CN107798056A - A kind of data query method and device - Google Patents
A kind of data query method and device Download PDFInfo
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- CN107798056A CN107798056A CN201710790807.3A CN201710790807A CN107798056A CN 107798056 A CN107798056 A CN 107798056A CN 201710790807 A CN201710790807 A CN 201710790807A CN 107798056 A CN107798056 A CN 107798056A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/14—Details of searching files based on file metadata
- G06F16/144—Query formulation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/18—File system types
- G06F16/182—Distributed file systems
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Abstract
A kind of data query method and device, methods described comprise the following steps：The data inquiry request that receiving terminal is sent；The listed files after equilibrium is obtained according to the data inquiry request and its corresponding historical query operation information；File is inquired about according to the listed files.Data query method and device provided by the invention, the load for realizing whole cluster is evenly distributed in whole day, reduce the load of peak period, improve the load of period in morning, the rising of the utilization rate of whole cluster is realized, simultaneously, passes through controllable data input, the reliability of cluster is further improved, avoids the awkward situation that task accumulation causes cluster resource frequently to exhaust.
Description
Technical field
The present invention relates to technical field of information processing, and in particular to a kind of data query method and device.
Background technology
User handles journey when renting Hadoop commercial digitals cluster to run its MapReduce program, for big data
Sequence generally requires to carry out timing operation task according to hour, analyzes the data result in each hour.For example, certain tenant A model
Program started to perform on the 20th minute at each hour, such as:0:20、1:20、2:20,…、21:20、22:20 and 23:20, one day
In need run 24 model tasks.The demand of above-mentioned task run was equally distributed, but Digital Clustering among one day
The distribution of middle initial data is not but uniform, as shown in figure 1, Fig. 1 is raw data set data block in 24 hours one day
The distribution of number.Initial data is as caused by the activity of the mankind, and the size of the initial data of each hour depends on the work of people
Dynamic number.Because people is often in sleep within 0 point~7 periods, data volume is caused to reduce；And period at high noon and evening
Upper prime time, then it was the peak of data volume.Which results in the load of Digital Clustering, skewness weighs in one day, to ensure
In peak period, the program charge of user is no more than cluster total load, generally requires to carry out redundant configuration to Digital Clustering, thus
Cause the computing capability for wasting whole Digital Clustering for idle state in less period in the morning Digital Clustering of data volume,
Reduce the utilization rate of whole Digital Clustering.
The content of the invention
Therefore, the technical problem to be solved in the present invention is to overcome the power load distributing of Digital Clustering in the prior art unbalanced
The defects of, and the defects of resulting Digital Clustering utilization rate is low, so as to provide a kind of data query method and device.
According in a first aspect, a kind of data query method of one embodiment of the present of invention offer, comprises the following steps：Receive
The data inquiry request that terminal is sent；Obtained according to the data inquiry request and its corresponding historical query operation information balanced
Listed files afterwards；File is inquired about according to the listed files.
Further, data inquiry request includes ID and query time information.
Further, the text after equilibrium is obtained according to the data inquiry request and its corresponding historical query operation information
The step of part list, including：The fileinfo amount of user's requesting query is determined according to the ID and query time information；Root
Information content limit value is determined according to the historical query operation information of ID, query time information and the user；According to described information amount
The fileinfo amount of limit value and user's requesting query determines currently input the file of the listed files.
Further, information content is determined according to the historical query operation information of ID, query time information and the user
The step of limit value, including：Obtain in the setting date under the time point range of requesting query, task corresponding to the ID is disappeared
The actual resource occupation value and its average resource occupation value of consumption；Obtain in the setting date under the time point range of requesting query,
The mean size for the data file that average resource quantity corresponding to the ID and its corresponding task are read；Described in acquisition
Current resource quantity corresponding to ID；According to the actual resource occupation value, average resource occupation value, average resource number
The mean size and Current resource quantity of amount, the data file read, calculate information content limit value.
Further, information content limit value is calculated according to equation below：
CURRENT_INPUT=(1-AVG_DEVIATE) * AVG_INPUT*CURRENT_RATE/AVG_RATE
Wherein CURRENT_INPUT represents information content limit value；AVG_INPUT represents the time of requesting query in the setting date
The mean size for the data file that task corresponding to the ID is read under point range；AVG_RATE was represented in the setting date
Average resource quantity corresponding to the ID under the time point range of requesting query；CURRENT_RATE represents the ID
Corresponding Current resource quantity；AVG_DEVIATE represents the deviation factor of resource occupation, AVG_DEVIATE=(CURRENT_
COST-AVG_COST)/AVG_COST*100%, CURRENT_COST and AVG_COST represent to set respectively request in the date and looked into
Under the time point range of inquiry, actual resource occupation value and its average resource that task corresponding to the ID is consumed take
Value.
