Hadoop 3.3.1 + Spark 3.1.2
- OpenJDK 1.8.0
- 斯卡拉 2.12.14
图书馆
- spark-sql-kafka-0-10_2.12-3.1.2.jar
- kafka-clients-2.6.0.jar
- spark-token-provider-kafka-0-10_2.12-3.1.2.jar
打开 PySpark 外壳
pyspark --master yarn \
--deploy-mode client \
--driver-memory 16g \
--executor-memory 16g \
--executor-cores 5 \
--num-executors 30 \
--jars \
hdfs://ad-cluster/spark-yarn/jars/spark-sql-kafka-0-10_2.12-3.1.2.jar,\
hdfs://ad-cluster/spark-yarn/jars/kafka-clients-2.6.0.jar,\
hdfs://ad-cluster/spark-yarn/jars/spark-token-provider-kafka-0-10_2.12-3.1.2.jar
PySpark 代码
>>> kdf = spark.read.parquet("/tmp/loc_kdf_2021080900/")
>>> kafka_topic="test.location.spark"
>>> kafka_servers="10.190.105.124:9092,10.190.105.125:9092,10.190.105.126:9092,10.190.105.149:9092,10.190.105.150:9092,10.190.105.151:9092,10.190.105.152:9092,10.190.105.153:9092,10.190.105.154:9092"
>>> kdf.write.format("kafka").option("kafka.bootstrap.servers",kafka_servers).option("topic",kafka_topic).save()
异常错误消息：
21/08/10 21:18:12 WARN TaskSetManager: Lost task 12.0 in stage 1.0 (TID 16) (ad-worker2 executor 14): org.apache.kafka.common.errors.TimeoutException: Topic test.location.spark not present in metadata after 60000 ms.
21/08/10 21:19:12 WARN TaskSetManager: Lost task 77.0 in stage 1.0 (TID 152) (ad-worker2 executor 14): org.apache.kafka.common.errors.TimeoutException: Topic test.location.spark not present in metadata after 60000 ms.
21/08/10 21:20:12 WARN TaskSetManager: Lost task 91.1 in stage 1.0 (TID 305) (ad-worker2 executor 14): org.apache.kafka.common.errors.TimeoutException: Topic test.location.spark not present in metadata after 60000 ms.
21/08/10 21:21:12 WARN TaskSetManager: Lost task 151.2 in stage 1.0 (TID 454) (ad-worker2 executor 14): org.apache.kafka.common.errors.TimeoutException: Topic test.location.spark not present in metadata after 60000 ms.
21/08/10 21:21:14 ERROR TaskSetManager: Task 17 in stage 1.0 failed 4 times; aborting job
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/data/spark/python/pyspark/sql/readwriter.py", line 1107, in save self._jwrite.save()
File "/data/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line 1304, in __call__
File "/data/spark/python/pyspark/sql/utils.py", line 111, in deco
return f(*a, **kw)
File "/data/spark/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py", line 326, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o54.save.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 17 in stage 1.0 failed 4 times, most recent failure: Lost task 17.3 in stage 1.0 (TID 458) (ad-worker1 executor 5): org.apache.kafka.common.errors.TimeoutException:
Topic test.location.spark not present in metadata after 60000 ms.
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2258)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2207)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2206)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2206)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1079)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1079)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1079)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2445)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2387)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2376)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:868)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2196)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2217)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2236)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2261)
at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$1(RDD.scala:1020)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:1018)
at org.apache.spark.sql.kafka010.KafkaWriter$.write(KafkaWriter.scala:70)
at org.apache.spark.sql.kafka010.KafkaSourceProvider.createRelation(KafkaSourceProvider.scala:180)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:46)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:90)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:180)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:218)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:215)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:176)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:132)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:131)
at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:989)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:989)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:438)
at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:415)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:301)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.kafka.common.errors.TimeoutException: Topic test.location.spark not present in metadata after 60000 ms.
主题分区信息。
Topic: test.location.spark PartitionCount: 54 ReplicationFactor: 1 Configs:
Topic: test.location.spark Partition: 0 Leader: 1 Replicas: 1 Isr: 1
Topic: test.location.spark Partition: 1 Leader: 6 Replicas: 6 Isr: 6
Topic: test.location.spark Partition: 2 Leader: 7 Replicas: 7 Isr: 7
Topic: test.location.spark Partition: 3 Leader: 3 Replicas: 3 Isr: 3
Topic: test.location.spark Partition: 4 Leader: 0 Replicas: 0 Isr: 0
Topic: test.location.spark Partition: 5 Leader: 5 Replicas: 5 Isr: 5
Topic: test.location.spark Partition: 6 Leader: 2 Replicas: 2 Isr: 2
Topic: test.location.spark Partition: 7 Leader: 8 Replicas: 8 Isr: 8
Topic: test.location.spark Partition: 8 Leader: 4 Replicas: 4 Isr: 4
Topic: test.location.spark Partition: 9 Leader: 1 Replicas: 1 Isr: 1
Topic: test.location.spark Partition: 10 Leader: 6 Replicas: 6 Isr: 6
Topic: test.location.spark Partition: 11 Leader: 7 Replicas: 7 Isr: 7
Topic: test.location.spark Partition: 12 Leader: 3 Replicas: 3 Isr: 3
Topic: test.location.spark Partition: 13 Leader: 0 Replicas: 0 Isr: 0
Topic: test.location.spark Partition: 14 Leader: 5 Replicas: 5 Isr: 5
Topic: test.location.spark Partition: 15 Leader: 2 Replicas: 2 Isr: 2
Topic: test.location.spark Partition: 16 Leader: 8 Replicas: 8 Isr: 8
Topic: test.location.spark Partition: 17 Leader: 4 Replicas: 4 Isr: 4
Topic: test.location.spark Partition: 18 Leader: 1 Replicas: 1 Isr: 1