$ git clone git:\/\/github.com\/couchbase\/couchbase-kafka-connector.git \/tmp\/kafka-connector<\/code><\/pre>\nAhora, vamos a configurar tu entorno de pruebas usando im\u00e1genes pre-configuradas de Kafka y Couchbase Server. Tienes que instalar Vagrant, VirtualBox y Ansible para configurarlos localmente. Si tienes estos servicios instalados en otro lugar, aseg\u00farate de ajustar las direcciones de host a lo largo de esta gu\u00eda apropiadamente.<\/p>\n
$ cd \/tmp\/kafka-connector\/env<\/code><\/pre>\nCompruebe las versiones de las dependencias:<\/p>\n
$ ansible --version\r\n$ vboxmanage --version\r\n$ vagrant -v<\/code><\/pre>\nPuede asignar nombres legibles por humanos a las cajas utilizando el plugin para Vagrant. Si a\u00fan no lo tienes instalado, utiliza el siguiente comando:<\/p>\n
$ vagrant plugin install vagrant-hostsupdater<\/code><\/pre>\nAhora ya puedes aprovisionar los servidores y ponerte en marcha:<\/p>\n
$ vagrant up<\/code><\/pre>\nNota: Si un servidor no se instala debido a los tiempos de espera, vuelva a intentar \"vagrant up\" despu\u00e9s de unos minutos y puede que funcione.<\/p>\n
Compruebe que los hosts responden:<\/p>\n
$ ping couchbase1.vagrant\r\n$ ping kafka1.vagrant<\/code><\/pre>\nSi navegas a deber\u00edas poder ver tu Couchbase Server de nodo \u00fanico configurado con credenciales\u00a0Administrador<\/code>\/contrase\u00f1a<\/code>.<\/p>\nConstrucci\u00f3n de las muestras<\/h2>\n
Para evitar cualquier problema de classpath, utilice maven para crear un archivo JAR aut\u00f3nomo para cada aplicaci\u00f3n de ejemplo.<\/p>\n
La aplicaci\u00f3n generadora es una aplicaci\u00f3n CLI m\u00ednima. Utiliza el SDK Java de Couchbase para envolver l\u00edneas de entrada desde STDIN en documentos JSON y los env\u00eda al bucket \"por defecto\" en Couchbase Server:<\/p>\n
$ cd \/tmp\/kafka-connector\/samples\/generator\r\n$ mvn assembly:assembly<\/code><\/pre>\nEl productor se conecta a Couchbase Server y transmite todas las mutaciones a Kafka. Esta aplicaci\u00f3n utiliza el proyecto couchbase-kafka-connector entre bastidores.<\/p>\n
$ cd \/tmp\/kafka-connector\/samples\/producer\r\n$ mvn assembly:assembly<\/code><\/pre>\nEl consumidor es un consumidor t\u00edpico de Kafka, que por defecto env\u00eda cualquier mensaje entrante en el tema \"default\" a STDOUT.<\/p>\n
$ cd \/tmp\/kafka-connector\/samples\/consumer\r\n$ mvn assembly:assembly\r\n<\/code><\/pre>\nEjecuci\u00f3n de las muestras<\/h2>\n
Ahora que lo tienes todo preparado, es el momento de ejecutar todas las muestras. Necesitar\u00e1s tres sesiones shell diferentes porque cada una de ellas ejecuta un proceso hasta que se detiene. Asumiremos que est\u00e1s en la sesi\u00f3n \u00a0<\/span>\/tmp\/conector-kafka\/muestras<\/code>\u00a0<\/span>directorio.<\/p>\nEn primer lugar, pon en marcha el generador:<\/p>\n
$ java -jar generator\/target\/kafka-samples-generator-1.0-SNAPSHOT-jar-with-dependencies.jar\r\n<\/code><\/pre>\nDeber\u00eda mostrar la configuraci\u00f3n de la conexi\u00f3n y, a continuaci\u00f3n, pasar al s\u00edmbolo del sistema\u00a0<\/span>><\/code>. Puede escribir cualquier cosa all\u00ed y verificar que se est\u00e1 creando correctamente mirando en la interfaz de usuario de administraci\u00f3n del servidor Couchbase:<\/p>\n![\"\"](\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2016\/01\/Couchbase-and-kafka.png\")
