All DSP releases prior to DSP 1.4.0 use Gravity, a Kubernetes orchestrator, which has been announced end-of-life. We have replaced Gravity with an alternative component in DSP 1.4.0. Therefore, we will no longer provide support for versions of DSP prior to DSP 1.4.0 after July 1, 2023. We advise all of our customers to upgrade to DSP 1.4.0 in order to continue to receive full product support from Splunk.
Get data from Kafka
Use the Kafka source function to get data from an Apache or Confluent Kafka topic.
The payload of the ingested data is stored in a bytes field named value
. During data previews, Splunk Data Stream Processor (DSP) displays the contents of bytes fields as Base64-encoded values. To deserialize the data so that you can view it as human-readable strings during data preview, see Deserialize and preview data from Kafka in DSP in the Connect to Data Sources and Destinations with DSP manual.
Prerequisites
Before you can use this function, you must create a connection. See the following pages in the Connect to Data Sources and Destinations with DSP manual for more information:
- For information about creating a SASL-authenticated connection, see Create a SASL-authenticated DSP connection to Kafka.
- For information about creating an SSL-authenticated connection, see Create an SSL-authenticated DSP connection to Kafka.
- For information about creating an unauthenticated connection, see Create an unauthenticated DSP connection to Kafka.
When configuring this source function, set the connection_id
argument to the ID of the connection that you created.
Function output schema
This function outputs records with the schema described in the following table.
Key | Description |
---|---|
key | The key of the record in bytes. |
value | The payload of the record in bytes. |
topic | The name of the Kafka topic where the record is stored, given as a string. |
partition | The number of the partition in the Kafka topic where the record is stored, given as an integer. |
offset | The offset of the record as a long. |
The following is an example of a typical record from the kafka
function:
{ "key": "YTE=", "value": "aGVsbG8gd29ybGQ=", "topic": "my-kafka-topic", "partition": 1, "offset": 248 }
Required arguments
- connection_id
- Syntax: string
- Description: The ID of your Kafka connection.
- Example in Canvas View: my-kafka-connection
- topic
- Syntax: string
- Description: The name of the Kafka topic.
- Example in Canvas View: my-kafka-topic
Optional arguments
- consumer_properties
- Syntax: "<name>": "<value>"
- Description: The consumer properties by which you want to delimit your data. Defaults to empty.
- When working in Canvas View, specify the name and value of the property in the fields on either side of the equal sign ( = ), and click Add to specify additional properties.
- When working in SPL View, specify each property using the format
"<name>": "<value>"
, and separate each property with a comma ( , ). Make sure to enclose the entire argument in braces ( { } ).
- For a list of valid consumer properties, see the "Consumer Configs" section in the Apache Kafka documentation.
- Example in Canvas View: name = value
SPL2 example
When working in the SPL View, you can write the function by providing the arguments in this exact order.
| from kafka("my-connection-id", "my-topic", {"property1": "value1", "property2": "value2"}) |...;
Alternatively, you can use named arguments to declare the arguments in any order. The following example uses named arguments to list the optional argument before the required arguments.
| from kafka(consumer_properties: {"property1": "value1", "property2": "value2"}, topic: "my-topic", connection_id: "my-connection-id") |...;
If you want to use a mix of unnamed and named arguments in your functions, you must list all unnamed arguments in the correct order before providing the named arguments.
Get data from Apache Pulsar | Get data from Google Cloud Pub/Sub |
This documentation applies to the following versions of Splunk® Data Stream Processor: 1.3.0, 1.3.1, 1.4.0, 1.4.1, 1.4.2, 1.4.3, 1.4.4, 1.4.5, 1.4.6
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