CN111998190A - Big data-based server platform - Google Patents

Big data-based server platform Download PDF

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Publication number
CN111998190A
CN111998190A CN202010859976.XA CN202010859976A CN111998190A CN 111998190 A CN111998190 A CN 111998190A CN 202010859976 A CN202010859976 A CN 202010859976A CN 111998190 A CN111998190 A CN 111998190A
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China
Prior art keywords
server
plate
loading
connecting rod
sub
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Granted
Application number
CN202010859976.XA
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Chinese (zh)
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CN111998190B (en
Inventor
龚小云
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SHANDONG ZHONGZHI ELECTRONICS CO Ltd
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Individual
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Priority to CN202010859976.XA priority Critical patent/CN111998190B/en
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    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16MFRAMES, CASINGS OR BEDS OF ENGINES, MACHINES OR APPARATUS, NOT SPECIFIC TO ENGINES, MACHINES OR APPARATUS PROVIDED FOR ELSEWHERE; STANDS; SUPPORTS
    • F16M11/00Stands or trestles as supports for apparatus or articles placed thereon ; Stands for scientific apparatus such as gravitational force meters
    • F16M11/02Heads
    • F16M11/04Means for attachment of apparatus; Means allowing adjustment of the apparatus relatively to the stand
    • F16M11/043Allowing translations
    • F16M11/048Allowing translations adapted to forward-backward translation movement
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16MFRAMES, CASINGS OR BEDS OF ENGINES, MACHINES OR APPARATUS, NOT SPECIFIC TO ENGINES, MACHINES OR APPARATUS PROVIDED FOR ELSEWHERE; STANDS; SUPPORTS
    • F16M11/00Stands or trestles as supports for apparatus or articles placed thereon ; Stands for scientific apparatus such as gravitational force meters
    • F16M11/02Heads
    • F16M11/04Means for attachment of apparatus; Means allowing adjustment of the apparatus relatively to the stand
    • F16M11/043Allowing translations
    • F16M11/046Allowing translations adapted to upward-downward translation movement
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16MFRAMES, CASINGS OR BEDS OF ENGINES, MACHINES OR APPARATUS, NOT SPECIFIC TO ENGINES, MACHINES OR APPARATUS PROVIDED FOR ELSEWHERE; STANDS; SUPPORTS
    • F16M11/00Stands or trestles as supports for apparatus or articles placed thereon ; Stands for scientific apparatus such as gravitational force meters
    • F16M11/02Heads
    • F16M11/18Heads with mechanism for moving the apparatus relatively to the stand
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16MFRAMES, CASINGS OR BEDS OF ENGINES, MACHINES OR APPARATUS, NOT SPECIFIC TO ENGINES, MACHINES OR APPARATUS PROVIDED FOR ELSEWHERE; STANDS; SUPPORTS
    • F16M13/00Other supports for positioning apparatus or articles; Means for steadying hand-held apparatus or articles
    • F16M13/02Other supports for positioning apparatus or articles; Means for steadying hand-held apparatus or articles for supporting on, or attaching to, an object, e.g. tree, gate, window-frame, cycle
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/30Monitoring
    • G06F11/3003Monitoring arrangements specially adapted to the computing system or computing system component being monitored
    • G06F11/3006Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for program control, e.g. control units
    • G06F9/06Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46Multiprogramming arrangements
    • G06F9/50Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5083Techniques for rebalancing the load in a distributed system

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  • Engineering & Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Computing Systems (AREA)
  • General Physics & Mathematics (AREA)
  • Software Systems (AREA)
  • Mathematical Physics (AREA)
  • Quality & Reliability (AREA)
  • Information Transfer Between Computers (AREA)
  • Computer And Data Communications (AREA)

Abstract

The invention discloses a server platform based on big data, which comprises a server and a working box for loading the server, wherein an extensible loading frame is arranged in the working box, the loading frame comprises a loading plate for loading the server and supporting plates positioned on two sides of the loading plate, the supporting plates are hinged with the inside of the working box through an extension mechanism, the supporting plates are provided with limit structures, and after the supporting plates are completely extended out of the working box, the limit structures are matched with the extension mechanism to limit the extension state of the supporting plates. According to the invention, the extensible loading frame is arranged in the working box, and after the loading frame is completely extended out of the working box, the limiting structure can be matched with the extension mechanism to limit the extension state of the loading frame, so that the server can be extended out of the working box, and the server is convenient to overhaul and maintain.

