Spark metrics

By default, Dataproc Serverless enables the collection of available Spark metrics unless you use Spark metrics collection properties to disable or override the collection of one or more Spark metrics.

Spark metrics collection properties

You can use the properties listed in this section to disable or override the collection of one or more available Spark metrics.

Property	Description
`spark.dataproc.driver.metrics`	Use to disable or override Spark driver metrics.
`spark.dataproc.executor.metrics`	Use to disable or override Spark executor metrics.
`spark.dataproc.system.metrics`	Use to disable Spark system metrics.

gcloud CLI examples:

Disable Spark driver metric collection:

gcloud dataproc batches submit spark \
    --properties spark.dataproc.driver.metrics="" \
    --region=region \
    other args ...

Override Spark default driver metric collection to collect only BlockManager:disk.diskSpaceUsed_MB and DAGScheduler:stage.failedStages metrics:

gcloud dataproc batches submit spark \
    --properties=spark.dataproc.driver.metrics="BlockManager:disk.diskSpaceUsed_MB,DAGScheduler:stage.failedStages" \
    --region=region \
    other args ...

Available Spark metrics

Dataproc Serverless collects the Spark metrics listed in this section unless you use Spark metric collection properties to disable or override their collection.

custom.googleapis.com/METRIC_EXPLORER_NAME.

Spark driver metrics

Metric	Metrics Explorer name
BlockManager:disk.diskSpaceUsed_MB	spark/driver/BlockManager/disk/diskSpaceUsed_MB
BlockManager:memory.maxMem_MB	spark/driver/BlockManager/memory/maxMem_MB
BlockManager:memory.memUsed_MB	spark/driver/BlockManager/memory/memUsed_MB
DAGScheduler:job.activeJobs	spark/driver/DAGScheduler/job/activeJobs
DAGScheduler:job.allJobs	spark/driver/DAGScheduler/job/allJobs
DAGScheduler:messageProcessingTime	spark/driver/DAGScheduler/messageProcessingTime
DAGScheduler:stage.failedStages	spark/driver/DAGScheduler/stage/failedStages
DAGScheduler:stage.runningStages	spark/driver/DAGScheduler/stage/runningStages
DAGScheduler:stage.waitingStages	spark/driver/DAGScheduler/stage/waitingStages

Spark executor metrics

Metric	Metrics Explorer name
ExecutorAllocationManager:executors.numberExecutorsDecommissionUnfinished	spark/driver/ExecutorAllocationManager/executors/numberExecutorsDecommissionUnfinished
ExecutorAllocationManager:executors.numberExecutorsExitedUnexpectedly	spark/driver/ExecutorAllocationManager/executors/numberExecutorsExitedUnexpectedly
ExecutorAllocationManager:executors.numberExecutorsGracefullyDecommissioned	spark/driver/ExecutorAllocationManager/executors/numberExecutorsGracefullyDecommissioned
ExecutorAllocationManager:executors.numberExecutorsKilledByDriver	spark/driver/ExecutorAllocationManager/executors/numberExecutorsKilledByDriver
LiveListenerBus:queue.executorManagement.listenerProcessingTime	spark/driver/LiveListenerBus/queue/executorManagement/listenerProcessingTime
executor:bytesRead	spark/executor/bytesRead
executor:bytesWritten	spark/executor/bytesWritten
executor:cpuTime	spark/executor/cpuTime
executor:diskBytesSpilled	spark/executor/diskBytesSpilled
executor:jvmGCTime	spark/executor/jvmGCTime
executor:memoryBytesSpilled	spark/executor/memoryBytesSpilled
executor:recordsRead	spark/executor/recordsRead
executor:recordsWritten	spark/executor/recordsWritten
executor:runTime	spark/executor/runTime
executor:shuffleFetchWaitTime	spark/executor/shuffleFetchWaitTime
executor:shuffleRecordsRead	spark/executor/shuffleRecordsRead
executor:shuffleRecordsWritten	spark/executor/shuffleRecordsWritten
executor:shuffleRemoteBytesReadToDisk	spark/executor/shuffleRemoteBytesReadToDisk
executor:shuffleWriteTime	spark/executor/shuffleWriteTime
executor:succeededTasks	spark/executor/succeededTasks
ExecutorMetrics:MajorGCTime	spark/executor/ExecutorMetrics/MajorGCTime
ExecutorMetrics:MinorGCTime	spark/executor/ExecutorMetrics/MinorGCTime

System metrics

Metric	Metric Explorer Name
agent:uptime	agent/uptime
cpu:utilization	cpu/utilization
disk:bytes_used	disk/bytes_used
disk:percent_used	disk/percent_used
memory:bytes_used	memory/bytes_used
memory:percent_used	memory/percent_used
network:tcp_connections	network/tcp_connections

View Spark metrics

To view Batch metrics, click a batch ID on the Dataproc Batches page in the Google Cloud console to open the batch Details page, which displays a metrics graph for the batch workload under the Monitoring tab.