I have a grafana dashboard with 2 influx queries which calculate a single value (A and B)
I now need to calculate the difference between those to A - B.
Is this somehow possible within influx or grafana?
Note, the two values come from the same database but from different measurements
To show the difference of your two queries you first need to select the "Transform" tab.
Then "Add field from calculation".
Select your field names A and B.
Choose "Difference" as calculation method.
Select "Replace all fields" if you only want to see the difference.
Related
I am creating an interactive 'calculator' using tableau. I have a series of dataframes that I have crossed with one another, such that the resulting dataframe is every possible combination between the tables, and every row is unique.
Each column is its own worksheet as a table. Each table in the dashboard is a pane. So, here we have a series of tables with selectable units of measurement, and the final pane on the dashboard should filter to the cell for its respective column, on the unique row of the dataset that the user has selected and 'filtered out'.
I'm having some issues getting this to work and not sure why.
The closest I can think to solving this would be 'Cascading Filters.' Here are a couple resources:
General Use
In dashboard action-filter form
The critical piece, however, is that the filters must be selected in a specific order - therefore making them 'cascading.' This may differ from your presumed concept of clicking/filtering in any order on the worksheets to then arrive to a final answer. I do think that this may be a limitation of Tableau - I don't think that a 'many to many' type of relationship can be set up within Action Filters.
I have multiple Prometheus instances providing the same metric, such as:
my_metric{app="foo", state="active", instance="server-1"} 20
my_metric{app="foo", state="inactive", instance="server-1"} 30
my_metric{app="foo", state="active", instance="server-2"} 20
my_metric{app="foo", state="inactive", instance="server-2"} 30
Now I want to display this metric in a Grafana singlestat widget. When I use the following query...
sum(my_metric{app="foo", state="active"})
...it, of course, sums up all values and returns 40. So I tell Prometheus to sum it by instance...
sum(my_metric{app="foo", state="active"}) by (instance)
...which results in a "Multiple Series Error" in Grafana. Is there a way to tell Prometheus/Grafana to only use the first of the results?
I don't know of a distinct, but I think this would work too:
topk(1, my_metric{app="foo", state="active"} by (instance))
Check out the second to last example in here:
https://prometheus.io/docs/prometheus/latest/querying/examples/
One way I just found is to additionally do an average over all values:
avg(sum(my_metric{app="foo", state="active"}) by(instance))
If you need to return an arbitrary time series out of multiple matching time series, then this can be done with topk() or bottomk() functions. For example, the following query returns a single time series with the maximum value out of multiple time series which match my_metric{app="foo", state="active"}:
topk(1, my_metric{app="foo", state="active"})
You need to set instant query option in Grafana when using topk(). Otherwise topk(1, ...) may return multiple time series when it is used for building a graph with range query. This is because topk(1, ...) selects a single time series with the max value individually per each point on the graph. Different points on the graph may have different time series with the max value. There is a workaround, which allows returning a single series out of many series on a graph in alternative Prometheus-like systems such as VictoriaMetrics. It provides topk_* and bottomk_* functions for this purpose. See, for example, topk_last or topk_avg.
Note that topk() has no common grounds with DISTINCT from SQL. If you need to select distinct label values with PromQL, then you need to use count(...) by (label). It will return unique label values for the given label alongside the number of unique time series per each label value. For example, count(my_metric) by (app) will return unique app label names for time series with my_metric name. This is roughly equivalent to the following SQL with DISTINCT clause:
SELECT DISTINCT app FROM my_metric
See count() docs for details.
I have two exporters for feeding data into prometheus - the node exporter and the elasticsearch exporter. I'm trying to combine sources from both exporters into one query, but unfortunately get "No data points" in the graph.
Each of the series successfully shows data:
elasticsearch_jvm_memory_max_bytes{cluster="$cluster", name=~"$node"}
node_memory_MemTotal{name=~"$node"}
This is the result when I try to subtract the two series from one another:
node_memory_MemTotal{name=~"$node"} - elasticsearch_jvm_memory_max_bytes{cluster="$cluster", name=~"$node"}
What am I missing here?
Thanks.
The subtraction you are trying here is more complex than it reads in the beginning. On both sides of the - operator are queries that can result in one or more time series. So the operation requested works as follows: Execute the query on the left hand side and get a result of one or more time series. A time series means a unique combination of a metric and all its labels and their values. Then a second query for your right hand side is executed which also results in one or more time series. Now to calculate the results, only those combinations with matching label combinations are used.
For your example this means that the metrics from node_exporter and from the elasticsearch_exporter have different label names (or even only different values for the labels). When there are no combinations that exist on both sides, you will see the empty result. For details on how operators are applied, please see the prometheus docs.
