Single-Machine Cluster Deployment

• Official website: DolphinDB
• Or you can download DolphinDB with a shell command:

wget https://www.dolphindb.com/downloads/DolphinDB_Linux64_V${release}.zip -O dolphindb.zip

${release} refers to the version of DolphinDB server. For example, you can download Linux64 server 2.00.11.3 with the following command:

wget https://www.dolphindb.com/downloads/DolphinDB_Linux64_V2.00.11.3.zip -O dolphindb.zip

To download the ABI or JIT version of DolphinDB server, add "ABI" or "JIT" after the version number (linked with an underscore). For example, you can download Linux64 ABI server 2.00.11.3 with the following command:

wget https://www.dolphindb.com/downloads/DolphinDB_Linux64_V2.00.11.3_ABI.zip -O dolphindb.zip

Download Linux64 JIT server 2.00.11.3 with the following command:

wget https://www.dolphindb.com/downloads/DolphinDB_Linux64_V2.00.11.3_JIT.zip -O dolphindb.zip

• Then extract the installation package to the specified directory (/path/to/directory):

unzip dolphindb.zip -d </path/to/directory>

Note: The directory name cannot contain any space characters, otherwise the startup of the data node will fail.

If you have obtained the Enterprise Edition license, use it to replace the following file:

/DolphinDB/server/dolphindb.lic

Otherwise, continue to use the community version, which allows up to 8 GB RAM use for 20 years.

Navigate to the folder /DolphinDB/server/. The file permissions need to be modified for the first startup. Execute the following shell command:

chmod +x dolphindb

Then go to /DolphinDB/server/clusterDemo to start the controller and agent with no specified order.

• Start Controller

sh startController.sh

• Start Agent

sh startAgent.sh

To check whether the node was started, execute the following shell command:

ps aux|grep dolphindb

The following information indicates a successful startup:

• Start Data Nodes and Compute Nodes

You can start or stop data nodes and compute nodes, and modify cluster configuration parameters on DolphinDB cluster management web interface. Enter the deployment server IP address and controller port number in the browser to navigate to the DolphinDB Web. The server address (ip:port) used in this tutorial is 10.0.0.80:8900. Below is the web interface. Log in with the default administrator account (username: admin, password: 123456). Then select the required data nodes and compute nodes, and click on the execute/stop button.

Click on the refresh button to check the status of the nodes. The following green check marks mean all the selected nodes have been turned on:

Note: If the browser and DolphinDB are not deployed on the same server, you should turn off the firewall or open the corresponding port beforehand.

Data nodes can be used for data storage, queries and computation. The following example shows how to create databases and write data on data nodes. First, open the web interface of the Controller, and click on the corresponding Data node to open its Shell interface:

You can also enter IP address and port number of the data nodes in your browser to navigate to the Shell interface.

Execute the following script to create a database and a partitioned table:

//create a database and a partitioned table
login("admin", "123456")
dbName = "dfs://testDB"
tbName = "testTB"
if(existsDatabase(dbName)){
        dropDatabase(dbName)
}
db = database(dbName, VALUE, 2021.01.01..2021.12.31)
colNames = `SecurityID`DateTime`PreClosePx`OpenPx`HighPx`LowPx`LastPx`Volume`Amount
colTypes = [SYMBOL, DATETIME, DOUBLE, DOUBLE, DOUBLE, DOUBLE, DOUBLE, INT, DOUBLE]
schemaTable = table(1:0, colNames, colTypes)
db.createPartitionedTable(table=schemaTable, tableName=tbName, partitionColumns=`DateTime)

Then, run the following script to generate 1-minute OHLC bars and append the data to the created partitioned table "tbName":

//simulate OHLC data and append it to the partitioned table
n = 1210000
randPrice = round(10+rand(1.0, 100), 2)
randVolume = 100+rand(100, 100)
SecurityID = lpad(string(take(0..4999, 5000)), 6, `0)
DateTime = (2023.01.08T09:30:00 + take(0..120, 121)*60).join(2023.01.08T13:00:00 + take(0..120, 121)*60)
PreClosePx = rand(randPrice, n)
OpenPx = rand(randPrice, n)
HighPx = rand(randPrice, n)
LowPx = rand(randPrice, n)
LastPx = rand(randPrice, n)
Volume = int(rand(randVolume, n))
Amount = round(LastPx*Volume, 2)
tmp = cj(table(SecurityID), table(DateTime))
t = tmp.join!(table(PreClosePx, OpenPx, HighPx, LowPx, LastPx, Volume, Amount))
dbName = "dfs://testDB"
tbName = "testTB"
loadTable(dbName, tbName).append!(t)

For more details about the above functions, see Function References or the function documentation popup on the web interface.

You can check the created database and table in the Database on the left side of the web interface.

