Big data analysis server system

Abstract

The invention relates to the field of big data, in particular to a big data analysis server system. Comprising a data acquisition module, a distributed storage module, a distributed calculation module, a data processing and analysis module, a visualization and report module and a security and authority control module. And the data acquisition module is responsible for acquiring data from a database and transmitting the data to the system for processing and analysis, and has the functions of data extraction, data cleaning and data conversion. The distributed storage module is a module for storing a large-scale data set and is composed of a plurality of storage modules, and each module is responsible for storing a part of data and providing storage services with high reliability and expandability. Data in the storage module can be prevented from being stolen manually.

Description

Technical Field

[0001] This invention relates to the field of big data, and more specifically to a big data analysis server system. Background Technology

[0002] Big data analytics server systems can be based on distributed computing and storage, enabling them to handle the analysis and mining of large-scale datasets. Such systems typically consist of multiple server nodes, each with computing and storage capabilities. The system can divide large datasets into multiple parts and distribute these parts to different server nodes for parallel computation. This significantly improves the speed and efficiency of data processing. However, traditional big data analytics server systems cannot guarantee that data in the storage modules will not be stolen manually. Summary of the Invention

[0003] To overcome the shortcomings of existing technologies, this invention provides a big data analysis server system, which has the advantage of preventing data in the storage module from being stolen by humans.

[0004] A big data analytics server system includes a data acquisition module, a distributed storage module, a distributed computing module, a data processing and analysis module, a visualization and reporting module, and a security and access control module.

[0005] The data acquisition module is responsible for collecting data from the database and transmitting it to the system for processing and analysis, including data extraction, data cleaning, and data transformation functions.

[0006] The distributed storage module is used to store large-scale datasets. It consists of multiple storage modules, each responsible for storing a portion of the data, providing highly reliable and scalable storage services.

[0007] The distributed computing module is used for distributed computing and analysis of large-scale datasets. It consists of multiple server nodes, each responsible for processing a portion of the data, and uses coordination and communication to distribute tasks and aggregate results. Attached Figure Description

[0008] The present invention will now be described in further detail with reference to the accompanying drawings and specific implementation methods.

[0009] Figure 1 This is a schematic diagram of a big data analytics server system;

[0010] Figure 2 Schematic diagram of the distributed storage module Figure 1 ;

[0011] Figure 3 Schematic diagram of the distributed storage module Figure 2;

[0012] Figure 4 Schematic diagram of the distributed storage module Figure 3 ;

[0013] Figure 5 This is a schematic diagram of the circular base.

[0014] Figure 6 This is a structural schematic diagram of the connecting frame;

[0015] Figure 7 Schematic diagram of the box structure Figure 1 ;

[0016] Figure 8 Schematic diagram of the box structure Figure 2 ;

[0017] Figure 9 Schematic diagram of the arched slab structure Figure 1 ;

[0018] Figure 10 Schematic diagram of the arched slab structure Figure 2 .

[0019] In the diagram: 101 round base; 102 crossbeam; 103 rotating block; 104 column; 105 square column; 106 L-shaped frame; 107 pressure block; 108 arc rod; 109 bar.

[0020] Connector 201; cam shaft 202; motor 203; gear 204; gear ring 205; stop block 206;

[0021] 301 Cabinet; 302 Curved panel; 303 Storage disk; 304 Socket; 305 Bracket; 306 Bottom case; 307 Large hard drive; 308 Rear pillar;

[0022] Arched plate 401; curved edge 402; center rod 403. Detailed Implementation

[0023] A big data analytics server system includes a data acquisition module, a distributed storage module, a distributed computing module, a data processing and analysis module, a visualization and reporting module, and a security and access control module.

[0024] The data acquisition module is responsible for collecting data from the database and transmitting it to the system for processing and analysis, including data extraction, data cleaning, and data transformation functions.

[0025] The distributed storage module is used to store large-scale datasets. It consists of multiple storage modules, each responsible for storing a portion of the data, providing highly reliable and scalable storage services.

[0026] The distributed computing module is used for distributed computing and analysis of large-scale datasets. It consists of multiple server nodes, each responsible for processing a portion of the data, and uses coordination and communication to distribute tasks and aggregate results.

