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Firehoses describe the data stream source. They are pluggable and thus the configuration schema can and will vary based on the type
of the firehose.
Field | Type | Description | Required |
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type | String | Specifies the type of firehose. Each value will have its own configuration schema, firehoses packaged with Druid are described here | yes |
We describe the configuration of the Kafka firehose from the example below, but check here for more information about the various firehoses that are available in Druid.
consumerProps
is a map of properties for the Kafka consumer. The JSON object is converted into a Properties object and passed along to the Kafka consumer.feed
is the feed that the Kafka consumer should read from.parser
represents a parser that knows how to convert from String representations into the requiredInputRow
representation that Druid uses. This is a potentially reusable piece that can be found in many of the firehoses that are based on text streams. The spec in the example describes a JSON feed (new-line delimited objects), with a timestamp column called “timestamp” in ISO8601 format and that it should not include the dimension “value” when processing. More information about the options available for the parser are available here.
Available Firehoses
There are several firehoses readily available in Druid, some are meant for examples, others can be used directly in a production environment.
KafkaFirehose
This firehose acts as a Kafka consumer and ingests data from Kafka.
StaticS3Firehose
This firehose ingests events from a predefined list of S3 objects.
TwitterSpritzerFirehose
See Examples. This firehose connects directly to the twitter spritzer data stream.
RandomFirehose
See Examples. This firehose creates a stream of random numbers.
RabbitMqFirehouse
This firehose ingests events from a define rabbit-mq queue.
Parsing Data
There are several ways to parse data.
StringInputRowParser
This parser converts Strings.
MapInputRowParser
This parser converts flat, key/value pair maps.