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Updated on 2024-05-20 GMT+08:00
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Test Method

Objectives

RTA poses higher technical requirements for advertisers, including quick response from the media and lower costs in data storage. In recent years, GeminiDB Redis API is widely used as a key-value (KV) signature database in RTA scenarios and delivers good performance at low costs.

This section describes a pressure test of GeminiDB Redis instances in RTA scenarios, including the performance on data compression, QPS, bandwidth, and latency.

Test Environment

This test used GeminiDB Redis clusters and Elastic Cloud Servers (ECSs). The following table lists the specifications.

  • GeminiDB Redis cluster specifications

    Region

    CN East-Shanghai1

    AZ type

    Deployment across AZ 1, AZ 2, and AZ 3

    vCPUs of nodes

    16

    Nodes

    20

    Total storage space

    2 TB
  • ECS specifications

    AZ type

    AZ 1

    Specifications

    c7.4xlarge.2, 3 PCS

    vCPUs

    16

    Memory

    32 GiB

    Operating System (OS)

    CentOS 8.2 64-bit

Test Tool

This test used memtier_benchmark, which is a multi-thread load test tool developed by Redis Labs. For details, see memtier_benchmark.

Test Metrics

Service scale of the simulated RTA scenario: 1 TB of data, 1.6 million QPS, and 1.5 Gbit/s of bandwidth.

  1. Data samples

    Categories of data samples are as follows.

    Category

    Key

    Value

    Hash

    34 characters

    10 field-value pairs. A field contains 10 characters and a value contains 20 to 80 characters.

    String

    68 characters

    32 random characters

    String

    19 characters

    500 to 2,000 random characters

    Four billion keys need to be stored in the Redis clusters. The proportion of each data category is about 2:7:1, and the frequently accessed data accounts for 50% of the total.

  2. Metrics

    Test metrics of database operations are as follows.

    Metric Abbreviation

    Description

    QPS

    Number of requests executed per second.

    Avg Latency (ms)

    Average request latency, indicating the overall performance of a GeminiDB Redis cluster.

    p99 Latency (ms)

    p99 latency of a request, indicating that 99% of the request execution time is shorter than the value of this parameter.

    p9999 Latency (ms)

    p9999 latency of a request, indicating that 99.99% of the request execution time is shorter than the value of this parameter.

Test Procedure

  1. Inject test data.

    Before the test, generate and inject test data. Configure the three categories of data as follows:

    1. Hash
      • A key consists of 34 characters in the format of string prefix + nine digits. The digits are consecutive from 100 million to 900 million. The key is used to control the total data volume and hot data distribution.
      • Inject 10 field-value pairs. A field contains 10 characters and a value contains 20 to 80 random characters. The average value of a field-value is 50 characters.
      • Construct and inject 800 million keys.
        memtier_benchmark -s ${ip} -a $(passwd} -p ${port} -c 20-t20 -n7500000 -d 32 -key-maximum=3
800000000 -key-minimum =1000000000 --key-pr efix ='cefkljrithuir123894873h4523blj4b2jkjh2iw13b
nfdhsbnkfhsdjkh' --key-pattern=P:P--ratio=1:0 -pipelire=100
    2. String
      • A key consists of 68 characters in the format of string prefix + 10 digits. The digits are consecutive from 1 billion to 3.8 billion. The key is used to control the total data volume and hot data distribution.
      • Inject 32 random characters for a value.
      • Construct and inject 2.8 billion keys.
        memtier_benchmark -s ${ip} -a ${passwd} -p ${port} -c 20 -t 20 -n 2500000 --command='hset __key__ mendke398d __data__ mebnejkehe __data__ fmebejdbnf __data__ j3i45u8923 __data__ j43245i908 __data__ jhiriu2349 __data__ 21021034ji __data__ jh23ui45j2 __data__ jiu5rj9234 __data__ j23io45u29 __data__' -d 50 --key-maximum=900000000 --key-minimum=100000000 --key-prefix='ewfdjkff43ksdh41fuihikucl' --command-key-pattern=P --pipeline=100
    3. String
      • A key consists of 19 characters in the format of string prefix + 9 digits. The digits are consecutive from 100 million to 300 million. The key is used to control the total data volume and hot data distribution.
      • Inject 500 to 2,000 random characters for a value. The average value is 1,250 bits.
      • Construct and inject 400 million keys.
        memtier_benchmark -s ${ip} -a ${passwd} -p ${port} -c 20 -t 20 -n 520000 -d 1250 --key-maximum=300000000 --key-minimum=100000000 --key-prefix='miqjkfdjiu' --key-pattern=P:P --ratio=1:0 --pipeline=100

    After data is injected, there were 3,809,940,889 (about 3.8 billion) keys. Obtain the total data volume on the GeminiDB Redis API console and calculate the data compression ratio. The compressed storage space was 155 GB, and the compression ratio was 13.8%.

    • About 4 billion data records were generated by memtier_benchmark of the current version. Data distribution among different categories is not affected.
    • A random character string constructed by memtier_benchmark contains many consecutive characters, so the compression ratio was low. The data compression ratio is about 30% to 50% in actual production.
  2. Pressure test commands

    Perform pressure tests on GeminiDB Redis clusters deployed on three ECSs, separately. The pressure test tasks are as follows:

    1. On ECS 1, run the HGETALL command for hashes and set a range for keys to allow access to hot data only.
      memtier_benchmark -s ${ip} -a ${passwd} -p ${port} -c 20 -t 30 --test-time 1200 --random-data --randomize --distinct-client-seed --command='hgetall __key__' --key-maximum=600000000 --key-minimum=200000000 --key-prefix='ewfdjkff43ksdh41fuihikucl' --out-file=./output_filename
    2. Run the GET command for type data 2 and set a range for keys to allow access to hot data only.
      memtier_benchmark -s ${ip} -a ${passwd} -p ${port} -c 70 -t 30 --test-time 1200 --random-data --randomize --distinct-client-seed --key-maximum=2400000000 --key-minimum=1000000000 --key-prefix='cefkljrithuin123894873h4523bhj4b2jkjh2iu13bnfdhsbnkfhsdjkh' --ratio=0:1 --out-file=./output_filename
    3. Run the GET command for type data 3 and set a range for keys to allow access to hot data only.
      memtier_benchmark -s ${ip} -a ${passwd} -p ${port} -c 10 -t 30 --test-time 1200 --random-data --randomize --distinct-client-seed --key-maximum=300000000 --key-minimum=100000000 --key-prefix='miqjkfdjiu' --ratio=0:1 --out-file=./output_filename

    The number of connections (the product of c and t) was adjusted to modify the number of clients and configuration of each instance, so as to achieve a QPS of 1,600,000 and a read request traffic of 1.5 Gbit/s. Remain the service volume unchanged and evaluate the performance of GeminiDB Redis API.