Variables you created can be checked in Local Variables. You can click on the corresponding variable name to preview the related information (including data type, size, and occupied memory size).

Return to the DFS file page of the controller to check the created partitions under the databases.

Compute nodes are used for queries and computation. The following example shows how to perform these operations in partitioned tables on a compute node.

First, open the web interface of the Controller, and then click the corresponding Compute node to open its Shell interface:

You can also enter IP address and port number of the compute nodes in your browser to navigate to the Shell interface.

Execute the following script to load the partitioned table:

// load the partitioned table
pt = loadTable("dfs://testDB", "testTB")

Note: Only metadata of the partitioned table is loaded here. Then execute the following script to count the number of the records for each day in table "pt":

//If the result contains a small amount of data, you can download it to display on the client directly.
select count(*) from pt group by date(DateTime) as Date

The result will be displayed at the bottom of the web interface:

Execute the following script to calculate OHLC bars for each stock per day:

// If the result contains a large amount of data, you can assign it to a variable that occupies the server memory, and download it to display in seperate pages on the client.
result = select first(LastPx) as Open, max(LastPx) as High, min(LastPx) as Low, last(LastPx) as Close from pt group by date(DateTime) as Date, SecurityID

The result is assigned to the variable result. It will not be displayed on the client directly, thus reducing the memory of the client. To check the results, click on the result in the Local Variables.

• Official website: DolphinDB
• Extract the installation package to the specified directory (e.g., to C:\DolphinDB):

C:\DolphinDB

Note: The directory name cannot contain any space characters, otherwise the startup of the data node will fail. For example, do not extract it to the Program Files folder on Windows.

If you have obtained the Enterprise Edition license, use it to replace the following file:

C:\DolphinDB\server\dolphindb.lic

Otherwise, continue to use the community version, which allows up to 8 GB RAM use for 20 years.

• Start Controller and Agent in Console Mode

Navigate to the folder C:\DolphinDB\server\clusterDemo. Then double click startController.bat and startAgent.bat.

• Start Controller and Agent in Background Mode

Navigate to the folder C:\DolphinDB\server\clusterDemo. Then double click backgroundStartController.vbs and backgroundStartAgent.vbs.

• Start Data Nodes and Compute Nodes

You can start or stop data nodes and compute nodes, and modify cluster configuration parameters on the web interface. Enter the deployment server IP address and controller port number in the browser to navigate to the DolphinDB Web. The server address (ip:port) used in this tutorial is 10.0.0.80:8900. Below is the web interface. Log in with the default administrator account (username: admin, password: 123456). Then select the required data nodes and compute nodes, and click on the execute/stop button.

Click on the refresh button to check the status of the nodes. The following green check marks mean all the selected nodes have been turned on:

Note: If the browser and DolphinDB are not deployed on the same server, you should turn off the firewall or open the corresponding port beforehand.

Data nodes can be used for data storage, queries and computation. The following example shows how to create databases and write data on data nodes. First, open the web interface of the Controller, and click on the corresponding Data node to open its Shell interface:

You can also enter IP address and port number of the data nodes in your browser to navigate to the Shell interface.

Execute the following script to create a database and a partitioned table:

// create a database and a partitioned table
login("admin", "123456")
dbName = "dfs://testDB"
tbName = "testTB"
if(existsDatabase(dbName)){
        dropDatabase(dbName)
}
db = database(dbName, VALUE, 2021.01.01..2021.12.31)
colNames = `SecurityID`DateTime`PreClosePx`OpenPx`HighPx`LowPx`LastPx`Volume`Amount
colTypes = [SYMBOL, DATETIME, DOUBLE, DOUBLE, DOUBLE, DOUBLE, DOUBLE, INT, DOUBLE]
schemaTable = table(1:0, colNames, colTypes)
db.createPartitionedTable(table=schemaTable, tableName=tbName, partitionColumns=`DateTime)

Then, run the following scripts to generate 1-minute OHLC bars and append the data to the created partitioned table "tbName":

// simulate OHLC data and append it to the partitioned table
n = 1210000
randPrice = round(10+rand(1.0, 100), 2)
randVolume = 100+rand(100, 100)
SecurityID = lpad(string(take(0..4999, 5000)), 6, `0)
DateTime = (2023.01.08T09:30:00 + take(0..120, 121)*60).join(2023.01.08T13:00:00 + take(0..120, 121)*60)
PreClosePx = rand(randPrice, n)
OpenPx = rand(randPrice, n)
HighPx = rand(randPrice, n)
LowPx = rand(randPrice, n)
LastPx = rand(randPrice, n)
Volume = int(rand(randVolume, n))
Amount = round(LastPx*Volume, 2)
tmp = cj(table(SecurityID), table(DateTime))
t = tmp.join!(table(PreClosePx, OpenPx, HighPx, LowPx, LastPx, Volume, Amount))
dbName = "dfs://testDB"
tbName = "testTB"
loadTable(dbName, tbName).append!(t)

For more details about the above functions, see Function References or the function documentation popup on the web interface.

