Ariticle

Introduction to the Real-Time Java Docker Image

October 02,2020

Jirapongse Phuriphanvichai

Last Updated: June 2024

The Real-Time SDK is a suite of modern and open source APIs that is designed to simplify development through a strong focus on ease of use and standardized access to a broad set of proprietary content and services.

It currently supports C, C++, and Java programming languages and can be run on several operating systems including Windows, Oracle Linux, Red Hat Enterprise Linux, and CentOS.

Note: Although the Real-Time SDKs can also run on Docker, it isn't officially qualified on the Docker platform. If you find any problems while running it on the Docker platform, the issues must be replicated on bare metal machines before contacting the helpdesk support.

This article demonstrates how to use the Real-Time SDK on the Docker platform. It has three sections including:

Real-Time APIs docker images on the Docker Hub
Deploying the Real-Time SDK Java docker image
Running examples in the docker container

Real-Time APIs docker images

The source of the Real-Time SDK is available in GitHub. The Real-Time SDK C/C++ and Java libraries can be built by using CMake and Gradle, respectively. Steps to build the Real-Time SDK libraries are mentioned in GitHub (C/C++, and Java). Moreover, you can create your own Real-Time SDK docker image by following steps in the Deploy and Run Real-Time SDK in Docker article.

Fortunately, the Real-Time SDK Docker images are now available in Docker Hub, as shown below.

lsegrealtime/realtimesdk_c: This docker image contains the latest version of Real-Time SDK C/C++ libraries and examples. The image is rebuilt when the new version of Real-Time SDK is available in GitHub. It uses Oracle Linux 7 as a based image and the GCC version is 4.8.5.
lsegrealtime/realtimesdk_java: This docker image contains the latest version of Real-Time SDK Java libraries and examples. The image is rebuilt when the new version of Real-Time SDK is available in GitHub. It uses Oracle Linux 7 as a based image and the Oracle OpenJDK version is 11.
lsegrealtime/websocket_api: This docker image contains WebSocket API Examples used to connect to Real-Time Distribution System or Data Platform to consume real-time data through the WebSocket connections. There are examples of various programming languages such as CSharp, Java, Python, Go, Ruby, Node, Perl, and R. The examples are available in GitHub. The image uses Oracle Linux 8 as a base image and it installs Python 3.9 used to run Python WebSocket API examples.

This article only focuses on the lsegrealtime/realtimesdk_java docker image.

In the next section, I will demonstrate how to deploy the lsegrealtime/realtimesdk_java image on Docker engines and Azure Containers.

Deploying the Real-Time SDK Java docker image

The docker images can be run as docker containers on local machines or cloud platforms. To follow steps in this section, the docker engine must be installed on a local machine or an Azure account is ready to be used.

Deploying the Real-Time SDK Java docker image on a local machine

First, the docker engine must be installed and run properly on the machine. The "docker version" command can be used to verify the docker engine.

    	
            # docker version
Client: Docker Engine - Community
 Version:           19.03.1-ol
 API version:       1.40
 Go version:        go1.12.5
 Git commit:        ead9442
 Built:             Wed Sep 11 06:40:28 2019
 OS/Arch:           linux/amd64
 Experimental:      false
 
Server: Docker Engine - Community
 Engine:
  Version:          19.03.1-ol
  API version:      1.40 (minimum version 1.12)
  Go version:       go1.12.5
  Git commit:       ead9442
  Built:            Wed Sep 11 06:38:43 2019
  OS/Arch:          linux/amd64
  Experimental:     false
  Default Registry: docker.io
 containerd:
  Version:          v1.2.0-rc.0-108-gc444666
  GitCommit:        c4446665cb9c30056f4998ed953e6d4ff22c7c39
 runc:
  Version:          1.0.0-rc5+dev
  GitCommit:        4bb1fe4ace1a32d3676bb98f5d3b6a4e32bf6c58
 docker-init:
  Version:          0.18.0
  GitCommit:        fec3683

When the docker engine is started, the "docker pull lsegrealtime/realtimesdk_java" command can be used to download the latest Real-Time SDK Java docker image from the Docker Hub.

    	
            # docker pull lsegrealtime/realtimesdk_java
Using default tag: latest
Trying to pull repository docker.io/lsegrealtime/realtimesdk_java ...
latest: Pulling from docker.io/lsegrealtime/realtimesdk_java
01eb3c96478b: Already exists
de98b59498ca: Pull complete
Digest: sha256:bd68e2302828dbfb7a6f5f62a76baad14c3bad6bd7ec21d3ee30d8de3c315e4e
Status: Downloaded newer image for lsegrealtime/realtimesdk_java:latest
lsegrealtime/realtimesdk_java:latest

After downloading, the "docker images" command can be used to verify that the Real-Time SDK Java docker image is available on the machine.

    	
            # docker images
REPOSITORY                    TAG                 IMAGE ID            CREATED             SIZE
lsegrealtime/realtimesdk_java   latest              7f5e78fd2b65        3 hours ago         1.84GB

The output of the "docker images" command must contain the lsegrealtime/realtimesdk_java repository.

A Docker image can be run inside a container. The "docker run" command creates a new running container instance of the docker image. The following command can be used to run a container instance of the Real-Time SDK Java docker image.

    	
            # docker run -it --name realtimejava lsegrealtime/realtimesdk_java
sh-4.2# ls
CHANGELOG.md  README.md                          etc      gradlew.bat
Ema           RTSDK-Java-Edition_Test_Plan.xlsx  gradle   settings.gradle
Eta           build.gradle                       gradlew
sh-4.2# pwd
/opt/lseg/Real-Time-SDK/Java

After running this command, you can access shell in the container. Then, you run the Real-Time SDK examples in the container. The Real-Time SDK Java is in /opt/lseg/Real-Time-SDK/Java directory.

