtain the characteristic value of each set of data points;Default characteristic function is according to set by needing user, is used
It either operation rule such as Fourier transformation, piece wire approximation or is calculated equal in the function for a certain feature for calculating data
The operation rule of value calculates the operation rule of variance, calculates extreme value operation rule etc., and characteristic value is led to for a certain feature of data
It crosses corresponding function or operation rule calculates the value obtained;Such as default characteristic function is chosen for piece wire approximation,
Then the characteristic value of first set of data points can be identified as 0.21 (slope) and 0 (vertical intercept);It, will for any data point set
The characteristic value of the period information of any data point set, the information of characteristic function and any data point set is as institute
State the characteristic information of any data point set.
Original data block and characteristic block are created, using an original data block as the original of set of data points
The mode of the memory space of data stores the initial data of each set of data points, i.e., an original data block is only deposited
Store up the initial data of a set of data points;Using characteristic information of the characteristic block as a set of data points
Memory space mode, the characteristic information of each set of data points is stored, i.e., a characteristic block is only deposited
Store up the characteristic information of a set of data points.
Time series data to be stored is divided into several set of data points for including multiple continuous data points by the present embodiment,
The characteristic value of each set of data points is calculated by default characteristic function, by the timestamp of data point in each set of data points
With initial data of the data value as corresponding data point set, the period of the information of characteristic function and each set of data points is believed
Breath and characteristic information of the characteristic value as corresponding data point set, using an original data block as a set of data points
Initial data memory space, the initial data of each set of data points is stored, using a characteristic block as
The memory space of the characteristic information of one set of data points deposits the characteristic information of each set of data points
Storage;The time series data stored by above-mentioned storage method can not only support the inquiry to original time series data, but also can support
Inquiry to the feature of original time series data.
Based on above example, time series data to be stored is divided into several set of data points, including:By data point
The continuous data point for often presetting quantity is divided into a set of data points by the sequencing of timestamp.
Specifically, since first data point of time series data to be stored, the continuous data of quantity will be often preset
Point is divided into a set of data points, such as the time series data of table 1, if default quantity is 5, p1、p2、p3、p4And p5It draws
It is divided into for first set of data points, p6、p7、p8、p9And p10It is divided into as second set of data points.
The present embodiment is by by the timestamp of first data point in each set of data points and the last one data point
Period information of the timestamp as corresponding set of data points owns so as to which the period information is contained in corresponding data point set
The information of the timestamp of data point when being inquired about, can be carried out preliminary inquiry based on period information, be conducive to improve inquiry
Efficiency.
Based on above example, the characteristic value of any data point set is obtained according to default characteristic function, including:
Characteristic function is called, the initial data of any data point set is dealt with, obtains the spy of any data point set
Value indicative.
It is specific to call characteristic function, the initial data of any data point set is dealt with, such as characteristic function
For piece wire approximation, then using piece wire approximation to data point p in first set of data points1、p2、p3、p4And p5When
Between stamp and data value deal with, can obtain first set of data points characteristic value be 0.21 (slope) and 0 (vertical intercept).
Based on above example, the initial data of each set of data points is stored, including:For any number
Strong point is gathered, and the timestamp of each data point and data value in any data point set are sequentially stored in an original number
According in block, and for any data point in any data point set, the timestamp of any data point is made to associate to institute
The data value of any data point is stated, to store the initial data of any data point set;Each data point set is stored successively
The initial data of conjunction.
Specifically, stored successively to the initial data of each set of data points, and set of data points is original
Data occupy an original data block;Storage for the initial data of any of which set of data points, by any data point
The timestamp of each data point and data value are sequentially stored in an original data block in set, form such as Fig. 2 institutes of storage
Show, and for any data point, the timestamp of any data point is made to associate to the data value of any data point, it is right according to this
The initial data of each set of data points is stored.
The present embodiment is stored by the initial data to each set of data points, the original number of a set of data points
According to one original data block of occupancy, and the timestamp of any data point is associated to data value, to realize to original time series data
Efficiently management, and can realize and corresponding data value is quickly found according to timestamp.
Based on above example, the characteristic information of each set of data points is stored, including:For described
One set of data points, by the period information of any data point set, the information of characteristic function and any data point set
The characteristic value of conjunction is sequentially stored in a characteristic block, to store the characteristic information of any data point set;
The characteristic information of each set of data points is stored successively.
Specifically, stored successively to the characteristic information of each set of data points, and set of data points
Characteristic information occupies a characteristic block;Storage for the characteristic information of any of which set of data points, will
The characteristic value of the period information of any data point set, the information of characteristic function and any data point set is sequentially stored in
In one characteristic block, the form of storage is as shown in Figure 3.
