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Apache Spark Receiver

OpenTelemetry Collector receiver · contrib distribution

The Apache Spark Receiver fetches metrics for an Apache Spark cluster through the Apache Spark REST API - specifically, the /metrics/json, /api/v1/applications/[app-id]/stages, /api/v1/applications/[app-id]/executors, and /api/v1/applications/[app-id]/jobs endpoints.

  • Component ID: contrib-apachesparkreceiver
  • Name: apachesparkreceiver
  • Type: receiver
  • Distribution: contrib
  • Repository: opentelemetry-collector-contrib

Stability

LevelSignals
alphametrics

Metrics

MetricTypeValue typeUnitStabilityEnabledAttributesDescription
spark.driver.block_manager.disk.usagesumintMBydevelopmentyesDisk space used by the BlockManager.
spark.driver.block_manager.memory.usagesumintMBydevelopmentyeslocation (string), state (string)Memory usage for the driver's BlockManager.
spark.driver.code_generator.compilation.average_timegaugedoublemsdevelopmentyesAverage time spent during CodeGenerator source code compilation operations.
spark.driver.code_generator.compilation.countsum (monotonic)int{ compilation }developmentyesNumber of source code compilation operations performed by the CodeGenerator.
spark.driver.code_generator.generated_class.average_sizegaugedoubleBydevelopmentyesAverage class size of the classes generated by the CodeGenerator.
spark.driver.code_generator.generated_class.countsum (monotonic)int{ class }developmentyesNumber of classes generated by the CodeGenerator.
spark.driver.code_generator.generated_method.average_sizegaugedoubleBydevelopmentyesAverage method size of the classes generated by the CodeGenerator.
spark.driver.code_generator.generated_method.countsum (monotonic)int{ method }developmentyesNumber of methods generated by the CodeGenerator.
spark.driver.code_generator.source_code.average_sizegaugedoubleBydevelopmentyesAverage size of the source code generated by a CodeGenerator code generation operation.
spark.driver.code_generator.source_code.operationssum (monotonic)int{ operation }developmentyesNumber of source code generation operations performed by the CodeGenerator.
spark.driver.dag_scheduler.job.activesumint{ job }developmentyesNumber of active jobs currently being processed by the DAGScheduler.
spark.driver.dag_scheduler.job.countsum (monotonic)int{ job }developmentyesNumber of jobs that have been submitted to the DAGScheduler.
spark.driver.dag_scheduler.stage.countsumint{ stage }developmentyesscheduler_status (string)Number of stages the DAGScheduler is either running or needs to run.
spark.driver.dag_scheduler.stage.failedsum (monotonic)int{ stage }developmentyesNumber of failed stages run by the DAGScheduler.
spark.driver.executor.gc.operationssum (monotonic)int{ gc_operation }developmentyesgc_type (string)Number of garbage collection operations performed by the driver.
spark.driver.executor.gc.timesum (monotonic)intmsdevelopmentyesgc_type (string)Total elapsed time during garbage collection operations performed by the driver.
spark.driver.executor.memory.executionsumintBydevelopmentyeslocation (string)Amount of execution memory currently used by the driver.
spark.driver.executor.memory.jvmsumintBydevelopmentyeslocation (string)Amount of memory used by the driver's JVM.
spark.driver.executor.memory.poolsumintBydevelopmentyespool_memory_type (string)Amount of pool memory currently used by the driver.
spark.driver.executor.memory.storagesumintBydevelopmentyeslocation (string)Amount of storage memory currently used by the driver.
spark.driver.hive_external_catalog.file_cache_hitssum (monotonic)int{ hit }developmentyesNumber of file cache hits on the HiveExternalCatalog.
spark.driver.hive_external_catalog.files_discoveredsum (monotonic)int{ file }developmentyesNumber of files discovered while listing the partitions of a table in the Hive metastore
spark.driver.hive_external_catalog.hive_client_callssum (monotonic)int{ call }developmentyesNumber of calls to the underlying Hive Metastore client made by the Spark application.
spark.driver.hive_external_catalog.parallel_listing_jobssum (monotonic)int{ listing_job }developmentyesNumber of parallel listing jobs initiated by the HiveExternalCatalog when listing partitions of a table.
spark.driver.hive_external_catalog.partitions_fetchedsum (monotonic)int{ partition }developmentyesTable partitions fetched by the HiveExternalCatalog.
spark.driver.jvm_cpu_timesum (monotonic)intnsdevelopmentyesCurrent CPU time taken by the Spark driver.
spark.driver.live_listener_bus.droppedsum (monotonic)int{ event }developmentyesNumber of events that have been dropped by the LiveListenerBus.
spark.driver.live_listener_bus.postedsum (monotonic)int{ event }developmentyesNumber of events that have been posted on the LiveListenerBus.
spark.driver.live_listener_bus.processing_time.averagegaugedoublemsdevelopmentyesAverage time taken for the LiveListenerBus to process an event posted to it.
spark.driver.live_listener_bus.queue_sizesumint{ event }developmentyesNumber of events currently waiting to be processed by the LiveListenerBus.
spark.executor.disk.usagesumintBydevelopmentyesDisk space used by this executor for RDD storage.
spark.executor.gc_timesum (monotonic)intmsdevelopmentyesElapsed time the JVM spent in garbage collection in this executor.
spark.executor.input_sizesum (monotonic)intBydevelopmentyesAmount of data input for this executor.
