druid/docs/content/Firehose.md

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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 |
|-------|------|-------------|----------|
| type | String | Specifies the type of firehose. Each value will have its own configuration schema, firehoses packaged with Druid are described below. | yes |
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We describe the configuration of the [Kafka firehose example](Realtime-ingestion.html#realtime-specfile), but there are other types available in Druid (see below).
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- `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 required `InputRow` 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 below.
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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
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See [Examples](Examples.html). This firehose connects directly to the twitter spritzer data stream.
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#### RandomFirehose
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See [Examples](Examples.html). This firehose creates a stream of random numbers.
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#### 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.