TIBCO Sink Connector for Confluent Platform¶

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

Note

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

Features¶

The TIBCO Sink connector includes the following features:

At least once delivery
Dead Letter Queue
Multiple tasks
JMS message format configuration
Kafka property forwarding to JMS

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.

Dead Letter Queue¶

This connector supports the Dead Letter Queue (DLQ) functionality. For information about accessing and using the DLQ, see Confluent Platform Dead Letter Queue.

Multiple tasks¶

The TIBCO Sink 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.

JMS message format¶

The format of outgoing JMS message values is configured with the jms.message.format property, using one of the following options:

string (default)¶

When using the string message format, record values are run through Values.convertToString(...) from the Connect Data package and produced as a JMS TextMessage.

Primitive values are converted to their string equivalent and structured objects are transformed to a sensible string representation that is similar to the JSON representation, with the exception of simple string values (not in objects or arrays) which are unquoted.

Tip

Single Message Transformation can be used with the configured jms.message.format to transform the record value to the desired string representation before the connector processes each record.

avro¶

Record values are serialized without the Avro schema information and produced as a JMS BytesMessage. JMS consumers must have the schema to deserialize the data.

Important

The connector attempts to infer the Avro schema for records that have no schema. If the connector cannot infer the schema, the task is killed. If you are processing data without a schema, consider using one of the other jms.message.format configurations.

json¶

Record values are converted to a UTF-8 encoded JSON representation and produced as a JMS TextMessage.

bytes¶

Record values are passed along in bytes form without any conversion.

Important

Record values must be converted to bytes form before the connector processes them. Configure the value.converter property to org.apache.kafka.connect.converters.ByteArrayConverter to ensure the record values arrive in byte format.

Forward Kafka properties to JMS¶

The connector can be configured to forward various values from the Kafka record to the JMS Message.

Enable jms.forward.kafka.key to convert the record’s key to a string and forward it as the JMSCorrelationID.
Enable jms.forward.kafka.metadata to forward the record’s topic, partition, and offset on JMS Message properties.
- Kafka topic is applied to the message as a string property named KAFKA_TOPIC.
- Partition is applied to the message as an Int property named KAFKA_PARTITION.
- Offset is applied to the message as a Long property named KAFKA_OFFSET.
Enable jms.forward.kafka.headers to add each header from the SinkRecord to the JMS Message as a string property.

Note

The connector converts the record key and headers to a sensible string representation that is similar to the JSON representation, with the exception of simple string values (not in objects or arrays), which are unquoted. No other conversion is done to the key and headers before forwarding them on to the JMS Message. If another format is needed, out-of-the-box or custom Single Message Transformation can be used with the connector to transform the record keys and/or headers to the desired string representation before the JMS sink connector processes each record.

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.

See Confluent Platform license for license properties and License topic configuration for information about the license topic.

Configuration¶

For a complete list of configuration properties for this connector, see TIBCO Sink Connector Configuration Properties.

Note

For an example of how to get Kafka Connect connected to Confluent Cloud, see Distributed Cluster.

Install the TIBCO Sink Connector¶

You can install this connector by using the Confluent Hub client installation instructions or by manually downloading the ZIP file.

Prerequisites¶

Important

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 TIBCO JMS Client Library.
Java 1.8
An install of the Confluent Hub Client.

Note

This is installed by default with Confluent Enterprise.
An install of the latest (latest) connector version.

To install the latest connector version, navigate to your Confluent Platform installation directory and run the following command:
```
confluent-hub 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-hub install confluentinc/kafka-connect-tibco-source:1.0.0-preview
```

TIBCO Client Library¶

The Kafka Connect TIBCO connector does not come with the TIBCO JMS client library.

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

Installing 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-sink directory of your Confluent Platform installation on each worker node.
Restart all of the Connect worker nodes.

Note

The share/java/kafka-connect-tibco-sink directory mentioned above is for Confluent Platform. If you are using a different installation, find the location of the Confluent TIBCO Sink connector JAR files and place the tibjms JAR file into the same directory.

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 Sink connector to consume records from Kafka and send them to TIBCO Enterprise Message Service™ - Community Edition.

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

Install the connector through the Confluent Hub Client.

# run from your CP installation directory
confluent-hub install confluentinc/kafka-connect-tibco-sink:latest

Install the TIBCO JMS Client Library.
Start the Confluent Platform.

Tip

The command syntax for the Confluent CLI development commands changed in 5.3.0. These commands have been moved to confluent local. For example, the syntax for confluent start is now confluent local services start. For more information, see confluent local.
```
confluent local start
```

Produce test data to the sink-messages topic in Kafka.

seq 10 | confluent local produce sink-messages

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

{
  "name": "TibcoSinkConnector",
  "config": {
    "connector.class": "io.confluent.connect.jms.TibcoSinkConnector",
    "tasks.max": "1",
    "topics": "sink-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 Sink 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-sink.json
```
Confirm that the connector is in a RUNNING state.
```
confluent local status tibco
```

Confirm the messages were delivered to the connector-quickstart queue in TIBCO.

# open TIBCO admin tool (password is empty)
tibco/ems/8.4/bin/tibemsadmin -server "tcp://localhost:7222" -user admin

> show queue connector-quickstart