To solve your problem, you could do the following:
Check the metrics of both left and right side on their own
Evaluate if there are additional labels that could be ignored
See if there is a good label to match on (e.g. instance / node / hostname)
Use the ignoring(a,b,c) on the required side(s) to drop superfluous dimensions, e.g. the job
Try the following query:
node_memory_MemTotal{name=~"$node"}
- on(name)
sum(elasticsearch_jvm_memory_max_bytes{cluster="$cluster", name=~"$node"}) by (name)
It works in the following way:
It selects all the time series matching the node_memory_MemTotal{name=~"$node"} time series selector.
It selects all the time series matching the elasticsearch_jvm_memory_max_bytes{cluster="$cluster", name=~"$node"} selector.
It groups time series found at step 2 by name label value and sums time series in each group with sum() aggregate function. The end result of the sum(...) by (name) is per-name sums.
It finds pairs of time series with identical name label value from the step 1 and step 3 and calculates the difference between the first and the second time series in each pair. The on(name) modifier is used for limiting the set of labels, which are used for finding time series pairs with matching labels. See more details about this process here.
I need to create a dashboard to be used in a control room, where a bunch of operators will need to monitor the number of tasks assigned to other employees (among other aspects).
Source data will be coming from a RDBMs (PostgreSQL, in this case). We have people with assigned and numbered tasks that also have a status, and the DB data is like this (purely fictional: but it resembles the real one)
Having to create and mantain a dashboard i was thinking to use tools like Grafana, Kibana or similars, to plot something like this
The problem is that Grafana, for example, doesn't let me use alphabetical values for the x-axis. It only allow numeric values, while i've names to plot (Mark, Luke, Brian).
Is there a best practice than i can follow? Am i trying to use the wrong tools?
Actually solution is easier then you think although it also took me some time to figure it out. I will place here an example for some unspecified shop data grouped over countries - you just need to change it for your task. Example was tested on Grafana 5.0.3
PostgreSQL query for metrics
SELECT
$__time( partition_date ),
country as metric,
sum(value) as value
FROM
aggregations.my_data_for_dashboard
WHERE
shop = 'myshopname' AND
$__timeFilter(partition_date )
group by 1, 2
Grafana will show usual metrics:
In "Axes" tab look at "X-Axis" section, item "Mode" - switch "Time" to "Series" and Grafana will show bar chart for countries.
I'm using Tableau Desktop 9.0 on OSX. I have data (loaded from a local CSV file) that looks like this:
code,org,items
0212000AA,142,10
0212000AA,143,15
0313000AA,142,90
0314000AA,143,85
I want a chart that shows the number of items beginning with 0212 as a percentage of all items, for each organisation. (I mean as a percentage of the organisation's items - for example, in the above, I would like to show 0.1 (10/(10+90)) for organisation 142.)
I have been able to get part way there, by adding org to Columns, and SUM(items) to Rows. Then by adding a Wildcard filter on code, for starts with 0212.
This shows me the number of items starting with 0212, by organisation.
But what I don't know how to do is show this divided by the value of all items for the organisation.
Is this possible in Tableau, or do I need to pre-calculate it before loading my data source?
One way is to define a calculated field called matches_code_prefix as:
left(code, 4) = "0212"
You can also define a parameter called, say, code_prefix to avoid hard coding the prefix string:
left(code, 4) = code_prefix
And then show the parameter control for code_prefix to allow the user to interact with it.
If you use this new field as a dimension to separate SUM(items) according to those that match the prefix and those that don't, you can then use a quick table calculation to get the percent of total.
For example, you can place org on the Rows shelf and matches_code_prefix on the Columns shelf, and SUM(items) on the Text shelf to make a table. Then under the analysis menu, turn on grand totals for both rows and columns to see the behavior. Next, right click on SUM(items) and choose Quick Table Calc->Percent of Total. Tableau will display the percents of total in the table.
If you want the percent of total defined differently than the default, then right click on the measure again and set Compute Using to a different value such as matches_code_prefix in your case. It's usually better to set compute using to a specific field.
If you only want to display the value for the matching case, select the column header you don't want to see and choose hide. You can also turn off the grand totals from the analysis menu when you are done.
When you are confident in the values in your table, you can turn it into a bar chart for example by moving matches_code_prefix to the detail shelf and the measure to the Columns shelf.
--
The above is the drag and drop approach. If you prefer to hard code everything in a single calculated field that is calculated on the database side, you could instead define a calculation such as:
zn(sum(if matches_code_prefix then items end)) / sum(items)
Then set the default number format for that field to display as a percentage