spark.executor.memory.usagesumintBydevelopmentyesStorage memory used by this executor.
spark.executor.shuffle.io.sizesum (monotonic)intBydevelopmentyesdirection (string)Amount of data written and read during shuffle operations for this executor.
spark.executor.storage_memory.usagesumintBydevelopmentyeslocation (string), state (string)The executor's storage memory usage.
spark.executor.task.activesumint{ task }developmentyesNumber of tasks currently running in this executor.
spark.executor.task.limitsumint{ task }developmentyesMaximum number of tasks that can run concurrently in this executor.
spark.executor.task.resultsum (monotonic)int{ task }developmentyesexecutor_task_result (string)Number of tasks with a specific result in this executor.
spark.executor.timesum (monotonic)intmsdevelopmentyesElapsed time the JVM spent executing tasks in this executor.
spark.job.stage.activesumint{ stage }developmentyesNumber of active stages in this job.
spark.job.stage.resultsum (monotonic)int{ stage }developmentyesjob_result (string)Number of stages with a specific result in this job.
spark.job.task.activesumint{ task }developmentyesNumber of active tasks in this job.
spark.job.task.resultsum (monotonic)int{ task }developmentyesjob_result (string)Number of tasks with a specific result in this job.
spark.stage.disk.spilledsum (monotonic)intBydevelopmentyesThe amount of disk space used for storing portions of overly large data chunks that couldn't fit in memory in this stage.
spark.stage.executor.cpu_timesum (monotonic)intnsdevelopmentyesCPU time spent by the executor in this stage.
spark.stage.executor.run_timesum (monotonic)intmsdevelopmentyesAmount of time spent by the executor in this stage.
spark.stage.io.recordssum (monotonic)int{ record }developmentyesdirection (string)Number of records written and read in this stage.
spark.stage.io.sizesum (monotonic)intBydevelopmentyesdirection (string)Amount of data written and read at this stage.
spark.stage.jvm_gc_timesum (monotonic)intmsdevelopmentyesThe amount of time the JVM spent on garbage collection in this stage.
spark.stage.memory.peaksum (monotonic)intBydevelopmentyesPeak memory used by internal data structures created during shuffles, aggregations and joins in this stage.
spark.stage.memory.spilledsum (monotonic)intBydevelopmentyesThe amount of memory moved to disk due to size constraints (spilled) in this stage.
spark.stage.shuffle.blocks_fetchedsum (monotonic)int{ block }developmentyessource (string)Number of blocks fetched in shuffle operations in this stage.
spark.stage.shuffle.fetch_wait_timesum (monotonic)intmsdevelopmentyesTime spent in this stage waiting for remote shuffle blocks.
spark.stage.shuffle.io.disksum (monotonic)intBydevelopmentyesAmount of data read to disk in shuffle operations (sometimes required for large blocks, as opposed to the default behavior of reading into memory).
spark.stage.shuffle.io.read.sizesum (monotonic)intBydevelopmentyessource (string)Amount of data read in shuffle operations in this stage.
spark.stage.shuffle.io.recordssum (monotonic)int{ record }developmentyesdirection (string)Number of records written or read in shuffle operations in this stage.
spark.stage.shuffle.io.write.sizesum (monotonic)intBydevelopmentyesAmount of data written in shuffle operations in this stage.
spark.stage.shuffle.write_timesum (monotonic)intnsdevelopmentyesTime spent blocking on writes to disk or buffer cache in this stage.
spark.stage.statussumint{ status }developmentyesstage_active (bool), stage_complete (bool), stage_failed (bool), stage_pending (bool)A one-hot encoding representing the status of this stage.
spark.stage.task.activesumint{ task }developmentyesNumber of active tasks in this stage.
spark.stage.task.resultsum (monotonic)int{ task }developmentyesstage_task_result (string)Number of tasks with a specific result in this stage.
spark.stage.task.result_sizesum (monotonic)intBydevelopmentyesThe amount of data transmitted back to the driver by all the tasks in this stage.

Attributes

AttributeTypeDescription
directionstringWhether the metric is in regards to input or output operations.
executor_task_resultstringThe result of the executor tasks for which the metric was recorded.
gc_typestringThe type of the garbage collection performed for the metric.
job_resultstringThe result of the job stages or tasks for which the metric was recorded.
locationstringThe location of the memory for which the metric was recorded..
pool_memory_typestringThe type of pool memory for which the metric was recorded.
scheduler_statusstringThe status of the DAGScheduler stages for which the metric was recorded.
sourcestringThe source from which data was fetched for the metric.
stage_activeboolWhether the stage for which the metric was recorded is active.
stage_completeboolWhether the stage for which the metric was recorded is complete.
stage_failedboolWhether the stage for which the metric was recorded is failed.
stage_pendingboolWhether the stage for which the metric was recorded is pending.
stage_task_resultstringThe result of the stage tasks for which the metric was recorded.
statestringThe state of the memory for which the metric was recorded.

Data

  • JSON (latest): /data/collector/components/contrib-apachesparkreceiver/latest.json
  • JSON (pinned): /data/collector/components/contrib-apachesparkreceiver/contrib-apachesparkreceiver-f452429bae82.json
  • Explore: /collector/components/contrib/apachesparkreceiver