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  • I'm looking for a way to edit the temp/RH data that mango stores. Whenever we lose power in the warehouse the temp/RH module reads -1,000 and that causes a lot of problems on the Mango graphs.
    Any ideas?


  • I think that you can do it by SQL queries. Third icon from end on icon bar.
    You have to see table DataPoints - check ID column and XID column. Right value ID can be used for query on table PointValues.

  • oja, you lost me. Especially when the SQL page states: "Warning: use this facility at your own risk. Incorrect usage may result in corrupted data and/or system failures."

    So unless you, or someone, has a known working SQL statement that I can fill in my particulars and use, I'm not going to risk it.

  • I think, it is only one way to change or delete old values.
    I did it one or two times without problems.

    You can this:

    1. Backup DERBY files or go to Export function in Mango
    2. Create new Mango on other PC
    3. Import data from backup
    4. Try SQL operations

    I think, that you will be succesfully.

    sorry for my English.

  • In addition, you can prevent this from happening in the first place by using "discard extreme values" checkbox for the data point. I was having the same problem with my 1-wire temperature sensors and this fixed it entirely.

    Attachment: download link

  • Can someone please post a sample SQL command that will purge extreme values from a datapoint, or purge values within a certain time range?

    I realize that I can set a discard low/high limit, but that does not help once the data is already logged. I have often found that when adjusting metadata formulas I sometimes wind up with a recent datapoint value that screws up my dataset, and consequently the graph scaling. My other option is the purge function, but that would cause me to lose all history before that point.

    It would also be useful to know how to replace point values that meet a certain date or value threshold. This would enable me to, for instance, change the scaling of prerecorded datapoints. e.g. to replace a Fahrenheit temperature dataset history with a Celsius dataset, or replace amperes with milliamperes.