mirror of https://github.com/apache/druid.git
parent
257bc5c62f
commit
59c8430d29
|
@ -56,7 +56,7 @@ Here is a JSON example of the 'metrics' data schema used in the example.
|
||||||
|
|
||||||
### Proto file
|
### Proto file
|
||||||
|
|
||||||
The corresponding proto file for our 'metrics' dataset looks like this. You can use Protobuf parser with a proto file or [Confluent Schema Registry](https://docs.confluent.io/platform/current/schema-registry/index.html).
|
The corresponding proto file for our 'metrics' dataset looks like this. You can use Protobuf `inputFormat` with a proto file or [Confluent Schema Registry](https://docs.confluent.io/platform/current/schema-registry/index.html).
|
||||||
```
|
```
|
||||||
syntax = "proto3";
|
syntax = "proto3";
|
||||||
message Metrics {
|
message Metrics {
|
||||||
|
@ -112,22 +112,14 @@ Important supervisor properties
|
||||||
- `protoBytesDecoder.descriptor` for the descriptor file URL
|
- `protoBytesDecoder.descriptor` for the descriptor file URL
|
||||||
- `protoBytesDecoder.protoMessageType` from the proto definition
|
- `protoBytesDecoder.protoMessageType` from the proto definition
|
||||||
- `protoBytesDecoder.type` set to `file`, indicate use descriptor file to decode Protobuf file
|
- `protoBytesDecoder.type` set to `file`, indicate use descriptor file to decode Protobuf file
|
||||||
- `parser` should have `type` set to `protobuf`, but note that the `format` of the `parseSpec` must be `json`
|
- `inputFormat` should have `type` set to `protobuf`
|
||||||
|
|
||||||
```json
|
```json
|
||||||
{
|
{
|
||||||
"type": "kafka",
|
"type": "kafka",
|
||||||
|
"spec": {
|
||||||
"dataSchema": {
|
"dataSchema": {
|
||||||
"dataSource": "metrics-protobuf",
|
"dataSource": "metrics-protobuf",
|
||||||
"parser": {
|
|
||||||
"type": "protobuf",
|
|
||||||
"protoBytesDecoder": {
|
|
||||||
"type": "file",
|
|
||||||
"descriptor": "file:///tmp/metrics.desc",
|
|
||||||
"protoMessageType": "Metrics"
|
|
||||||
},
|
|
||||||
"parseSpec": {
|
|
||||||
"format": "json",
|
|
||||||
"timestampSpec": {
|
"timestampSpec": {
|
||||||
"column": "timestamp",
|
"column": "timestamp",
|
||||||
"format": "auto"
|
"format": "auto"
|
||||||
|
@ -145,8 +137,6 @@ Important supervisor properties
|
||||||
"timestamp",
|
"timestamp",
|
||||||
"value"
|
"value"
|
||||||
]
|
]
|
||||||
}
|
|
||||||
}
|
|
||||||
},
|
},
|
||||||
"metricsSpec": [
|
"metricsSpec": [
|
||||||
{
|
{
|
||||||
|
@ -184,9 +174,23 @@ Important supervisor properties
|
||||||
"consumerProperties": {
|
"consumerProperties": {
|
||||||
"bootstrap.servers": "localhost:9092"
|
"bootstrap.servers": "localhost:9092"
|
||||||
},
|
},
|
||||||
|
"inputFormat": {
|
||||||
|
"type": "protobuf",
|
||||||
|
"protoBytesDecoder": {
|
||||||
|
"type": "file",
|
||||||
|
"descriptor": "file:///tmp/metrics.desc",
|
||||||
|
"protoMessageType": "Metrics"
|
||||||
|
},
|
||||||
|
"flattenSpec": {
|
||||||
|
"useFieldDiscovery": true
|
||||||
|
},
|
||||||
|
"binaryAsString": false
|
||||||
|
},
|
||||||
"taskCount": 1,
|
"taskCount": 1,
|
||||||
"replicas": 1,
|
"replicas": 1,
|
||||||
"taskDuration": "PT1H"
|
"taskDuration": "PT1H",
|
||||||
|
"type": "kafka"
|
||||||
|
}
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
```
|
```
|
||||||
|
@ -253,7 +257,7 @@ If necessary, from your Kafka installation directory run the following command t
|
||||||
This example script requires `protobuf` and `kafka-python` modules. With the topic in place, messages can be inserted running the following command from your Druid installation directory
|
This example script requires `protobuf` and `kafka-python` modules. With the topic in place, messages can be inserted running the following command from your Druid installation directory
|
||||||
|
|
||||||
```
|
```
|
||||||
./bin/generate-example-metrics | ./quickstart/protobuf/pb_publisher.py
|
./bin/generate-example-metrics | python /quickstart/protobuf/pb_publisher.py
|
||||||
```
|
```
|
||||||
|
|
||||||
You can confirm that data has been inserted to your Kafka topic using the following command from your Kafka installation directory
|
You can confirm that data has been inserted to your Kafka topic using the following command from your Kafka installation directory
|
||||||
|
|
Loading…
Reference in New Issue