The present embodiment is stored by the characteristic information to each set of data points, and set of data points
Characteristic information occupies a characteristic block, can be by using to realize the efficient management to the characteristic information of time series data
Information determines period information at the time of family inputs, and passes through the characteristic value quickly to be searched of period information.
Original data block and characteristic block are created, using an original data block as the original number of a set of data points
According to memory space, the initial data of each set of data points is stored, using a characteristic block as a data
The memory space of the characteristic information of point set, after being stored to the characteristic information of each set of data points, also
Including:Incidence relation is established between original data block and characteristic block, wherein, for storing the original of a set of data points
The original data block of beginning data is associated to for storing the characteristic block of the characteristic information of same set of data points.
Specifically, it will be associated for storing the original data block of the initial data of a set of data points to same for storing
The characteristic block of the characteristic information of one set of data points when user's input time is inquired about, is conducive to first root
Set of data points, then the searching data point in set of data points are determined according to characteristic period information in the block, without traversal
Each data point realizes quick lookup with this,
The time series data of the method storage of the time series data storage of supported feature inquiry based on above-described embodiment, can support
Inquiry to original time series data and support two kinds of query types of inquiry to characteristic value, query type can be determined by user:
(1) to the inquiry of original time series data:Temporal information input by user is received, is believed according to the time input by user
Breath traversal characteristic period information in the block is to determine characteristic block, according to associating for characteristic block and original data block
Relation determines original data block, and each data point is traveled through in definite original data block, if the temporal information of family input with
The matching of a certain date stamp then returns to the matched associated data value of date stamp to user, if the temporal information of family input with
The timestamp of all data points can not match in original data block, such as the interval of timestamp is 5s, timestamp be respectively 5s,
10s, 15s ... ..., but the temporal information of family input is 12s, then is called according to the information of characteristic characteristic function in the block
Corresponding characteristic function handles this feature data period information in the block and characteristic value, obtains the data at inquiry moment
Value returns to user.
(2) to the inquiry of characteristic value:Temporal information input by user is received, is traveled through according to temporal information input by user special
Data period information in the block is levied to determine characteristic block, the characteristic value stored in definite characteristic block is returned into use
Family.
As another embodiment of the present invention, a kind of device of the time series data storage of supported feature inquiry is provided, including:
At least one processor;And at least one processor being connected with the processor communication, wherein:The memory storage has
The program instruction that can be performed by the processor, the processor call described program instruction to perform above-mentioned each method embodiment
The method provided, such as including:Time series data to be stored is divided into several set of data points, each set of data points bag
Multiple continuous data points are included, each data point includes a timestamp and a data value, will for any data point set
Initial data of the timestamp and data value of data point as set of data points in any data point set;It will be described any
The earliest time stamp of data point and latest time stab the period information as any data point set, root in set of data points
The characteristic value of any data point set is obtained according to default characteristic function, the period of any data point set is believed
Characteristic of the characteristic value of breath, the information of characteristic function and any data point set as any data point set
Information;Original data block and characteristic block are created, using an original data block as the initial data of a set of data points
Memory space, the initial data of each set of data points is stored, using a characteristic block as a data point
The memory space of the characteristic information of set stores the characteristic information of each set of data points.
As another embodiment of the present invention, a kind of computer program product is provided, which includes
The computer program being stored on non-transient computer readable storage medium storing program for executing, the computer program include program instruction, work as program
Instruction is when being computer-executed, and computer is able to carry out the method that above-mentioned each method embodiment is provided, such as including:It will wait to deposit
The time series data of storage is divided into several set of data points, and each set of data points includes multiple continuous data points, each data
Point includes a timestamp and a data value, for any data point set, by data point in any data point set
Initial data as set of data points of timestamp and data value;By in any data point set data point it is earliest when
Between stamp and latest time stab period information as any data point set, according to obtaining default characteristic function times
The characteristic value of one set of data points, by the period information of any data point set, the information of characteristic function and described any
Characteristic information of the characteristic value of set of data points as any data point set;Create original data block and characteristic
According to block, using an original data block as the memory space of the initial data of a set of data points, to each set of data points
Initial data stored, a characteristic block is empty as the storage of the characteristic information of a set of data points
Between, the characteristic information of each set of data points is stored.
As another embodiment of the present invention, a kind of non-transient computer readable storage medium storing program for executing is provided, the non-transient meter
Calculation machine readable storage medium storing program for executing stores computer program, which put forward the above-mentioned each method embodiment of computer execution
The method of confession, such as including:Time series data to be stored is divided into several set of data points, each set of data points includes more
A continuous data point, each data point include a timestamp and a data value, for any data point set, by described in
The initial data of the timestamp of data point and data value as set of data points in any data point set;By any data
The earliest time stamp of data point and latest time stab the period information as any data point set in point set, according to pre-
If characteristic function obtain the characteristic value of any data point set, by the period information of any data point set, spy
The characteristic information of the information of sign function and the characteristic value of any data point set as any data point set;
Original data block and characteristic block are created, using an original data block as the storage of the initial data of a set of data points
Space stores the initial data of each set of data points, using a characteristic block as set of data points
The memory space of characteristic information stores the characteristic information of each set of data points.