Further, determine currently should according to the fileinfo amount of described information amount limit value and user's requesting query
The step of inputting the file of the listed files, including：Compare the fileinfo of described information amount limit value and user's requesting query
Amount, and according to comparative result and the file generated listed files of user's requesting query.
Further, when described information amount limit value is not less than the fileinfo amount of user's requesting query, by described in
The file of user's requesting query is all included in listed files.
Further, when described information amount limit value is more than the fileinfo amount of user's requesting query, in the use
Some files are randomly selected in the file of family requesting query and are included in listed files, until corresponding all texts in the listed files
The size of part reaches described information amount limit value.
Further, data query method also includes detection, obtains and store the change of initial data in predetermined period of time
Change information.
Further, inputted in computation model corresponding to the data inquiry request by the use of the listed files as task
After completing calculating task, obtain and store resource occupation value corresponding to the task and fully enter the size of file.
According to second aspect, one embodiment of the present of invention provides a kind of data query arrangement, including：At least one processing
Device and the memory being connected with least one processor communication；Wherein, the memory storage have can by it is described at least
The instruction of one computing device, the instruction is by least one computing device, so that at least one processor
Perform the data query method as described in first aspect embodiment.
Technical solution of the present invention, have the following advantages that：
Data query method and device provided by the invention, the load for realizing whole cluster are evenly distributed in whole day,
The load of peak period is reduced, improves the load of period in morning, realizes the rising of the utilization rate of whole cluster, it is same in this
When, by controllable data input, the reliability of cluster is further improved, avoiding task accumulation causes cluster resource frequency
Numerous awkward situation exhausted.
Brief description of the drawings
, below will be to specific in order to illustrate more clearly of the specific embodiment of the invention or technical scheme of the prior art
The required accompanying drawing used is briefly described in embodiment or description of the prior art, it should be apparent that, in describing below
Accompanying drawing is some embodiments of the present invention, for those of ordinary skill in the art, before creative work is not paid
Put, other accompanying drawings can also be obtained according to these accompanying drawings.
Fig. 1 is the distribution of raw data set data block number in 24 hours one day；Its abscissa represents time, ordinate
Represent data block number；
Fig. 2 is the flow chart of a specific example of data query method in the embodiment of the present invention 1；
Fig. 3 is the flow chart of a specific example of data query method in the embodiment of the present invention 2；
Fig. 4 according to ID, query time information and is somebody's turn to do for step S22 in the data query method of the embodiment of the present invention 2
The historical query operation information of user determines the flow chart of a specific example of information content limit value；
Fig. 5 is the theory diagram of a specific example of data query arrangement in the embodiment of the present invention 3.
Reference：
1-processor, 2-memory.
Embodiment
Technical scheme is clearly and completely described below in conjunction with accompanying drawing, it is clear that described implementation
Example is part of the embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the present invention, ordinary skill
The every other embodiment that personnel are obtained under the premise of creative work is not made, belongs to the scope of protection of the invention.
In addition, as long as technical characteristic involved in invention described below different embodiments does not form conflict just each other
It can be combined with each other.
Embodiment 1
Embodiment 1 provides a kind of data query method, applied to server, as shown in Fig. 2 comprising the following steps：
Step S1：The data inquiry request that receiving terminal is sent.Data inquiry request should at least include ID and look into
Ask temporal information.Typically, query time information needs to indicate the exact date and time point of user's requesting query, such as inquires about
Time can be August in 2017 28 days 8:00、9:00 and 11:00.Server is when performing data query, it is necessary to the time point of finding
In the range of corresponding all files, such as time point is 8:When 00, server should inquire about 8:00:00—8:59:59 time models
Enclose interior data file.
Step S2：The file after equilibrium is obtained according to data inquiry request and its corresponding historical query operation information to arrange
Table.Existing commercial digital cluster, such as Hadoop, in Hadoop MapReduce Computational frames, not for HDFS
(Hadoop Distributed File System distributed file systems, abbreviation HDFS) is input to the interface in computation model
Any balanced and current limliting design is done at place, has only done delineation of power.For example, only allowing tenant A to read directory A, only allow to rent
Family B reads catalogue B etc..Common commercial cluster when in use, actual to tenant can not often have read which file do it is any
Careful record and management.Between the computing resource bought which results in tenant and the data file actually read in, without real
Now associate.Prior art is to be provided with a resource red line (maximum resource occupation value) to user, and user is limited by scheduler
Computation model operate under red line, this just brings two problems：
One：The resource of user's actual use is less than the resource of user's purchase all the time, causes user to try to achieve fully
Using the resource of purchase, in risk resource utilization (resource of actual use divided by the resource of user's purchase) is approached all the time
100%.
