我流蒙哥oplog数据通过Kafka。我使用debezium cdcKafka连接器到尾部mongo oplog。
模式注册表使用avroconverter转换器序列化键和值
bootstrap.servers服务器=localhost:9092
kafka key.converter=io.confluent.connect.avro.avroconverter key.converter.schema.registry.url=http://localhost：8081 value.converter=io.confluent.connect.avro.avroconverter value.converter.schema.registry.url=http://localhost:8081
internal.key.converter=org.apache.kafka.connect.json.jsonconverter internal.value.converter=org.apache.kafka.connect.json.jsonconverter internal.key.converter.schemas.enable=false internal.value.converter.schemas.enable=false
offset.storage.file.filename=/tmp/connect.offsets
下面的代码流的Kafka数据和反序列化它使用Kafka夫罗德序列化

import io.confluent.kafka.schemaregistry.client.rest.RestService
import io.confluent.kafka.serializers.KafkaAvroDeserializer
import org.apache.avro.Schema
import org.apache.spark.sql.SparkSession
import scala.collection.JavaConverters._
object KafkaStream{

  case class DeserializedFromKafkaRecord(key: String, value: String)

  def main(args: Array[String]): Unit = {

    val sparkSession = SparkSession
      .builder
      .master("local[*]")
      .appName("kafka")
      .getOrCreate()
    //sparkSession.sparkContext.setLogLevel("ERROR")

    import sparkSession.implicits._

    val schemaRegistryURL = "http://127.0.0.1:8081"

    val topicName = "prodCollection.inventory.Prod"
    val subjectValueName = topicName + "-value"

    //create RestService object
    val restService = new RestService(schemaRegistryURL)

    //.getLatestVersion returns io.confluent.kafka.schemaregistry.client.rest.entities.Schema object.
    val valueRestResponseSchema = restService.getLatestVersion(subjectValueName)

    //Use Avro parsing classes to get Avro Schema
    val parser = new Schema.Parser
    val topicValueAvroSchema: Schema = parser.parse(valueRestResponseSchema.getSchema)

    //key schema is typically just string but you can do the same process for the key as the value
    val keySchemaString = "\"string\""
    val keySchema = parser.parse(keySchemaString)

    //Create a map with the Schema registry url.
    //This is the only Required configuration for Confluent's KafkaAvroDeserializer.
    val props = Map("schema.registry.url" -> schemaRegistryURL)

    //Declare SerDe vars before using Spark structured streaming map. Avoids non serializable class exception.
    var keyDeserializer: KafkaAvroDeserializer = null
    var valueDeserializer: KafkaAvroDeserializer = null

    //Create structured streaming DF to read from the topic.
    val rawTopicMessageDF = sparkSession.readStream
      .format("kafka")
      .option("kafka.bootstrap.servers", "localhost:9092")
      .option("subscribe", topicName)
      .option("startingOffsets", "earliest")
      .option("key.deserializer","KafkaAvroDeserializer")
      .option("value.deserializer","KafkaAvroDeserializer")
      //.option("maxOffsetsPerTrigger", 20)  //remove for prod
      .load()
    rawTopicMessageDF.printSchema()

    //instantiate the SerDe classes if not already, then deserialize!
    val deserializedTopicMessageDS = rawTopicMessageDF.map{
      row =>
        if (keyDeserializer == null) {
          keyDeserializer = new KafkaAvroDeserializer
          keyDeserializer.configure(props.asJava, true)  //isKey = true
        }
        if (valueDeserializer == null) {
          valueDeserializer = new KafkaAvroDeserializer
          valueDeserializer.configure(props.asJava, false) //isKey = false
        }

        //Pass the Avro schema.
        val deserializedKeyString = keyDeserializer.deserialize(topicName, row.getAs[Array[Byte]]("key"), keySchema).toString //topic name is actually unused in the source code, just required by the signature. Weird right?
      val deserializedValueJsonString = valueDeserializer.deserialize(topicName, row.getAs[Array[Byte]]("value"), topicValueAvroSchema).toString

        DeserializedFromKafkaRecord(deserializedKeyString, deserializedValueJsonString)
    }
    deserializedTopicMessageDS.printSchema()

      deserializedTopicMessageDS.writeStream
      .outputMode("append")
      .format("console")
      .option("truncate", false)
      .start()

反序列化的TopicMessageDS数据集架构正在根据需要进行转换，但流将被以下信息停止，

root
 |-- key: binary (nullable = true)
 |-- value: binary (nullable = true)
 |-- topic: string (nullable = true)
 |-- partition: integer (nullable = true)
 |-- offset: long (nullable = true)
 |-- timestamp: timestamp (nullable = true)
 |-- timestampType: integer (nullable = true)

root
 |-- key: string (nullable = true)
 |-- value: string (nullable = true)

