似乎没有解决方案可以自动将 Confluence SchemaRegistry 的最新 schema 与 Kafka-topic 中的数据同步。因此，我通过从 Confluence Schema Registry API 响应复制来手动添加架构。
问题是：如何使用 Flink 从 Kafka 读取 Debezium Avro 格式的数据，使用 DataStream API？
我的环境:
架构是：
{
"type": "record",
"name": "Envelope",
"namespace": "uat.dwh.debezium.data",
"fields": [
{
"name": "before",
"type": [
"null",
{
"type": "record",
"name": "Value",
"fields": [
{
"name": "Sender",
"type": "int"
},
{
"name": "Target",
"type": "int"
},
{
"name": "SeqNum",
"type": "long"
},
{
"name": "TmSent",
"type": "long"
},
{
"name": "Action",
"type": {
"type": "int",
"connect.type": "int16"
}
},
{
"name": "OrderID",
"type": "long"
},
{
"name": "ClientID",
"type": "long"
},
{
"name": "SymbolID",
"type": "long"
},
{
"name": "OrderType",
"type": {
"type": "int",
"connect.type": "int16"
}
}
],
"connect.name": "uat.dwh.debezium.data.Value"
}
],
"default": null
},
{
"name": "after",
"type": [
"null",
"Value"
],
"default": null
},
{
"name": "source",
"type": {
"type": "record",
"name": "Source",
"namespace": "io.debezium.connector.mysql",
"fields": [
{
"name": "version",
"type": "string"
},
{
"name": "connector",
"type": "string"
},
{
"name": "name",
"type": "string"
},
{
"name": "ts_ms",
"type": "long"
},
{
"name": "snapshot",
"type": [
{
"type": "string",
"connect.version": 1,
"connect.parameters": {
"allowed": "true,last,false,incremental"
},
"connect.default": "false",
"connect.name": "io.debezium.data.Enum"
},
"null"
],
"default": "false"
},
{
"name": "db",
"type": "string"
},
{
"name": "sequence",
"type": [
"null",
"string"
],
"default": null
},
{
"name": "table",
"type": [
"null",
"string"
],
"default": null
},
{
"name": "server_id",
"type": "long"
},
{
"name": "gtid",
"type": [
"null",
"string"
],
"default": null
},
{
"name": "file",
"type": "string"
},
{
"name": "pos",
"type": "long"
},
{
"name": "row",
"type": "int"
},
{
"name": "thread",
"type": [
"null",
"long"
],
"default": null
},
{
"name": "query",
"type": [
"null",
"string"
],
"default": null
}
],
"connect.name": "io.debezium.connector.mysql.Source"
}
},
{
"name": "op",
"type": "string"
},
{
"name": "ts_ms",
"type": [
"null",
"long"
],
"default": null
},
{
"name": "transaction",
"type": [
"null",
{
"type": "record",
"name": "block",
"namespace": "event",
"fields": [
{
"name": "id",
"type": "string"
},
{
"name": "total_order",
"type": "long"
},
{
"name": "data_collection_order",
"type": "long"
}
],
"connect.version": 1,
"connect.name": "event.block"
}
],
"default": null
}
],
"connect.version": 1,
"connect.name": "uat.dwh.debezium.data.Envelope"
}
我使用以下代码启动了我的 Flink 应用程序：
package com.zfx.topbook;
import io.confluent.kafka.serializers.subject.TopicRecordNameStrategy;
import org.apache.avro.Schema;
import org.apache.avro.generic.GenericRecord;
import org.apache.flink.api.common.eventtime.WatermarkStrategy;
import org.apache.flink.api.common.serialization.DeserializationSchema;
import org.apache.flink.connector.kafka.source.KafkaSource;
import org.apache.flink.connector.kafka.source.enumerator.initializer.OffsetsInitializer;
import org.apache.flink.formats.avro.registry.confluent.ConfluentRegistryAvroDeserializationSchema;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import io.confluent.kafka.serializers.KafkaAvroDeserializerConfig;
import java.util.Properties;
public class TopBook {
public static void main(String[] args) throws Exception {
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
Properties properties = new Properties();
Schema avroSchema = new Schema.Parser().parse(properties.getProperty("avro.schema"));
// DeserializationSchema<GenericRecord> deserializer = AvroDeserializationSchema.forGeneric(avroSchema);
DeserializationSchema<GenericRecord> deserializer = ConfluentRegistryAvroDeserializationSchema.forGeneric(avroSchema);
KafkaSource<GenericRecord> source = KafkaSource.<GenericRecord>builder()
.setBootstrapServers(properties.getProperty("bootstrap.servers"))
.setTopics(properties.getProperty("topic"))
.setGroupId(properties.getProperty("group.id"))
.setStartingOffsets(OffsetsInitializer.latest())
.setValueOnlyDeserializer(deserializer)
.setProperties(properties)
.build();
env.fromSource(
source,
WatermarkStrategy.forMonotonousTimestamps(),
"Kafka Source"
)
.print();
env.execute();
}
}
最后我得到一个错误：
Exception in thread "main" org.apache.flink.runtime.client.JobExecutionException: Job execution failed.
