Well,
For some reason I have a Kusto query (which I'll not share) that generates over ~500 rows and ~40 columns.
Then, I don't know why, but the following error is printed: RangeError: Invalid array length when I try to visualize the data on a heatmap visualization.
I'm looking for the limits of this visualization on Internet and I cannot find anything.
Related
I am creating a dashboard using metrics in graphite. I have tried consolidatedBy to get all the metrics. The metric values looks correct and are of the range of 1000s.
The graphite query for the same is
consolidateBy(monitors.x.y.z.client_metrics.k.*.*.*.*.*.response_codes.*.count, 'sum')
I want to get the total number of requests, which would be sum of all this series.
So, I tried the sum function but it is giving the sum around 1-12, which is actually less than the actual values.
The query is
sum(consolidateBy(monitors.x.y.z.client_metrics.k.*.*.*.*.*.response_codes.*.count, 'sum'))
This query also gives the same result
sum(monitors.x.y.z.client_metrics.k.*.*.*.*.*.response_codes.*.count)
My questions are:
Why is the sum of series giving point's value less than the actual values ?
I just want to calculate the total number of requests. If there is an easier solution. Can you please specify it.
I used grafana to display data from cloudwatch. I found grafana shows value incorrectly, for example, from this graph, the test_value is 1.000 at time 2021-02-28 07:29:00,
however, from this graph, u can see the test_value is still 1.000 at time 2021-02-28 10:29:00, while the bar graph shows there should be no test_value at this time slot;
it is very confused to see this? maybe the grafana setting is wrong? any suggestion?
You have sparse metric, so Grafana is showing the closest previous value. I would switch Hower tooltip Mode to Single instead of All series to avoid confusion.
You can also use CloudWatch Metric Math with FILL() function to fill the missing values of a metric with the specified filler value when the metric values are sparse.
I need help regarding the time series in Tableau. So far Here is what I can do.
Connect to TabPY
Call / Run scripts on TabPy
My current issue is that tableau doesn't seem to allow more output than input elements. Say I want to use the last 100 data points to predict the coming 10 points. Input of the data to python isn't a problem. The problem comes when I want to return a list with 110 elements. I've also tried returning the 10 elements and it complaints that it expects 100 elements list.
Thanks for reading
I've found a work around. You can see the post here for more information. Basically you shift the original values by the prediction amount and then have the prediction return the same amount as the shifted original
I am new to Graphite and can't understand how to do this:
I have a large number of time-metrics (celery metrics) in format stats.timers.*.median
I want to show:
Top N metrics with average value above X
Display them on one graph with the names of metrics
Now I have averageAbove(stats.timers.*.median,50) but it displays graphs without names and renders strangely and in bad scale. Help, please! :)
You will need to chain a few functions together in order to get the desired result.
limit(sortByMaxima(averageAbove(stats.timers.*.median, X)), N)
Starting the the averageAbove as the base.
The next thing you want to do is get all the metrics in order, "top-to-bottom" by using sortByMAxima.
Then you can limit the results that are rendered with the limit function.
You might not be rending the legend if you have too many metrics for the size of the graph. You can do 3 things.
Make the graph larger
Reduce the number of metrics using limit
Force the legend to be displayed via hideLegend
The documentation of Postgresql is the explanation that this histogram_bounds field in pg_stats.
The histogram divides the range into equal frequency buckets, so all we have to do is locate the bucket that our value is in and count part of it and all of the ones before.
But I still can not understand how the algorithms based on this field. I would like to describe in more detail how ANALYZE puts value in this field.