João Esteves created HUDI-867:
---------------------------------
Summary: Graphite metrics are generating IllegalArgumentException
on continuous mode
Key: HUDI-867
URL: https://issues.apache.org/jira/browse/HUDI-867
Project: Apache Hudi (incubating)
Issue Type: Bug
Components: DeltaStreamer
Reporter: João Esteves
Hello everyone, I am trying to extract Graphite metrics from Hudi using a Spark
Streaming process, but the method that sends metrics is throwing
java.lang.IllegalArgumentException after the first microbatch, like this:
{code:java}
20/05/06 11:49:25 ERROR Metrics: Failed to send metrics:
java.lang.IllegalArgumentException: A metric named kafka_hudi.finalize.duration
already exists
at
org.apache.hudi.com.codahale.metrics.MetricRegistry.register(MetricRegistry.java:97)
at org.apache.hudi.metrics.Metrics.registerGauge(Metrics.java:83)
at
org.apache.hudi.metrics.HoodieMetrics.updateFinalizeWriteMetrics(HoodieMetrics.java:177)
at
org.apache.hudi.HoodieWriteClient.lambda$finalizeWrite$14(HoodieWriteClient.java:1233)
at org.apache.hudi.common.util.Option.ifPresent(Option.java:96)
at
org.apache.hudi.HoodieWriteClient.finalizeWrite(HoodieWriteClient.java:1231)
at org.apache.hudi.HoodieWriteClient.commit(HoodieWriteClient.java:497)
at org.apache.hudi.HoodieWriteClient.commit(HoodieWriteClient.java:479)
at org.apache.hudi.HoodieWriteClient.commit(HoodieWriteClient.java:470)
at
org.apache.hudi.HoodieSparkSqlWriter$.write(HoodieSparkSqlWriter.scala:152)
at
org.apache.hudi.HoodieStreamingSink$$anonfun$1$$anonfun$2.apply(HoodieStreamingSink.scala:51)
at
org.apache.hudi.HoodieStreamingSink$$anonfun$1$$anonfun$2.apply(HoodieStreamingSink.scala:51)
at scala.util.Try$.apply(Try.scala:192)
at
org.apache.hudi.HoodieStreamingSink$$anonfun$1.apply(HoodieStreamingSink.scala:50)
at
org.apache.hudi.HoodieStreamingSink$$anonfun$1.apply(HoodieStreamingSink.scala:50)
at
org.apache.hudi.HoodieStreamingSink.retry(HoodieStreamingSink.scala:114)
at
org.apache.hudi.HoodieStreamingSink.addBatch(HoodieStreamingSink.scala:49)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$5$$anonfun$apply$17.apply(MicroBatchExecution.scala:537)
at
org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:84)
at
org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:165)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:74)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$5.apply(MicroBatchExecution.scala:535)
at
org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:351)
at
org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch(MicroBatchExecution.scala:534)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply$mcV$sp(MicroBatchExecution.scala:198)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply(MicroBatchExecution.scala:166)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply(MicroBatchExecution.scala:166)
at
org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:351)
at
org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1.apply$mcZ$sp(MicroBatchExecution.scala:166)
at
org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:56)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:160)
at
org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:281)
at
org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:193)
{code}
Here is my config object for Hudi:
{code:scala}
val hudiOptions = Map[String,String](
HoodieWriteConfig.TABLE_NAME -> hudiTableName,
DataSourceWriteOptions.RECORDKEY_FIELD_OPT_KEY -> "key",
DataSourceWriteOptions.PARTITIONPATH_FIELD_OPT_KEY -> "dt",
DataSourceWriteOptions.PRECOMBINE_FIELD_OPT_KEY -> "timestamp",
DataSourceWriteOptions.OPERATION_OPT_KEY -> "insert",
DataSourceWriteOptions.INSERT_DROP_DUPS_OPT_KEY -> "true",
HoodieCompactionConfig.CLEANER_COMMITS_RETAINED_PROP -> "1",
HoodieMetricsConfig.METRICS_ON -> "true",
HoodieMetricsConfig.METRICS_REPORTER_TYPE -> "GRAPHITE",
HoodieMetricsConfig.GRAPHITE_SERVER_HOST -> "localhost",
HoodieMetricsConfig.GRAPHITE_SERVER_PORT -> "4756",
HoodieMetricsConfig.GRAPHITE_METRIC_PREFIX -> "hudi"
)
{code}
Environment Description
* Hudi version: 0.5.0
* Spark version : 2.4.4
* Hive version : 2.3.6
* Hadoop version : Amazon 2.8.5 (emr-5.29.0)
* Storage (HDFS/S3/GCS..) : S3
* Running on Docker? (yes/no) : No
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