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[SPARK-52346][SDP] Fix counter initialization and increment logic for flow retries #52094

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[SPARK-52346][SDP] Fix counter initialization and increment logic for flow retries #52094

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854ac17
default to 1 when key DNE
jackywang-db Aug 22, 2025
d34d10e
add unit test
jackywang-db Aug 25, 2025
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5 changes: 4 additions & 1 deletion sql/pipelines/src/main/scala/org/apache/spark/sql/pipelines/graph/GraphExecution.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -49,7 +49,10 @@ abstract class GraphExecution(

/** Increments flow execution retry count for `flow`. */
private def incrementFlowToNumConsecutiveFailure(flowIdentifier: TableIdentifier): Unit = {
flowToNumConsecutiveFailure.put(flowIdentifier, flowToNumConsecutiveFailure(flowIdentifier) + 1)
flowToNumConsecutiveFailure.updateWith(flowIdentifier) {
case Some(count) => Some(count + 1)
case None => Some(1)
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@JiaqiWang18 shall we have a unit test for this one?

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added unit test "consecutive failure event level is correct". flowToNumConsecutiveFailure controls the log level and if it is incremented correctly, we should only see the last retry execution event having ERROR level and all previous events having WARN level .

}
}

/**
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31 changes: 30 additions & 1 deletion ...es/src/test/scala/org/apache/spark/sql/pipelines/graph/TriggeredGraphExecutionSuite.scala
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Expand Up @@ -26,7 +26,7 @@ import org.apache.spark.sql.connector.catalog.{CatalogV2Util, Identifier, TableC
import org.apache.spark.sql.execution.streaming.runtime.MemoryStream
import org.apache.spark.sql.pipelines.common.{FlowStatus, RunState}
import org.apache.spark.sql.pipelines.graph.TriggeredGraphExecution.StreamState
import org.apache.spark.sql.pipelines.logging.EventLevel
import org.apache.spark.sql.pipelines.logging.{EventLevel, FlowProgress}
import org.apache.spark.sql.pipelines.utils.{ExecutionTest, TestGraphRegistrationContext}
import org.apache.spark.sql.test.SharedSparkSession
import org.apache.spark.sql.types.{IntegerType, StringType, StructType}
Expand Down Expand Up @@ -1027,4 +1027,33 @@ class TriggeredGraphExecutionSuite extends ExecutionTest with SharedSparkSession
}
)
}

test("consecutive failure event level is correct") {
val session = spark
import session.implicits._

val pipelineDef = new TestGraphRegistrationContext(spark) {
registerMaterializedView(
"retry_test",
partitionCols = Some(Seq("nonexistent_col")),
query = dfFlowFunc(spark.range(5).withColumn("id_mod", ($"id" % 2).cast("int")))
)
}

val graph = pipelineDef.toDataflowGraph
val updateContext = TestPipelineUpdateContext(spark, graph)
updateContext.pipelineExecution.runPipeline()
updateContext.pipelineExecution.awaitCompletion()

val failedEvents = updateContext.eventBuffer.getEvents.filter { e =>
e.details.isInstanceOf[FlowProgress] &&
e.details.asInstanceOf[FlowProgress].status == FlowStatus.FAILED
}

val warnCount = failedEvents.count(_.level == EventLevel.WARN)
// flowToNumConsecutiveFailure controls that the last failure should be logged as ERROR
val errorCount = failedEvents.count(_.level == EventLevel.ERROR)

assert(warnCount == 2 && errorCount == 1)
}
}