I connected my sonarqube server to my postgres db however when I view the the "metrics" table, it lacks the actual value of the metric.
Those are all the columns I get, which are not particularly helpful. How can I get the actual values of the metrics?
My end goal is to obtain metrics such as duplicate code, function size, complexity etc. on my projects. I understand I could also use the REST api to do this however another application I am using will need a db to extract data from.
As far as i know connecting to db just helps to store data, not to display data.
You can check stored data on sonarqube's gui
Click on project
Click on Activity
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I have a grafana dashboard where I want to use an orcestra cities map dashboard to show status of some stations. The status is available as json from a http server (using nagios for this part) but the status has no idea of the location of the stations. This I have in a postGIS database.
I know I can set up a script that reads the status json and inserts the data into a table in the postgis database. This can run each five minutes or something. This feels a bit kludgy, so I wonder if there are some other ways of doing this.
Could it be possible to use a foreign data wrapper to fetch the json into postgis? The only json fdw I have found is to read a set of files, I would need to read from a http server.
If not, is it possible to combine data from json and postgres in one data set in grafana? I can read in data from both sources and present them e.g. as time series in one panel, but here I need to be able to join the two so that I use some of the attributes from json to categorize the points from postgis (or the other way around if that should be easier)
In theory you can do that in the Grafana. You need to have 2 queries with results from both sources (how to write query, configure datasources for that is not in the scope of this question) + you need a key, which can be used for a join in both results (e.g. city_id).
Then you may use join transformation to "join" both query results into single dataset.
Someone in my org created a Data Extract. There is an issue in one of the worksheets that uses it, and we suspect it's due to a mistake in how the Union was built.
But since it's a Data Extract, I can't see the UI for the data merge. Is there anyway to take a current Data Extract and view the logic that creates it?
Download the extract from the server (I'm assuming you're using server), then open that extract using desktop. You should be able to see the details of it.
Before going too deep into extract details, note that extracts are not intended to be permanent systems of record for data - just an efficient way to work with query results for optimized reporting. So in general, you should always be able to throw away the extract and look at the original source - or recreate the extract on command. But life isn't always perfect so ...
If you use Tableau Desktop to look at your worksheet, and look at the data source icon at the top of the data pane in the left sidebar, do you see an icon for your data source that looks like two databases with one on top of (shadowing) the other? If so, you can at right click on the data source icon and view its properties to see the source database table or file path. You can then even try disabling the extract to view the original source data.
If instead you see a single database icon, you have a "naked" extract where you've discarded the reference to the original source, (unless it is stored in the catalog mentioned below.)
If your organization purchased the Data Management Add-on for Tableau Server (strongly recommended), then if your data source is published to Tableau Server you can trace its history and origin by exploring the Tableau Catalog. That is especially valuable if the extract was built by a Tableau Prep Flow.
If instead, someone built the extract another way, say by writing a custom app using the Tableau Data Extract API, then the answer is to find that program.
One last point, in recent versions of Tableau, extracts are stored in an efficient relational type database file called Hyper. Hyper extracts can either be a single table (say serializing the results of a query joining multiple tables) or a Hyper extract can contain multiple tables (say serializing caching individual tables and deferring the join for later).
That may not be relevant to your question, but could turn out to matter as you reverse engineer how the extract was created.
I need to show metrics in real time but my metrics are stored in a relational database not supported by the datasources listed here https://grafana.com/docs/grafana/latest/http_api/data_source/
Can I somehow provide the JDBC (or other DB driver) to Grafana?
As #danielle clearly mentioned, "There is no direct support for JDBC or ODBC currently. You could get this data in time series form and into Grafana if you are prepared to do some programming.
The simple json data source is a generic backend that could make JDBC/ODBC calls to MapD and then transform the data into the right form for Grafana."
https://github.com/grafana/grafana/issues/8739#issuecomment-312118425
Though this comment is a bit old, i'm pretty sure there is no out of the box way to visualize data using JDBC/ODBC, yet.
