Examples with DistributedHerder org.apache.kafka.connect.runtime.distributed.DistributedHerder used on opensource projects

Example 1 with DistributedHerder

use of org.apache.kafka.connect.runtime.distributed.DistributedHerder in project apache-kafka-on-k8s by banzaicloud.

the class ConnectDistributed method main.

public static void main(String[] args) throws Exception {
    if (args.length < 1) {
        log.info("Usage: ConnectDistributed worker.properties");
        Exit.exit(1);
    }
    try {
        Time time = Time.SYSTEM;
        log.info("Kafka Connect distributed worker initializing ...");
        long initStart = time.hiResClockMs();
        WorkerInfo initInfo = new WorkerInfo();
        initInfo.logAll();
        String workerPropsFile = args[0];
        Map<String, String> workerProps = !workerPropsFile.isEmpty() ? Utils.propsToStringMap(Utils.loadProps(workerPropsFile)) : Collections.<String, String>emptyMap();
        log.info("Scanning for plugin classes. This might take a moment ...");
        Plugins plugins = new Plugins(workerProps);
        plugins.compareAndSwapWithDelegatingLoader();
        DistributedConfig config = new DistributedConfig(workerProps);
        String kafkaClusterId = ConnectUtils.lookupKafkaClusterId(config);
        log.debug("Kafka cluster ID: {}", kafkaClusterId);
        RestServer rest = new RestServer(config);
        URI advertisedUrl = rest.advertisedUrl();
        String workerId = advertisedUrl.getHost() + ":" + advertisedUrl.getPort();
        KafkaOffsetBackingStore offsetBackingStore = new KafkaOffsetBackingStore();
        offsetBackingStore.configure(config);
        Worker worker = new Worker(workerId, time, plugins, config, offsetBackingStore);
        Converter internalValueConverter = worker.getInternalValueConverter();
        StatusBackingStore statusBackingStore = new KafkaStatusBackingStore(time, internalValueConverter);
        statusBackingStore.configure(config);
        ConfigBackingStore configBackingStore = new KafkaConfigBackingStore(internalValueConverter, config);
        DistributedHerder herder = new DistributedHerder(config, time, worker, kafkaClusterId, statusBackingStore, configBackingStore, advertisedUrl.toString());
        final Connect connect = new Connect(herder, rest);
        log.info("Kafka Connect distributed worker initialization took {}ms", time.hiResClockMs() - initStart);
        try {
            connect.start();
        } catch (Exception e) {
            log.error("Failed to start Connect", e);
            connect.stop();
            Exit.exit(3);
        }
        // Shutdown will be triggered by Ctrl-C or via HTTP shutdown request
        connect.awaitStop();
    } catch (Throwable t) {
        log.error("Stopping due to error", t);
        Exit.exit(2);
    }
}

Example 2 with DistributedHerder

use of org.apache.kafka.connect.runtime.distributed.DistributedHerder in project kafka by apache.

the class MirrorMaker method addHerder.

