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## `CountTableRows` MapReduce Job Results

Whether running against a secure or non-secure store, as the job runs, assuming no errors, the output from the job will look like the following:

    ...
    INFO  [main] mapreduce.Job (Job.java:monitorAndPrintJob(1344))
        - Running job: job_1409172332346_0024
    INFO  [main] mapreduce.Job (Job.java:monitorAndPrintJob(1372))
        -  map 0% reduce 0% INFO  [main] mapreduce.Job
        (Job.java:monitorAndPrintJob(1372))
        -  map 26% reduce 0%
    INFO  [main] mapreduce.Job (Job.java:monitorAndPrintJob(1372))
        -  map 56% reduce 0%
    INFO  [main] mapreduce.Job (Job.java:monitorAndPrintJob(1372))
        -  map 100% reduce 0% INFO  [main] mapreduce.Job
        (Job.java:monitorAndPrintJob(1383))
        - Job job_1409172332346_0024 completed successfully
    INFO  [main] mapreduce.Job (Job.java:monitorAndPrintJob(1390))
        - Counters: 49
        File System Counters
            FILE: Number of bytes read=2771
            FILE: Number of bytes written=644463
            FILE: Number of read operations=0
            FILE: Number of large read operations=0
            FILE: Number of write operations=0
            HDFS: Number of bytes read=2660
            HDFS: Number of bytes written=32
            HDFS: Number of read operations=15
            HDFS: Number of large read operations=0
            HDFS: Number of write operations=2
        Job Counters
            Launched map tasks=6
            Launched reduce tasks=1
            Rack-local map tasks=6
            Total time spent by all maps in occupied slots (ms)=136868
            Total time spent by all reduces in occupied slots (ms)=2103
            Total time spent by all map tasks (ms)=136868
            Total time spent by all reduce tasks (ms)=2103
            Total vcore-seconds taken by all map tasks=136868
            Total vcore-seconds taken by all reduce tasks=2103
            Total megabyte-seconds taken by all map tasks=140152832
            Total megabyte-seconds taken by all reduce tasks=2153472
        Map-Reduce Framework
            Map input records=79
            Map output bytes=2607
            Map output materialized bytes=2801
            Input split bytes=2660
            Combine input records=0
            Combine output records=0
            Reduce input groups=1
            Reduce shuffle bytes=2801
            Reduce input records=79
            Reduce output records=1
            Spilled Records=158
            Shuffled Maps =6
            Failed Shuffles=0
            Merged Map outputs=6
            GC time elapsed (ms)=549
            CPU time spent (ms)=9460
            Physical memory (bytes) snapshot=1888358400
            Virtual memory (bytes) snapshot=6424895488
            Total committed heap usage (bytes)=1409286144
        Shuffle Errors
            BAD_ID=0
            CONNECTION=0
            IO_ERROR=0
            WRONG_LENGTH=0
            WRONG_MAP=0
            WRONG_REDUCE=0
        File Input Format Counters
            Bytes Read=0
        File Output Format Counters
            Bytes Written=32

To see the results of the job and to verify that the program counted the correct number of rows in the table, use the Hadoop CLI to display the contents of the MapReduce results file located in HDFS. To do this, type the following at the command line of the Hadoop cluster's access node:

    hadoop fs -cat \
        /user/example-user/CountTableRows/vehicleTable/<000N>/part-r-00000

where the `<000N>` token should be replaced with the value you used when the job was run. Assuming the table was populated with 79 rows, if the job was successful, then the output should look like the following:

    /type/make/model/class  79

where `/type/make/model/class` are the names of the fields making up the PrimaryKey of the `vehicleTable`, and 79 is the number of rows in the table.