I've been asked to implement a way to load data to my datasets once a month. As Power BI Service doesn't have this option, I had to find a solution using Power Query and bellow I describe the step-by-step of my solution.
If it helps you at some way, please, let me know by posting a comment bellow. If you have a better and/or more elegant solution I'm glad to hear from you.
So, as my first solution didn't work, here I'll post the definity solution that we (me and my colleges) found.
I have to say that this solution is not so simple as it uses a Linux server, Gitlab and Jenkins, so it require a relative complex environment and I'll not describe how to build it.
At the end, I'll suggest a simpler solution.
THE ENVIRONMENT
On my company we use Jenkins to schedule jobs, Gitlab to store source code and we have a Linux Server to execute small tasks using Shell Script. For this problem I used all three services besides Power BI API.
JENKINS
I use Jenkins to schedule a job that run montlhy. This job was created using the following configs:
Parameters: I created 2 parameters (workspace_id and dataset_id) so I can test the script at any environment (Power BI Workspace) by just changing the value of those parameters;
Schedule Job: this job was schedule to run every day 1 at 02:00 a.m. As Jenkins uses the same sintax as CRON (I thing it is just a intermediate between you and CRON) the value of this field is 0 2 1 * *.
Build: as here we have a remote linux server to execute the scripts, I used a Execute shell script on remote host using ssh. I don't know why on Jenkins you can not execute the curl command direct on the job, it just didn't work, so I had to split the solution into both Jenkins and Linux server. At SSH site you have to select the credentials (previously created by my team) and at command are the commands bellow:
#Navigate to the script shell directory
cd "script-shell-script/"
# pulls the last version of the script. If you aren't using Gitlab,
# remove this command
git pull
# every time git pulls a new file version, it has read access.
# This command allows the execution of the filechmod +x powerbi_refresh_dataset.sh
# make a call to the file passing as parameter the workspace id and dataset id
./powerbi_refresh_dataset.sh $ID_WORKSPACE $ID_DATASET
SHELL SCIPT
As you already imagine, the core solution is the content of powerbi_refresh_dataset.sh. But, before going, there, you must understand how Power BI API works and you have to configure your Power BI environment to make API calls work. So, please, make sure that you already have your Principal Service properly configured by following this tutorial: https://learn.microsoft.com/en-us/power-bi/developer/embedded/embed-service-principal
Once you got your object_id, client_id and client_secret you can create your shell script file. Bellow is the code of my .sh file.
# load OBJECT_ID, CLIENT_ID and CLIENT_SECRET as environment variables
source credential_file.sh
# This command retrieves a new token from Microsoft Credentials Manager
token_msg=$(curl -X POST "https://login.windows.net/$OBJECT_ID/oauth2/token" \
-H 'Content-Type: application/x-www-form-urlencoded' \
-H 'Accept: application/json' \
-d 'grant_type=client_credentials&resource=https://analysis.windows.net/powerbi/api&client_id='$CLIENT_ID'&client_secret='$CLIENT_SECRET
)
# Extract the token from the response message
token=$(echo "$token_msg" | jq -r '.access_token')
# Ask Power BI to refresh dataset
refresh_msg=$(curl -X POST 'https://api.powerbi.com/v1.0/myorg/groups/'$1'/datasets/'$2'/refreshes' \
-H 'Authorization: Bearer '$token \
-H 'Content-Type: application/json' \
-d '{"notifyOption": "NoNotification"}')
And here goes some explanation. The first command is source credential_file.sh which loads 3 variables (OBJECT_ID, CLIENT_ID and CLIENT_SECRET). The intention here is to separate confidential info from the script so I can store the main script file on a version control (Git) and not disclosure any sensitivy information. So, besides powerbi_refresh_dataset.sh file you must have credential_file.sh at the same directory and with the following content:
OBJECT_ID=OBJECT_ID_VALUE
CLIENT_ID=CLIENT_ID_VALUE
CLIENT_SECRET=CLIENT_SECRET_VALUE
It's important to say that if you are using Git or any other version control, only powerbi_refresh_dataset.sh file goes to version control and credential_file.sh file must remain only at your Linux Server. I suggest you to save it's content into a password store application like keepass, as CLIENT_SECRET is not possible to retrieve.
FINAL CONSIDERATIONS
So above is the most relevant info of my solution. As you can see I'm ommiting (intentionally) how to build the environment and make them talk (jekins with linux, jenkins with Git and so on).
If all you have is a Linux or Windows host, I suggest you this:
Linux Host
On this simpler environment, just create the powerbi_refresh_dataset.sh and credential_file.sh, place it at any directory and create a CRON task to call powerbi_refresh_dataset as many time as you wish.