<\/p>\n
Documentos del generador en el cubo<\/p>\n
...\r\nINFO: Opened bucket default\r\n> hello, kafka demo!\r\n>> key=key-5, value={\"line\":\"hello, kafka demo!\"}\r\n<\/code><\/pre>\nEn este momento puedes ejecutar el ejemplo de conector<\/p>\n
$ java -jar producer\/target\/kafka-samples-producer-1.0-SNAPSHOT-jar-with-dependencies.jar<\/code><\/pre>\nPor cada l\u00ednea que escriba en el generador, ver\u00e1 una l\u00ednea del productor como \u00e9sta:<\/p>\n
RECEIVED: com.couchbase.kafka.DCPEvent@4e44cb88<\/code><\/pre>\nLa muestra lo escribe justo antes de enviar la carga \u00fatil a Kafka, en la implementaci\u00f3n de la clase filtro. Comprobemos c\u00f3mo recibe Kafka estos mensajes.<\/p>\n
$ java -jar consumer\/target\/kafka-samples-consumer-1.0-SNAPSHOT-jar-with-dependencies.jar\r\n1: {\"line\":\"hello, kafka demo!\"}\r\n2: {\"line\":\"hello, this is a test\"}<\/code><\/pre>\nPuedes seguir jugando con \u00e9l mientras los tres servicios est\u00e9n en marcha.<\/p>\n
Desarrollando con Couchbase Kafka Connector<\/h2>\n
Sigamos adelante y echemos un vistazo al c\u00f3digo. Las tres aplicaciones son bastante amigables para los experimentos, por ejemplo, el generador cabe en unas pocas l\u00edneas:<\/p>\n
public class Example {\r\n public static void main(String args[]) throws IOException {\r\n Random random = new Random();\r\n Cluster cluster = CouchbaseCluster.create(\"couchbase1.vagrant\");\r\n Bucket bucket = cluster.openBucket();\r\n BufferedReader input = new BufferedReader(new InputStreamReader(System.in));\r\n String line;\r\n do {\r\n System.out.print(\"> \");\r\n line = input.readLine();\r\n if (line == null) {\r\n break;\r\n }\r\n String key = \"key-\" + random.nextInt(10);\r\n JsonObject value = JsonObject.create().put(\"line\", line);\r\n bucket.upsert(JsonDocument.create(key, value));\r\n System.out.printf(\">> key=%s, value=%sn\", key, value);\r\n } while (true);\r\n }\r\n}<\/code><\/pre>\nB\u00e1sicamente, el generador abre una conexi\u00f3n al bucket \"default\" en tu instancia \"couchbase1.vagrant\" y escribe tus mensajes en claves aleatorias. Puedes extenderlo para enviar otros tipos de eventos. Otra cosa que puedes intentar es eliminar claves.<\/p>\n
Por defecto, Couchbase Connector para Kafka se ejecuta en modo servidor, donde toma prestado el hilo activo y escucha activamente a Couchbase Server en busca de nuevos eventos. Hay varios puntos donde puedes aplicar tus ideas o cambios. El m\u00e1s obvio es el constructor de configuraci\u00f3n, donde no s\u00f3lo especificas las credenciales y direcciones de los servicios a los que te conectas, sino que tambi\u00e9n puedes especificar varias clases de serializadores y filtros.<\/p>\n
La aplicaci\u00f3n de ejemplo implementa varias de ellas. La clase Filter es la m\u00e1s sencilla:<\/p>\n
