druid/docs/content/development/extensions-core/protobuf.md

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---
layout: doc_page
---
# Protobuf
This extension enables Druid to ingest and understand the Protobuf data format. Make sure to [include](../../operations/including-extensions.html) `druid-protobuf-extensions` as an extension.
## Protobuf Parser
| Field | Type | Description | Required |
|-------|------|-------------|----------|
| type | String | This should say `protobuf`. | no |
| descriptor | String | Protobuf descriptor file name in the classpath or URL. | yes |
| protoMessageType | String | Protobuf message type in the descriptor. Both short name and fully qualified name are accepted. The parser uses the first message type found in the descriptor if not specified. | no |
| parseSpec | JSON Object | Specifies the timestamp and dimensions of the data. The format must be json. See [JSON ParseSpec](../../ingestion/index.html) for more configuration options. Please note timeAndDims parseSpec is no longer supported. | yes |
## Example: Load Protobuf messages from Kafka
This example demonstrates how to load Protobuf messages from Kafka. Please read the [Load from Kafka tutorial](../../tutorials/tutorial-kafka.html) first. This example will use the same "metrics" dataset.
Files used in this example are found at `./examples/quickstart/protobuf` in your Druid directory.
- We will use [Kafka Indexing Service](./kafka-ingestion.html) instead of Tranquility.
- Kafka broker host is `localhost:9092`.
- Kafka topic is `metrics_pb` instead of `metrics`.
- datasource name is `metrics-kafka-pb` instead of `metrics-kafka` to avoid the confusion.
Here is the metrics JSON example.
```json
{
"unit": "milliseconds",
"http_method": "GET",
"value": 44,
"timestamp": "2017-04-06T02:36:22Z",
"http_code": "200",
"page": "/",
"metricType": "request/latency",
"server": "www1.example.com"
}
```
### Proto file
The proto file should look like this. Save it as metrics.proto.
```
syntax = "proto3";
message Metrics {
string unit = 1;
string http_method = 2;
int32 value = 3;
string timestamp = 4;
string http_code = 5;
string page = 6;
string metricType = 7;
string server = 8;
}
```
### Descriptor file
Using the `protoc` Protobuf compiler to generate the descriptor file. Save the metrics.desc file either in the classpath or reachable by URL. In this example the descriptor file was saved at /tmp/metrics.desc.
```
protoc -o /tmp/metrics.desc metrics.proto
```
### Supervisor spec JSON
Below is the complete Supervisor spec JSON to be submitted to the Overlord.
Please make sure these keys are properly configured for successful ingestion.
- `descriptor` for the descriptor file URL.
- `protoMessageType` from the proto definition.
- parseSpec `format` must be `json`.
- `topic` to subscribe. The topic is "metrics_pb" instead of "metrics".
- `bootstrap.server` is the kafka broker host.
```json
{
"type": "kafka",
"dataSchema": {
"dataSource": "metrics-kafka2",
"parser": {
"type": "protobuf",
"descriptor": "file:///tmp/metrics.desc",
"protoMessageType": "Metrics",
"parseSpec": {
"format": "json",
"timestampSpec": {
"column": "timestamp",
"format": "auto"
},
"dimensionsSpec": {
"dimensions": [
"unit",
"http_method",
"http_code",
"page",
"metricType",
"server"
],
"dimensionExclusions": [
"timestamp",
"value"
]
}
}
},
"metricsSpec": [
{
"name": "count",
"type": "count"
},
{
"name": "value_sum",
"fieldName": "value",
"type": "doubleSum"
},
{
"name": "value_min",
"fieldName": "value",
"type": "doubleMin"
},
{
"name": "value_max",
"fieldName": "value",
"type": "doubleMax"
}
],
"granularitySpec": {
"type": "uniform",
"segmentGranularity": "HOUR",
"queryGranularity": "NONE"
}
},
"tuningConfig": {
"type": "kafka",
"maxRowsPerSegment": 5000000
},
"ioConfig": {
"topic": "metrics_pb",
"consumerProperties": {
"bootstrap.servers": "localhost:9092"
},
"taskCount": 1,
"replicas": 1,
"taskDuration": "PT1H"
}
}
```
## Kafka Producer
Here is the sample script that publishes the metrics to Kafka in Protobuf format.
1. Run `protoc` again with the Python binding option. This command generates `metrics_pb2.py` file.
```
protoc -o metrics.desc metrics.proto --python_out=.
```
2. Create Kafka producer script.
This script requires `protobuf` and `kafka-python` modules.
```python
#!/usr/bin/env python
import sys
import json
from kafka import KafkaProducer
from metrics_pb2 import Metrics
producer = KafkaProducer(bootstrap_servers='localhost:9092')
topic = 'metrics_pb'
metrics = Metrics()
for row in iter(sys.stdin):
d = json.loads(row)
for k, v in d.items():
setattr(metrics, k, v)
pb = metrics.SerializeToString()
producer.send(topic, pb)
```
3. run producer
```
./bin/generate-example-metrics | ./pb_publisher.py
```
4. test
```
kafka-console-consumer --zookeeper localhost --topic metrics_pb
```
It should print messages like this
> millisecondsGETR"2017-04-06T03:23:56Z*2002/list:request/latencyBwww1.example.com