FineDataLink Deployment Environment Preparation- FineDataLink Help Document

Last update: September 23, 2025

Operating System Requirement

Category		Model
Linux	CentOS 6	CentOS 6.5, CentOS 6.6, CentOS 6.7, CentOS 6.8, and CentOS 6.9
	CentOS 7	CentOS 7.0, CentOS 7.1, CentOS 7.2, CentOS 7.3, CentOS 7.4, CentOS 7.6, CentOS 7.8, and CentOS 7.9
	Red Hat 6	Red Hat 6.5, Red Hat 6.6, Red Hat 6.7, Red Hat 6.8, and Red Hat 6.9
	Red Hat 7	Red Hat 7.0, Red Hat 7.1, Red Hat 7.2, Red Hat 7.3, Red Hat 7.4, Red Hat 7.7, and Red Hat 7.9
	Red Hat 8	Red Hat 8.1
	Ubuntu	Ubuntu 10.04.4, Ubuntu 18.04, and Ubuntu 20
	Amazon Linux	Amazon Linux AMI 2018.03
	Rocky Linux	Rocky Linux 8.8 to 9.4
Windows		Windows Server 2008 and later releases and Windows 11
Configuration database	Amazon RDS for MySQL, MySQL, SQL Server, Oracle, Db2, and PostgreSQL Note: Configure an external database for formal projects. For details, see External Database Configuration.
Browser	Chromium-based browser You are advised to use modern mainstream browsers (such as Google Chrome and Microsoft Edge) of the latest versions.
	Google Chrome	The browser version should be equal to or later than 94 for FineDataLink of versions from V4.1.x (inclusive) to 4.1.6.x (exclusive). The browser version should be equal to or later than 105 for FineDataLink of V4.1.6.x and later versions. You are advised to use browsers of the latest versions. Note: Starting from FineDataLink V4.2.9.4, browsers based on the Chrome 86 kernel are supported. For browsers running on older-version kernels, page display anomalies will occur, and only functional usability is guaranteed.
	Microsoft Edge

Note that:

1. The above operating systems are recommended for use. To deploy FineDataLink on other Linux systems, contact FanRuan technical support for assistance by sending an email to international@fanruan.com.

2. You need to deploy Kafka to use Data Pipeline and Real-Time Task, which is preferred to be installed on a Linux system. (Kafka installed on a Windows system is not suitable for production environments and can be used for demonstration purposes only, as it has limited performance.) You can deploy Kafka and FineDataLink on different servers.

Server Configuration

Configuration of CPU, Memory, Disk, and Network

This document provides multiple standard schemes based on the number of scheduled tasks, real-time tasks, and pipeline tasks. Choose the one that best meets your needs.

Scheme Applicability

The schemes in this document are designed for new project deployment scenarios, providing recommended server configuration based on business usage. You can select the scheme according to the task quantity.
The schemes in this document are intended for scenarios where the volume of data (calculated by Row count * Column count) changed in an hour in a single business database does not exceed one million. If the data change volume surpasses this limit, contact FanRuan technical support personnel for further assistance.
These schemes offer resource recommendations based on typical scales of customers’ projects. If the number of tasks exceeds the applicable range, contact FanRuan technical support personnel for further assistance.
As usage increases over time, if your current server resources become insufficient and require expansion, contact FanRuan technical support personnel for assistance.