Description

Big data-based server platform
Technical Field
The invention relates to the technical field of big data processing, in particular to a server platform based on big data.
Background
Big data processing is higher to the requirement of server platform, need regularly overhaul and maintain the server platform, and present server platform is used for loading the work box of server, does not have the extension function for overhaul and maintenance personnel must squat just can go on, are unfavorable for like this to overhaul and maintain.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a server platform based on big data aiming at the defects in the prior art, so as to overcome the defect that the server platform is not beneficial to overhaul and maintenance in the prior art.
According to the invention, the server platform based on big data comprises a server and a working box for loading the server, wherein an extensible loading frame is arranged in the working box, the loading frame comprises a loading plate for loading the server and supporting plates positioned on two sides of the loading plate, the supporting plates are hinged with the inside of the working box through an extension mechanism, the supporting plates are provided with limit structures, and after the supporting plates are completely extended out of the working box, the limit structures are matched with the extension mechanism to limit the extension state of the supporting plates.
Furthermore, the supporting plate is rotatably connected with an upper connecting rod and a lower connecting rod, the upper connecting rod and the lower connecting rod are respectively and parallelly rotatably connected in the working box, an upper limiting pin is arranged on the upper connecting rod, and after the supporting plate is completely extended out of the working box, the upper limiting pin is matched with the limiting structure to limit the upper connecting rod.
Further, a lower positioning pin is fixed in the working box and is abutted against the lower connecting rod to limit the lower connecting rod.
Furthermore, limit structure includes the limiting plate of being connected with the backup pad rotation, and the limiting plate is equipped with the spacing groove, and the limiting plate is equipped with the torsional spring with the rotation department of backup pad, goes up the connecting rod and the lower connecting rod expandes the back completely, goes up the spacer pin and slides in the spacing inslot.
Further, the arc wall has been seted up to the backup pad, is equipped with the slider in the arc wall, slider and limiting plate fixed connection, the slider is located the arc wall inner under the effect of torsional spring.
Furthermore, the supporting plate is provided with a pull rod seat, a pull rod is arranged in the pull rod seat in a sliding mode, and the pull rod is fixedly connected with the sliding block.
Furthermore, a moving plate is arranged on the loading plate, the moving plate is connected with the loading plate in a sliding mode, and the server is loaded on the moving plate.
Furthermore, a moving groove is formed in the loading plate, and the moving plate moves on the loading plate along the moving groove.
Furthermore, after the supporting plate is completely extended out of the working box, the height of the moving plate is consistent with that of the working box, and the moving plate can be in butt joint with the table top of the working box.
Furthermore, an armrest is arranged on the loading plate.
According to the server platform based on the big data, the extensible loading frame is arranged in the work box, after the loading frame is completely extended out of the work box, the limiting structure can be matched with the extension mechanism to limit the extension state of the loading frame, the server can be extended out of the work box, and therefore the server platform is convenient to overhaul and maintain.
Drawings
A more complete understanding of the present invention, and the attendant advantages and features thereof, will be more readily understood by reference to the following detailed description when considered in conjunction with the accompanying drawings wherein:
FIG. 1 is a schematic flow chart of a big data-based processing method according to the present invention;
FIG. 2 is a schematic diagram of a big data based processing system according to the present invention;
FIG. 3 is a schematic structural diagram of a work box in a big data-based server platform according to the present invention;
FIG. 4 is a schematic view of the loading carriage of FIG. 3 fully extended out of the work box;
FIG. 5 is a schematic structural view of the upper and lower links of FIG. 4;
FIG. 6 is a schematic view of the structure of the loading plate and the supporting plate in FIG. 4;
FIG. 7 is a schematic view of the structure of the additional movable plate of the working box of the present invention;
fig. 8 is a bottom structure diagram of the loading frame of the present invention.