Secondly：Due to cluster supply initial data resource in one day skewness, cause user can not fully profit
With the resource of its purchase, the data volume big period easily causes task to overstock break the bank, and the period that data volume is small, and resource is again
It is not utilized fully.
The tenant that the two problems often lead to commercial cluster is discontented with.And occur tenant's control again and again and bad actually enter text
The amount of part, cause resource utilization exceeded, so that whole cluster is absorbed in during task overstocks and broken down.Embodiment 1
Step S2 is by the historical operation information of user, and as the history data file of certain period reads in quantity and size, and user goes through
History buys resource quantity, is incorporated into the equalization process of current data file inquiry, avoids prior art directly please by user
The data file asked be fully loaded to Digital Clustering caused by load it is excessive the problem of, realize to the confession of the data of Digital Clustering
Monitoring to side is supplied, in short, realizing data query supply and controllable supply.
Step S3：File is inquired about according to listed files.
The data query method that embodiment 1 provides, the load of whole cluster is evenly distributed in whole day, reduces peak
The load of period, the load of period in morning is improved, realize the rising of the utilization rate of whole cluster, simultaneously, by can
The data input of control, the reliability of cluster is further improved, avoiding task accumulation causes what cluster resource frequently exhausted
Awkward situation.
Embodiment 2
Embodiment 2 provides a kind of data query method, and applied to server, it includes the Overall Steps of embodiment 1, to keep away
Exempt to repeat, will not be repeated here.Embodiment 2 discloses step S2 and operated according to data inquiry request and its corresponding historical query
The specific method of listed files after information acquisition equilibrium, as shown in figure 3, it comprises the following steps：
Step S21：The fileinfo amount of user's requesting query is determined according to ID and query time information.
Step S22：Determine that information content limits according to the historical query operation information of ID, query time information and the user
Value.First, the query time scope of a historical data is set, letter is operated to obtain the historical query for being used to equalize calculating
Breath.In an embodiment, the historical query operation information inquired about in nearest 7 days is preset.Specifically, for setting
Certain day in date (such as in nearest 7 days), if being looked into time point in corresponding query time information without producing history
Operation information is ask, then gives up the historical data of this day, is also required to accordingly to during the averaging of follow-up historical data
Denominator reduces one day.
In an embodiment, as shown in figure 4, calculating information content limit value with the following method：
Step S221：Obtain in the setting date under the time point range of requesting query, task is consumed corresponding to ID
Actual resource occupation value CURRENT_COST and its average resource occupation value AVG_COST.Wherein, the setting date refers to
Historical query operation needs to recall the historical date of inquiry, for example, the setting date can be defined as in nearest 7 days；Requesting query
Time point be time point in the data inquiry request that terminal is sent in step S1 specified by query time information.Gone through in acquisition
, it is necessary to corresponding whole almanac datas in the range of the time point of acquisition during history data, such as time point is 8:When 00, server should
Obtain 8:00:00—8:59:History data in 59 time ranges.Resource occupation value is megabyte-
Milliseconds values, average resource occupation value are integration of the internal memory spent by user task to the time.Utilize the money of reality
Source occupation value CURRENT_COST and average resource occupation value AVG_COST, the task institute of user in the setting date can be calculated
The deviation factor AVG_DEVIATE of caused resource occupation, calculation formula are as follows：
AVG_DEVIATE=(CURRENT_COST-AVG_COST)/AVG_COST*100% (1)
In formula 1, CURRENT_COST and AVG_COST represent to set respectively in the date under the time point range of requesting query,
The actual resource occupation value and its average resource occupation value that task corresponding to ID is consumed.
Step S222：Obtain in the setting date under the time point range of requesting query, average resource number corresponding to ID
The mean size for the data file that amount and its corresponding task are read.The data file that average resource quantity and task are read
Mean size be daily mean.