Scheme Introduction

Scheme	Applicable Condition	Server Configuration
Minimum Requirement	The number of development tasks is less than 35. Pipeline tasks are not needed.	Note: This scheme is intended for customers with little business usage and limited server resources only. 1. Server: 8-core CPU, 16 GB of memory, and 300 GB of disk space 2. Network and port: Intranet latency: less than 1 ms Intranet bandwidth (for transmission between the FineDataLink server and the business database): greater than or equal to 100 Mbps (12.5 MB/s) Extranet bandwidth (for transmission between the FineDataLink server and FineDataLink project users’ network): greater than or equal to 10 Mbps (1.25 MB/s) Port: For details, see the "Port Preparation" section of this document. 3. To use the Cloud App System data source, ensure the server where the project is located has internet access permission, or you can configure an allowlist for the following domain and IP address: Domain: dm.shukuajing.com IP address: 47.110.75.116
Scheme One	The number of scheduled tasks is less than 150. Pipeline tasks are not needed.	1. Server: 8-core CPU, 32 GB of memory, and 300 GB of disk space 2. Network and port: Intranet latency: less than 1 ms Intranet bandwidth (for transmission between the FineDataLink server and the business database): greater than or equal to 1000 Mbps (125 MB/s) Extranet bandwidth (for transmission between the FineDataLink server and FineDataLink project users’ network): greater than or equal to 10 Mbps (1.25 MB/s) Port: For details, see the "Port Preparation" section of this document. 3. To use the Cloud App System data source, ensure the server where the project is located has internet access permission, or you can configure an allowlist for the following domain and IP address: Domain: dm.shukuajing.com IP address: 47.110.75.116
Scheme Two	The number of scheduled tasks is less than 300. The number of pipeline tasks is less than 16. The number of real-time tasks is less than 20.	1. Server: 16-core CPU, 64 GB of memory, and 300 GB of disk space 2. Network and port: Intranet latency: less than 1 ms Intranet bandwidth (for transmission between the FineDataLink server and the business database): greater than or equal to 1000 Mbps (125 MB/s) Extranet bandwidth (for transmission between the FineDataLink server and FineDataLink project users’ network): greater than or equal to 10 Mbps (1.25 MB/s) Port: For details, see the "Port Preparation" section of this document. 3. To use the Cloud App System data source, ensure the server where the project is located has internet access permission, or you can configure an allowlist for the following domain and IP address: Domain: dm.shukuajing.com IP address: 47.110.75.116
Scheme Three	The number of scheduled tasks is less than 500. The number of pipeline tasks is less than 16. The number of real-time tasks is less than 40.	1. Server: 16-core CPU, 64 GB of memory, and 500 GB of disk space 2. Network and port: Intranet latency: less than 1 ms Intranet bandwidth (for transmission between the FineDataLink server and the business database): greater than or equal to 1000 Mbps (125 MB/s) Extranet bandwidth (for transmission between the FineDataLink server and FineDataLink project users’ network): greater than or equal to 10 Mbps (1.25 MB/s) Port: For details, see the "Port Preparation" section of this document. 3. To use the Cloud App System data source, ensure the server where the project is located has internet access permission, or you can configure an allowlist for the following domain and IP address: Domain: dm.shukuajing.com IP address: 47.110.75.116
Scheme Four	The number of scheduled tasks is less than 500 * N. The number of pipeline tasks is less than 16 * N. The number of real-time tasks is less than 40 * N.	1. The number of FineDataLink main application servers is N. Each main application server: 16-core CPU, 64 GB of memory, and 500 GB of disk space Each one should be deployed with one FineDataLink component. 2. Network and port: Intranet latency: less than 1 ms Intranet bandwidth (for transmission between the FineDataLink server and the business database): greater than or equal to 1000 Mbps (125 MB/s) Extranet bandwidth (for transmission between the FineDataLink server and FineDataLink project users’ network): greater than or equal to 10 Mbps (1.25 MB/s) Port: For details, see the "Port Preparation" section of this document. 3. To use the Cloud App System data source, ensure the server where the project is located has internet access permission, or you can configure an allowlist for the following domain and IP address: Domain: dm.shukuajing.com IP address: 47.110.75.116

Scheme

Applicable Condition

Server Configuration

Minimum Requirement

The number of development tasks is less than 35.

Pipeline tasks are not needed.

Note:

This scheme is intended for customers with little business usage and limited server resources only.

1. Server: 8-core CPU, 16 GB of memory, and 300 GB of disk space

2. Network and port:

Intranet latency: less than 1 ms
Intranet bandwidth (for transmission between the FineDataLink server and the business database): greater than or equal to 100 Mbps (12.5 MB/s)
Extranet bandwidth (for transmission between the FineDataLink server and FineDataLink project users’ network): greater than or equal to 10 Mbps (1.25 MB/s)
Port: For details, see the "Port Preparation" section of this document.

3. To use the Cloud App System data source, ensure the server where the project is located has internet access permission, or you can configure an allowlist for the following domain and IP address:

Domain: dm.shukuajing.com
IP address: 47.110.75.116

Scheme One

The number of scheduled tasks is less than 150.

Pipeline tasks are not needed.