It is to be noted, however, that the appended drawings illustrate rather than limit the invention. It is noted that the drawings representing structures may not be drawn to scale. Also, in the drawings, the same or similar elements are denoted by the same or similar reference numerals.
Detailed Description
In order that the present disclosure may be more clearly and readily understood, reference will now be made in detail to the present disclosure as illustrated in the accompanying drawings.
As shown in fig. 1, the big data based processing method of this embodiment includes the following steps:
and step S1, after receiving the data, distributing the data to one sub server of a plurality of sub servers in the server according to the data distribution rule for processing. The data distribution rules include: distributing data according to the number sequence of a plurality of sub-servers, such as 1, 2 … … n, distributing the data to one sub-server each time, distributing the next data to the next sub-server, namely distributing the data 1 to the sub-server 1 after receiving the data 1, distributing the data 2 to the sub-server 2 … … after receiving the data 2, distributing the data n to the sub-server n after receiving the data n, and judging the operation load rate of the current sub-server before distributing, if the operation load rate of the current sub-server exceeds the load threshold value, skipping the current sub-server, for example, when the data 2 is to be distributed to the sub-server 2, judging the operation load rate of the sub-server 2 first, if the operation load rate of the sub-server 2 does not exceed the load threshold value, distributing the data 2 to the sub-server 2, if the operation load rate of the sub-server 2 exceeds the load threshold value, skipping the sub-server 2, judging the operation load rate of the next sub-server, i.e. the sub-server 3, and so on, if the operation load rate of the sub-server 3 does not exceed the load threshold, distributing the data 2 to the sub-server 3. In addition, if the current sub-server is the last sub-server, the next sub-server of the current sub-server is the first sub-server, that is, after the data n is distributed to the sub-server n, the next data n +1 is distributed to the sub-server 1.
The data distribution rule in the step is reasonable, and the sub-server can be skipped when the operation load rate of the sub-server exceeds the load threshold value, so that all the sub-servers can be mobilized to the maximum extent.
And step S2, monitoring the operation load rates of a plurality of sub servers in real time, and comparing the operation load rate of each sub server with a load threshold value. Here, the operation load rate is a ratio of the operation load realized by the sub-server to a rated operation load, and is between 0% and 100%, if the operation load rate is 0, it indicates that the sub-server does not have a data processing task currently, and if the operation load rate is 100%, it indicates that the sub-server is operating at full load and processing data currently.
Step S3, if the operation load rate of any one of the sub-servers exceeds the load threshold a times within the first preset time period, the load threshold is increased once according to the load threshold adjustment rule, where the threshold adjustment rule is to increase the load threshold 10% each time, for example, if it is monitored that the operation load rate of the sub-server 2 exceeds the load threshold a times within 10S, which indicates that substantially all the sub-servers have operated and the data distribution is uniform, the load threshold is increased by 10%, and the load threshold is not higher than 100%, and the next batch of data is received. If the operation load rates of all the sub-servers do not exceed the load threshold for b times within the second preset time period, the load threshold is adjusted to an initial value, for example, it is monitored that the operation load rates of all the sub-servers do not exceed the load threshold for b times within 30S, which indicates that the task of processing data is not large at this time, and the load threshold needs to be reduced to enable the data distribution to be uniform, and the load threshold is adjusted to the initial value. Here, the load threshold is 30% -100%, the initial value of the load threshold is 30%, the second preset time period is greater than the first preset time period, b is greater than a, and the specific value is set according to the number of the sub-servers and the data processing amount.
