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Big Dataset Scenario Test Results

Last updated: 2023-11-20 17:29:52
    This document lists the performance comparison test results between TDSQL-C for MySQL and TencentDB for MySQL in the big dataset scenario.

    Big Dataset Scenario Overview

    In the big dataset scenario, the entire volume of data cannot be all stored in the cache (the data volume is twice the memory size), and the disk needs to be read and written to update the cache during queries.

    Test Conclusion for Big Dataset Scenario

    In the read scenario, TDSQL-C for MySQL can achieve a CPU utilization of above 90% on compute nodes. The test shows that the resource utilization of TDSQL-C for MySQL is better than that of TencentDB for MySQL.
    In the write scenario, TDSQL-C for MySQL outperforms TencentDB for MySQL under lower specifications, and as the specifications and data volume increase, its performance advantage gets much greater.
    Dataset Characteristics
    Test Scenario
    Read Type
    Conclusion
    Big dataset
    Write
    -
    TDSQL-C for MySQL outperforms TencentDB for MySQL, especially under high specifications
    Read
    POINT SELECT
    TDSQL-C for MySQL has a higher performance
    Read
    RANGE SELECT
    TDSQL-C for MySQL and TencentDB for MySQL have generally the same performance under most specifications
    Read-write
    POINT SELECT
    TDSQL-C for MySQL has a higher performance
    Read-write
    RANGE SELECT
    TDSQL-C for MySQL and TencentDB for MySQL have generally the same performance under most specifications

    Test Results for Big Dataset Scenario

    Scenario 1: Write
    
    Specification
    Concurrency
    Table Size
    Tables
    QPS
    TencentDB for MySQL
    TDSQL-C for MySQL
    2-core 16 GB MEM
    96
    800000
    150
    14772
    26864
    4-core 16 GB MEM
    96
    800000
    300
    31140
    45881
    4-core 32 GB MEM
    192
    800000
    300
    31539
    53082
    8-core 32 GB MEM
    192
    800000
    300
    54397
    97005
    8-core 64 GB MEM
    192
    800000
    450
    54945
    92988
    16-core 64 GB MEM
    192
    800000
    450
    60948
    111596
    16-core 96 GB MEM
    256
    800000
    600
    79163
    109014
    16-core 128 GB MEM
    384
    5000000
    300
    105781
    142165
    32-core 128 GB MEM
    384
    5000000
    300
    81662
    252668
    32-core 256 GB MEM
    384
    5000000
    400
    101277
    270367
    64-core 256 GB MEM
    384
    6000000
    450
    115992
    301974
    Scenario 2: Read
    
    Specification
    Concurrency
    Table Size
    Tables
    QPS
    TencentDB for MySQL
    TDSQL-C for MySQL
    2-core 16 GB MEM
    512
    800000
    150
    38594
    45597
    4-core 16 GB MEM
    512
    800000
    300
    73117
    75483
    4-core 32 GB MEM
    1000
    800000
    300
    74664
    92117
    8-core 32 GB MEM
    1000
    800000
    300
    142866
    181402
    8-core 64 GB MEM
    1000
    800000
    450
    149526
    172378
    16-core 64 GB MEM
    1000
    800000
    450
    303341
    325878
    16-core 96 GB MEM
    1000
    800000
    600
    311256
    336011
    16-core 128 GB MEM
    1000
    5000000
    300
    262724
    323877
    32-core 128 GB MEM
    1000
    5000000
    300
    483449
    573631
    32-core 256 GB MEM
    1000
    5000000
    400
    474329
    615283
    64-core 256 GB MEM
    1000
    6000000
    450
    663715
    940105
    Scenario 3: Read
    
    Specification
    Concurrency
    Table Size
    Tables
    QPS
    TencentDB for MySQL
    TDSQL-C for MySQL
    2-core 16 GB MEM
    64
    800000
    150
    13571
    14388
    4-core 16 GB MEM
    64
    800000
    300
    28962
    26079
    4-core 32 GB MEM
    64
    800000
    300
    30045
    28314
    8-core 32 GB MEM
    64
    800000
    300
    47298
    57353
    8-core 64 GB MEM
    64
    800000
    450
    58638
    57281
    16-core 64 GB MEM
    128
    800000
    450
    104072
    98246
    16-core 96 GB MEM
    128
    800000
    600
    114502
    106160
    16-core 128 GB MEM
    128
    5000000
    300
    121297
    109978
    32-core 128 GB MEM
    256
    5000000
    300
    192649
    183658
    32-core 256 GB MEM
    256
    5000000
    400
    185941
    184855
    64-core 256 GB MEM
    256
    6000000
    450
    283903
    278997
    Scenario 4: Read-write
    
    Specification
    Concurrency
    Table Size
    Tables
    QPS
    TencentDB for MySQL
    TDSQL-C for MySQL
    2-core 16 GB MEM
    64
    800000
    150
    20726
    22997
    4-core 16 GB MEM
    256
    800000
    300
    47820
    51545
    4-core 32 GB MEM
    256
    800000
    300
    52680
    62105
    8-core 32 GB MEM
    256
    800000
    300
    94132
    108540
    8-core 64 GB MEM
    256
    800000
    450
    100882
    120153
    16-core 64 GB MEM
    256
    800000
    450
    192474
    193744
    16-core 96 GB MEM
    256
    800000
    600
    186854
    184257
    16-core 128 GB MEM
    512
    5000000
    300
    188389
    195375
    32-core 128 GB MEM
    512
    5000000
    300
    227494
    306809
    32-core 256 GB MEM
    512
    5000000
    400
    245819
    307072
    64-core 256 GB MEM
    512
    6000000
    450
    335819
    453163
    Scenario 5: Read-write (RANGE SELECT)
    
    Specification
    Concurrency
    Table Size
    Tables
    QPS
    TencentDB for MySQL
    TDSQL-C for MySQL
    2-core 16 GB MEM
    32
    800000
    150
    13177
    13883
    4-core 16 GB MEM
    32
    800000
    300
    27935
    20720
    4-core 32 GB MEM
    64
    800000
    300
    30705
    29914
    8-core 32 GB MEM
    96
    800000
    300
    50166
    58060
    8-core 64 GB MEM
    64
    800000
    450
    57866
    53804
    16-core 64 GB MEM
    128
    800000
    450
    107923
    95976
    16-core 96 GB MEM
    128
    800000
    600
    107589
    107180
    16-core 128 GB MEM
    256
    5000000
    300
    138710
    110169
    32-core 128 GB MEM
    256
    5000000
    300
    165299
    180335
    32-core 256 GB MEM
    256
    5000000
    400
    166066
    171670
    64-core 256 GB MEM
    512
    6000000
    450
    208616
    190824
    
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