Step S223：Calculate information content limit value CURRENT_INPUT.Information content limit value is calculated using formula 2：
CURRENT_INPUT=(1-AVG_DEVIATE) * AVG_INPUT*CURRENT_RATE/AVG_RATE (2)
In formula 2, CURRENT_INPUT represents information content limit value；AVG_INPUT represent setting the date in requesting query when
Between under point range the data file that task corresponding to ID is read mean size；AVG_RATE is represented please in the setting date
Seek average resource quantity corresponding to ID under the time point range of inquiry；CURRENT_RATE represents current corresponding to ID
Resource quantity；AVG_DEVIATE is the deviation factor for the resource occupation that step S221 calculates gained.
The current information amount limit value being adapted with history data can be calculated by step S221-S223, enter
And utilize the information content limit value to instruct the reading quantity of current data file, avoiding reading in heap file suddenly causes task to be accumulated
Press break the bank.
Step S23：Being determined according to the fileinfo amount of information content limit value and user's requesting query currently should input file
The file of list.Prime minister, compare the fileinfo amount of described information amount limit value and user's requesting query；Next, ties according to comparing
Fruit and the file generated listed files of user's requesting query.When information content limit value is not less than the fileinfo amount of user's requesting query
When, the file of user's requesting query is all included in listed files；The file for being more than user's requesting query when information content limit value is believed
During breath amount, some files are randomly selected in the file of user's requesting query and are included in listed files, until corresponding in listed files
The sizes of all files reach information content limit value.
The data query method that embodiment 2 provides realizes controllable data input, improves the reliable of Digital Clustering
Property, avoid the awkward situation that task accumulation causes cluster resource frequently to exhaust.
Initial data in the data query method that embodiment 2 provides, in addition to detection, acquisition and storage predetermined period of time
Change information, such as detection HDFS on initial data catalogue under file change, by the data of each hour increase newly situation
Cluster health data storehouse is charged to, and information is provided when data query calculates.For example, utilizing embodiment 1 or embodiment 2
After obtaining the listed files after equilibrium, on the one hand inquired about according to listed files and read file, on the other hand by listed files
File as task input so that computation model corresponding with ID using listed files as task input completion calculating
Task, and obtained after calculating task is completed and store resource occupation value corresponding to the task and fully enter the big of file
It is small, for subsequently providing information when data query calculates.
Embodiment 3
Embodiment 3 provides a kind of data query arrangement, as shown in figure 5, including processor 1 and with the communication link of processor 1
The memory 2 connect.Wherein, memory 2 is stored with the instruction that can be performed by processor 1, instructs and is performed by processor 1 so as to handle
Device 1 performs the data query method as described in embodiment 1 or embodiment 2.
Embodiment 4
Embodiment 4 provides a kind of WebService servers, and using operating system Centos 7, its exemplary hardware configuration is such as
Under：
1000M Ethernet cards
Intel (R) Xeon (R) CPU E5-2420 or higher level processor
128GB DDR3 server memories
More than 1TB server hard discs
The WebService servers access the LAN of commercial Hadoop clusters, and the client into hadoop cluster appoints
Business submits machine to open unique 20771 port, and this port, which will only be used in, calls load balancing input, to guarantee data security.
Start the program for realizing embodiment 1 or the data balancing method described in embodiment 2 on this server, this program can scan
Whole HDFS will file the file of completion, be evenly distributed in 24 hours to establish file index.When there is user Shen
Please obtain certain block number of some hour according to when, first inquiry corresponding to all files of these data blocks of request filename and
Fileinfo amount, current information content limit value is secondly calculated according to historical data, finally returns to filename in the form of a list
To the computation model of user, as finally entering for computation model, the input of computation model should be not more than information content limit value.
It should be understood by those skilled in the art that, embodiments of the invention can be provided as method, system or computer program
Product.Therefore, the present invention can use the reality in terms of complete hardware embodiment, complete software embodiment or combination software and hardware
Apply the form of example.Moreover, the present invention can use the computer for wherein including computer usable program code in one or more
The computer program production that usable storage medium is implemented on (including but is not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of product.
The present invention is the flow with reference to method according to embodiments of the present invention, equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that can be by every first-class in computer program instructions implementation process figure and/or block diagram
Journey and/or the flow in square frame and flow chart and/or block diagram and/or the combination of square frame.These computer programs can be provided
The processors of all-purpose computer, special-purpose computer, Embedded Processor or other programmable data processing devices is instructed to produce
A raw machine so that produced by the instruction of computer or the computing device of other programmable data processing devices for real
The device for the function of being specified in present one flow of flow chart or one square frame of multiple flows and/or block diagram or multiple square frames.
These computer program instructions, which may be alternatively stored in, can guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works so that the instruction being stored in the computer-readable memory, which produces, to be included referring to
Make the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one square frame of block diagram or
The function of being specified in multiple square frames.
