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

---
id: protobuf
title: "Protobuf"
---

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This Apache Druid extension enables Druid to ingest and understand the Protobuf data format. Make sure to [include](../../development/extensions.md#loading-extensions) `druid-protobuf-extensions` as an extension.

The `druid-protobuf-extensions` provides the [Protobuf Parser](../../ingestion/data-formats.md#protobuf-parser)
for [stream ingestion](../../ingestion/index.md#streaming). See corresponding docs for details.

## 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.md) first, and see [Kafka Indexing Service](./kafka-ingestion.md) documentation for more details.

The files used in this example are found at [`./examples/quickstart/protobuf` in your Druid directory](https://github.com/apache/druid/tree/master/examples/quickstart/protobuf).

For this example:
- Kafka broker host is `localhost:9092`
- Kafka topic is `metrics_pb`
- Datasource name is `metrics-protobuf`

Here is a JSON example of the 'metrics' data schema used in the 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 corresponding proto file for our 'metrics' dataset looks like this.

```
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

Next, we use the `protoc` Protobuf compiler to generate the descriptor file and save it as `metrics.desc`. The descriptor file must be either in the classpath or reachable by URL.  In this example the descriptor file was saved at `/tmp/metrics.desc`, however this file is also available in the example files. From your Druid install directory:

```
protoc -o /tmp/metrics.desc ./quickstart/protobuf/metrics.proto
```

## Create Kafka Supervisor

Below is the complete Supervisor spec JSON to be submitted to the Overlord.
Make sure these keys are properly configured for successful ingestion.

Important supervisor properties
- `descriptor` for the descriptor file URL
- `protoMessageType` from the proto definition
- `parser` should have `type` set to `protobuf`, but note that the `format` of the `parseSpec` must be `json`

```json
{
  "type": "kafka",
  "dataSchema": {
    "dataSource": "metrics-protobuf",
    "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"
  }
}
```

## Adding Protobuf messages to Kafka

If necessary, from your Kafka installation directory run the following command to create the Kafka topic

```
./bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic metrics_pb
```

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
```

You can confirm that data has been inserted to your Kafka topic using the following command from your Kafka installation directory

```
./bin/kafka-console-consumer --zookeeper localhost --topic metrics_pb
```

which should print messages like this

```
millisecondsGETR"2017-04-06T03:23:56Z*2002/list:request/latencyBwww1.example.com
```

If your supervisor created in the previous step is running, the indexing tasks should begin producing the messages and the data will soon be available for querying in Druid.

## Generating the example files

The files provided in the example quickstart can be generated in the following manner starting with only `metrics.proto`.

### `metrics.desc`

The descriptor file is generated using `protoc` Protobuf compiler. Given a `.proto` file, a `.desc` file can be generated like so.

```
protoc -o metrics.desc metrics.proto
```

### `metrics_pb2.py`
`metrics_pb2.py` is also generated with `protoc`

```
 protoc -o metrics.desc metrics.proto --python_out=.
```

### `pb_publisher.py`
After `metrics_pb2.py` is generated, another script can be constructed to parse JSON data, convert it to Protobuf, and produce to a Kafka topic

```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'

for row in iter(sys.stdin):
    d = json.loads(row)
    metrics = Metrics()
    for k, v in d.items():
        setattr(metrics, k, v)
    pb = metrics.SerializeToString()
    producer.send(topic, pb)

producer.flush()
```