--- id: protobuf title: "Protobuf" --- 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. ## 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.md) 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.md) 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.md). - 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 ```