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  • Validate segments generated by realtime against raw data in HDFS.
  • Rebuild segments that have discrepancies from raw data in HDFS.
  • Collapse existing segments into higher granularity segments.


$ bin/dumbo
You must supply -s PATH!
Usage: bin/dumbo (options)
    -d, --database PATH              path to database config, defaults to "database.json"
    -D, --debug                      Enable debug output
    -N, --dryrun                     do not submit tasks to overlord (dry-run)
    -e, --environment ENVIRONMENT    Set the daemon environment
    -l, --limit LIMIT                limit the number of tasks to spawn (defaults to unlimited)
    -m, --mode MODE                  mode to perform (verify, compact, unshard)
        --name NAME                  Process name
    -n, --namenodes LIST             HDFS namenodes (comma seperated), defaults to "localhost"
        --offset HOURS               offset from now used as interval end, defaults to 3 hours
    -o, --overlord HOST[:PORT]       overlord hostname and port, defaults to "localhost:8090"
    -s, --sources PATH               path to sources config (required)
    -t, --topics LIST                Topics to process (comma seperated), defaults to all in sources.json
    -w, --window HOURS               scan window in hours, defaults to 24 hours
    -z, --zookeeper URI              zookeeper URI, defaults to "localhost:2181/druid"
        --zookeeper-path PATH        druid's discovery path within zookeeper, defaults to "/discovery"
    -h, --help                       Show this message

The repo contains examples for database.json and sources.json.

Assumption / Notes

About verify

Verify uses gobblin counters in HDFS to compare the total number of events in HDFS vs. in druid. To do this, there is a hard coded aggregation count named "events". If the count mismatches or the schema, an index hadoop task is spawned.

If a source['input']['epoc'] is set, verify will enforce the interval to not go beyond this point. This is useful, if you know you have incomplete HDFS data and want to keep the existing segments.

About compacting

Compacting verifies segmentGranularity and schema. If a mismatch is detected, an ingestSegment task is spawned.


  1. Fork it
  2. Create your feature branch (git checkout -b my-new-feature)
  3. Commit your changes (git commit -am 'Add some feature')
  4. Push to the branch (git push origin my-new-feature)
  5. Create a new Pull Request


Based on remerge/dumbo (which is a rewrite from scratch of druid-dumbo v1)