Deploying the Real-Time SDK Java docker image on Azure

Instead of running docker containers on the local machine, you can run the Real-Time SDK Java docker container on Azure Container Instances. Azure Container Instances are used to create and manage Docker containers in Azure without having to set up virtual machines or manage additional infrastructure.

First, log in to Azure and then create a new Container Instances resource.

On the Create container instance page, fill in all required information. Select Docker Hub or other registry for the Image source and enter lsegrealtime/realtimesdk_java for the Image. Then, click on the Next: Networking button.

On the Networking tab, keep the default setting. Then click on the Next: Advanced button.

On the Advanced tab, enter [ "/bin/bash", "-c", "echo hello; sleep 60m" ] for the Command override. This command will keep the container running for 60 minutes before exiting. You can use another command or change the sleep time to keep the container running. Then, click on Review + create button.

Next, review the information and then click on the Create button to create a container instance.

Wait for the deployment process to be completed. After the deployment is complete, click on the created resource (realtimesdkjava).

On the overview page, verify that the status of the container is Running.

Then, select Containers under Settings, click on the Connect tab, choose the shell to be used, and then click on the Connect button.

Now, you can access shell in the container.

Running examples in the container

This section demonstrates how to run EMA and ETA examples in the container to consume real-time data from Real-Time - Optimized. The Real-Time SDK Java is in the /opt/lseg/Real-Time-SDK/Java.

To access Real-Time -- Optimized, you should have a v1 authentication (Machine ID) or v2 authentication (Service account). These authentication accounts are used to get tokens. Then the tokens can be used to login to Real-Time – Optimized. For more information regarding v1 and v2 authentication, please refer to the Account authorization V1 to V2 migration cheat sheet article.

The v1 authentication comprises of:

Machine ID: A username in the form of GE-A-XXXXXXXX-X-XXXX
Password: A password for the machine ID
Client ID: A client ID or App Key that can be generated by using the AppKey Generator

The v2 authentication comprises of:

Client ID: A public identifier for apps
Client Secret: A secret known only to the application and the authorization server

Note: The client_id in the v2 authentication is not the same value as the client_id in the v1 authentication which is an app key.

Please find more detail from the following resources about the v2 authentication.

Note: After June 2024, the V1 authentication is only available for Wealth users. RTO uses must migrate to the v2 authentication.

Running an EMA example

In the Real-Time SDK package, ex113_MP_SessionMgmt is an OMM Consumer application example that demonstrates the basic usage of the EMA library in accessing and parsing OMM MarketPrice data from Real-Time - Optimized. The source code files and the working directory of this example are available in the following directories:

Source code files: /opt/lseg/Real-Time-SDK/Java/Ema/Examples/src/main/java/com/refinitiv/ema/examples/training/consumer/series100/ex113_MP_SessionMgmt
Working directory: /opt/lseg/Real-Time-SDK/Java/Ema/Examples

Follow these steps to run the ex113_MP_SessionMgmt example:

1. Change the current directory to /opt/lseg/Real-Time-SDK/Java

sh-4.2# cd /opt/lseg/Real-Time-SDK/Java

2. Run the ex113_MP_SessionMgmt example with the following command.

Connecting to RTO with the V1 authentication

sh-4.2# ./gradlew runConsumer113 -PcommandLineArgs="-username <UserID or MachineID> -password <Password> -clientId <AppKey> -itemName JPY="

Sep 22, 2020 9:24:59 AM com.refinitiv.ema.access.ChannelCallbackClient reactorChannelEventCallback

INFO: loggerMsg

ClientName: ChannelCallbackClient

Severity: Info

Text: Received ChannelUp event on channel Channel_4

Instance Name Consumer_4_1

Component Version ads3.2.1.L1.linux.tis.rrg 64-bit

loggerMsgEnd

RefreshMsg

streamId="5"

domain="MarketPrice Domain"

solicited

RefreshComplete

state="Open / Ok / None / '*All is well'"

itemGroup="00 ca"

permissionData="03 01 01 52 6c"

name="JPY="

nameType="1"

serviceId="257"

serviceName="ELEKTRON_DD"

Payload dataType="FieldList"

FieldList FieldListNum="99" DictionaryId="1"

FieldEntry fid="1" name="PROD_PERM" dataType="UInt" value="526"

FieldEntry fid="2" name="RDNDISPLAY" dataType="UInt" value="153"

FieldEntry fid="3" name="DSPLY_NAME" dataType="Rmtes" value="SEB STO"

FieldEntry fid="5" name="TIMACT" dataType="Time" value="09:25:00:000:000:000"

FieldEntry fid="11" name="NETCHNG_1" dataType="Real" value="-0.07"

FieldEntry fid="12" name="HIGH_1" dataType="Real" value="104.75"

FieldEntry fid="13" name="LOW_1" dataType="Real" value="104.47"

FieldEntry fid="15" name="CURRENCY" dataType="Enum" value="392"

FieldEntry fid="17" name="ACTIV_DATE" dataType="Date" value="22 SEP 2020"

FieldEntry fid="19" name="OPEN_PRC" dataType="Real" value="104.63"

FieldEntry fid="21" name="HST_CLOSE" dataType="Real" value="104.64"

FieldEntry fid="22" name="BID" dataType="Real" value="104.57"

Connecting to RTO with the V2 authentication

sh-4.2# ./gradlew runConsumer113 -PcommandLineArgs="clientId <ClientID> -clientSecret <ClientSecret> -itemName JPY="