mirror of https://github.com/apache/druid.git
108 lines
4.1 KiB
Markdown
108 lines
4.1 KiB
Markdown
---
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layout: doc_page
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---
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# Druid Firehoses
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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.
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| Field | Type | Description | Required |
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|-------|------|-------------|----------|
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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 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.
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- `feed` is the feed that the Kafka consumer should read from.
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- `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
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-------------------
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There are several firehoses readily available in Druid, some are meant for examples, others can be used directly in a production environment.
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#### KafkaFirehose
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This firehose acts as a Kafka consumer and ingests data from Kafka.
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#### StaticS3Firehose
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This firehose ingests events from a predefined list of S3 objects.
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#### 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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#### RabbitMqFirehose
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This firehose ingests events from a define rabbit-mq queue.
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#### LocalFirehose
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This Firehose can be used to read the data from files on local disk.
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It can be used for POCs to ingest data on disk.
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A sample local firehose spec is shown below:
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```json
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{
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"type" : "local",
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"filter" : "*.csv",
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"parser" : {
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"timestampSpec": {
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"column": "mytimestamp",
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"format": "yyyy-MM-dd HH:mm:ss"
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},
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"data": {
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"format": "csv",
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"columns": [...],
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"dimensions": [...]
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}
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}
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}
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```
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|property|description|required?|
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|--------|-----------|---------|
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|type|This should be "local".|yes|
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|filter|A wildcard filter for files. See [here](http://commons.apache.org/proper/commons-io/apidocs/org/apache/commons/io/filefilter/WildcardFileFilter.html) for more information.|yes|
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|data|A data spec similar to what is used for batch ingestion.|yes|
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#### IngestSegmentFirehose
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This Firehose can be used to read the data from existing druid segments.
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It can be used ingest existing druid segments using a new schema and change the name, dimensions, metrics, rollup, etc. of the segment.
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A sample ingest firehose spec is shown below -
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```json
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{
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"type" : "ingestSegment",
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"dataSource" : "wikipedia",
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"interval" : "2013-01-01/2013-01-02"
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}
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```
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|property|description|required?|
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|--------|-----------|---------|
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|type|ingestSegment. Type of firehose|yes|
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|dataSource|A String defining the data source to fetch rows from, very similar to a table in a relational database|yes|
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|interval|A String representing ISO-8601 Interval. This defines the time range to fetch the data over.|yes|
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|dimensions|The list of dimensions to select. If left empty, no dimensions are returned. If left null or not defined, all dimensions are returned. |no|
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|metrics|The list of metrics to select. If left empty, no metrics are returned. If left null or not defined, all metrics are selected.|no|
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|filter| See [Filters](Filters.html)|yes|
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Parsing Data
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------------
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There are several ways to parse data.
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#### StringInputRowParser
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This parser converts Strings.
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#### MapInputRowParser
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This parser converts flat, key/value pair maps.
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