One possible approach can make use of:
Grafana can access PostgreSQL
PostgreSQL can transparently display data in other databases as though it was a PostgreSQL table through Foreign Data Wrappers
Doing it this way, you'd use PostgreSQL to act as a gateway to the data. Depending on the table structure, you might also need to create a view in PG to shape the data to match Grafana's requirements for PG data source.
I have a dashboard in Tableau which pulls data from about 10 tables in a SQL database.
These tables are refreshed at various times of day. There are occasions where one of them is not available (or has been deleted and awaiting rebuild)
However when I open my tableau dashboard on the server it wont let me see any of it. Not seeing the data from the missing table is fine but the majority of the data that does not come from that table is unavailable too.
I get this error
An unexpected error occurred. If you continue to receive this error please contact your Tableau Server Administrator.
TableauException: [Microsoft][SQL Server Native Client 11.0][SQL Server]Invalid object name 'dbo.survey_order_info_fy16_TV_L'. The table "[dbo].[survey_order_info_fy16_TV_L]" does not exist. Unable to connect to the server "dbedwro.vistaprint.net". Check that the server is running and that you have access privileges to the requested database.
"survey_order_info_fy16_TV_L" being the missing table but not one I'm bothered about right now.
Is there an option that might help me see all the other data?
I am not sure if it's possible to avoid this behavior.
If there isn't there is a workaround for that by creating extract of these tables and storing them on the Tableau server. You can then use these extracts instead of the tables on the DB and just refresh them either by schedule if you know when the tables are available again or from the SQL server (eg. with SSIS by triggering the refresh once the data is available again).
Advantage of that would be that
you can refresh them independently and always have the latest data
it performs better than an SQL connection
you don't jam your SQL server with connections (in case you have a lot of users accesing)
you can filter and select if you didn't want your users to get access to the full dataset
disadvantages:
you will have to create one extract per table, and replace all data sources in workbooks you already use
It's a matter of creating a workbook, connecting to the source (adding filters or hiding fields) and publishing it to the server. Details of that can be found here:
http://onlinehelp.tableau.com/current/pro/online/mac/en-us/publish_datasources.html
I am using ELK stack (first project) to centralize logs of a server and visualize some real-time statistics with Kibana. The logs are stored in an ES index and I have another index with user information (IP, name, demographics). I am trying to:
Join user information with the server logs, matching the IPs. I want to include this information in the Kibana dashboard (e.g. to show in real-time the username of the connected users).
Create new indexes with filtered and processed information (e.g. users that have visited more than 3 times certain url).
Which is the best design to solve those problems (e.g. include username in the logstash stage through a filter, do scheduled jobs,...)? If the processing task (2) gets more complex, would it be better to use MongoDB instead?
Thank you!
I recently wanted to cross reference some log data with user data (containing IPs among other data) and just used elasticsearch's bulk import API. This meant extracting the data from a RDBMS, converting it to JSON and outputting a flat file that adhered to the format desired by the bulk import API (basically prefixing a row that describes the index and type).
That should work for an initial import, then your delta could be achieved using triggers in whatever stores your user data. Might simply write to a flat file and process like other logs. Other options might be JDBC River.
I am also interested to know where the data is stored originally (DB, pushing straight from a server..). However, I initially used the ELK stack to pull data back from a DB server using a batch file utilizing BCP (running on a scheduled task) and storing it to a flat file, monitoring the file with Logstash, and manipulating the data inside the LS config (grok filter). You may also consider a simple console/web application to manipulate the data before grokking with Logstash.
If possible, I would attempt to pull your data via SQL Server SPROC/BCP command and match the returned, complete message within Logstash. You can then store the information in a single index.
I hope this helps as I am by no means an expert, but I will be happy to answer more questions for you if you get a little more specific with the details of your current data storage; namely how the data is entering Logstash. RabbitMQ is another valuable tool to take a look at for your input source.