As shown in fig. 2, the big data based processing system of the present embodiment includes a data distribution unit, a monitoring unit, and an adjustment unit. The data distribution unit is used for distributing the data to a sub-server of one of a plurality of sub-servers in the server for processing according to a data distribution rule after receiving the data, and the data distribution rule comprises the following steps: distributing data according to the number sequence of a plurality of sub-servers, such as 1, 2 … … n, distributing the data to one sub-server each time, distributing the next data to the next sub-server, namely distributing the data 1 to the sub-server 1 after receiving the data 1, distributing the data 2 to the sub-server 2 … … after receiving the data 2, distributing the data n to the sub-server n after receiving the data n, and judging the operation load rate of the current sub-server before distributing, if the operation load rate of the current sub-server exceeds the load threshold value, skipping the current sub-server, for example, when the data 2 is to be distributed to the sub-server 2, judging the operation load rate of the sub-server 2 first, if the operation load rate of the sub-server 2 does not exceed the load threshold value, distributing the data 2 to the sub-server 2, if the operation load rate of the sub-server 2 exceeds the load threshold value, skipping the sub-server 2, judging the operation load rate of the next sub-server, i.e. the sub-server 3, and so on, if the operation load rate of the sub-server 3 does not exceed the load threshold, distributing the data 2 to the sub-server 3. In addition, if the current sub-server is the last sub-server, the next sub-server of the current sub-server is the first sub-server, that is, after the data n is distributed to the sub-server n, the next data n +1 is distributed to the sub-server 1. The monitoring unit is used for monitoring the operation load rate of a plurality of sub-servers in real time, and comparing the operation load rate of each sub-server with a load threshold value, wherein the operation load rate refers to the ratio of the operation load realized by the sub-servers to the rated operation load, and is between 0 and 100 percent, if the operation load rate is 0, the sub-servers are indicated to have no data processing task at present, and if the operation load rate is 100 percent, the sub-servers are indicated to be operated and processed with data at full load at present. The adjusting unit is configured to, if the operation load rate of any one of the sub-servers exceeds the load threshold a times within a first preset time period, increase the load threshold according to a threshold adjustment rule, for example, if it is monitored that the operation load rate of the sub-server 2 exceeds the load threshold a times within 10S, which indicates that substantially all the sub-servers have been operated and data distribution is uniform, increase the load threshold by 10%, where the load threshold is not higher than 100%, and receive the next batch of data. If the operation load rates of all the sub-servers do not exceed the load threshold for b times within the second preset time period, the load threshold is adjusted to an initial value, for example, it is monitored that the operation load rates of all the sub-servers do not exceed the load threshold for b times within 30S, which indicates that the task of processing data is not large at this time, and the load threshold needs to be reduced to enable the data distribution to be uniform, and the load threshold is adjusted to the initial value. Here, the load threshold is 30% -100%, the initial value of the load threshold is 30%, the second preset time period is greater than the first preset time period, b is greater than a, and the specific value is set according to the number of the sub-servers and the data processing amount. Wherein the adjusting unit includes: the device comprises a first counting module, a second counting module and an adjusting module, wherein the first counting module is provided with a plurality of sub-servers, and is used for recording that the sub-servers exceed a load threshold once when the running load rate of the sub-servers exceeds the load threshold once within a first preset time period. And the second counting module is used for counting and adding 1 when the running load rates of all the sub servers do not exceed the load threshold once in a second preset time period. The adjusting module is used for increasing the load threshold value according to a preset threshold value adjusting rule when the running load rate of any one of the sub-servers exceeds the load threshold value for a times within a first preset time period; and adjusting the load threshold value to an initial value when the operation load rates of all the sub-servers do not exceed the load threshold value for b times in a second preset time period.