1. Server: 8-core CPU, 32 GB of memory, and 300 GB of disk space

2. Network and port:

Intranet latency: less than 1 ms
Intranet bandwidth (for transmission between the FineDataLink server and the business database): greater than or equal to 1000 Mbps (125 MB/s)
Extranet bandwidth (for transmission between the FineDataLink server and FineDataLink project users’ network): greater than or equal to 10 Mbps (1.25 MB/s)
Port: For details, see the "Port Preparation" section of this document.

Domain: dm.shukuajing.com
IP address: 47.110.75.116

Scheme Two

The number of scheduled tasks is less than 300.

The number of pipeline tasks is less than 16.

The number of real-time tasks is less than 20.

1. Server: 16-core CPU, 64 GB of memory, and 300 GB of disk space

2. Network and port:

Intranet latency: less than 1 ms
Intranet bandwidth (for transmission between the FineDataLink server and the business database): greater than or equal to 1000 Mbps (125 MB/s)
Extranet bandwidth (for transmission between the FineDataLink server and FineDataLink project users’ network): greater than or equal to 10 Mbps (1.25 MB/s)
Port: For details, see the "Port Preparation" section of this document.

Domain: dm.shukuajing.com
IP address: 47.110.75.116

Scheme Three

The number of scheduled tasks is less than 500.

The number of pipeline tasks is less than 16.

The number of real-time tasks is less than 40.

1. Server: 16-core CPU, 64 GB of memory, and 500 GB of disk space

2. Network and port:

Intranet latency: less than 1 ms
Intranet bandwidth (for transmission between the FineDataLink server and the business database): greater than or equal to 1000 Mbps (125 MB/s)
Extranet bandwidth (for transmission between the FineDataLink server and FineDataLink project users’ network): greater than or equal to 10 Mbps (1.25 MB/s)
Port: For details, see the "Port Preparation" section of this document.

Domain: dm.shukuajing.com
IP address: 47.110.75.116

Scheme Four

The number of scheduled tasks is less than 500 * N.

The number of pipeline tasks is less than 16 * N.

The number of real-time tasks is less than 40 * N.

1. The number of FineDataLink main application servers is N.

Each main application server: 16-core CPU, 64 GB of memory, and 500 GB of disk space

Each one should be deployed with one FineDataLink component.

2. Network and port:

Intranet latency: less than 1 ms
Intranet bandwidth (for transmission between the FineDataLink server and the business database): greater than or equal to 1000 Mbps (125 MB/s)
Extranet bandwidth (for transmission between the FineDataLink server and FineDataLink project users’ network): greater than or equal to 10 Mbps (1.25 MB/s)
Port: For details, see the "Port Preparation" section of this document.

Domain: dm.shukuajing.com
IP address: 47.110.75.116

Port Preparation

This section describes the ports to be opened for FineDataLink deployment.

Port Opening Notes

1. If the default port number conflicts with that of other projects, modify the port number and then open the corresponding port.

2. If you want to deploy multiple Tomcat projects on a server, modify the Tomcat port number to prevent port conflict.

3. If the firewall is enabled, you need to open the relevant port.

4. For the Docker container or environments with strict port restrictions between servers, it is necessary to open ports between the servers of nodes for inter-node communication.

If you use the TCP protocol, open ports 7800, 7810, 7820, 7830, 7840, 7850, 7860, and 7870.
If you use the UDP protocol, open ports ranging from 45588 to 65536, since random ones will be used.

Port Description

Classification	Content	Port Number	Remark
Standalone	A project-occupied port	8068	It is an external port that can be closed to the public and can be modified (in server.xml). You can configure SSL and a short address in the load balancer.
	A port for the crash-handling tool	12100	/
	A port for the gpfdist service	15500	/
Cluster	A project-occupied port	8068	It is an external port that can be closed to the public and can be modified (in server.xml). You can configure SSL and a short address in the load balancer.
	A port for the crash-handling tool	12100	/
	A port for TCP communication in the cluster	7800 7830 7840 7850 7870	/
	A port for the gpfdist service	15500	/
Notification	WebSocket port	Starting from FineDataLink 4.0.6, the default port number ranges from 58888 to 59888.	/
Notification	WebSocket forwarding port	Starting from FineDataLink 4.0.6, the default port number is 58889.	/

Resource Control Memory

Note:

For details about resource control settings, see Load Distribution.

Unknown Number of Scheduled Tasks and Pipeline Tasks (Applicable to Newly Deployed Projects)

For details, see the "Configuration of CPU, Memory, Disk, and Network" section.

