Performance Issues with Embedded Power BI Dashboards
I have embedded multiple Power BI dashboards on my website. However, when multiple end users try to access the dashboards simultaneously, they experience significant delays in loading. I have verified that the dashboard performance is generally fast, and I have implemented incremental refresh, RLS methods, and have only 4 to 5 visuals with several filters. I am using Pro licenses.
API Performance Issues
I am having a strange issue. We have two servers, one with Windows Server 2016 and the other with Windows Server 2019. Both servers are running the latest May 2020 Power BI Report Server. When I make a simple API call: http://127.0.0.1/Reports/api/v2.0/System/AllowedActions On the Windows 2016 Server, it comes back in < 150 ms. Making the same call on the WIndows 2019 Server, it takes over 4+ seconds. I wanted to rule out a first time run, or other issues, so I ran each command 10 times. It was consistent. < 150 ms for the 2016 Server and >4000ms for the 2019 Server. I then ran some other tests, running the API call from various places to various endpoints: Ran From API Endpoint Time Windows Server 2016 Self 148ms Windows Server 2019 Self 4205ms Windows Server 2016 Windows Server 2019 142ms Windows Server 2019 Windows Server 2016 144ms Laptop Windows Server 2016 156ms Laptop Windows Server 2019 153ms As can be seen, calling the API from anywhere to anywhere gets fast response times, except for when I call the API from the Windows 2019 Server to itself. I can't find any differences between the 2016 Server and the 2019 Server that might cause a difference. The only thing I know of off hand is that on 2016 we are running .Net Framework 4.7.2 and on 2019 it is running 4.8. But I doubt that would make the difference. If anyone has any thoughts of ideas, i'm open. We have a simple web app that runs on the server to provide some details via the API. I know I coudl move it off to another server, but I'd rather keep it all together if possible.
Know and manage the data process flow for performance
Hello everyone! I have this environment: SQL Server 2017 (latest patch) with data SSAS with Import Model Power BI Report Server in Connect Live Mode with SSAS Model I would like to know how this entire environment works with memory usage, like RAM and DISK.... Is there a data process flow that explains how the data navigates from the database to the final report? I want to prevent any performance issue or server crashes. How can I read some info about it? Just an example: If I have a tabel with 800k records... how does it translate into ram and disk consumption? What I have to configure? Server RAM? Client RAM? SSAS RAM Configuration? Many thanks! RiccardoPowerBI.ReportServer.AsServer.AsConnectionException: Failed to get connection string for model
Does anyone know what this message means? We get it on a very small number of reports but with a reasonable frequency. We are investigating this as part of our performance deterioration in Power BI Report Server. Thanks
Performance worse after increasing CPU Cores
We have Power BI Report server based reports that connect to SSAS Tabular Models (SQL Server 2017). We recently tried upgrading our VM , adding in more cores (4 to 8) and RAM (64 to 128GB). This ended up making performance of reports/dashboards worse. When we reverted back the configuration things are fine again. We specifically noticed a strange scenario with the upgraded configuration. When I ran a certain MDX query as myself (I'm setup as an admin on the server) in SSMS Browser mode it ran in a 2 secs but the exact same query took >30secs when I was impersonating another user (we do have a fairly complicated row level security logic built into the models). With the older VM configuration it only took about 5-6 secs in impersonated mode. Any reason why there is such a huge difference with the addition of cores/RAM? Any tips on how I can go about understanding this better?How does performance for each user differ with row-level security in place?
We have several Power BI Report Server based reports/dashboards deployed that connect to SSAS data models. Most models until now have been reasonably sized model with fact tables that range from say 100K to about 5M records so performance has not been an issue. However, we now have a model that has 40M records and growing, with somewhat complicated measures as well, so performance is starting to become a concern i.e. on say filtering or drilling down, the visuls could take 15-20 secs to refresh as opposed to say 2-5 secs. What we've also noticed is that the very first time a user runs a report it takes quite a while but the 2nd time it will be much better. This however applies to every new query getting generated upon using say a new set of filters or something. So I have 2 questions:- 1. Does SSAS have some kind of caching concept where once a new query is run for the first time it will kind of keep it cached so when it is run again it will be faster? 2. If above is true, will the "query" differ for each user if row level security is in place e.g. Let's say user A runs a report and then user B runs the same report with same UI fitlers. User B however is not benefitted by the caching of User A's query because User B's query is slightly different given there is an additional row level security (where clause of sorts) being applied making the query slightly different?
Why does scheduled refresh lag sometimes?
On PBIRS, I've set a scheduled refresh for every 5 minutes. It will run every 5 mins but the refreshed data will not consistently be displayed on the report. This doesn't happen every time the scheduled refresh runs, but it definitely happens to my report every day, perhaps multiple times a day. Why is that? Example: Scheduled Refresh last ran at 1:55PM, but my visuals still show the data from the 1:35PM refresh.