5.1.4.4. Management and Monitoring of Hadoop Deployments

Once the two services — extractor and applier — have been installed, the services can be monitored using trepctl. To monitor the master (extractor) service:

shell>  trepctl status
Processing status command...
NAME                     VALUE
----                     -----
appliedLastEventId     : mysql-bin.000023:0000000505545003;0
appliedLastSeqno       : 10992
appliedLatency         : 42.764
channels               : 1
clusterName            : alpha
currentEventId         : mysql-bin.000023:0000000505545003
currentTimeMillis      : 1389871897922
dataServerHost         : host1
extensions             : 
host                   : host1
latestEpochNumber      : 0
masterConnectUri       : thl://localhost:/
masterListenUri        : thl://host1:2112/
maximumStoredSeqNo     : 10992
minimumStoredSeqNo     : 0
offlineRequests        : NONE
pendingError           : NONE
pendingErrorCode       : NONE
pendingErrorEventId    : NONE
pendingErrorSeqno      : -1
pendingExceptionMessage: NONE
pipelineSource         : jdbc:mysql:thin://host1:13306/
relativeLatency        : 158296.922
resourcePrecedence     : 99
rmiPort                : 10000
role                   : master
seqnoType              : java.lang.Long
serviceName            : alpha
serviceType            : local
simpleServiceName      : alpha
siteName               : default
sourceId               : host1
state                  : ONLINE
timeInStateSeconds     : 165845.474
transitioningTo        : 
uptimeSeconds          : 165850.047
useSSLConnection       : false
version                : Tungsten Replicator 6.0.5 build 40
Finished status command...

When monitoring, the primary concernrs beyond identifying and copying with any errors is to monitor the applied latency. LArger numbers for applied latency generally indicate the the information is being written out to disk effectively. There are a number of strategies that should be checked:

  • Confirm that the Hadoop environment is running effectively. Any delays to writing to HDFS will impact the replicator.

  • Adjust the block commit parameters. Tuning the block commit levels should find the balance between frequent updates to achieve the required latency, and generating files of a suitable file sizes so that Hadoop can process them effectively for processing through map/reduce. You should try both increasing and reducing the sizes to find and figure out the the correct settings according to your source data.