The server platform based on big data of the embodiment comprises a server, wherein a computer program is stored on the server, and the server realizes the big data processing method when executing the computer program. As shown in fig. 3 to 6, the server platform further includes a work box 1 for loading the server, an extensible loading frame is disposed in the work box 1, the loading frame includes a loading plate 2 and supporting plates 3 located at two sides of the loading plate 2, the supporting plates 3 are hinged to the inside of the work box 1 through an extending mechanism, the supporting plates 3 are provided with a limiting structure, and after the supporting plates 3 are completely extended out of the work box 1, the limiting structure cooperates with the extending mechanism to limit the extending state of the supporting plates 3. Like this, be equipped with the loading frame that can extend in work box 1, after the loading frame stretches out work box 1 completely, limit structure can cooperate with the extension state in order to inject the loading frame with the extension mechanism, can stretch out work box 1 with the server, easy to overhaul and maintain.
The supporting plate 3 is rotatably connected with an upper connecting rod 4 and a lower connecting rod 5, the upper connecting rod 4 and the lower connecting rod 5 are respectively and parallelly connected in the working box 1 in a rotating mode, an upper limiting pin 6 is arranged on the upper connecting rod 4, and after the supporting plate 3 is completely extended out of the working box 1, the upper limiting pin 6 is matched with a limiting structure to limit the upper connecting rod 4. Particularly, limit structure includes the limiting plate 7 of being connected with the backup pad 3 rotation, limiting plate 7 is equipped with spacing groove 8, limiting plate 7 is equipped with the torsional spring with the rotation department of backup pad 3, go up connecting rod 4 and lower connecting rod 5 and expand the back completely, go up the spacer pin 6 and slide in the spacing groove 8 and realize spacing to last connecting rod 4, arc 9 has been seted up to backup pad 3 in addition, be equipped with slider 10 in the arc 9, slider 10 and limiting plate 7 fixed connection, backup pad 3 is equipped with pull rod seat 11, it is equipped with pull rod 12 to slide in the pull rod seat 11, pull rod 12 and slider 10 fixed connection. When the loading plate 2 and the supporting plate 3 are not completely extended out of the working box 1, the sliding block 10 is positioned at the inner end of the arc-shaped groove 9 under the action of the torsion spring, when the loading plate 2 and the supporting plate 3 are completely extended out of the working box 1, the upper limiting pin 6 can automatically slide into the limiting groove 8 and is firmly connected with the limiting groove 8 under the action of the torsion spring, the limitation on the upper connecting rod 4 is realized, the server positioned on the loading plate 2 is lifted at the moment, the maintenance is convenient, the sliding block 10 is pulled through the pull rod 12 after the maintenance, the limiting groove 8 is separated from the upper limiting pin 6, and the loading plate 2 and the supporting plate 3 can be folded into the working box 1.
After the loading plate 2 and the supporting plate 3 are completely extended out of the working box 1, in order to further improve the limiting locking strength of the loading plate 2 and the supporting plate 3, a lower positioning pin 13 is fixed in the working box 1 of the embodiment, and the lower positioning pin 13 is abutted to the lower connecting rod 5 to limit the lower connecting rod 5.
As shown in fig. 7, in another embodiment, a moving plate 14 is provided on a loading plate 2, the moving plate 14 is slidably connected to the loading plate 2, a server is loaded on the moving plate 14, a moving slot 15 is provided on the loading plate 2, the moving plate 14 moves on the loading plate 2 along the moving slot 15, and after the loading plate 2 and a supporting plate 3 are completely extended out of a work box 1, the height of the moving plate 14 is consistent with the height of the work box 1 and can be abutted against the table top of the work box 1, and an armrest 16 is provided on the loading plate 2. After the loading plate 2 and the support plate 3 are completely extended out of the work box 1 by the armrest 16, the moving plate 14 can be moved from the loading plate 2 so as to be in butt joint with the table top of the work box 1, which facilitates the movement of the server from the loading plate 2 to the table top of the work box 1, and facilitates the maintenance and repair.