\r\npublic class SampleFilter implements Filter {\r\n\u00a0 \u00a0 @Override\r\n\u00a0 \u00a0 public boolean pass(DCPEvent dcpEvent) {\r\n\u00a0 \u00a0 \u00a0 \u00a0 System.out.println(\"RECEIVED: \" + dcpEvent);\r\n\u00a0 \u00a0 \u00a0 \u00a0 return true;\r\n\u00a0 \u00a0 }\r\n}\r\n<\/code><\/pre>\nAqu\u00ed puedes poner las comprobaciones personalizadas que quieras, y si\u00a0<\/span>pasar()<\/code>\u00a0<\/span>devuelve \u00a0<\/span>falso<\/code>el conector descarta el mensaje y no lo env\u00eda a Kafka.<\/p>\nDefault Encoder, que viene con la distribuci\u00f3n del conector, intenta representar cada mensaje como JSON, pero eso probablemente no es lo que necesitas, as\u00ed que puedes aplicar y conversi\u00f3n a\u00a0<\/span>Evento DCPEvent<\/code>\u00a0<\/span>y devuelve una matriz de bytes que se almacenar\u00e1 en Kafka. En este ejemplo, solo convertimos los eventos a su representaci\u00f3n de cadena.<\/p>\n\r\npublic class SampleEncoder extends AbstractEncoder {\r\n\u00a0 \u00a0 public SampleEncoder(final VerifiableProperties properties) {\r\n\u00a0 \u00a0 \u00a0 \u00a0 super(properties);\r\n\u00a0 \u00a0 }\r\n\r\n\r\n\u00a0 \u00a0 @Override\r\n\u00a0 \u00a0 public byte[] toBytes(final DCPEvent dcpEvent) {\r\n\u00a0 \u00a0 \u00a0 \u00a0 if (dcpEvent.message() instanceof MutationMessage) {\r\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 MutationMessage message = (MutationMessage) dcpEvent.message();\r\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 return message.content().toString(CharsetUtil.UTF_8).getBytes();\r\n\u00a0 \u00a0 \u00a0 \u00a0 } else {\r\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 return dcpEvent.message().toString().getBytes();\r\n\u00a0 \u00a0 \u00a0 \u00a0 }\r\n\u00a0 \u00a0 }\r\n}\r\n<\/code><\/pre>\nUn ajuste m\u00e1s avanzado es\u00a0<\/span>SerializadorEstado<\/code>\u00a0<\/span>de Couchbase. Implement\u00e1ndolo, puedes controlar c\u00f3mo la librer\u00eda rastrear\u00e1 los cursores de flujo (es decir, los n\u00fameros de secuencia para cada partici\u00f3n dentro de Couchbase Server), y si se reanudar\u00e1 despu\u00e9s de reiniciar el conector. Hay una implementaci\u00f3n Zookeeper del serializador de estado en la distribuci\u00f3n. Aqu\u00ed en el ejemplo, hemos implementado NullStateSerializer<\/code>\u00a0<\/span>que no persiste nada, pero muestra una implementaci\u00f3n m\u00ednima.<\/p>\n\r\npublic class NullStateSerializer implements StateSerializer {\r\n\u00a0 \u00a0 public NullStateSerializer(final CouchbaseKafkaEnvironment environment) {\r\n\u00a0 \u00a0 }\r\n\r\n\u00a0 \u00a0 @Override\r\n\u00a0 \u00a0 public void dump(BucketStreamAggregatorState aggregatorState) {\r\n\u00a0 \u00a0 }\r\n\r\n\u00a0 \u00a0 @Override\r\n\u00a0 \u00a0 public void dump(BucketStreamAggregatorState aggregatorState, short partition) {\r\n\u00a0 \u00a0 }\r\n\r\n\u00a0 \u00a0 @Override\r\n\u00a0 \u00a0 public BucketStreamAggregatorState load(BucketStreamAggregatorState aggregatorState) {\r\n\u00a0 \u00a0 \u00a0 \u00a0 return new BucketStreamAggregatorState(aggregatorState.name());\r\n\u00a0 \u00a0 }\r\n\r\n\u00a0 \u00a0 @Override\r\n\u00a0 \u00a0 public BucketStreamState load(BucketStreamAggregatorState aggregatorState, short partition) {\r\n\u00a0 \u00a0 \u00a0 \u00a0 return new BucketStreamState(partition, 0, 0, 0xffffffff, 0, 0xffffffff);\r\n\u00a0 \u00a0 }\r\n}\r\n<\/code><\/pre>\nEl \u00faltimo