at org.apache.flink.runtime.jobmaster.JobResult.toJobExecutionResult(JobResult.java:144)
at org.apache.flink.runtime.minicluster.MiniClusterJobClient.lambda$getJobExecutionResult$3(MiniClusterJobClient.java:141)
at java.base/java.util.concurrent.CompletableFuture$UniApply.tryFire(CompletableFuture.java:646)
at java.base/java.util.concurrent.CompletableFuture.postComplete(CompletableFuture.java:510)
at java.base/java.util.concurrent.CompletableFuture.complete(CompletableFuture.java:2147)
at org.apache.flink.runtime.rpc.pekko.PekkoInvocationHandler.lambda$invokeRpc$1(PekkoInvocationHandler.java:268)
at java.base/java.util.concurrent.CompletableFuture.uniWhenComplete(CompletableFuture.java:863)
at java.base/java.util.concurrent.CompletableFuture$UniWhenComplete.tryFire(CompletableFuture.java:841)
at java.base/java.util.concurrent.CompletableFuture.postComplete(CompletableFuture.java:510)
at java.base/java.util.concurrent.CompletableFuture.complete(CompletableFuture.java:2147)
at org.apache.flink.util.concurrent.FutureUtils.doForward(FutureUtils.java:1267)
at org.apache.flink.runtime.concurrent.ClassLoadingUtils.lambda$null$1(ClassLoadingUtils.java:93)
at org.apache.flink.runtime.concurrent.ClassLoadingUtils.runWithContextClassLoader(ClassLoadingUtils.java:68)
at org.apache.flink.runtime.concurrent.ClassLoadingUtils.lambda$guardCompletionWithContextClassLoader$2(ClassLoadingUtils.java:92)
at java.base/java.util.concurrent.CompletableFuture.uniWhenComplete(CompletableFuture.java:863)
at java.base/java.util.concurrent.CompletableFuture$UniWhenComplete.tryFire(CompletableFuture.java:841)
at java.base/java.util.concurrent.CompletableFuture.postComplete(CompletableFuture.java:510)
at java.base/java.util.concurrent.CompletableFuture.complete(CompletableFuture.java:2147)
at org.apache.flink.runtime.concurrent.pekko.ScalaFutureUtils$1.onComplete(ScalaFutureUtils.java:47)
at org.apache.pekko.dispatch.OnComplete.internal(Future.scala:310)
at org.apache.pekko.dispatch.OnComplete.internal(Future.scala:307)
at org.apache.pekko.dispatch.japi$CallbackBridge.apply(Future.scala:234)
at org.apache.pekko.dispatch.japi$CallbackBridge.apply(Future.scala:231)
at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:64)
at org.apache.flink.runtime.concurrent.pekko.ScalaFutureUtils$DirectExecutionContext.execute(ScalaFutureUtils.java:65)
at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:72)
at scala.concurrent.impl.Promise$DefaultPromise.$anonfun$tryComplete$1(Promise.scala:288)
at scala.concurrent.impl.Promise$DefaultPromise.$anonfun$tryComplete$1$adapted(Promise.scala:288)
at scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:288)
at org.apache.pekko.pattern.PromiseActorRef.$bang(AskSupport.scala:629)
at org.apache.pekko.pattern.PipeToSupport$PipeableFuture$$anonfun$pipeTo$1.applyOrElse(PipeToSupport.scala:34)
at org.apache.pekko.pattern.PipeToSupport$PipeableFuture$$anonfun$pipeTo$1.applyOrElse(PipeToSupport.scala:33)
at scala.concurrent.Future.$anonfun$andThen$1(Future.scala:536)
at scala.concurrent.impl.Promise.liftedTree1$1(Promise.scala:33)
at scala.concurrent.impl.Promise.$anonfun$transform$1(Promise.scala:33)
at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:64)
at org.apache.pekko.dispatch.BatchingExecutor$AbstractBatch.processBatch(BatchingExecutor.scala:73)
at org.apache.pekko.dispatch.BatchingExecutor$BlockableBatch.$anonfun$run$1(BatchingExecutor.scala:110)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at scala.concurrent.BlockContext$.withBlockContext(BlockContext.scala:85)
at org.apache.pekko.dispatch.BatchingExecutor$BlockableBatch.run(BatchingExecutor.scala:110)
at org.apache.pekko.dispatch.TaskInvocation.run(AbstractDispatcher.scala:59)
at org.apache.pekko.dispatch.ForkJoinExecutorConfigurator$PekkoForkJoinTask.exec(ForkJoinExecutorConfigurator.scala:57)