As shown in fig. 8, in another embodiment, a lock pin 17, a triangular rod 18, a lock rod 19 and a spring sleeve 20 are arranged at the bottom of the loading plate 2, the triangular rod 18 has a first end, a second end and a third end, the first end of the triangular rod 18 is hinged to the lock pin 17, the second end of the triangular rod 18 is hinged to the support plate 3, the third end of the triangular rod 18 is hinged to the lock rod 19, the lock rod 19 is sleeved on the spring sleeve 20 and then extends out of the armrest 16, an irregular tooth socket is arranged in the work box 1, the lock pin 17 extends out of the support plate 3 under the action of the spring sleeve 20 and is in locking connection with the irregular tooth socket, and the limit that the loading plate 2 and the support. And the locking pins 17 are disengaged from the irregular tooth grooves in the working box 1 by pulling the triangular bar 18 through the locking bar 19, so that the loading plate 2 and the supporting plate 3 can be extended.
Through setting up structures such as lockpin 17, can realize on the one hand that loading plate 2 and backup pad 3 are folded completely spacing and position locking in work box 1, prevent that loading plate 2 and backup pad 3 move unusually and lead to the server to operate unstably, on the other hand can be to loading plate 2 and backup pad 3 and even the server be in the position locking (the restriction that receives irregular tooth's socket position) under the state of little amplitude extension, promptly in this interval, can lock loading plate 2 and backup pad 3 and even server to any position, be convenient for the maintenance and the maintenance of minor problems, need not to stretch out it completely.
It is to be understood that while the present invention has been described in conjunction with the preferred embodiments thereof, it is not intended to limit the invention to those embodiments. It will be apparent to those skilled in the art from this disclosure that many changes and modifications can be made, or equivalents modified, in the embodiments of the invention without departing from the scope of the invention. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention are still within the scope of the protection of the technical solution of the present invention, unless the contents of the technical solution of the present invention are departed.

Claims (10)

1. The utility model provides a server platform based on big data, its characterized in that includes server and the work box that is used for loading the server, is equipped with the loading frame that can extend in the work box, loads the frame including the loading board that is used for loading the server and the backup pad that is located loading board both sides, and the backup pad is articulated through the inside of extension mechanism with the work box, and the backup pad is equipped with limit structure, and after the backup pad extended the work box completely, limit structure and extension mechanism cooperation were in order to inject the extended state of backup pad.
2. The big-data-based server platform as claimed in claim 1, wherein the supporting plate is rotatably connected with an upper connecting rod and a lower connecting rod, the upper connecting rod and the lower connecting rod are rotatably connected in the work box in parallel, the upper connecting rod is provided with an upper limit pin, and the upper limit pin is matched with the limit structure to limit the upper connecting rod after the supporting plate is completely extended out of the work box.
3. The big data-based server platform according to claim 2, wherein a lower positioning pin is fixed in the work box, and the lower positioning pin abuts against the lower connecting rod to limit the lower connecting rod.
4. The big-data-based server platform as claimed in claim 2, wherein the limiting structure comprises a limiting plate rotatably connected to the supporting plate, the limiting plate is provided with a limiting groove, a torsion spring is provided at a rotating position of the limiting plate and the supporting plate, and the upper limiting pin slides into the limiting groove after the upper connecting rod and the lower connecting rod are completely unfolded.
5. The big-data-based server platform according to claim 4, wherein the supporting plate is provided with an arc-shaped groove, a sliding block is arranged in the arc-shaped groove, the sliding block is fixedly connected with the limiting plate, and the sliding block is located at the inner end of the arc-shaped groove under the action of the torsion spring.
6. The big-data-based server platform as claimed in claim 5, wherein the supporting plate has a rod seat, a rod is slidably disposed in the rod seat, and the rod is fixedly connected to the sliding block.
7. The big data based server platform as claimed in claim 1, wherein the loading plate is provided with a moving plate, the moving plate is slidably connected to the loading plate, and the server is loaded on the moving plate.
8. The big data based server platform as claimed in claim 7, wherein the loading plate is provided with a moving slot, and the moving plate moves on the loading plate along the moving slot.
9. The big data based server platform of claim 7, wherein the height of the moving plate is the same as the height of the work box and can be abutted with the table top of the work box after the supporting plate is completely extended out of the work box.
10. The big data based server platform of claim 7, wherein the load board has a handrail.
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