TheNeuralBit commented on a change in pull request #13112: URL: https://github.com/apache/beam/pull/13112#discussion_r530039085
########## File path: examples/templates/java/kafka-to-pubsub/src/main/java/org/apache/beam/templates/kafka/consumer/SslConsumerFactoryFn.java ########## @@ -0,0 +1,125 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.beam.templates.kafka.consumer; + +import java.io.File; +import java.io.IOException; +import java.nio.channels.FileChannel; +import java.nio.channels.ReadableByteChannel; +import java.nio.file.Paths; +import java.nio.file.StandardOpenOption; +import java.util.HashSet; +import java.util.Map; +import java.util.Set; +import org.apache.beam.sdk.io.FileSystems; +import org.apache.beam.sdk.transforms.SerializableFunction; +import org.apache.kafka.clients.CommonClientConfigs; +import org.apache.kafka.clients.consumer.Consumer; +import org.apache.kafka.clients.consumer.KafkaConsumer; +import org.apache.kafka.common.config.SslConfigs; +import org.apache.kafka.common.security.auth.SecurityProtocol; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +/** Class to create Kafka Consumer with configured SSL. */ +public class SslConsumerFactoryFn + implements SerializableFunction<Map<String, Object>, Consumer<byte[], byte[]>> { + private final Map<String, String> sslConfig; + private static final String TRUSTSTORE_LOCAL_PATH = "/tmp/kafka.truststore.jks"; + private static final String KEYSTORE_LOCAL_PATH = "/tmp/kafka.keystore.jks"; + + /* Logger for class.*/ + private static final Logger LOG = LoggerFactory.getLogger(SslConsumerFactoryFn.class); + + public SslConsumerFactoryFn(Map<String, String> sslConfig) { + this.sslConfig = sslConfig; + } + + @SuppressWarnings("nullness") + @Override + public Consumer<byte[], byte[]> apply(Map<String, Object> config) { + try { + String truststoreLocation = sslConfig.get(SslConfigs.SSL_TRUSTSTORE_LOCATION_CONFIG); + if (truststoreLocation.startsWith("gs://")) { + getGcsFileAsLocal(truststoreLocation, TRUSTSTORE_LOCAL_PATH); + } else { + checkFileExists(truststoreLocation); Review comment: Since your implementation for `getGcsFileAsLocal` relies on `FileSystems.matchSingleFileSpec` I think it will actually work for the else path here as well (It could also pull a truststore from AWS s3 if you include the dependency). It's worth noting that the local file option will fail at execution time for a distributed runner, we may want to catch that and raise a more helpful error - e.g. suggest that they stage the file on cloud storage ########## File path: examples/templates/java/kafka-to-pubsub/src/main/java/org/apache/beam/templates/KafkaToPubsub.java ########## @@ -0,0 +1,229 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.beam.templates; + +import static org.apache.beam.templates.kafka.consumer.Utils.configureKafka; +import static org.apache.beam.templates.kafka.consumer.Utils.configureSsl; +import static org.apache.beam.templates.kafka.consumer.Utils.getKafkaCredentialsFromVault; +import static org.apache.beam.templates.kafka.consumer.Utils.isSslSpecified; +import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.base.Preconditions.checkArgument; + +import java.util.ArrayList; +import java.util.Arrays; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import org.apache.beam.sdk.Pipeline; +import org.apache.beam.sdk.PipelineResult; +import org.apache.beam.sdk.io.gcp.pubsub.PubsubIO; +import org.apache.beam.sdk.options.PipelineOptionsFactory; +import org.apache.beam.sdk.transforms.Values; +import org.apache.beam.templates.avro.AvroDataClass; +import org.apache.beam.templates.avro.AvroDataClassKafkaAvroDeserializer; +import org.apache.beam.templates.options.KafkaToPubsubOptions; +import org.apache.beam.templates.transforms.FormatTransform; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +/** + * The {@link KafkaToPubsub} pipeline is a streaming pipeline which ingests data in JSON format from + * Kafka, and outputs the resulting records to PubSub. Input topics, output topic, Bootstrap servers + * are specified by the user as template parameters. <br> + * Kafka may be configured