FineBI Project Deployment Environment Preparation

  • Last update:November 07, 2023
  • Overview

    Version

    FineBI Version

    6.0

    Functions

    FineBI is an intelligent business analysis and service platform in B/S port. It can be deployed on a server through the web application server, providing a cloud server for companies. Users can visit and use the service platform only by one browser.

    FineBI uses the Spider engine, which flexibly supports the analysis of different data magnitudes.

    This passage will introduce the requirements of configuring FineBI software and hardware.

    FineBI Performance Test Report

    The following shows reports of the direct connect data and the extracted data.

    Performance test report of the direct connection data: 

    FineBl V6.0 Direct Connection Performance Test Report.pdf

    Performance test report of the extraction data: 

    FineBl V6.0 Extraction Performance Test Report.pdf

    Software Environment Recommendation

    Software environments suitable for FineBI are as follows:

    • Company deployment: The Linux system is preferred rather than Windows and virtual machine systems. The Tomcat system is also recommended. You'd better not to deploy directly.

    • Personal use: There is no requirement for the way to deploy.

    Operating systems like Windows, Linux, Mac, Unix, Axi, and IRIX which support 1.8 version of JDK can be used to deploy.

    Operating SystemDescription

    Database

    Some main relational databases like Apache Kylin, Derby, HP Vertica, IBM DB2, Informix, Sql Server, MySQL, Oracle, Pivotal Greenplum Database, Postgresql, ADS, Amazon Redshift, Apache Impala, Apache Phoenix, Gbase 8A, Gbase8S, Gbase 8T, Hadoop Hive, Kingbase, Presto, SAP HANA, SAP Sybase, SparkTranswarp Inceptor, and HBase and some non-relational databases like MongoDB can be used to deploy. For details, see Support Range of Data Connection.

    App Server

    Web app servers like Tomcat, Jboss, Weblogic, and Websphere are supported.

    Browser

    Single core: Chrome, Firefox, other browsers that support IE11 and above (including Edge), Safari, and opera.

    It is recommended to use Google and Firefox browsers in terms of the compatibility of the rendering engine.

    Dual core: 360 Browser, Sogou Browser, QQ Browser, UC Browser, CM Browser, and Baidu Browser. Only fast mode is supported. Compatibility mode is not supported.

    Note:

    1. The Web server of FineBI should not be installed in physical computers or VM virtual machines which run resource-intensive apps at the same time. (For example, the database or app servers.) CPU that allows FineBI to actually take up 80% resources is recommended.

    2. The version of Google browser is better in version 70 or above.

    3. It is not recommended to use Safari browser if you are not using a Mac computer, because the older version of FineBI may be incompatible with it.

    Server Recommendation

    You need to first know whether you have used real-time data or extracted data.

    Extracted Data

    Select configurations according to the project concurrency and the size of metering. Select higher configurations when it falls into multiple configuration intervals.

    The concurrency that businessmen often pay attention to refers to the number of online users per hour in scenario one or the total number of users in scenario two.

    When the maximum data volume of single form is below 100 million, you can directly use the local disk of the Web server as the data storage medium.

    1. Scenario 1: Self-service Analytics for High Daily Active Users

    Scenario description: BI projects with high daily active users can use self-service analytics to analyze data. (Data cannot be directly obtained from the FineBI query cache.)

    Estimate the concurrency according to the node number summary: the number of online users (Y)= 300 * (The number of nodes (X) - 1) + 400.

    Disk throughput and bandwidth need to be greater than 100 MB/s(the performance of a regular local hard disk HDD). SSD solid state hard disk is recommended.

    Data Volume (Unit: row)

    Available Disk Space

    0 to 500 million

    100 to 300 GB

    500 million to 1 billion

    300 to 600 GB

    10 million to 100 million

    600 GB to 1.5 TB

    Note:

    1. FineBI is an IO intensive app, which relies heavily on the IO dish. Therefore, it is recommended to use the local disk or the SSD.

    2. The read/write speed of disk needs to be at least 100 MB/s. The throughput of IOPS needs to be at least 10 KB.

    According to the number of online users per hour during working hours, the reference table is configured as follows:

    Number of Daily Active Users

    Online (Number of Users Per Hour)

    Concurrency (Number of Users Per Second)

    Number of Forms-The Size of Forms

    Recommended Configuration

    Minimum Configuration

    Number of Nodes

    JVM/Physical Memory

    CPU (2.5 GHz or Above)

    Number of Nodes

    JVM/Physical Memory

    CPU (2.5 GHz or Above)

    500

    < 100

    < 20

    < 100 pieces or < 1 TB

     

    1

    16 GB/32 GB

    Eight cores and 16 threads

    /
    //

    1000

    300 to 1000

    20 to 70

    < 100 pieces or < 1 TB

     

    2

    16 GB/32 GB

    Eight cores and 16 threads

    1

    32 GB/64 GB

    16 cores and 32 threads

    2000

    600 to 2000

    40 to 120

    > 2000 pieces or > 1TB

     

    2

    32 GB/64 GB

    16 cores and 32 threads

    2

    24 GB/48 GB

    16 cores and 32 threads

    3000

    900 to 3000

    50 to 160

    > 4000 pieces or > 2 TB

     