at java.base/java.util.concurrent.ForkJoinTask.doExec(ForkJoinTask.java:373)
at java.base/java.util.concurrent.ForkJoinPool$WorkQueue.topLevelExec(ForkJoinPool.java:1182)
at java.base/java.util.concurrent.ForkJoinPool.scan(ForkJoinPool.java:1655)
at java.base/java.util.concurrent.ForkJoinPool.runWorker(ForkJoinPool.java:1622)
at java.base/java.util.concurrent.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:165)
Caused by: org.apache.flink.runtime.JobException: Recovery is suppressed by NoRestartBackoffTimeStrategy
at org.apache.flink.runtime.executiongraph.failover.flip1.ExecutionFailureHandler.handleFailure(ExecutionFailureHandler.java:176)
at org.apache.flink.runtime.executiongraph.failover.flip1.ExecutionFailureHandler.getFailureHandlingResult(ExecutionFailureHandler.java:107)
at org.apache.flink.runtime.scheduler.DefaultScheduler.recordTaskFailure(DefaultScheduler.java:285)
at org.apache.flink.runtime.scheduler.DefaultScheduler.handleTaskFailure(DefaultScheduler.java:276)
at org.apache.flink.runtime.scheduler.DefaultScheduler.onTaskFailed(DefaultScheduler.java:269)
at org.apache.flink.runtime.scheduler.SchedulerBase.onTaskExecutionStateUpdate(SchedulerBase.java:764)
at org.apache.flink.runtime.scheduler.SchedulerBase.updateTaskExecutionState(SchedulerBase.java:741)
at org.apache.flink.runtime.scheduler.SchedulerNG.updateTaskExecutionState(SchedulerNG.java:83)
at org.apache.flink.runtime.jobmaster.JobMaster.updateTaskExecutionState(JobMaster.java:488)
at jdk.internal.reflect.GeneratedMethodAccessor8.invoke(Unknown Source)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:568)
at org.apache.flink.runtime.rpc.pekko.PekkoRpcActor.lambda$handleRpcInvocation$1(PekkoRpcActor.java:309)
at org.apache.flink.runtime.concurrent.ClassLoadingUtils.runWithContextClassLoader(ClassLoadingUtils.java:83)
at org.apache.flink.runtime.rpc.pekko.PekkoRpcActor.handleRpcInvocation(PekkoRpcActor.java:307)
at org.apache.flink.runtime.rpc.pekko.PekkoRpcActor.handleRpcMessage(PekkoRpcActor.java:222)
at org.apache.flink.runtime.rpc.pekko.FencedPekkoRpcActor.handleRpcMessage(FencedPekkoRpcActor.java:85)
at org.apache.flink.runtime.rpc.pekko.PekkoRpcActor.handleMessage(PekkoRpcActor.java:168)
at org.apache.pekko.japi.pf.UnitCaseStatement.apply(CaseStatements.scala:33)
at org.apache.pekko.japi.pf.UnitCaseStatement.apply(CaseStatements.scala:29)
at scala.PartialFunction.applyOrElse(PartialFunction.scala:127)
at scala.PartialFunction.applyOrElse$(PartialFunction.scala:126)
at org.apache.pekko.japi.pf.UnitCaseStatement.applyOrElse(CaseStatements.scala:29)
at scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:175)
at scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:176)
at scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:176)
at org.apache.pekko.actor.Actor.aroundReceive(Actor.scala:547)
at org.apache.pekko.actor.Actor.aroundReceive$(Actor.scala:545)
at org.apache.pekko.actor.AbstractActor.aroundReceive(AbstractActor.scala:229)
at org.apache.pekko.actor.ActorCell.receiveMessage(ActorCell.scala:590)
at org.apache.pekko.actor.ActorCell.invoke(ActorCell.scala:557)
at org.apache.pekko.dispatch.Mailbox.processMailbox(Mailbox.scala:280)
at org.apache.pekko.dispatch.Mailbox.run(Mailbox.scala:241)
at org.apache.pekko.dispatch.Mailbox.exec(Mailbox.scala:253)
... 5 more
Caused by: java.io.IOException: Failed to deserialize consumer record due to
at org.apache.flink.connector.kafka.source.reader.KafkaRecordEmitter.emitRecord(KafkaRecordEmitter.java:56)
at org.apache.flink.connector.kafka.source.reader.KafkaRecordEmitter.emitRecord(KafkaRecordEmitter.java:33)
at org.apache.flink.connector.base.source.reader.SourceReaderBase.pollNext(SourceReaderBase.java:160)
at org.apache.flink.streaming.api.operators.SourceOperator.emitNext(SourceOperator.java:419)