with SASL/SCRAM security mechanism, in this case a Vault secret storage + * with credentials should be provided. URL to credentials and Vault token are specified by the user + * as template parameters. + * + * <p><b>Pipeline Requirements</b> + * + * <ul> + * <li>Kafka Bootstrap Server(s). + * <li>Kafka Topic(s) exists. + * <li>The PubSub output topic exists. + * <li>(Optional) An existing HashiCorp Vault secret storage + * </ul> + * + * <p><b>Example Usage</b> + * + * <pre> + * # Set the pipeline vars + * PROJECT=id-of-my-project + * BUCKET_NAME=my-bucket + * + * # Set containerization vars + * IMAGE_NAME=my-image-name + * TARGET_GCR_IMAGE=gcr.io/${PROJECT}/${IMAGE_NAME} + * BASE_CONTAINER_IMAGE=my-base-container-image + * TEMPLATE_PATH="gs://${BUCKET_NAME}/templates/kafka-pubsub.json" + * + * # Create bucket in the cloud storage + * gsutil mb gs://${BUCKET_NAME} + * + * # Go to the beam folder + * cd /path/to/beam + * + * <b>FLEX TEMPLATE</b> + * # Assemble uber-jar + * ./gradlew -p templates/kafka-to-pubsub clean shadowJar + * + * # Go to the template folder + * cd /path/to/beam/templates/kafka-to-pubsub + * + * # Build the flex template + * gcloud dataflow flex-template build ${TEMPLATE_PATH} \ + * --image-gcr-path "${TARGET_GCR_IMAGE}" \ + * --sdk-language "JAVA" \ + * --flex-template-base-image ${BASE_CONTAINER_IMAGE} \ + * --metadata-file "src/main/resources/kafka_to_pubsub_metadata.json" \ + * --jar "build/libs/beam-templates-kafka-to-pubsub-<version>-all.jar" \ + * --env FLEX_TEMPLATE_JAVA_MAIN_CLASS="org.apache.beam.templates.KafkaToPubsub" + * + * # Execute template: + * API_ROOT_URL="https://dataflow.googleapis.com"; + * TEMPLATES_LAUNCH_API="${API_ROOT_URL}/v1b3/projects/${PROJECT}/locations/${REGION}/flexTemplates:launch" + * JOB_NAME="kafka-to-pubsub-`date +%Y%m%d-%H%M%S-%N`" + * + * time curl -X POST -H "Content-Type: application/json" \ + * -H "Authorization: Bearer $(gcloud auth print-access-token)" \ + * -d ' + * { + * "launch_parameter": { + * "jobName": "'$JOB_NAME'", + * "containerSpecGcsPath": "'$TEMPLATE_PATH'", + * "parameters": { + * "bootstrapServers": "broker_1:9091, broker_2:9092", + * "inputTopics": "topic1, topic2", + * "outputTopic": "projects/'$PROJECT'/topics/your-topic-name", + * "secretStoreUrl": "http(s)://host:port/path/to/credentials", + * "vaultToken": "your-token" + * } + * } + * } + * ' + * "${TEMPLATES_LAUNCH_API}" + * </pre> + * + * <p><b>Example Avro usage</b> + * + * <pre> + * This template contains an example Class to deserialize AVRO from Kafka and serialize it to AVRO in Pub/Sub. + * + * To use this example in the specific case, follow the few steps: + * <ul> + * <li> Create your own class to describe AVRO schema. As an example use {@link AvroDataClass}. Just define necessary fields. + * <li> Create your own Avro Deserializer class. As an example use {@link AvroDataClassKafkaAvroDeserializer}. Just rename it, and put your own Schema class as the necessary types. + * <li> Modify the {@link FormatTransform}. Put your Schema class and Deserializer to the related parameter. + * <li> Modify write step in the {@link KafkaToPubsub} by put your Schema class to "writeAvrosToPubSub" step. + * </ul> + * </pre> + */ +public class KafkaToPubsub { + + /* Logger for class.*/ + private static final Logger LOG = LoggerFactory.getLogger(KafkaToPubsub.class); + + /** + * Main entry point for pipeline execution. + * + * @param args Command line arguments to the pipeline. + */ + public static void main(String[] args) { + KafkaToPubsubOptions options = + PipelineOptionsFactory.fromArgs(args).withValidation().as(KafkaToPubsubOptions.class); + + run(options); + } + + /** + * Runs a pipeline which reads message from Kafka and writes it to GCS. + * + * @param options arguments to the pipeline + */ + public static PipelineResult run(KafkaToPubsubOptions options) { + // Configure Kafka consumer properties + Map<String, Object> kafkaConfig = new HashMap<>(); + if (options.getSecretStoreUrl() != null && options.getVaultToken() != null) { + Map<String, Map<String, String>> credentials = + getKafkaCredentialsFromVault(options.getSecretStoreUrl(), options.getVaultToken()); + kafkaConfig = configureKafka(credentials.get(KafkaPubsubConstants.KAFKA_CREDENTIALS)); + } else { + LOG.warn( + "No information to retrieve Kafka credentials was provided. " + + "Trying to initiate an unauthorized connection."); + } + + Map<String, String> sslConfig = new HashMap<>(); + if (isSslSpecified(options)) { + sslConfig.putAll(configureSsl(options)); + } else { + LOG.info( + "No information to retrieve SSL certificate was provided. " + + "Trying to initiate a plain text connection."); + } + + List<String> topicsList = new ArrayList<>(Arrays.asList(options.getInputTopics().split(","))); + + checkArgument( + topicsList.size() > 0 && topicsList.get(0).length() > 0, + "inputTopics cannot be an empty string."); + + List<String> bootstrapServersList = + new ArrayList<>(Arrays.asList(options.getBootstrapServers().split(","))); + + checkArgument( + bootstrapServersList.size() > 0 && topicsList.get(0).length() > 0, + "bootstrapServers cannot be an empty string."); + + // Create the pipeline + Pipeline pipeline = Pipeline.create(options); + LOG.info( + "Starting Kafka-To-PubSub pipeline with parameters bootstrap servers:" + + options.getBootstrapServers() + + " input topics: " + + options.getInputTopics() + + " output pubsub topic: " + + options.getOutputTopic()); + + /* + * Steps: + * 1) Read messages in from Kafka + * 2) Extract values only + * 3) Write successful records to PubSub + */ + + if (options.getOutputFormat() == FormatTransform.FORMAT.AVRO) { + pipeline + .apply( + "readAvrosFromKafka", + FormatTransform.readAvrosFromKafka( + options.getBootstrapServers(), topicsList, kafkaConfig, sslConfig)) + .apply("createValues", Values.create()) + .apply("writeAvrosToPubSub", PubsubIO.writeAvros(AvroDataClass.class)); + + } else if (options.getOutputFormat() == FormatTransform.FORMAT.AVRO) { Review comment: This will never be triggered its the same condition as the `if` ########## File path: examples/templates/java/README.md ########## @@ -0,0 +1,254 @@ +<!-- + Licensed to the Apache Software Foundation (ASF) under one + or more contributor license agreements. See the NOTICE file + distributed with this work for additional information + regarding copyright ownership. The ASF licenses this file + to you under the Apache License, Version 2.0 (the + "License"); you may not use this file except in compliance + with the License. You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, + software distributed under the License is distributed on an + "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + KIND, either express or implied. See the License for the + specific language governing permissions and limitations + under the License. +--> + +# Apache Beam Template to ingest data from Apache Kafka to Google Cloud Pub/Sub + +This directory contains an [Apache Beam](https://beam.apache.org/) Template that creates a pipeline +to read data from a single or multiple topics from +[Apache Kafka](https://kafka.apache.org/) and write data into a single topic +in [Google Cloud Pub/Sub](https://cloud.google.com/pubsub). + +Supported data formats: +- Serializable plaintext formats, such as JSON +- [PubSubMessage](https://cloud.google.com/pubsub/docs/reference/rest/v1/PubsubMessage). + +Supported input source configurations: +- Single or multiple Apache Kafka bootstrap servers +- Apache Kafka SASL/SCRAM authentication over plaintext or SSL connection +- Secrets vault service [HashiCorp Vault](https://www.vaultproject.io/). + +Supported destination configuration: +- Single Google Cloud Pub/Sub topic. + +In a simple scenario, the template will create an Apache Beam pipeline that will read messages from a source Kafka server with a source topic, and stream the text messages into specified Pub/Sub destination topic. Other scenarios may need Kafka SASL/SCRAM authentication, that can be performed over plain text or SSL encrypted connection. The template supports using a single Kafka user account to authenticate in the provided source Kafka servers and topics. To support SASL authenticaton over SSL the template will need