Windows Host
On windows you can do almost the same as on Linux, but you'll have to replace the content of shell script file by Power Shell command (google it) and use the Scheduled Task to regularly execute you Power Shell file.
Well, I think this would help you. I know it's not a complete answer as it will only works if you have a similar environment, but I hope that the final tips might help you.
Best regards
The Solution
First let me resume the solution. I just putted a condition execution at the end of each query that checks if today is the day where new data must be uploaded or not. If yes, it returns the step to be executed, if not, it raises a error.
There is many ways to implement that and I'll go from the simplest form to the more complex one.
Simplest Version: checking if it's the day to load new data directly at the query
This is the simplest way to implement the solution, but, depending on your dataset it may not be the smartest one.
Lets say you have this foo query:
let
step1 = ...,
...,
...,
step10 = SomeFunction(Somevariable, someparameter)
in
setp10
Now lets pretend you want that query to upload new data just on 1st day of the month. To do that, you just insert a condicional struction at in clause.
let
step1 = ...,
...,
...,
step10 = SomeFunction(Somevariable, someparameter)
in
if Date.Day(DateTime.LocalNow()) = 1 then setp10 else error "Today is not the day to load data"
At this example I just replaced the setp10 at the return of the query by this piece of code:if Date.Day(DateTime.LocalNow()) = 1 then setp10 else error "Today is not the day to load data". By doing that, setp10 will be the result of this query only if this query is been executed at day 1st of the month, otherwise, it will return a error.
And here it's worthy some explanation. Power Query is not a script language that runs at the same order that it's declared. So the fact the condicional statement was placed at the end of the query doesn't mean that all code above will be executed before the error is launched. As Power Query just executes what's necessary, the if... statement it will probably be the first one to be executed. For more info about how Power Query works behind the scene, I stronlgy recomend you this reading: https://bengribaudo.com/blog/2018/02/28/4391/power-query-m-primer-part5-paradigm
Using function
Now lets move foward. Lets say that your Dataset set has not only one, but many queries and all of them needs to be executed only once a month. In this case, a smart way to do that is by using what all other programming languages have to reuse block of code: create a function!
For this, create a new Blank Query and paste this code on its body:
(step) =>
let
result = if Date.Day(DateTime.LocalNow()) = 1 then step else error "Today is not the day to load data"
in
result
Now, at each query you'll call this function, sending the last setp as parameter. The function will check which day is today and return the same step passed as parameter if it's the day to load the data. Otherwise, it will return the error.
Bellow is the code of our query using our function called check_if_upload
let
step1 = ...,
...,
...,
step10 = SomeFunction(Somevariable, someparameter)
step11 = check_if_upload(step10)
in
step11
Using parameters
One final tip. As your query raises a error if today is not the day to upload day, it means that you can only test your ETL once a month, right? The error message also limite you to save you Power Query, which means that if you don't apply the modifications you can't upload the new Power Query version (having this implementations) to Power BI Service.
Well, you could change the value of the day verification into the function, but it's let's say, a little dummy.
A more ellegante way to change this parameter is by using parameters. So, lets do it. Create a parameter (I'll call it Upload Day) as a number type. Now, all you have to do is use this parameter at your function. It will look like this:
(step) =>
let
result = if Date.Day(DateTime.LocalNow()) = #"Upload Day" then step else error "Today is not the day to load data"
in
result
That's it. Now you can change the upload day directly at Power BI Service, just changing this parameter at the dataset (click on dataset name and goes to Settings >> Parameters).
Hope you neiled it and that its helpful for you.
Best regards.
I have to cheack the status of workflow weather that workflow completed within scheduled time or not in sql query format. And also send an email of workflow status like 'completed within time ' or not 'completed within time'. So, please help me out
You can do it either using option1 or option 2.
You need access to repository meta database.
Create a post session shell script. You can pass workflow name and benchmark value to the shell script.
Get workflow run time from repository metadata base.
SQL you can use -
SELECT WORKFLOW_NAME,(END_TIME-START_TIME)*24*60*60 diff_seconds
FROM
REP_WFLOW_RUN
WHERE WORKFLOW_NAME='myWorkflow'
You can then compare above value with benchmark value. Shell script can send a mail depending on outcome.
you need to create another workflow to check this workflow.
If you do not have access to Metadata, please follow above steps except metadata SQL.
Use pmcmd GetWorkflowDetails to check status, start and end time for a workflow.
pmcmd GetWorkflowDetails -sv service -d domain -f folder myWorkflow
You can then grep start and end time from there, compare them with benchmark values. The problem is the format etc. You need little bit scripting here.