private void addHerder(SourceAndTarget sourceAndTarget) {
    log.info("creating herder for " + sourceAndTarget.toString());
    Map<String, String> workerProps = config.workerConfig(sourceAndTarget);
    String advertisedUrl = advertisedBaseUrl + "/" + sourceAndTarget.source();
    String workerId = sourceAndTarget.toString();
    Plugins plugins = new Plugins(workerProps);
    plugins.compareAndSwapWithDelegatingLoader();
    DistributedConfig distributedConfig = new DistributedConfig(workerProps);
    String kafkaClusterId = ConnectUtils.lookupKafkaClusterId(distributedConfig);
    // Create the admin client to be shared by all backing stores for this herder
    Map<String, Object> adminProps = new HashMap<>(distributedConfig.originals());
    ConnectUtils.addMetricsContextProperties(adminProps, distributedConfig, kafkaClusterId);
    SharedTopicAdmin sharedAdmin = new SharedTopicAdmin(adminProps);
    KafkaOffsetBackingStore offsetBackingStore = new KafkaOffsetBackingStore(sharedAdmin);
    offsetBackingStore.configure(distributedConfig);
    Worker worker = new Worker(workerId, time, plugins, distributedConfig, offsetBackingStore, CLIENT_CONFIG_OVERRIDE_POLICY);
    WorkerConfigTransformer configTransformer = worker.configTransformer();
    Converter internalValueConverter = worker.getInternalValueConverter();
    StatusBackingStore statusBackingStore = new KafkaStatusBackingStore(time, internalValueConverter, sharedAdmin);
    statusBackingStore.configure(distributedConfig);
    ConfigBackingStore configBackingStore = new KafkaConfigBackingStore(internalValueConverter, distributedConfig, configTransformer, sharedAdmin);
    // Pass the shared admin to the distributed herder as an additional AutoCloseable object that should be closed when the
    // herder is stopped. MirrorMaker has multiple herders, and having the herder own the close responsibility is much easier than
    // tracking the various shared admin objects in this class.
    Herder herder = new DistributedHerder(distributedConfig, time, worker, kafkaClusterId, statusBackingStore, configBackingStore, advertisedUrl, CLIENT_CONFIG_OVERRIDE_POLICY, sharedAdmin);
    herders.put(sourceAndTarget, herder);
}

Example 3 with DistributedHerder

use of org.apache.kafka.connect.runtime.distributed.DistributedHerder in project kafka by apache.

the class ConnectDistributed method startConnect.

public Connect startConnect(Map<String, String> workerProps) {
    log.info("Scanning for plugin classes. This might take a moment ...");
    Plugins plugins = new Plugins(workerProps);
    plugins.compareAndSwapWithDelegatingLoader();
    DistributedConfig config = new DistributedConfig(workerProps);
    String kafkaClusterId = ConnectUtils.lookupKafkaClusterId(config);
    log.debug("Kafka cluster ID: {}", kafkaClusterId);
    RestServer rest = new RestServer(config);
    rest.initializeServer();
    URI advertisedUrl = rest.advertisedUrl();
    String workerId = advertisedUrl.getHost() + ":" + advertisedUrl.getPort();
    // Create the admin client to be shared by all backing stores.
    Map<String, Object> adminProps = new HashMap<>(config.originals());
    ConnectUtils.addMetricsContextProperties(adminProps, config, kafkaClusterId);
    SharedTopicAdmin sharedAdmin = new SharedTopicAdmin(adminProps);
    KafkaOffsetBackingStore offsetBackingStore = new KafkaOffsetBackingStore(sharedAdmin);
    offsetBackingStore.configure(config);
    ConnectorClientConfigOverridePolicy connectorClientConfigOverridePolicy = plugins.newPlugin(config.getString(WorkerConfig.CONNECTOR_CLIENT_POLICY_CLASS_CONFIG), config, ConnectorClientConfigOverridePolicy.class);
    Worker worker = new Worker(workerId, time, plugins, config, offsetBackingStore, connectorClientConfigOverridePolicy);
    WorkerConfigTransformer configTransformer = worker.configTransformer();
    Converter internalValueConverter = worker.getInternalValueConverter();
    StatusBackingStore statusBackingStore = new KafkaStatusBackingStore(time, internalValueConverter, sharedAdmin);
    statusBackingStore.configure(config);
    ConfigBackingStore configBackingStore = new KafkaConfigBackingStore(internalValueConverter, config, configTransformer, sharedAdmin);
    // Pass the shared admin to the distributed herder as an additional AutoCloseable object that should be closed when the
    // herder is stopped. This is easier than having to track and own the lifecycle ourselves.
    DistributedHerder herder = new DistributedHerder(config, time, worker, kafkaClusterId, statusBackingStore, configBackingStore, advertisedUrl.toString(), connectorClientConfigOverridePolicy, sharedAdmin);
    final Connect connect = new Connect(herder, rest);
    log.info("Kafka Connect distributed worker initialization took {}ms", time.hiResClockMs() - initStart);
    try {
        connect.start();
    } catch (Exception e) {
        log.error("Failed to start Connect", e);
        connect.stop();
        Exit.exit(3);
    }
    return connect;
}