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Transform Tabular Pollers to remove entries?

I have some tabular universal device pollers which are working fine - however i would like to filter the results from the table that I display. Can the Transform Results app apply any filters to text results from a tabular poller?

  • FormerMember
    0 FormerMember

     Unfortunately no.  There is no way to filter out rows of a table using Transform Results.  On a chart, you have the ability to remove rows that are being displayed if you click "Edit" on the chart page.  We don't have similar functionality for tables, but we're working on it.

  • FormerMember
    0 FormerMember in reply to FormerMember

    Is this still being worked on?  I can't find any details anywhere...

    Removing rows from the chart is not an acceptable solution - I am trying to monitor a process from hrSWRunName where there are multiple instances of a given process and that number fluctuates regularly - there is no way to determine which rows the process will show up in in each poll, nor how many entries/rows there will be during any given poll.  Ideally I would like to poll to find out how many instances of this process are running at any given time, but without filtering, this does not seem possible....

  • Hi sduff,

    Just to be clear you only want to see actual number of rows retrieved for this OID from the last poll? This is possilbe through Universal Device Poller Status resource which in case of table oids (like hrSWRunName) shows this number as a current status.

    Hope this helps,

    Zbynek Botlo

  • FormerMember
    0 FormerMember in reply to zbynek.botlo

    "you only want to see actual number of rows retrieved for this OID from the last poll?"

    Not exactly, I want to see the actual number of rows that relate to a specific process, not the entire poll.  We have servers that compile software and I wish to see how many compilers are running at any given time to be able to relate that to CPU load, memory usage and other statistics.  However, I have solved this issue on Linux servers by using a Linux script monitor to run a perl script that returns this result, and I can then graph the statistic, which works for my needs.