[0027] The data processing and analysis module provides data processing and analysis functions, including data cleaning, data transformation, data aggregation, data mining, and machine learning, to help users extract valuable information and insights from large-scale data.

[0028] The visualization and reporting module is used to present the analysis results to users in the form of charts and reports, helping users understand and analyze data, and supporting interactive data exploration and visualization.

[0029] The security and access control module is used to protect data security and manage user permissions. It performs user authentication, access control, and data encryption to ensure that only authorized users can access and operate the data.

[0030] like Figure 7-8 As shown, this example can achieve the effect of setting up multiple storage disks 303 in an arc-shaped array on the arc-shaped plate 302.

[0031] The distributed storage module includes a housing 301, with an arc-shaped plate 302 welded to its upper side. Multiple sockets 304 are welded to the upper side of the arc-shaped plate 302, and storage disks 303 are plugged into each socket 304. Therefore, multiple storage disks 303 can be arranged in an arc-shaped array on the arc-shaped plate 302. These multiple storage disks 303 constitute multiple storage modules, each responsible for storing a portion of the data, providing highly reliable and scalable storage services.

[0032] like Figure 7-8 As shown, this example can be used to store the main data in the system.

[0033] The bottom of the enclosure 301 is connected to the base 306 by screws. The base 306 is connected to a large hard drive 307. The bottom of the base 306 is connected to the bracket 305 by screws. The bracket 305 is used to support the base 306 and the enclosure 301. The large hard drive 307 is used to store the main data in the system. The large hard drive 307 has the feature of large storage capacity.

[0034] like Figure 2-8 As shown, this example can achieve the effect of preventing thieves from inserting data cables into the storage disk through the gaps between the multiple bars 109 and the multiple posts 104 without affecting heat dissipation.

[0035] Since the front of the enclosure 301 is connected to the connecting frame 201 by screws, and the rear of the round seat 101 is welded with a cam 202, the cam 202 is rotatably connected to the front of the connecting frame 201. The upper and lower ends of the front of the round seat 101 are hinged with rotating blocks 103. An arc rod 108 is welded on the upper rotating block 103, and multiple bars 109 are welded on the arc rod 108. The multiple bars 109 block the front of the multiple storage disks 303. A crossbeam 102 is welded on the lower rotating block 103, and multiple posts 104 are welded on the crossbeam 102. The multiple posts 104 block the front of the large hard disk 307. Multiple bars 109 shield the front of multiple storage disks 303 to prevent data theft by inserting data cables into them. Multiple posts 104 shield the front of a large hard drive 307 to prevent data theft by inserting data cables into it. The circular base 101 can reciprocate in both directions via the convex shaft 202, thereby driving the bars 109 and posts 104 to reciprocate in both directions, continuously changing their positions. This ensures that, without affecting heat dissipation, thieves cannot insert data cables into the storage disks through the gaps between the bars 109 and posts 104. When it is necessary to remove the shielding from the storage disks 303 and the large hard drive 307, two rotating blocks 103 are driven to rotate forward, thus opening the bars 109 and posts 104.

[0036] An L-shaped frame 106 is welded to the front side of the circular base 101. A square column 105 is slidably connected to the L-shaped frame 106. A pressure block 107 is welded to the rear of the square column 105. The pressure block 107 presses on the front side of the two rotating blocks 103. A fastening screw is threadedly connected to the L-shaped frame 106. The fastening screw presses on the square column 105.

[0037] like Figure 5-6 As shown, this example can achieve the effect of blocking multiple bars 109 and multiple posts 104 on multiple storage disks 303 and large hard disks 307.

[0038] The square column 105 can move backward, thereby causing the pressure block 107 to press against the front side of the two rotating blocks 103, thereby fixing the two rotating blocks 103, and thus blocking the multiple bars 109 and multiple bars 104 on the multiple storage disks 303 and the large hard disk 307.

[0039] A motor 203 is connected to the connecting frame 201 by screws. A gear 204 is connected to the output shaft of the motor 203. A gear ring 205 is connected to the upper part of the round seat 101 by screws. Both ends of the gear ring 205 are fixed with stop blocks 206. The gear 204 meshes with the gear ring 205 for transmission.

[0040] like Figure 5-6As shown, this example can achieve the effect of driving the circular seat 101 to swing back and forth in both directions via the convex shaft 202.