My tasks are added to Task Queue, but nothing executed automatically. I need to click the button "Run now" to run tasks, tasks are executed without problem. Have I missed some configurations ?
I use default queue configuration, standard App Engine with python 27.
from google.appengine.api import taskqueue
taskqueue.add(
url='/inserturl',
params={'name': 'tablename'})
This documentation is for the API you are now mentioning. The idea would be the same: you need to specify the parameter for when you want the task to be executed. In this case, you have different options, such as countdown or eta. Here is the specific documentation for the method you are using to add a task to the queue (taskqueue.add)
ORIGINAL ANSWER
If you follow this tutorial to create queues and tasks, you will see it is based on the following github repo. If you go to the file where the tasks are created (create_app_engine_queue_task.py). There is where you should specify the time when the task must be executed. In this tutorial, to finally create the task, they use the following command:
python create_app_engine_queue_task.py --project=$PROJECT_ID --location=$LOCATION_ID --queue=$QUEUE_ID --payload=hello
However, it is missing the time when you want to execute it, it should look like this
python create_app_engine_queue_task.py --project=$PROJECT_ID --location=$LOCATION_ID --queue=$QUEUE_ID --payload=hello --in_seconds=["countdown" for when the task will be executed, in seconds]
Basically, the key is in this part of the code in create_app_engine_queue_task.py:
if in_seconds is not None:
# Convert "seconds from now" into an rfc3339 datetime string.
d = datetime.datetime.utcnow() + datetime.timedelta(seconds=in_seconds)
# Create Timestamp protobuf.
timestamp = timestamp_pb2.Timestamp()
timestamp.FromDatetime(d)
# Add the timestamp to the tasks.
task['schedule_time'] = timestamp
If you create the task now and you go to your console, you will see you task will execute and disappear from the queue in the amount of seconds you specified.
All of sudden the AWS CloudWatch logs started to open from the middle, or from the beginning of the log stream. They used to open from the end of the log stream showing the latest lines. I wonder if this is something that I can configure or has AWS just changed something.
It is really frustrating when you want to follow how the progresses of your lambda app but cannot do it because when you open the log in AWS it shows the first lines in that log stream, and in order to see the latest lines you need to set a custom time frame. And it doesn't allow you to set a future timestamp into the end time, which forces you to always update the end time to see the new lines. I hope there is a solution for getting it to open the trail of the log stream.
Try clicking on ALL in timeframe option? For me recently they started setting start time, and logs are visible from that time onwards, like you described, but when I click on ALL, it shows logs regularly, like it used to.
Second thing you can do is to have rolling start of logs (like, last 15 minutes, 1 hour).
To do that, add:
;start=PT1H at the end of your URL if you want last hour
;start=PT15M at the end of your URL if you want last 15 minutes
You can change numbers depending on timeframe you want
I have a Lambda function and its logs in Cloudwatch (Log group and Log Stream). Is it possible to filter (in Cloudwatch Management Console) all logs that contain "error"? For example logs containing "Process exited before completing request".
In Log Groups there is a button "Search Events". You must click on it first.
Then it "changes" to "Filter Streams":
Now you should just type your filter and select the beginning date-time.
So this is kind of a side issue, but it was relevant for us. (I posted this to another answer on StackOverflow but thought it would be relevant to this conversation too)
We've noticed that tailing and searching logs gets really slow after a log group has a lot of Log Streams in it, like when an AWS Lambda Function has had a lot of invocations. This is because "tail" type utilities and searching need to connect to each log stream to run. Log Events get expired and deleted due to the policy you set on the Log Group itself, but the Log Streams never get cleaned up. I made a few little utility scripts to help with that:
https://github.com/four43/aws-cloudwatch-log-clean
Hopefully that save you some agony over waiting for those logs to get searched.
You can also use CloudWatch Insights (https://aws.amazon.com/about-aws/whats-new/2018/11/announcing-amazon-cloudwatch-logs-insights-fast-interactive-log-analytics/) which is an AWS extension to CloudWatch logs that gives a pretty powerful query and analytics tool. However it can be slow. Some of my queries take up to a minute. Okay, if you really need that data.
You could also use a tool I created called SenseLogs. It downloads CloudWatch data to your browser where you can do queries like you ask about. You can use either full text and search for "error" or if your log data is structured (JSON), you can use a Javascript like expression language to filter by field, eg:
error == 'critical'
Posting an update as CloudWatch has changed since 2016:
In the Log Groups there is a Search all button for a full-text search
Then just type your search: