I have a very strange problem with Doughnut chart from vue-chartjs.. when I'm getting my response from rest api and converting it to datasets which looks almost the same like hard coded datasets the chart won't rerender itself. It seems like data from resp is not identical but I tried to give him both datasets in 2 separate attempts. So when I give him my hardcoded dataset then doughnut rerender but In case of rest api datasets converted to normal arrays it won't.. I printed everything in console so please check if those 2 datasets are not the same, in my opinion they are the same...
Hardcoded dataset:
Data set from api after conversion:
I don't really know what is going wrong but yesterday I tired to resolve this for 7 hours looking for a lot of problem with re rendering this chart and finally it rerenders but only when I use hard coded dataset. Please help me if You have some ideas.
Solved. I tried to assign data to existing empty datasets when it should be done by creating new one with assigned data from response.
Related
I'm using Grafana v9.1.8.
I created a panel bases on data from influxdb.
The data only sent when application is working, so sometimes there is no data.
And the dashboard will show just 'No Data' in the middile of the panel without any graph.
I'm trying to keep the graph(axis) shown even if there's no data, but I cannot find the solution.
As far as I know, there is no such feature on Grafana at the moment, but I found this solution:
https://community.grafana.com/t/what-to-show-when-the-panel-is-without-data/66524/9
Make a fake union, check if you have any data and if you don't create some random time data without other parameters. As they say in the answer, this may not be scalable, as you need to add extra lines for each query, but it may be a workaround.
I have an InfluxDB database with only x11 data points in it. These data are not displaying correctly (or at least as I would expect) in Grafana when the time between them is shorter than 1ms.
If I insert data points 1 ms apart, then everything works as expected and I see all x11 points at the correct times, as shown below.:
However, if I delete these points and upload new ones but this time one point per 100 μs, then although the data displays correctly in InfluxDB, in Grafana I see only two points in my graph:
It seems like the data is being rounded/binned to the nearest millisecond, an that this is related to the “precision=ms” setting in the query here:
but I cannot find any way to change this setting. What is the correct way to fix this?
You can't configure Grafana to support different time precision for the InfluxDB. It is hardcoded in the source code: https://github.com/grafana/grafana/blob/36fd746c5df1438f27aa33fc74b24be77debc7ff/public/app/plugins/datasource/influxdb/datasource.ts#L364 (It may need to be fixed in multiple places of the source, not only in this one.)
So the correct way to fix it is to code it, which is of course not in the scope of this question.
I'm creating the timeseries_stacked_column chart using SAPUI5 and the framework is plotting data for missing weeks even thought it's not fed to the chart. Please can anyone guide what's the best approach to avoid this.
Document link for chart property reference:
https://sapui5.hana.ondemand.com/docs/vizdocs/index.html#reference/chartProperty/Charts/Bar%20%20(15)/Stacked%20Column%20Chart%20for%20Date/Time%20Series/
Please see the screenshot below for the issue
Unfortunately the time series doesn't skip the intervals so the alternate solution to this was to use stacked_column chart with array of dimensions ["Year", "Week"] and plot accordingly.
Example: https://jsbin.com/nejefizuve/edit?html,output
This should be pretty straight forward, just haven't been able to find any documentation, so unsure if it is possible, and if it is - how.
I'm calling the Sharepoint 2013 REST API, specifically the Excel REST services (ExcelRest.aspx), to fetch values from specific cells in an Excel workbook.
I've had success with the following two types of calls:
Fetch one specific cell (E5):
http://somesharepointsite.com/testsite/_vti_bin/ExcelRest.aspx/Shared%20Documents/Excelfile.xlsx/Model/Ranges('''Front%20page''!E5')?$format=html
Fetch range (E5-F20):
http://somesharepointsite.com/testsite/_vti_bin/ExcelRest.aspx/Shared%20Documents/Excelfile.xlsx/Model/Ranges('''Front%20page''!E5|F20')?$format=html
However I would very much like to be able to fetch multiple specific cells e.g: E5, E7, F15, F18.
This is due to how the information is placed in the spreadsheet, which isn't really convenient for automated extration. So instead of counting rows/columns to find relevant cells when extracting a range, it would much easier if all cells of relevance could be indicated directly.
I know I could just make a bunch of separate calls fetching one cell at the time, but that doesn't really seem like the optimum solution.
I've tried separating the range with commas, semicolons - also tried making two separate Ranges - no luck
Any suggestions are welcome
Actually, simplify the problem. I would create a hidden sheet that puts all the relevant data in a single range that you can pull from and give it a Named Range. Then call that Range. These values are linked the the master sheet. Hidden only in there's no reason to confuse anyone if they open up the spreadsheet.
I've a problem with the dashboard in Tableau. In the dashboard there are many worksheets, and all the columns that are in the report are calculable. The problem is that dashboard is being formed for a very long time. The report contains approximately 2 million rows. And it is generated about 5 minutes.
Tell me, what are the solutions in this case?
Maybe I can somehow adjust the page display and not all the records at once?
To reduce the calculation time, try to exclude data you don't need with a data source filter in tableau. You can also hide or delete unused calculated fields. Other things you can do is reduce sheets that are not used.
Here's a link: https://www.tableau.com/about/blog/2016/1/5-tips-make-your-dashboards-more-performant-48574
Steps to follow to reduce calculation time:
Extract the data and use Extract data and also keep option as extract instead of live.Also replace the data source using extract data.
Use "User Filter" to reduce calculation time so that tableau will display of particular user data only.
I hope this will work to solve your problems.
I have one more idea to resolve this issue.
1)when you loan first time your dashboard put into Dashboard Action Filter
First Time load dashboard data exclude in your sheet.
Dashboard Menu->Action->add action->select sheet and exclude option.
2) Live to Extract data source and select radio button extract.
3)use user filter.
I am following the other answers (use extract, dashboard action filter...) and I want to add one point:
Drag every field used by any tablesheet on the dashboard on "Detail" of every tablesheet you are using on the Dashboard. Now Tableau loads all needed data while loading the first tablesheet and can use this data for the other sheets.
i.e. A dashboard contains three tablesheets (A, B, C) now you drag every field used by A on "Deatil" of B and C, every field used by B on "Deatil" of A and C, every field used by C on "Deatil" of B and A.
We are also having a similar issue with 150 million rows but I want to check if you are doing following steps. This may help you. This goes back to fundamentals of Tableau reporting.
1/ Try to make sure your data set is in star schema format. This will help a lot in report.
2/ Try to have tables and views in DB in such a way that same columns are used in Tableau. Any extra columns in tables adds to the performance issue.
3/Make sure indexing is done properly for all the fields that are joined.
4/ In my experience Dashboard adds extra performance lag. So make sure you try to get as much performance tuning on sheets as possible before even going to dashboard.
5/ If required try to use materialized views.
hope this helps.
Try to capture performance metrics using performance recorder option in Tableau.
Check for the underlying DB tables and joins present on the data source layer.
Try using optimized sets and parameters as required and get rid of less relevant filters.
Try using data extracts with scheduled refresh with data source filter for limited business years data.