18/08/13 22:53:54 INFO StateStoreCoordinatorRef: Registered StateStoreCoordinator endpoint
18/08/13 22:53:54 INFO StreamExecution: Starting [id = b1fb3ce2-08d0-4d87-b031-af129432d91a, runId = 38b66e4a-040f-42c8-abbe-bc27fa3b9462]. Use /private/var/folders/zf/6dh44_fx1sn2dp2w7d_54wg80000gn/T/temporary-ae7a93f6-0307-4f39-ba44-93d5d3d7c0ab to store the query checkpoint.
18/08/13 22:53:54 INFO SparkContext: Invoking stop() from shutdown hook
18/08/13 22:53:54 INFO SparkUI: Stopped Spark web UI at http://192.168.0.100:4040
18/08/13 22:53:54 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
18/08/13 22:53:54 INFO MemoryStore: MemoryStore cleared
18/08/13 22:53:54 INFO BlockManager: BlockManager stopped
18/08/13 22:53:54 INFO BlockManagerMaster: BlockManagerMaster stopped
18/08/13 22:53:54 INFO ConsumerConfig: ConsumerConfig values: 
    auto.commit.interval.ms = 5000
    auto.offset.reset = earliest
    bootstrap.servers = [localhost:9092]
    check.crcs = true
    client.id = 
    connections.max.idle.ms = 540000
    default.api.timeout.ms = 60000
    enable.auto.commit = false
    exclude.internal.topics = true
    fetch.max.bytes = 52428800
    fetch.max.wait.ms = 500
    fetch.min.bytes = 1
    group.id = spark-kafka-source-b9f0f64b-952d-4733-ba3e-aa753954b2ef--1115279952-driver-0
    heartbeat.interval.ms = 3000
    interceptor.classes = []
    internal.leave.group.on.close = true
    isolation.level = read_uncommitted
    key.deserializer = class org.apache.kafka.common.serialization.ByteArrayDeserializer
    max.partition.fetch.bytes = 1048576
    max.poll.interval.ms = 300000
    max.poll.records = 1
    metadata.max.age.ms = 300000
    metric.reporters = []
    metrics.num.samples = 2
    metrics.recording.level = INFO
    metrics.sample.window.ms = 30000
    partition.assignment.strategy = [class org.apache.kafka.clients.consumer.RangeAssignor]
    receive.buffer.bytes = 65536
    reconnect.backoff.max.ms = 1000
    reconnect.backoff.ms = 50
    request.timeout.ms = 30000
    retry.backoff.ms = 100
    sasl.client.callback.handler.class = null
    sasl.jaas.config = null
    sasl.kerberos.kinit.cmd = /usr/bin/kinit
    sasl.kerberos.min.time.before.relogin = 60000
    sasl.kerberos.service.name = null
    sasl.kerberos.ticket.renew.jitter = 0.05
    sasl.kerberos.ticket.renew.window.factor = 0.8
    sasl.login.callback.handler.class = null
    sasl.login.class = null
    sasl.login.refresh.buffer.seconds = 300
    sasl.login.refresh.min.period.seconds = 60
    sasl.login.refresh.window.factor = 0.8
    sasl.login.refresh.window.jitter = 0.05
    sasl.mechanism = GSSAPI
    security.protocol = PLAINTEXT
    send.buffer.bytes = 131072
    session.timeout.ms = 10000
    ssl.cipher.suites = null
    ssl.enabled.protocols = [TLSv1.2, TLSv1.1, TLSv1]
    ssl.endpoint.identification.algorithm = https
    ssl.key.password = null
    ssl.keymanager.algorithm = SunX509
    ssl.keystore.location = null
    ssl.keystore.password = null
    ssl.keystore.type = JKS
    ssl.protocol = TLS
    ssl.provider = null
    ssl.secure.random.implementation = null
    ssl.trustmanager.algorithm = PKIX
    ssl.truststore.location = null
    ssl.truststore.password = null
    ssl.truststore.type = JKS
    value.deserializer = class org.apache.kafka.common.serialization.ByteArrayDeserializer

18/08/13 22:53:54 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
18/08/13 22:53:54 INFO SparkContext: Successfully stopped SparkContext
18/08/13 22:53:54 INFO ShutdownHookManager: Shutdown hook called
18/08/13 22:53:54 INFO ShutdownHookManager: Deleting directory /private/var/folders/zf/6dh44_fx1sn2dp2w7d_54wg80000gn/T/spark-e1c2b259-39f2-4d65-9919-74ab1ad6acae
18/08/13 22:53:54 INFO ShutdownHookManager: Deleting directory /private/var/folders/zf/6dh44_fx1sn2dp2w7d_54wg80000gn/T/temporary-ae7a93f6-0307-4f39-ba44-93d5d3d7c0ab

Process finished with exit code 0