    3

    32 GB/64 GB

    16 cores and 32 threads

    3

    24 GB/48 GB

    16 cores and 32 threads

    3500

    1200 to 3500

    60 to 190

    > 5000 pieces or > 3 TB

     

    4

    32 GB/64 GB

    16 cores and 32 threads

    3

    32 GB/64 GB

    16 cores and 32 threads

    4000

    1500 to 4000

    80 to 220

    > 5000 pieces or > 3 TB

     

    5

    32 GB/64 GB

    16 cores and 32 threads

    4

    32 GB/64 GB

    16 cores and 32 threads

    Note: JVM memory is not the same as the whole machine memory. It is recommended that JVM memory should account for 2/3 to 3/4 of the total machine memory.

    2. Scenario 2: Many Users Viewing Dashboards At the Same Time

    Scenarios like corresponding users view a report at the same time can use data extraction. It is the cumulative number of visitors (Y) within 5 to10 minutes. (Data can be directly obtained from the FineBI query cache. That is to say, multiple identical calculation requests can be directly obtained and return results.)

    When the number of requesting users per second reaches 160, the download speed of the load balancing server needs to reach 100 MB/s.

    Estimating concurrent users based on the summary of the number of nodes: the number of  concurrent users per 5 minutes (Y) = 380 * the number of nodes (X).

    Number of Users Per 5 minutes

    Number of Users Per Second

    Recommended Configuration

    Minimum Configuration

    Number of Nodes

    JVM/Physical Memory

    CPU (2.5 GHz or Above)

    Number of Nodes

    JVM/Physical Memory

    CPU (2.5 GHz or Above)

    < 400

    40

    2

    16 GB/32 GB

    Eight cores and 16 threads

    1

    32 GB/64 GB

    16 cores and 32 threads

    400 to 800

    80

    2

    32 GB/64 GB

    16 cores and 32 threads

    2

    24 GB/48 GB

    16 cores and 32 threads

    800 to 1100

    110

    3

    32 GB/64 GB

    16 cores and 32 threads

    3

    24 GB/48 GB

    16 cores and 32 threads

    1100 to 1600

    160

    4

    32 GB/64 GB

    16 cores and 32 threads

    3

    32 GB/64 GB

    16 cores and 32 threads

    1600 to 2000

    190

    5

    32 GB/64 GB

    16 cores and 32 threads

    4

    32 GB/64 GB

    16 cores and 32 threads

    Note: JVM memory is not the same as the whole machine memory. It is recommended that JVM memory should account for 2/3 to 3/4 of the total machine memory.

    Description of user types are shown in the following:

    User Type

    Description

    Number of Daily Active Users

    Within one day, the number of users logging into the BI system

    Number of Online Users

    The number of users logging into the BI system at the same time

    The number of concurrent users

    The number of users operating the BI system at the same time. That is, the number of users who are sending requests to the server at the same time. That is, the number of requests from the users the server can handle simultaneously.

    Concurrency limit when registering for Lic

    For those from IP address, the server gets the IP address from the request as a concurrent key. The main restriction is on the cumulative number of IP in visiting systems. The parameter of Lic has no correlation with the number of users in the following text.

    Direct Connect Data

    Description: Provide a recommended configuration based on the test results of the fourth section. The bandwidth between cluster nodes, nodes, and other components is 1000 MB/s.

    According to the project concurrency and the calculation capability of the data source DB, select a higher configuration when it falls into multiple configuration intervals.

    Editing concurrency cannot directly obtain data from the cache.

    The upper limit of concurrent users per second corresponds to the cache hit and the lower limit corresponds to the cache miss. Recommended configuration are as follows:

    Number of Daily Active Users

    Online
    (Number of Users Per Hour)

    Concurrency
    (Number of Users Per Second)

    Data Source Calculation Capability

    Processed Calculations Per Second

    Recommended Configuration

    Minimum Configuration


    Number of Nodes

    JVM/

    Physical Memory

    CPU in 2.5 GHz and Above

     

    Number of Nodes

    JVM/

    Physical Memory

    CPU in 2.5 GHz and Above

     

    500

    < 100

    < 20

    < 10

    1

    16 GB/24 GB

    Eight cores and 16 threads

    1

    8 GB/12 GB

    Four cores and eight threads

    2000

    100 to 1000

    40 to 90

    10 to 20

    2

    16 GB/24 GB

    16 cores and 32 threads

    1

    16 GB/24 GB

    16 cores and 32 threads

    3000

    600 to 1500

    60 to 130

    ≥ 30

    3

    16 GB/24 GB

    16 cores and 32 threads

    2

    24 GB/48 GB

    16 cores and 32 threads

    4000

    600 to 2000

    60 to 170

    ≥ 30

    4

    16 GB/24 GB

    16 cores and 32 threads

    3

    24 GB/48 GB

    16 cores and 32 threads

     

    Involving Direct Connect Data and Extracted Data

    If you are in a situation where both direct connect data and extracted data are involved, you can configure it as the highest configuration requirements.

    Modifying Parameters After Deployment

    After deploying FineBI, it is necessary to modify the FineBI configuration parameters.

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