You can check the created database and table in the Database on the left side of the web interface.

Variables you created can be checked in Local Variables. You can click on the corresponding variable name to preview the related information (including data type, size, and occupied memory size).

Compute nodes are used for queries and computation. The following example shows how to perform these operations in partitioned tables on a compute node. First, open the web interface of the Controller, and then click the corresponding Compute node to open its Shell interface:

You can also enter IP address and port number of the compute nodes in your browser to navigate to the Shell interface.

Execute the following script to load the partitioned table:

// load the partitioned table
pt = loadTable("dfs://testDB", "testTB")

Note: Only metadata of the partitioned table is loaded here. Then execute the following script to count the number of the records for each day in table "pt":

//If the result contains a small amount of data, you can download it to display on the client directly.
select count(*) from pt group by date(DateTime) as Date

The result will be displayed at the bottom of the web interface:

Execute the following script to calculate OHLC bars for each stock per day:

// If the result contains a large amount of data, you can assign it to a variable that occupies the server memory, and download it to display in seperate pages on the client.
result = select first(LastPx) as Open, max(LastPx) as High, min(LastPx) as Low, last(LastPx) as Close from pt group by date(DateTime) as Date, SecurityID

The result is assigned to the variable result. It will not be displayed on the client directly, thus reducing the memory of the client. To check the results, click on the result in the Local Variables.

Step 1: Close all nodes

Navigate to the folder /DolphinDB/server/clusterDemo to execute the following command:

./stopAllNode.sh

Step 2: Back up the Metadata

The metadata file is created only when data is written to the single-server cluster. Otherwise, you can just skip this step.

• Back up the Metadata of Controller

By default, the metadata of controller is stored in the DFSMetaLog.0 file under the folder /DolphinDB/server/clusterDemo/data:

/DolphinDB/server/clusterDemo/data

When the metadata exceeds certain size limits, a DFSMasterMetaCheckpoint.0 file will be generated.

Navigate to the folder /DolphinDB/server/clusterDemo/data to execute the following shell commands:

mkdir backup
cp -r DFSMetaLog.0 backup
cp -r DFSMasterMetaCheckpoint.0 backup

• Back up the Metadata of Data Nodes

By default, the metadata of data nodes is stored in the folder /DolphinDB/server/clusterDemo/data/<data node alias>/storage/CHUNK_METADATA. The default storage directory in this tutorial is:

/DolphinDB/server/clusterDemo/data/dnode1/storage/CHUNK_METADATA

Navigate to the above directory to execute the following shell command:

cp -r CHUNK_METADATA ../../backup

Note: If the backup files are not in the above default directory, check the directory specified by the configuration parameters dfsMetaDir and chunkMetaDir. If the two parameters are not modified but the configuration parameter volumes is specified, then you can find the CHUNK_METADATA under the volumes directory.

Step 3: Upgrade

Note: When the server is upgraded to a certain version, the plugin should also be upgraded to the corresponding version.

• Online Upgrade

Navigate to the folder /DolphinDB/server/clusterDemo to execute the following command:

./upgrade.sh

The following prompt is returned:

Type y and press Enter:

Type 1 and press Enter:

Type a version number and press Enter. To update to version 2.00.9.1, for example, type 2.00.9.1 and press Enter. The following prompt indicates a successful upgrade.

• Offline Upgrade

Download a new version of server package from DolphinDB website.

Upload the installation package to /DolphinDB/server/clusterDemo. Take version 2.00.9.1 as an example.

Navigate to the folder /DolphinDB/server/clusterDemo to execute the following command:

./upgrade.sh

The following prompt is returned:

Type y and press Enter:

Type 2 and press Enter:

Type a version number and press Enter. To update to version 2.00.9.1, for example, type 2.00.9.1 and press Enter. The following prompt indicates a successful upgrade.

Step 4: Restart the Cluster

Navigate to folder /DolphinDB/server/clusterDemo to start the controller and agent with no specified order.

• Start Controller

sh startController.sh

• Start Agent

sh startAgent.sh

Open the web interface and execute the following script to check the current version of DolphinDB.

version()

Step 1: Close all nodes

• In console mode, close the foreground process.
• In background mode, close DolphinDB process from Task Manager.

Step 2: Back up the Metadata

The metadata file is created only when data is written to the single-server cluster. Otherwise, you can just skip this step.

