google bigquery sink Google Big Query Sink

Provided by: "Apache Software Foundation"

Support Level for this Kamelet is: "Stable"

Send data to a Google Big Query table.

The data must be JSON format to represent an object or an array of objects.

Configuration Options

The following table summarizes the configuration options available for the google-bigquery-sink Kamelet:

Property Name Description Type Default Example

dataset

Big Query Dataset Id

Required The Big Query Dataset ID.

string

projectId

Google Cloud Project Id

Required The Google Cloud Project ID.

string

serviceAccountKey

Service Account Key

Required The service account key to use as credentials for the BigQuery Service. You must encode this value in base64.

binary

table

Big Query Table Id

Required The Big Query Table ID.

string

Dependencies

At runtime, the google-bigquery-sink Kamelet relies upon the presence of the following dependencies:

  • camel:core

  • camel:kamelet

  • camel:google-bigquery

  • camel:jackson

Camel JBang usage

Prerequisites

  • You’ve installed JBang.

  • You have executed the following command:

jbang app install camel@apache/camel

Supposing you have a file named route.yaml with this content:

- route:
    from:
      uri: "kamelet:timer-source"
      parameters:
        period: 10000
        message: 'test'
      steps:
        - to:
            uri: "kamelet:log-sink"

You can now run it directly through the following command

camel run route.yaml

Camel K Environment Usage

This section describes how you can use the google-bigquery-sink.

Knative sink

You can use the google-bigquery-sink Kamelet as a Knative sink by binding it to a Knative object.

google-bigquery-sink-binding.yaml
apiVersion: camel.apache.org/v1
kind: KameletBinding
metadata:
  name: google-bigquery-sink-binding
spec:
  source:
    ref:
      kind: Channel
      apiVersion: messaging.knative.dev/v1
      name: mychannel
  sink:
    ref:
      kind: Kamelet
      apiVersion: camel.apache.org/v1
      name: google-bigquery-sink
    properties:
      dataset: The Big Query Dataset Id
      projectId: The Google Cloud Project Id
      serviceAccountKey: The Service Account Key
      table: The Big Query Table Id

Prerequisite

You have Camel K installed on the cluster.

Procedure for using the cluster CLI

  1. Save the google-bigquery-sink-binding.yaml file to your local drive, and then edit it as needed for your configuration.

  2. Run the sink by using the following command:

    kubectl apply -f google-bigquery-sink-binding.yaml

Procedure for using the Kamel CLI

Configure and run the sink by using the following command:

kamel bind channel:mychannel -p "sink.dataset=The Big Query Dataset Id" -p "sink.projectId=The Google Cloud Project Id" -p "sink.serviceAccountKey=The Service Account Key" -p "sink.table=The Big Query Table Id" google-bigquery-sink

This command creates the KameletBinding in the current namespace on the cluster.

Kafka sink

You can use the google-bigquery-sink Kamelet as a Kafka sink by binding it to a Kafka topic.

google-bigquery-sink-binding.yaml
apiVersion: camel.apache.org/v1
kind: KameletBinding
metadata:
  name: google-bigquery-sink-binding
spec:
  source:
    ref:
      kind: KafkaTopic
      apiVersion: kafka.strimzi.io/v1beta1
      name: my-topic
  sink:
    ref:
      kind: Kamelet
      apiVersion: camel.apache.org/v1
      name: google-bigquery-sink
    properties:
      dataset: The Big Query Dataset Id
      projectId: The Google Cloud Project Id
      serviceAccountKey: The Service Account Key
      table: The Big Query Table Id

Prerequisites

  • You’ve installed Strimzi.

  • You’ve created a topic named my-topic in the current namespace.

  • You have Camel K installed on the cluster.

Procedure for using the cluster CLI

  1. Save the google-bigquery-sink-binding.yaml file to your local drive, and then edit it as needed for your configuration.

  2. Run the sink by using the following command:

    kubectl apply -f google-bigquery-sink-binding.yaml

Procedure for using the Kamel CLI

Configure and run the sink by using the following command:

kamel bind kafka.strimzi.io/v1beta1:KafkaTopic:my-topic -p "sink.dataset=The Big Query Dataset Id" -p "sink.projectId=The Google Cloud Project Id" -p "sink.serviceAccountKey=The Service Account Key" -p "sink.table=The Big Query Table Id" google-bigquery-sink

This command creates the KameletBinding in the current namespace on the cluster.