at org.apache.flink.streaming.runtime.io.StreamTaskSourceInput.emitNext(StreamTaskSourceInput.java:68)
at org.apache.flink.streaming.runtime.io.StreamOneInputProcessor.processInput(StreamOneInputProcessor.java:65)
at org.apache.flink.streaming.runtime.tasks.StreamTask.processInput(StreamTask.java:562)
at org.apache.flink.streaming.runtime.tasks.mailbox.MailboxProcessor.runMailboxLoop(MailboxProcessor.java:231)
at org.apache.flink.streaming.runtime.tasks.StreamTask.runMailboxLoop(StreamTask.java:858)
at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:807)
at org.apache.flink.runtime.taskmanager.Task.runWithSystemExitMonitoring(Task.java:953)
at org.apache.flink.runtime.taskmanager.Task.restoreAndInvoke(Task.java:932)
at org.apache.flink.runtime.taskmanager.Task.doRun(Task.java:746)
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:562)
at java.base/java.lang.Thread.run(Thread.java:842)
Caused by: java.io.EOFException
at org.apache.avro.io.BinaryDecoder$InputStreamByteSource.readRaw(BinaryDecoder.java:883)
at org.apache.avro.io.BinaryDecoder.doReadBytes(BinaryDecoder.java:405)
at org.apache.avro.io.BinaryDecoder.readString(BinaryDecoder.java:313)
at org.apache.avro.io.ResolvingDecoder.readString(ResolvingDecoder.java:208)
at org.apache.avro.generic.GenericDatumReader.readString(GenericDatumReader.java:469)
at org.apache.avro.generic.GenericDatumReader.readString(GenericDatumReader.java:459)
at org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:191)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:160)
at org.apache.avro.generic.GenericDatumReader.readField(GenericDatumReader.java:259)
at org.apache.avro.generic.GenericDatumReader.readRecord(GenericDatumReader.java:247)
at org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:179)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:160)
at org.apache.avro.generic.GenericDatumReader.readField(GenericDatumReader.java:259)
at org.apache.avro.generic.GenericDatumReader.readRecord(GenericDatumReader.java:247)
at org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:179)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:160)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:153)
at org.apache.flink.formats.avro.AvroDeserializationSchema.deserialize(AvroDeserializationSchema.java:142)
at org.apache.flink.api.common.serialization.DeserializationSchema.deserialize(DeserializationSchema.java:82)
at org.apache.flink.connector.kafka.source.reader.deserializer.KafkaValueOnlyDeserializationSchemaWrapper.deserialize(KafkaValueOnlyDeserializationSchemaWrapper.java:51)
at org.apache.flink.connector.kafka.source.reader.KafkaRecordEmitter.emitRecord(KafkaRecordEmitter.java:53)
... 14 more
这里的主要原因是错误使用了
ConfluentRegistryAvroDeserializationSchemaSchema然后，融合模式注册表中的模式 ID 出现了一些混乱（由于某些原因，模式没有通过 Kafka 消息包含的 ID 注册）。
修复这 2 个员工后，我最终可以以 Confluence Schema Registry Avro 格式反序列化来自 Kafka 的记录。
固定解决方案的代码是：
public class TopBook {
public static void main(String[] args) throws Exception {
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
Properties properties = getProperties();
Schema avroSchema = new Schema.Parser().parse(properties.getProperty("avro.schema.row"));
DeserializationSchema<GenericRecord> deserializer = ConfluentRegistryAvroDeserializationSchema.forGeneric(avroSchema, properties.getProperty("schema.registry.url"));
KafkaSource<GenericRecord> source = KafkaSource.<GenericRecord>builder()
.setBootstrapServers(properties.getProperty("bootstrap.servers"))
.setTopics(properties.getProperty("topic"))
.setGroupId(properties.getProperty("group.id"))
.setStartingOffsets(OffsetsInitializer.latest())
.setValueOnlyDeserializer(deserializer)
.setProperties(properties)
.build();
env
.fromSource(
source,
WatermarkStrategy.forMonotonousTimestamps(),
"Kafka Source"
)
.print();
env.execute();
}
}