One of ordinary skill in the art will appreciate that:Realizing all or part of step of above method embodiment can pass through
Computer program instructions relevant hardware is completed, and foregoing computer program can be stored in a computer-readable storage and be situated between
In matter, the computer program upon execution, execution the step of including above method embodiment;And foregoing storage medium includes:
The various media that can store program code such as ROM, RAM, magnetic disc or CD.
Through the above description of the embodiments, those skilled in the art can be understood that each embodiment can
It is realized by the mode of software plus required general hardware platform, naturally it is also possible to pass through hardware.Based on such understanding, on
Technical solution is stated substantially in other words to embody the part that the prior art contributes in the form of software product, it should
Computer software product can store in a computer-readable storage medium, such as ROM/RAM, magnetic disc, CD, including several fingers
Order, which is used, so that computer equipment (can be personal computer, server or the network equipment etc.) performs each implementation
Method described in some parts of example or embodiment.
What is finally illustrated is:The above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations;Although ginseng
The present invention is described in detail according to previous embodiment, it will be understood by those of ordinary skill in the art that:It still can be with
It modifies to the technical solution recorded in foregoing embodiments or equivalent substitution is carried out to which part technical characteristic;And
These modifications are replaced, and the essence of appropriate technical solution is not made to depart from the spirit and model of various embodiments of the present invention technical solution
It encloses.
Claims (9)
- A kind of 1. method of the time series data storage of supported feature inquiry, which is characterized in that including:Time series data to be stored is divided into several set of data points, each set of data points includes multiple continuous data Point, each data point includes a timestamp and a data value, for any data point set, by any data point set The initial data of the timestamp of data point and data value as any data point set in conjunction;The earliest time stamp and latest time of data point in any data point set are stabbed as any data point set The period information of conjunction obtains the characteristic value of any data point set according to default characteristic function, by any data The characteristic value of the period information of point set, the information of the characteristic function and any data point set is as any number The characteristic information of strong point set;Original data block and characteristic block are created, using an original data block as the initial data of a set of data points Memory space stores the initial data of each set of data points, using a characteristic block as a data point set The memory space of the characteristic information of conjunction stores the characteristic information of each set of data points.
- 2. according to the method described in claim 1, it is characterized in that, described be divided into several data by time series data to be stored Point set, including:By the sequencing of the timestamp of data point, the continuous data point for often presetting quantity is divided into a data point set It closes.
- 3. according to the method described in claim 1, it is characterized in that, described obtain any number according to default characteristic function The characteristic value of strong point set, including:The characteristic function is called, the initial data of any data point set is handled, obtains any data The characteristic value of point set.
- 4. according to the method described in claim 1, it is characterized in that, the initial data to each set of data points is deposited Storage, including:For any data point set, by the timestamp of each data point in any data point set and data value according to It is secondary to be stored in an original data block, and for any data point in any data point set, make any data The timestamp of point is associated to the data value of any data point, to store the initial data of any data point set;The initial data of each set of data points is stored successively.
- 5. according to the method described in claim 1, it is characterized in that, the characteristic information to each set of data points into Row storage, including:For any data point set, by the period information of any data point set, the information of the characteristic function It is sequentially stored in the characteristic value of any data point set in a characteristic block, to store any data point set The characteristic information of conjunction;The characteristic information of each set of data points is stored successively.
- 6. according to the method described in claim 1, it is characterized in that, described create original data block and characteristic block, by one Memory space of a original data block as the initial data of a set of data points, to the initial data of each set of data points It is stored, using a characteristic block as the memory space of the characteristic information of a set of data points, to each number After the characteristic information of strong point set is stored, further include:Incidence relation is established between original data block and characteristic block, wherein, for storing the original of a set of data points The original data block of beginning data is associated to for storing the characteristic block of the characteristic information of same set of data points.
- 7. a kind of device of the time series data storage of supported feature inquiry, which is characterized in that including:At least one processor;And at least one processor being connected with the processor communication, wherein:The memory storage has a program instruction that can be performed by the processor, the processor call described program instruction with Perform the method as described in claim 1 to 6 is any.
- 8. a kind of computer program product, which is characterized in that the computer program product includes being stored in non-transient computer Computer program on readable storage medium storing program for executing, the computer program include program instruction, when described program is instructed by computer During execution, the computer is made to perform the method as described in claim 1 to 6 is any.
