TIBCO Source Connector for Confluent Platform¶

The Kafka Connect TIBCO Source connector is used to move messages from TIBCO Enterprise Messaging Service (EMS) to Apache Kafka®.

Messages are consumed from the TIBCO EMS broker using the configured message selectors and written to a single Kafka topic. A Single Message Transformation can be used to route messages to multiple Kafka topics.

The connector currently supports consuming JMS TextMessage and BytesMessage but not ObjectMessage or StreamMessage.

Note

If you are required to use the Java Naming and Directory Interface™ (JNDI) to connect to TIBCO EMS, there is a general JMS Source connector for Confluent Platform available that uses a JNDI-based mechanism to connect to the JMS broker.

At least once delivery¶

This connector guarantees that records are delivered to the Kafka topic at least once. If the connector restarts, there may be some duplicate records in the Kafka topic.

Multiple tasks¶

The TIBCO Source connector supports running one or more tasks. You can specify the number of tasks in the tasks.max configuration parameter. This can lead to performance gains when multiple files need to be parsed.

Schemas¶

The TIBCO Source connector produces messages with keys and values that adhere to the schemas described in the following sections.

io.confluent.connect.jms.Key¶

This schema is used to store the incoming MessageID on the message interface. This will ensure that when the same message ID arrives it will end up in the same partition. In practice this should never occur. The schema defines the following fields:

Name	Schema	Required	Default Value	Documentation
messageID	STRING	yes		This field stores the value of Message.getJMSMessageID().

io.confluent.connect.jms.Value¶

This schema is used to store the value of the JMS message. The schema defines the following fields:

Name	Schemna	Required	Documentation
messageID	STRING	yes	This field stores the value of Message.getJMSMessageID().
messageType	STRING	yes	This field stores the type of message that was received. This corresponds to the sub-interfaces of Message. BytesMessage = `bytes`, MapMessage = `map`, ObjectMessage = `object`, StreamMessage = `stream` and TextMessage = `text`. The corresponding field will be populated with the values from the respective message sub-interface.
timestamp	INT64	yes	Data from the getJMSTimestamp() method.
deliveryMode	INT32	yes	This field stores the value of Message.getJMSDeliveryMode(). method.
correlationID	STRING	no	This field stores the value of Message.getJMSCorrelationID(). method.
replyTo	Destination	no	This schema is used to represent a JMS Destination, and is either queue or topic.
destination	Destination	no	This schema is used to represent a JMS Destination, and is either queue or topic.
redelivered	BOOLEAN	yes	This field stores the value of Message.getJMSRedelivered().
type	STRING	no	This field stores the value of Message.getJMSType().
expiration	INT64	no	This field stores the value of Message.getJMSExpiration().
priority	INT32	no	This field stores the value of Message.getJMSPriority().
properties	Map of STRING, PropertyValue	yes	This field stores the data from all of the properties for the Message indexed by their propertyName.
bytes	BYTES	no	This field stores the value from BytesMessage.html.readBytes(byte[]).
map	Map of STRING, PropertyValue	no	This field stores the data from all of the map entries returned from MapMessage.getMapNames() for the Message indexed by their key.
text	STRING	no	This field stores the value from TextMessage.html.getText().

io.confluent.connect.jms.Destination¶

This schema is used to represent a JMS Destination, and is either queue or topic.

The schema defines the following fields:

Name	Schema	Required	Default Value	Documentation
destinationType	STRING	yes		The type of JMS Destination, and either `queue` or `topic`.
name	STRING	yes		The name of the destination. This will be the value of Queue.getQueueName() or Topic.getTopicName().

io.confluent.connect.jms.PropertyValue¶

This schema is used to store the data that is found in the properties of the message. To ensure that the proper type mappings are preserved field propertyType stores the value type for the field. The corresponding field in the schema will contain the data for the property. This ensures that the data is retrievable as the type returned by Message.getObjectProperty(). The schema defines the following fields:

Name	Schema	Required	Documentation
propertyType	STRING	yes	The Java type of the property on the Message. One of `boolean`, `byte`, `short`, `integer`, `long`, `float`, `double`, or `string`.
boolean	BOOLEAN	no	The value stored as a boolean. Null unless `propertyType` is set to `boolean`.
byte	INT8	no	The value stored as a byte. Null unless `propertyType` is set to `byte`.
short	INT16	no	The value stored as a short. Null unless `propertyType` is set to `short`.
integer	INT32	no	The value stored as a integer. Null unless `propertyType` is set to `integer`.
long	INT64	no	The value stored as a long. Null unless `propertyType` is set to `long`.
float	FLOAT32	no	The value stored as a float. Null unless `propertyType` is set to `float`.
double	FLOAT64	no	The value stored as a double. Null unless `propertyType` is set to `double`.
string	STRING	no	The value stored as a string. Null unless `propertyType` is set to `string`.

License¶

You can use this connector for a 30-day trial period without a license key.

After 30 days, you must purchase a connector subscription which includes Confluent enterprise license keys to subscribers, along with enterprise-level support for Confluent Platform and your connectors. If you are a subscriber, you can contact Confluent Support at support@confluent.io for more information.

For license properties, see Confluent Platform license. For information about the license topic, refer to License topic configuration.

Configuration¶

This section describes how the connector internally configures the acknowledgement mode. For a complete list of configuration properties for this connector, see Configuration Reference for TIBCO Source Connector for Confluent Platform.

For an example of how to get Kafka Connect connected to Confluent Cloud, see Connect Self-Managed Kafka Connect to Confluent Cloud.