componente de su cl\u00faster de demostraci\u00f3n es el consumidor Kafka\u00a0<\/span>ConsumidorAbstracto<\/code>que es un ejemplo bastante t\u00edpico de consumidor. Consta de dos partes: , que implementa el arranque y el posicionamiento en el tema Kafka, y ImprimirConsumidor<\/span>que lleva su \"l\u00f3gica de negocio\", o simplemente emite cada mensaje que se le pasa por ConsumidorAbstracto<\/span>:<\/p>\n\r\npublic class PrintConsumer extends AbstractConsumer {\r\n\u00a0 \u00a0 public PrintConsumer(String[] seedBrokers, int port) {\r\n\u00a0 \u00a0 \u00a0 \u00a0 super(seedBrokers, port);\r\n\u00a0 \u00a0 }\r\n\r\n\r\n\u00a0 \u00a0 public PrintConsumer(String seedBroker, int port) {\r\n\u00a0 \u00a0 \u00a0 \u00a0 super(seedBroker, port);\r\n\u00a0 \u00a0 }\r\n\r\n\r\n\u00a0 \u00a0 @Override\r\n\u00a0 \u00a0 public void handleMessage(long offset, byte[] bytes) {\r\n\u00a0 \u00a0 \u00a0 \u00a0 System.out.println(String.valueOf(offset) + \": \" + new String(bytes));\r\n\u00a0 \u00a0 }\r\n}\r\n<\/code><\/pre>\nComo en los otros ejemplos aqu\u00ed, puedes jugar modificando el consumidor de ejemplo. Incluso puedes cerrar el circuito enviando todo de vuelta a Couchbase Server. Kafka es software distribuido, al igual que Couchbase Server, as\u00ed que tenlo en cuenta cuando ejecutes en tu propio cluster y ajusta la funci\u00f3n main() en consecuencia. En nuestro ejemplo, s\u00f3lo tenemos una \u00fanica partici\u00f3n, partition (0<\/span>) en Kafka, por lo que nuestro principal tiene este aspecto:<\/p>\npublic class Example {\r\n public static void main(String args[]) {\r\n PrintConsumer example = new PrintConsumer(\"kafka1.vagrant\", 9092);\r\n example.run(\"default\", 0);\r\n }\r\n}<\/code><\/pre>\nPor supuesto, en un cl\u00faster de producci\u00f3n se ejecutar\u00e1 m\u00e1s de una partici\u00f3n.<\/p>\n
Conclusi\u00f3n<\/h2>\n
Espero que esto te ayude a empezar con buen pie con Couchbase y Kafka. Gracias.<\/p>","protected":false},"excerpt":{"rendered":"
Intro Couchbase Kafka Connector 1.2.0 just shipped. Along with the various bug fixes, there is new sample code for a Kafka consumer in addition to the Kafka producer that was previously available. To quickly review the terms: A Kafka producer […]<\/p>","protected":false},"author":25,"featured_media":13873,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[1295,1487],"ppma_author":[8995],"class_list":["post-2010","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized","tag-connectors","tag-kafka"],"acf":[],"yoast_head":"\n
Up & Running with the Sample Kafka Consumer in 10 Minutes<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.couchbase.com\/blog\/es\/kafka-and-couchbase-up-and-running-in-10-minutes\/\" \/>\n<meta property=\"og:locale\" content=\"es_MX\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Kafka and Couchbase: Up and Running with the Sample Kafka Consumer in 10 Minutes\" \/>\n<meta property=\"og:description\" content=\"Intro Couchbase Kafka Connector 1.2.0 just shipped. Along with the various bug fixes, there is new sample code for a Kafka consumer in addition to the Kafka producer that was previously available. 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