These computer program instructions can be also loaded into computer or other programmable data processing devices so that counted
Series of operation steps is performed on calculation machine or other programmable devices to produce computer implemented processing, so as in computer or
The instruction performed on other programmable devices is provided for realizing in one flow of flow chart or multiple flows and/or block diagram one
The step of function of being specified in individual square frame or multiple square frames.
Obviously, above-described embodiment is only intended to clearly illustrate example, and is not the restriction to embodiment.It is right
For those of ordinary skill in the art, can also make on the basis of the above description it is other it is various forms of change or
Change.There is no necessity and possibility to exhaust all the enbodiments.And the obvious change thus extended out or
Among changing still in the protection domain of the invention.
Claims (11)
- A kind of 1. data query method, it is characterised in that comprise the following steps：The data inquiry request that receiving terminal is sent；The listed files after equilibrium is obtained according to the data inquiry request and its corresponding historical query operation information；File is inquired about according to the listed files.
- 2. data query method according to claim 1, it is characterised in that：The data inquiry request include ID and Query time information.
- 3. data query method according to claim 2, it is characterised in that it is described according to the data inquiry request and its Corresponding historical query operation information obtains the step of listed files after equilibrium, including：The fileinfo amount of user's requesting query is determined according to the ID and query time information；Information content limit value is determined according to the historical query operation information of ID, query time information and the user；Determined currently input the file according to the fileinfo amount of described information amount limit value and user's requesting query The file of list.
- 4. data query method according to claim 3, it is characterised in that described according to ID, query time information And the historical query operation information of user the step of determining information content limit value, including：Obtain in the setting date under the time point range of requesting query, the actual money that task corresponding to the ID is consumed Source occupation value and its average resource occupation value；Obtain in the setting date under the time point range of requesting query, average resource quantity corresponding to the ID and its correspondingly The mean size of data file that is read of task；Obtain Current resource quantity corresponding to the ID；It is averaged according to the actual resource occupation value, average resource occupation value, average resource quantity, the data file that reads Size and Current resource quantity, calculate information content limit value.
- 5. data query method according to claim 4, it is characterised in that calculate information content limit value according to equation below：CURRENT_INPUT=(1-AVG_DEVIATE) * AVG_INPUT*CURRENT_RATE/AVG_RATEWherein CURRENT_INPUT represents information content limit value；AVG_INPUT represents the time point model of requesting query in the setting date The mean size for the data file that task corresponding to enclosing the lower ID is read；AVG_RATE represents to ask in the setting date Average resource quantity corresponding to the ID under the time point range of inquiry；CURRENT_RATE represents that the ID is corresponding Current resource quantity；AVG_DEVIATE represents the deviation factor of resource occupation, AVG_DEVIATE=(CURRENT_COST- AVG_COST)/AVG_COST*100%, CURRENT_COST and AVG_COST represent respectively set the date in requesting query when Between under point range, actual resource occupation value and its average resource occupation value that task corresponding to the ID is consumed.
- 6. data query method according to claim 3, it is characterised in that described according to described information amount limit value and described The step of fileinfo amount of user's requesting query determines currently input the file of the listed files, including：Compare the fileinfo amount of described information amount limit value and user's requesting query, and according to comparative result and user's requesting query File generated listed files.
- 7. data query method according to claim 6, it is characterised in that when described information amount limit value is not less than the use During the fileinfo amount of family requesting query, the file of user's requesting query is all included in listed files.
- 8. data query method according to claim 6, it is characterised in that when described information amount limit value is more than the user During the fileinfo amount of requesting query, some files are randomly selected in the file of user's requesting query and are included in file row Table, until the size of corresponding all files reaches described information amount limit value in the listed files.
- 9. data query method according to claim 1, it is characterised in that also include detection, obtain and store pre- timing Between in the cycle initial data change information.
- 10. data query method according to claim 1, it is characterised in that in meter corresponding to the data inquiry request Calculate model using the listed files as task input completion calculating task after, obtain and resource account for corresponding to storing the task With the size for being worth and fully entering file.
- A kind of 11. data query arrangement, it is characterised in that including：At least one processor and the memory being connected with least one processor communication；Wherein, the memory is deposited Containing can be by the instruction of at least one computing device, and the instruction is by least one computing device, so that institute State the data query method any one of at least one computing device claim 1-10.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108965405A (en) * | 2018-06-27 | 2018-12-07 | 阿里巴巴集团控股有限公司 | A kind of table data requested service processing method and processing device |
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