List Of Hadoop System Counters

Below is a list of all the Hadoop System counters, along with the Counter Groups, and example values (from my own MapReduce application).

* Counter Group: File System Counters (org.apache.hadoop.mapreduce.FileSystemCounter)

  - FILE: Number of bytes read: FILE_BYTES_READ: 176727

  - FILE: Number of bytes written: FILE_BYTES_WRITTEN: 611042

  - FILE: Number of read operations: FILE_READ_OPS: 0

  - FILE: Number of large read operations: FILE_LARGE_READ_OPS: 0

  - FILE: Number of write operations: FILE_WRITE_OPS: 0

  - HDFS: Number of bytes read: HDFS_BYTES_READ: 105677917

  - HDFS: Number of bytes written: HDFS_BYTES_WRITTEN: 447

  - HDFS: Number of read operations: HDFS_READ_OPS: 6

  - HDFS: Number of large read operations: HDFS_LARGE_READ_OPS: 0

  - HDFS: Number of write operations: HDFS_WRITE_OPS: 2


* Counter Group: Job Counters  (org.apache.hadoop.mapreduce.JobCounter)

  - Launched map tasks: TOTAL_LAUNCHED_MAPS: 1

  - Launched reduce tasks: TOTAL_LAUNCHED_REDUCES: 1

  - Rack-local map tasks: RACK_LOCAL_MAPS: 1

  - Total time spent by all maps in occupied slots (ms): SLOTS_MILLIS_MAPS: 95592

  - Total time spent by all reduces in occupied slots (ms): SLOTS_MILLIS_REDUCES: 11064

  - Total time spent by all map tasks (ms): MILLIS_MAPS: 47796

  - Total time spent by all reduce tasks (ms): MILLIS_REDUCES: 5532

  - Total vcore-seconds taken by all map tasks: VCORES_MILLIS_MAPS: 47796

  - Total vcore-seconds taken by all reduce tasks: VCORES_MILLIS_REDUCES: 5532

  - Total megabyte-seconds taken by all map tasks: MB_MILLIS_MAPS: 73414656

  - Total megabyte-seconds taken by all reduce tasks: MB_MILLIS_REDUCES: 11329536


* Counter Group: Map-Reduce Framework (org.apache.hadoop.mapreduce.TaskCounter)

  - Map input records: MAP_INPUT_RECORDS: 39129

  - Map output records: MAP_OUTPUT_RECORDS: 32295

  - Map output bytes: MAP_OUTPUT_BYTES: 370059

  - Map output materialized bytes: MAP_OUTPUT_MATERIALIZED_BYTES: 176723

  - Input split bytes: SPLIT_RAW_BYTES: 139

  - Combine input records: COMBINE_INPUT_RECORDS: 32295

  - Combine output records: COMBINE_OUTPUT_RECORDS: 29495

  - Reduce input groups: REDUCE_INPUT_GROUPS: 29495

  - Reduce shuffle bytes: REDUCE_SHUFFLE_BYTES: 176723

  - Reduce input records: REDUCE_INPUT_RECORDS: 29495

  - Reduce output records: REDUCE_OUTPUT_RECORDS: 50

  - Spilled Records: SPILLED_RECORDS: 58990

  - Shuffled Maps : SHUFFLED_MAPS: 1

  - Failed Shuffles: FAILED_SHUFFLE: 0

  - Merged Map outputs: MERGED_MAP_OUTPUTS: 1

  - GC time elapsed (ms): GC_TIME_MILLIS: 603

  - CPU time spent (ms): CPU_MILLISECONDS: 59310

  - Physical memory (bytes) snapshot: PHYSICAL_MEMORY_BYTES: 1158512640

  - Virtual memory (bytes) snapshot: VIRTUAL_MEMORY_BYTES: 6419664896

  - Total committed heap usage (bytes): COMMITTED_HEAP_BYTES: 1595932672


* Counter Group: Shuffle Errors (Shuffle Errors)

  - BAD_ID: BAD_ID: 0

  - CONNECTION: CONNECTION: 0

  - IO_ERROR: IO_ERROR: 0

  - WRONG_LENGTH: WRONG_LENGTH: 0

  - WRONG_MAP: WRONG_MAP: 0

  - WRONG_REDUCE: WRONG_REDUCE: 0

* Counter Group: File Input Format Counters  (org.apache.hadoop.mapreduce.lib.input.FileInputFormatCounter)

  - Bytes Read: BYTES_READ: 105677778

* Counter Group: File Output Format Counters  (org.apache.hadoop.mapreduce.lib.output.FileOutputFormatCounter)

  - Bytes Written: BYTES_WRITTEN: 447


Accessing the Counters

You can access a counter on a specific job using the following (you need the Counter Group, and the Counter Name):

job.getCounters().findCounter("org.apache.hadoop.mapreduce.FileSystemCounter", "HDFS_BYTES_READ").getValue()

Listing all the Counters

You can use the following code to list all the counters available for your job:

for (CounterGroup group : job.getCounters()) {
    System.out.println("* Counter Group: " + group.getDisplayName() + " (" + group.getName() + ")");
    System.out.println("  number of counters in this group: " + group.size());
    for (Counter counter : group) {
        System.out.println("  - " + counter.getDisplayName() + ": " + counter.getName() + ": "+counter.getValue());
    }
}

Hopefully someone finds this information useful!



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