Acknowledgement mode¶

The connector internally uses CLIENT_ACKNOWLEDGE mode to receive and acknowledge messages from the JMS broker. In this mode, acknowledging any message will acknowledge every message received (see section 6.2.10 in the JMS 2.0 Specification). To prevent messages from being prematurely acknowledged, the connector processes only one message at time. In other words, the connector will not try to receive new messages until the last message is committed to a Kafka topic. This might compromise the throughput of the connector, but messages will be transferred to Kafka successfully.

Install the TIBCO Source connector¶

You can install this connector by using the confluent connect plugin install command, or by manually downloading the ZIP file.

Prerequisites¶

You must install the connector on every machine where Connect will run.
Kafka Broker: Confluent Platform 3.3.0 or later, or Kafka 0.11.0 or later.
Connect: Confluent Platform 4.1.0 or later, or Kafka 1.1.0 or later (requires header support in Connect).
TIBCO EMS with JMS 1.1 support.
tibjms Client Library. For more details, see Installing the TIBCO JMS client library.
Java 1.8.
The latest (latest) connector version.

Install the connector using Confluent CLI¶

To install the latest connector version, navigate to your Confluent Platform installation directory and run the following command:

confluent connect plugin install confluentinc/kafka-connect-tibco-source:latest

You can install a specific version by replacing latest with a version number as shown in the following example:

confluent connect plugin install confluentinc/kafka-connect-tibco-source:1.0.0-preview

TIBCO Client library¶

The Kafka Connect TIBCO Source connector does not include the TIBCO JMS client library.

If you are running a multi-node Connect cluster, the connector and TIBCO JMS client JAR must be installed on every Connect worker in the cluster. The following section for details.

Installing the TIBCO JMS client library¶

This connector relies on a provided tibjms client JAR that is included in the TIBCO EMS installation. The connector will fail to create a connection to TIBCO EMS if you have not installed the JAR on each Connect worker node.

The installation steps are:

Download and Install TIBCO Enterprise Message Service™ (Mac or Linux). If you have already installed TIBCO EMS, skip to the next step.
Unzip the download and copy only the tibco/ems/{version}/lib/tibjms.jar file into the share/java/kafka-connect-tibco-source directory of your Confluent Platform installation on each worker node. If you are using a different installation, find the location of the Confluent TIBCO Source connector JAR files and place the tibjms JAR file into the same directory.
Restart all of the Connect worker nodes.

Install the connector manually¶

Download and extract the ZIP file for your connector and then follow the manual connector installation instructions.

Quick start¶

This quick start uses the TIBCO Source connector to consume records from TIBCO Enterprise Message Service™ - Community Edition and sends them to Kafka.

Download TIBCO Enterprise Message Service™ - Community Edition (Mac or Linux) and run the appropriate installer. For more details, see the TIBCO Enterprise Message Service™ Installation Guide. Similar documentation is available for each version of TIBCO EMS.

Install the connector through the Confluent Hub Client.

# run from your Confluent Platform installation directory
confluent connect plugin install confluentinc/kafka-connect-tibco-source:latest

Install the TIBCO JMS Client Library.
Start Confluent Platform.
```
confluent local start
```

Create a connector-quickstart queue with the TIBCO Admin Tool.

# connect to TIBCO with the Admin Tool (PASSWORD IS EMPTY)
tibco/ems/8.4/bin/tibemsadmin -server "tcp://localhost:7222" -user admin

> create queue connector-quickstart

Compile the TIBCO Java samples so that they can be run in the following step.

# setup Java's classpath so that the Java compiler can find the imports of the samples
cd tibco/ems/8.4/samples/java
export TIBEMS_JAVA=tibco/ems/8.4/lib
CLASSPATH=${TIBEMS_JAVA}/jms-2.0.jar:${CLASSPATH}
CLASSPATH=.:${TIBEMS_JAVA}/tibjms.jar:${TIBEMS_JAVA}/tibjmsadmin.jar:${CLASSPATH}
export CLASSPATH

# compile the java classes (run from the tibco/ems/8.4/samples/java directory)
javac *.java

Produce a set of messages to the connector-quickstart queue.

cd tibco/ems/8.4/samples/java

# produce 5 test messages
java tibjmsMsgProducer -user admin -queue connector-quickstart m1 m2 m3 m4 m5

------------------------------------------------------------------------
tibjmsMsgProducer SAMPLE
------------------------------------------------------------------------
Server....................... localhost
User......................... admin
Destination.................. connector-quickstart
Send Asynchronously.......... false
Message Text.................
m1
m2
m3
m4
m5
------------------------------------------------------------------------

Publishing to destination 'connector-quickstart'

Published message: m1
Published message: m2
Published message: m3
Published message: m4
Published message: m5

Create a tibco-source.json file with the following contents:

{
  "name": "TibcoSourceConnector",
  "config": {
    "connector.class": "io.confluent.connect.tibco.TibcoSourceConnector",
    "tasks.max": "1",
    "kafka.topic": "from-tibco-messages",
    "tibco.url": "tcp://localhost:7222",
    "tibco.username": "admin",
    "tibco.password": "",
    "jms.destination.type": "queue",
    "jms.destination.name": "connector-quickstart",
    "key.converter": "org.apache.kafka.connect.storage.StringConverter",
    "value.converter": "org.apache.kafka.connect.storage.StringConverter",
    "confluent.topic.bootstrap.servers": "localhost:9092",
    "confluent.topic.replication.factor": "1"
  }
}

Load the TIBCO Source connector.

Caution

You must include a double dash (--) between the topic name and your flag. For more information, see this post.
```
confluent local load tibco --config tibco-source.json
```

Confirm that the connector is in a RUNNING state.

confluent local status TibcoSourceConnector

Confirm the messages were delivered to the from-tibco-messages topic in Kafka.
```
confluent local consume from-tibco-messages --from-beginning
```