an SSL certificate location and access to a secrets vault service with Kafka username and password, currently supporting HashiCorp Vault. + +## Requirements + +- Java 8 +- Kafka Bootstrap Server(s) up and running +- Existing source Kafka topic(s) +- An existing Pub/Sub destination output topic +- (Optional) An existing HashiCorp Vault +- (Optional) A configured secure SSL connection for Kafka + +## Getting Started + +This section describes what is needed to get the template up and running. +- Assembling the Uber-JAR +- Local execution +- Google Dataflow Template + - Set up the environment + - Creating the Dataflow Flex Template + - Create a Dataflow job to ingest data using the template. +- Avro format transferring. + +## Assembling the Uber-JAR + +To run this template the template Java project should be built into +an Uber JAR file. + +Navigate to the Beam folder: + +``` +cd /path/to/beam +``` + +In order to create Uber JAR with Gradle, [Shadow plugin](https://github.com/johnrengelman/shadow) +is used. It creates the `shadowJar` task that builds the Uber JAR: + +``` +./gradlew -p examples/templates/java/kafka-to-pubsub clean shadowJar +``` + +ℹ️ An **Uber JAR** - also known as **fat JAR** - is a single JAR file that contains +both target package *and* all its dependencies. + +The result of the `shadowJar` task execution is a `.jar` file that is generated +under the `build/libs/` folder in kafka-to-pubsub directory. + +## Local execution +To execute this pipeline locally, specify the parameters: +- Kafka Bootstrap servers +- Kafka input topics +- Pub/Sub output topic +in the following format: +```bash +--bootstrapServers=host:port \ +--inputTopics=your-input-topic \ +--outputTopic=projects/your-project-id/topics/your-topic-pame +``` +Optionally, to retrieve Kafka credentials for SASL/SCRAM, +specify a URL to the credentials in HashiCorp Vault and the vault access token: +```bash +--secretStoreUrl=http(s)://host:port/path/to/credentials +--vaultToken=your-token +``` +Optionally, to configure secure SSL connection between the Beam pipeline and Kafka, +specify the parameters: +- A path to a truststore file (it can be a local path or a GCS path, which should start with `gs://`) +- A path to a keystore file (it can be a local path or a GCS path, which should start with `gs://`) +- Truststore password +- Keystore password +- Key password +```bash +--truststorePath=path/to/kafka.truststore.jks +--keystorePath=path/to/kafka.keystore.jks +--truststorePassword=your-truststore-password +--keystorePassword=your-keystore-password +--keyPassword=your-key-password +``` +To change the runner, specify: +```bash +--runner=YOUR_SELECTED_RUNNER +``` +See examples/java/README.md for steps and examples to configure different runners. + +## Google Dataflow Template + +### Setting Up Project Environment + +#### Pipeline variables: + +``` +PROJECT=id-of-my-project +BUCKET_NAME=my-bucket +REGION=my-region +``` + +#### Template Metadata Storage Bucket Creation + +The Dataflow Flex template has to store its metadata in a bucket in Review comment: I'm not sure it makes sense to discuss Dataflow Flex templates here, we should leave that to https://github.com/GoogleCloudPlatform/DataflowTemplates/pull/176 I think this README should instead discuss how to run _directly_ on Dataflow and/or how to run on some other Beam runners ########## File path: examples/templates/java/README.md ########## @@ -0,0 +1,252 @@ +<!-- + Licensed to the Apache Software Foundation (ASF) under one + or more contributor license agreements. See the NOTICE file + distributed with this work for additional information + regarding copyright ownership. The ASF licenses this file + to you under the Apache License, Version 2.0 (the + "License"); you may not use this file except in compliance + with the License. You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, + software distributed under the License is distributed on an + "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + KIND, either express or implied. See the License for the + specific language governing permissions and limitations + under