- 9. a kind of non-transient computer readable storage medium storing program for executing, which is characterized in that the non-transient computer readable storage medium storing program for executing is deposited Computer program is stored up, the computer program makes the computer perform the method as described in claim 1 to 6 is any.
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Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112163015A (en) * | 2020-09-22 | 2021-01-01 | 南京信息职业技术学院 | Real-time monitoring method, device and system for time sequence data of Internet of things |
CN114547027A (en) * | 2022-02-11 | 2022-05-27 | 清华大学 | Data compression processing method and device with capacity and value constraint and storage medium |
CN117370329A (en) * | 2023-12-07 | 2024-01-09 | 湖南易比特大数据有限公司 | Intelligent management method and system for equipment data based on industrial Internet of things |
Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102611454A (en) * | 2012-01-29 | 2012-07-25 | 上海锅炉厂有限公司 | Dynamic lossless compressing method for real-time historical data |
CN103003803A (en) * | 2010-08-11 | 2013-03-27 | 株式会社日立制作所 | Time-series data processing apparatus and method thereof |
CN105242882A (en) * | 2015-10-13 | 2016-01-13 | 东方网力科技股份有限公司 | Frame storage method and apparatus for timing data and query method and apparatus for timing data |
CN105843891A (en) * | 2016-03-22 | 2016-08-10 | 浙江大学 | Incremental online characteristic extraction and analysis method and system |
CN106383585A (en) * | 2016-09-30 | 2017-02-08 | 山东瀚岳智能科技股份有限公司 | Wearable device-based user emotion identification method and system |
CN106649438A (en) * | 2016-09-09 | 2017-05-10 | 西安交通大学 | Time series data unexpected fault detection method |
CN106682077A (en) * | 2016-11-18 | 2017-05-17 | 山东鲁能软件技术有限公司 | Method for storing massive time series data on basis of Hadoop technologies |
CN106776823A (en) * | 2016-11-25 | 2017-05-31 | 华为技术有限公司 | A kind of time series data management method, equipment and device |
US20170161661A1 (en) * | 2015-12-07 | 2017-06-08 | Sap Se | Advisor Generating Multi-representations of Time Series Data |
-
2017
- 2017-12-12 CN CN201711322634.9A patent/CN108052599A/en active Pending
Patent Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103003803A (en) * | 2010-08-11 | 2013-03-27 | 株式会社日立制作所 | Time-series data processing apparatus and method thereof |
CN102611454A (en) * | 2012-01-29 | 2012-07-25 | 上海锅炉厂有限公司 | Dynamic lossless compressing method for real-time historical data |
CN105242882A (en) * | 2015-10-13 | 2016-01-13 | 东方网力科技股份有限公司 | Frame storage method and apparatus for timing data and query method and apparatus for timing data |
US20170161661A1 (en) * | 2015-12-07 | 2017-06-08 | Sap Se | Advisor Generating Multi-representations of Time Series Data |
CN105843891A (en) * | 2016-03-22 | 2016-08-10 | 浙江大学 | Incremental online characteristic extraction and analysis method and system |
CN106649438A (en) * | 2016-09-09 | 2017-05-10 | 西安交通大学 | Time series data unexpected fault detection method |
CN106383585A (en) * | 2016-09-30 | 2017-02-08 | 山东瀚岳智能科技股份有限公司 | Wearable device-based user emotion identification method and system |
CN106682077A (en) * | 2016-11-18 | 2017-05-17 | 山东鲁能软件技术有限公司 | Method for storing massive time series data on basis of Hadoop technologies |
CN106776823A (en) * | 2016-11-25 | 2017-05-31 | 华为技术有限公司 | A kind of time series data management method, equipment and device |
Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112163015A (en) * | 2020-09-22 | 2021-01-01 | 南京信息职业技术学院 | Real-time monitoring method, device and system for time sequence data of Internet of things |
CN112163015B (en) * | 2020-09-22 | 2023-09-22 | 南京信息职业技术学院 | Real-time monitoring method, device and system for time sequence data of Internet of things |
CN114547027A (en) * | 2022-02-11 | 2022-05-27 | 清华大学 | Data compression processing method and device with capacity and value constraint and storage medium |
CN114547027B (en) * | 2022-02-11 | 2023-01-31 | 清华大学 | Data compression processing method and device with capacity and value constraint and storage medium |
CN117370329A (en) * | 2023-12-07 | 2024-01-09 | 湖南易比特大数据有限公司 | Intelligent management method and system for equipment data based on industrial Internet of things |
CN117370329B (en) * | 2023-12-07 | 2024-02-27 | 湖南易比特大数据有限公司 | Intelligent management method and system for equipment data based on industrial Internet of things |
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