• Back up the Metadata of Controller

By default, the metadata of controller is stored in the DFSMetaLog.0 file under the folder C:\DolphinDB\server\clusterDemo\data:

C:\DolphinDB\server\clusterDemo\data

When the metadata exceeds certain size limits, a DFSMasterMetaCheckpoint.0 file will be generated.

Create a folder backup in this directory, then copy the DFSMetaLog.0 file and DFSMasterMetaCheckpoint.0 file to the folder:

• Back up the Metadata of Data Nodes

By default, the metadata of data nodes is stored in the folder C:\DolphinDB\server\clusterDemo\data\ <data node alias>\storage\CHUNK_METADATA. The default storage directory in this tutorial is:

C:\DolphinDB\server\clusterDemo\data\dnode1\storage\CHUNK_METADATA

Copy the CHUNK_METADATA file to the above backup folder:

Note: If the backup files are not in the above default directory, check the directory specified by the configuration parameters dfsMetaDir and chunkMetaDir. If the two parameters are not modified but the configuration parameter volumes is specified, then you can find the CHUNK_METADATA under the volumes directory.

Step 3: Upgrade

• Download a new version of installation package from DolphinDB website.
• Replace an existing files with all files (except dolphindb.cfg and dolphindb.lic) in the current \DolphinDB\server folder.

Note: When the server is upgraded to a certain version, the plugin should also be upgraded to the corresponding version.

Step 4: Restart the Cluster

• Start Controller and Agent in Console Mode:

Navigate to the folder C:\DolphinDB\server\clusterDemo. Then double click startController.bat and startAgent.bat.

• Start Controller and Agent in Background Mode

Navigate to the folder C:\DolphinDB\server\clusterDemo. Then double click backgroundStartController.vbs and backgroundStartAgent.vbs.

Open the web interface and execute the following script to check the current version of DolphinDB.

version()

Replace an existing license file with a new one.

License file path on Linux:

/DolphinDB/server/dolphindb.lic

License file path on Windows:

C:\DolphinDB\server\dolphindb.lic

• Online Update

Open the web interface to execute the following script:

use ops
updateAllLicenses()

The "end_date" is updated:

Note:

The client name of the license cannot be changed.

The number of nodes, memory size, and the number of CPU cores cannot be smaller than the original license.

The update takes effect only on the node where the function is executed. Therefore, in a cluster mode, the function needs to be run on all controllers, agents, data nodes, and compute nodes.

The license type must be either commercial (paid) or free.

• Offline Update

Restart DolphinDB cluster to complete the updates.

Execute the following shell command to modify controller.cfg:

vim ./controller.cfg

mode=controller
localSite=localhost:8900:controller8900
dfsReplicationFactor=1
dfsReplicaReliabilityLevel=2
dataSync=1
workerNum=4
localExecutors=3
maxConnections=512
maxMemSize=8
lanCluster=0
 

The default port number of the controller is 8900. You can specify its IP address, port number and alias by modifying the localSite parameter.

• For example, specify <ip>:<port>:<alias> as 10.0.0.80:8900:controller8900:

localSite=10.0.0.80:8900:controller8900

Other parameters can be modified based on your own device.

Execute the following shell command to modify agent.cfg:

vim ./agent.cfg

mode=agent
localSite=localhost:8901:agent1
controllerSite=localhost:8900:controller8900
workerNum=4
localExecutors=3
maxMemSize=4
lanCluster=0

The parameter controllerSite in the file agent.cfg must be identical with the parameter localSite in controller.cfg, because the agent has to use this information to contact the controller.

The default port number of the agent is 8901. You can specify its IP address, port number and alias by modifying the localSite parameter.

• For example:

localSite=10.0.0.80:8901:agent1

Other parameters can be modified based on your own device.

Execute the following shell command to modify cluster.nodes:

vim ./cluster.nodes

localSite,mode
localhost:8901:agent1,agent
localhost:8902:dnode1,datanode
localhost:8903:cnode1,computenode

cluster.nodes is used to store information about agents, data nodes and compute nodes. The default cluster configuration file contains 1 agent, 1 data node and 1 compute node. You can configure the number of nodes as required. This configuration file specifies localSite and mode. The parameter localSite contains the node IP address, port number and alias, which are separated by colons ":". The parameter mode specifies the node type.

❗ Node aliases are case sensitive and must be unique in a cluster.

Execute the following shell command to modify cluster.cfg:

vim ./cluster.cfg

maxMemSize=32
maxConnections=512
workerNum=4
localExecutors=3
maxBatchJobWorker=4
OLAPCacheEngineSize=2
TSDBCacheEngineSize=1
newValuePartitionPolicy=add
maxPubConnections=64
subExecutors=4
lanCluster=0
enableChunkGranularityConfig=true

The configuration parameters in this file apply to each data node and compute node in the cluster. You can modify them based your own device.