the License. +--> + +# Apache Beam Template to ingest data from Apache Kafka to Google Cloud Pub/Sub + +This directory contains an [Apache Beam](https://beam.apache.org/) Template that creates a pipeline +to read data from a single or multiple topics from +[Apache Kafka](https://kafka.apache.org/) and write data into a single topic +in [Google Pub/Sub](https://cloud.google.com/pubsub). + +Supported data formats: +- Serializable plaintext formats, such as JSON +- [PubSubMessage](https://cloud.google.com/pubsub/docs/reference/rest/v1/PubsubMessage). + +Supported input source configurations: +- Single or multiple Apache Kafka bootstrap servers +- Apache Kafka SASL/SCRAM authentication over plaintext or SSL connection +- Secrets vault service [HashiCorp Vault](https://www.vaultproject.io/). + +Supported destination configuration: +- Single Google Pub/Sub topic. + +In a simple scenario, the template will create an Apache Beam pipeline that will read messages from a source Kafka server with a source topic, and stream the text messages into specified Pub/Sub destination topic. Other scenarios may need Kafka SASL/SCRAM authentication, that can be performed over plain text or SSL encrypted connection. The template supports using a single Kafka user account to authenticate in the provided source Kafka servers and topics. To support SASL authenticaton over SSL the template will need an SSL certificate location and access to a secrets vault service with Kafka username and password, currently supporting HashiCorp Vault. + +## Requirements + +- Java 11 +- Kafka Bootstrap Server(s) up and running +- Existing source Kafka topic(s) +- An existing Pub/Sub destination output topic +- (Optional) An existing HashiCorp Vault +- (Optional) A configured secure SSL connection for Kafka + +## Getting Started + +This section describes what is needed to get the template up and running. +- Assembling the Uber-JAR +- Local execution +- Google Dataflow Template + - Set up the environment + - Creating the Dataflow Flex Template + - Create a Dataflow job to ingest data using the template. +- Avro format transferring. + +## Assembling the Uber-JAR + +To run this template the template Java project should be built into +an Uber JAR file. + +Navigate to the Beam folder: + +``` +cd /path/to/beam +``` + +In order to create Uber JAR with Gradle, [Shadow plugin](https://github.com/johnrengelman/shadow) +is used. It creates the `shadowJar` task that builds the Uber JAR: + +``` +./gradlew -p examples/templates/java/kafka-to-pubsub clean shadowJar +``` + +ℹ️ An **Uber JAR** - also known as **fat JAR** - is a single JAR file that contains +both target package *and* all its dependencies. + +The result of the `shadowJar` task execution is a `.jar` file that is generated +under the `build/libs/` folder in kafka-to-pubsub directory. + +## Local execution +To execute this pipeline locally, specify the parameters: +- Kafka Bootstrap servers +- Kafka input topics +- Pub/Sub output topic +in the following format: +```bash +--bootstrapServers=host:port \ +--inputTopics=your-input-topic \ +--outputTopic=projects/your-project-id/topics/your-topic-pame +``` +Optionally, to retrieve Kafka credentials for SASL/SCRAM, +specify a URL to the credentials in HashiCorp Vault and the vault access token: +```bash +--secretStoreUrl=http(s)://host:port/path/to/credentials +--vaultToken=your-token +``` +Optionally, to configure secure SSL connection between the Beam pipeline and Kafka, +specify the parameters: +- A local path to a truststore file +- A local path to a keystore file +- Truststore password +- Keystore password +- Key password +```bash +--truststorePath=path/to/kafka.truststore.jks +--keystorePath=path/to/kafka.keystore.jks +--truststorePassword=your-truststore-password +--keystorePassword=your-keystore-password +--keyPassword=your-key-password +``` +To change the runner, specify: +```bash +--runner=YOUR_SELECTED_RUNNER +``` +See examples/java/README.md for steps and examples to configure different runners. + +## Google Dataflow Template + +### Setting Up Project Environment + +#### Pipeline variables: + +``` +PROJECT=id-of-my-project +BUCKET_NAME=my-bucket +REGION=my-region +``` + +#### Template Metadata Storage Bucket Creation + +The Dataflow Flex template has to store its metadata in a bucket in +[Google Cloud Storage](https://cloud.google.com/storage), so it can be executed from the Google Cloud Platform. +Create the bucket in Google Cloud Storage if it doesn't exist yet: + +``` +gsutil mb gs://${BUCKET_NAME} +``` + +#### Containerization variables: + +``` +IMAGE_NAME=my-image-name +TARGET_GCR_IMAGE=gcr.io/${PROJECT}/${IMAGE_NAME} +BASE_CONTAINER_IMAGE=my-base-container-image +TEMPLATE_PATH="gs://${BUCKET_NAME}/templates/kafka-pubsub.json" +``` + +### Creating the Dataflow Flex Template + +Dataflow Flex Templates package the pipeline as a Docker image and stage these images +on your project's [Container Registry](https://cloud.google.com/container-registry). + +To execute the template you need to create the template spec file containing all +the necessary information to run the job. This template already has the following +[metadata file](kafka-to-pubsub/src/main/resources/kafka_to_pubsub_metadata.json) in resources. + +Navigate to the template folder: + +``` +cd /path/to/beam/examples/templates/java/kafka-to-pubsub +``` + +Build the Dataflow Flex Template: + +``` +gcloud dataflow flex-template build ${TEMPLATE_PATH} \ + --image-gcr-path ${TARGET_GCR_IMAGE} \ + --sdk-language "JAVA" \ + --flex-template-base-image ${BASE_CONTAINER_IMAGE} \ + --metadata-file "src/main/resources/kafka_to_pubsub_metadata.json" \ + --jar "build/libs/beam-examples-templates-java-kafka-to-pubsub-2.25.0-SNAPSHOT-all.jar" \ + --env FLEX_TEMPLATE_JAVA_MAIN_CLASS="org.apache.beam.templates.KafkaToPubsub" +``` + +### Create Dataflow Job Using the Apache Kafka to Google Pub/Sub Dataflow Flex Template + +To deploy the pipeline, you should refer to the template file and pass the +[parameters](https://cloud.google.com/dataflow/docs/guides/specifying-exec-params#setting-other-cloud-dataflow-pipeline-options) +required by the pipeline. + +You can do this in 3 different ways: +1. Using [Dataflow Google Cloud Console](https://console.cloud.google.com/dataflow/jobs) + +2. Using `gcloud` CLI tool + ``` + gcloud dataflow flex-template run "kafka-to-pubsub-`date +%Y%m%d-%H%M%S`" \ + --template-file-gcs-location "${TEMPLATE_PATH}" \ + --parameters bootstrapServers="broker_1:9092,broker_2:9092" \ + --parameters inputTopics="topic1,topic2" \ + --parameters outputTopic="projects/${PROJECT}/topics/your-topic-name" \ + --parameters outputFormat="PLAINTEXT" \ + --parameters secretStoreUrl="http(s)://host:port/path/to/credentials" \ + --parameters vaultToken="your-token" \ + --region "${REGION}" + ``` +3. With a REST API request + ``` + API_ROOT_URL="https://dataflow.googleapis.com"; + TEMPLATES_LAUNCH_API="${API_ROOT_URL}/v1b3/projects/${PROJECT}/locations/${REGION}/flexTemplates:launch" + JOB_NAME="kafka-to-pubsub-`date +%Y%m%d-%H%M%S-%N`" + + time curl -X POST -H "Content-Type: application/json" \ + -H "Authorization: Bearer $(gcloud auth print-access-token)" \ + -d ' + { + "launch_parameter": { + "jobName": "'$JOB_NAME'", + "containerSpecGcsPath": "'$TEMPLATE_PATH'", + "parameters": { + "bootstrapServers": "broker_1:9091, broker_2:9092", + "inputTopics": "topic1, topic2", + "outputTopic": "projects/'$PROJECT'/topics/your-topic-name", + "outputFormat": "PLAINTEXT", + "secretStoreUrl": "http(s)://host:port/path/to/credentials", + "vaultToken": "your-token" + } + } + } + ' + "${TEMPLATES_LAUNCH_API}" + ``` + +## AVRO format transferring. +This template contains an example Class to deserialize AVRO from Kafka and serialize it to AVRO in Pub/Sub. Review comment: But even with the updated language, the user would just deserialize the byte array to an instance `MyAvroClass` and then reserialize it back to the same byte array to send to PubSub. If we want to show an example of deserializing and serializing, it should at least do some processing, or convert the message to another format. Otherwise I feel this could just confuse users. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected]