[0041] The motor 203 drives the gear 204 to rotate, which in turn drives the gear ring 205 and the round seat 101 to rotate. When the gear 204 contacts the stop block 206 and can no longer rotate, the gear 204 rotates in the opposite direction, which in turn drives the round seat 101 to swing back and forth through the cam shaft 202.

[0042] A rear column 308 is fixed to the rear side of the enclosure 301. A central rod 403 is welded to the arched plate 401. The central rod 403 is slidably connected to the rear column 308 in the front-back direction. A second fastening screw is threaded onto the central rod 403. The second fastening screw presses against the rear column 308. The arched plate 401 is located above the multiple storage disks 303. A large hard disk 307 is located inside the arched plate 401. An arc-shaped edge 402 is welded to the upper rear side of the arched plate 401. The arc-shaped edge 402 blocks the rear side of the multiple storage disks 303.

[0043] like Figure 2-10 As shown, this example can prevent thieves from removing multiple storage disks 303 and large hard drives 307.

[0044] An arched plate 401 is located on the upper side of multiple storage disks 303, and a hard disk 307 is located on the inner side of the arched plate 401. The arched plate 401 thus blocks the multiple storage disks 303 and the large hard disk 307, preventing thieves from removing the multiple storage disks 303 and the large hard disk 307. An arc-shaped edge 402 blocks the rear side of multiple storage disks 303, preventing thieves from stealing multiple storage disks 303 from the rear. The drive rod 403 slides on the rear column 308, which can move the arched plate 401 away.

Claims

1. A big data analytics server system, characterized in that: It includes a data acquisition module, a distributed storage module, a distributed computing module, a data processing and analysis module, a visualization and reporting module, and a security and access control module.

2. The big data analysis server system according to claim 1, characterized in that: The data acquisition module is responsible for collecting data from the database and transmitting it to the system for processing and analysis, including data extraction, data cleaning, and data transformation functions.

3. The big data analysis server system according to claim 1, characterized in that: The distributed storage module is used to store large-scale datasets. It consists of multiple storage modules, each responsible for storing a portion of the data, providing highly reliable and scalable storage services.

4. The big data analysis server system according to claim 1, characterized in that: The distributed computing module is used for distributed computing and analysis of large-scale datasets. It consists of multiple server nodes, each responsible for processing a portion of the data, and uses coordination and communication to distribute tasks and aggregate results.

5. The big data analysis server system according to claim 1, characterized in that: The data processing and analysis module provides data processing and analysis functions, including data cleaning, data transformation, data aggregation, data mining, and machine learning, to help users extract valuable information and insights from large-scale data.

6. The big data analysis server system according to claim 1, characterized in that: The visualization and reporting module is used to display the analysis results to users in the form of charts and reports, helping users understand and analyze data, and supporting interactive data exploration and visualization.

7. The big data analysis server system according to claim 1, characterized in that: The security and access control module is used to protect data security and manage user permissions. It performs user authentication, access control, and data encryption to ensure that only authorized users can access and operate the data.

8. A big data analysis server system according to claim 3, characterized in that: The distributed storage module includes a housing (301), an arc-shaped plate (302) is fixed on the upper side of the housing (301), and multiple sockets (304) are fixed on the upper side of the arc-shaped plate (302), with storage disks (303) plugged into each of the multiple sockets (304).

9. A big data analysis server system according to claim 8, characterized in that: A base box (306) is fixed to the lower side of the enclosure (301), a large hard disk (307) is connected to the base box (306), and a bracket (305) is fixed to the lower side of the base box (306).

10. A big data analysis server system according to claim 9, characterized in that: A connecting frame (201) is fixed to the front side of the interior of the housing (301), and a convex shaft (202) is fixed to the rear side of the round seat (101). The convex shaft (202) is rotatably connected to the front of the connecting frame (201). A rotating block (103) is hinged to the upper and lower ends of the front side of the round seat (101). An arc rod (108) is fixed on the upper rotating block (103), and multiple bars (109) are fixed on the arc rod (108). The multiple bars (109) block the front side of the multiple storage disks (303). A crossbeam (102) is fixed on the lower rotating block (103), and multiple columns (104) are fixed on the crossbeam (102). The multiple columns (104) block the front side of the large hard disk (307).

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