Page History

...

So dashboards can be set per resource / dataset specifically for a model or for all nodes (in that case use word "node" instead of the model name).  The default config ships with an example of this (with no dataset) for all node interfaces which is named "node interface defaults".

Charts

Charts can display several data sets in one place.  The data sets can come from different sources if desired, each data set has it's own set of options and parameters.  There are also options and parameters for the chart as a whole.

Creating an SQL Chart

SQL charts are not currently supported in the chart creator.  To make an SQL chart you will need to edit /usr/local/omk/conf/charts/charts.json.  The default configuration comes with several examples for SQL data sets.  The layout of an SQL chart is this: 

{
         "parameters" : {
            "time_period" : "time_difference",
            "end_date" : "7-Mar-2014 14:03:01",
            "start_date" : "7-Mar-2014 13:48:01"
         },
         "datasets" : [
            {
               "parameters" : {
                  "aggregation_function" : 1,
                  "lineType" : "column",
                  "query" : "select * from nodes",
                  "value_column" : "sum",
                  "axis" : "0",
                  "groupby" : [
                     "group_column"
                  ]
               },
               "data_source" : "local_mysql",
               "options" : {
                  "datasetTitle" : "Groups"
               },
               "name" : "sqlquery_dataset",
               "type" : "sql_query"
            }
         ],
         "options" : {
            "titleText" : ""
         },
         "name" : "SQL Test",
         "type" : "non-time-chart"
      },

Dataset:

Looking at an individual dataset will help us understand: 

 {
               "parameters" : {
                  "query" : "select * from nodes",
                  "groupby" : [
                     "group_column"
                  ],
                  "aggregation_function" : 1,
                  "value_column" : "unused",
                  "lineType" : "column",
                  "axis" : "0",
               },
               "data_source" : "local_mysql",
               "options" : {
                  "datasetTitle" : "Groups"
               },
               "name" : "sqlquery_dataset",
               "type" : "sql_query"
}

Breaking this down:

From the data_source "local_mysql", run the "sql_query" that is "select * from nodes", group the result by "group_column" and COUNT the number or rows in each group.  Display the results in a column graph on the 0 axis.

query:

The SQL to run.  This SQL can contain almost anything you would like. 

query subsitutions

Currently supported subsitutions are:

For the timestamps the time column being queried may need to be converted into a unix timestamp to make a comparison valid.  MySQL's timestamp function is UNIX_TIMESTAMP( timecolumn )

Example: SELECT * FROM interface WHERE UNIX_TIMESTAMP(lastUpdate) >= time.start AND UNIX_TIMESTAMP(lastUpdate) < time.end AND customerName = user.customer

groupby:

If the data returned from the SQL statement needs to be grouped (for summing or counting, works much like SQL GROUP BY) use this field to specify the group, as an array, order matters.  This works in tandem with the aggregation function to produce results.  Just like in an SQL GROUP BY each column requires a function to aggregate it's result.

value_column:

The column in the dataset to run the aggregation function on.  If you are not sure what the column name will be, use SELECT column AS some_unique_name. "some_unique_name" can then be used as the value column

aggregation_function:

PASSTHROUGH => 0, COUNT => 1, SUM => 2, MAX => 3, MIN => 4, AVG => 5

This function should be run on each entry in the "group" to produce one row.  The value_column will be read and have this function run on it, unless PASSTHROUGH or COUNT are used. For PASSTHROUGH no grouping or aggregation are done.  For COUNT the number of rows in each group is tallied.  both PASSTHROUGH or COUNT ignore the value_column setting.

lineType:

column is most likely, other options are available, open the chart creator (go to charts and click new chart), there is a drop down with the options.

name:

this is of little consequence, functionally not used at all right now but a way for you to name the dataset for later recognition.

type:

must be sql_query for the above parameters to work.

Back to the chart

The name is the unique name that identifies this chart when using it elsewhere (like creating a dashboard).  What is type for?

type

         "type" : "non-time-chart"

         "type" : "graph"

2 options exist for this.  "non-time-chart" means the data will not be an "over time" graph, but a snapshot of the data at a specific time.  This is the most likely candidate for an SQL chart.  "graph" is a data over time view, the time base is in unix epoc, the SQL query must return the time column in this format and "time_column" must be specified in the dataset telling it what the column is that holds the time value.