Known Number of Scheduled Tasks and Pipeline Tasks (Applicable to Project Migration and Configuration Optimization Scenarios)

The minimum memory size shall be the greater one between the minimum memory size for running scheduled tasks and for running pipeline tasks.

Accuracy	Memory
Accurate	The minimum memory size shall be the greater one between the minimum memory size for running scheduled tasks and for running pipeline tasks. For details, see the following table.
Rough	The minimum memory size shall be the greater one between the minimum memory size for running scheduled tasks and for running pipeline tasks. Assume that each scheduled or pipeline task requires 1 GB of memory.

1. For 4.1.55 and later releases:

Type

Node

Memory

Scheduled task

Single input node

Calculation formula: Buffer size + outputSize * 2 * Channel size

The formula is described below.

Buffer size:

For inputs from non-relational DB tables (such as Jiandaoyun and Mongo) and other inputs (such as API input and file input), a Reader takes up 64 MB of memory.

For inputs from relational DB tables, the size depends on the table structures. Allocate 1 MB of memory for each column of the input table, and in particular, 2 MB if the precision of the column exceeds 1024. The resulting size shall be a positive multiple of 8 MB and not exceed 64 MB.

For example, if a table has the following structure, it takes 9 MB of memory and should be allocated with 16 GB of memory.

For a table of the following structure:

Type	Precision
SMALLINT	5
BIGINT	19
DECIMAL	18
VARCHAR	100
VARBINARY	2000
TIME	0
FLOAT	15
BIT	0

It takes 9 MB (1 + 1 + 1 + 1 + 2 + 1 + 1 + 1 = 9) of memory and shall be allocated with 16 GB of memory.

Channel size:

The calculation of channel memory is relatively complex. Generally, it takes 8 MB or 16 MB of memory, not exceeding 64 MB.

outputSize:

It is the number of succeeding nodes connected with the input node.

Process node

64 + outputSize * 2 * 64

outputSize (different from the one mentioned above):

It is the sum of the number of output nodes and Python nodes that are directly connected to the process node.

The succeeding process node of the process node is not included.

Single output node

32 MB

An output node usually takes 32 MB of memory. Specifically, if the data is output to a Doris or StarRocks database, a single output node takes 90 MB of memory.

Pipeline task

The memory calculation method of input and output nodes is the same as that of the scheduled task.

Take the following task as an example. The required memory is described below.

Input nodes (three): (8 + 1 * 2 * 24) * 3

Process node (one): 64 + 2 * 2 * 64

Output nodes (two): 32 + 32

Total: 552 MB

You can find the description in the corresponding log.

2. For FineDataLink of versions before 4.1.55:

Estimated memory required for running scheduled/pipeline tasks (applicable to multi-task scenarios where accurate calculation is impossible)

Type	Node	Memory
Scheduled task	/	1024 MB per task
Pipeline task	/	1024 MB per task

Accurate memory required for running scheduled/pipeline tasks

Type	Node	Memory
Scheduled task	Single input node	64 MB + 128 MB * Number of output channels
	All process nodes	64 MB + 128 MB * Number of connected output nodes
	Single output node	32 MB
Pipeline task	/	1024 MB per task

The following is an example of calculating the memory required for a scheduled task.

Input: 64 MB + Output node quantity * (64 MB +64 MB)

Process: 64 MB + Ultimate output node quantity * (64 MB + 64 MB)

Output: Output node quantity * 32 MB

Calculate the memory used by the task:

Input: 2 * (64 MB + 1 * (64 MB + 64 MB)) = 384 MB

Process: 64 MB + 3 * (64 MB + 64 MB) = 448 MB

Output: 3 * 32 MB =96 MB

Total: 928 MB

Web Container Memory

The Web container memory should be equal to or larger than the resource control memory. For example, if a new project has a resource control memory of 16 GB, the Web container memory should be set to a value higher than 16 GB, but not more than 80% of the system memory (recommended).

Deployment Package Preparation

Contact the technical support personnel for the installation package. To contact our technical support personnel, you can send an email to international@fanruan.com or click the icon in the lower right corner at https://help.fanruan.com/finedatalink-en/.

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Next：FineDataLink Deployment Method Selection

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FineDataLink Deployment Environment Preparation

Operating System Requirement

Server Configuration

Configuration of CPU, Memory, Disk, and Network

Port Preparation

Resource Control Memory

Web Container Memory

Deployment Package Preparation

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