Our company has many schedule reports in BigQuery that generate aggregation tables of Google Analytics data. Because we cannot control when Google Analytics data is imported into our BigQuery environment we keep getting days with no data.
This means we then have to manually run the data for missing days.
I have edited my schedule query to keep pushing back the time of day the scheduled query runs however it is now running around 8 AM. These queries are for reports for stakeholders and stakeholders are requesting them earlier. Is there any way to ensure Google Analytics export to BigQuery processing times?
You may also think about a Scheduled Query solution that reruns at a later time if the requested table isn't available yet.
You can't current add a conditional trigger to a BigQuery scheduled query.
You could manually add a fail safe to your query to check for table from yesterday using a combination of the code below and DATE_SUB(CURRENT_DATE(), INTERVAL 1 DAY):
SELECT
MAX(FORMAT_TIMESTAMP('%F %T', TIMESTAMP(PARSE_DATE('%Y%m%d',
REGEXP_EXTRACT(_TABLE_SUFFIX,r'^\d\d\d\d\d\d\d\d'))) ))
FROM `DATASET.ga_sessions_*` AS ga_sessions
Obviously this will fail if the conditions are not met and will not retry, which I understand is not an advancement on your current setup.
I've encountered this many times in the past and eventually had to move my data pipelines to another solution, as scheduled queries are still quite simplistic.
I would recommend you take a look at CRMint for simple pipelines into BigQuery:
https://github.com/google/crmint
If you still find this too simplistic then you should look at Google Cloud Composer, where you can check a table exists before running a particular job in a pipeline:
Related
I'm looking for some best (simplest;)) practices here.
I have Google Analytics data that is send to BigQuery on a daily basis. I have a query running on a daily basis that uses the data from the previous day's table.
However, I can't be sure this table and the data is there at the time the query runs and I'd like to check if it does. If it isn't there I want to retry later.
Ideally I have some monitoring/alerting around this as well.
Of course this can be done within the Google Cloud in many ways, I'm looking for some best practices how others do this?
I'm used to working with Airflow, but using Composer just for this seems a bit over the top. Cloud Run would be an option and I'm sure there are others. Also I've seen this question discussing how to handle a dependency in SQL, I'm just not sure if I could have it retry using just SQL as well?
EDIT:
I've got the check for the table working in SQL. I guess I just have to see if BigQuery has a way to build in delay like 'WAITFOR'
I'm looking for a cloud service that can do advanced statistics calculations on a large amount of votes submitted by users, in "real time".
In our app, users can submit different kind of votes like picking a favorite, rating 1-5, say yes/no etc. on various topics.
We also want to show "live" statistics to the user, showing the popularity of a person etc. This will be generated by a rather complex SQL where we are calculating the average number of times a person was picked as favorite, divided by total number of votes and the number of games in which the person has been participating etc. And the score for the latest X games should count higher than the overall score for all games. This is just an example, there are several other SQL queries with similar complexity.
All our presentable data (including calculated statistics) is served from Firestore documents, and the votes will be saved as Firestore documents.
Ideally, the Firebase-backend (functions, firestore etc) should not need to know about the query logic.
What I wish for is a pay as you go cloud service that does the following:
I define some schemas and set up the queries we need for the statistics we have (15-20 different SQLs). Like setting up views in MySQL
On every vote, we push the vote data to this service, which will store it in a row.
The service should then, based on its knowledge about the defined queries, and the content of the pushed vote data, determine which statistics that are affected by the newly added row, and recalculate these. A specific vote type can affect one or more statistics.
Every time a statistic is recalculated, the result should be automatically pushed back to our Firebase backend (for instance by calling an HTTPS endpoint that hits a cloud function) - so we can update the relevant Firestore documents.
The service should be able to throttle the calculations, like only regenerating new statistics every 1 minute despite having several votes per second on the same topic.
Is there any product like this in the market? Or can it be built by combining available cloud services? And what is the official term for such a product, if I should search for it myself?
I know that I can probably build a solution like this myself, and run it on a cloud hosted database server, which can scale as our need grows - but I believe that I'm not the first developer with a need of this, so I hope that someone has solved it before me :)
You can leverage the existing cloud services available on the Google Cloud Platform.
Google BigQuery, Google Cloud Firestore, Google App Engine (CRON Jobs), Google Cloud Tasks
The services can be used to solve the problems mentioned above:
1) Google BigQuery : Here you can define schema for the data on which you're going to run the SQL queries. BigQuery supports Standard and legacy SQL queries.
2) Every vote can be pushed to the defined BigQuery tables using its streaming insert service.
3) Every vote pushed can trigger the recalculation service which calculates the statistics by executing the defined SQL queries and the query results can be stored as documents in collections in Google Cloud Firestore.
4) Google Cloud Firestore: Here you can store the live statistics of the user. This is a real time database, so you'll be able to configure listeners for the modifications to the statistics and show the modifications as soon as the statistics are recalculated.
5) In the same service which inserts every vote, create a new record with a "syncId" in an another table. The idea is to group a number of votes cast in a particular interval to a its corresponding syncId. The syncId can be suffixed with a timestamp. According to your requirement a particular time interval can be set so that the recalculation can be triggered using CRON jobs service which invokes the recalculation service within the interval. Once the recalculation related to a particular syncId is completed the record corresponding to the syncId should be marked as completed.
We are leveraging the above technologies to build a web application on Google Cloud Platform, where the inputs are recorded on Google Firestore and then stream-inserted to Google BigQuery. The data stored in BigQuery is queried after 30 sec of each update using SQL queries and the query results are stored in Google Cloud Firestore to serve dashboards which are automatically updated using listeners configured for the collection in which the dashboard information is stored.
To track BQ usage we created a new dataset and configured it in Billing export. But after waiting for a day also the dataset seems to be empty as no new tables is created.
Is there any other setup needs to be done for this to work.
Refer this link,
https://cloud.google.com/billing/docs/how-to/export-data-bigquery
Thanks and regards,
Gour
You just need to follow the How to enable billing export to BigQuery steps to begin using this functionality. Keep in mind that you have to wait certain time to start seeing your data, as mentioned in the Export Billing Data to BigQuery documentation.
After you enable BigQuery export, it might take a few hours to start seeing your data. Billing data automatically exports your data to BigQuery in regular intervals, but the frequency of updates in BigQuery varies depending on the services you're using.
In case you continue having this issue, I recommend you to take a look the Issue Tracker tool that you can use to raise a BigQuery ticket in order to verify this scenario with the Google Technical Support Team. Since this is an automated process, you might need some of their help to review your Project's internal configuration.
I've been trying out BigQuery for a week or so. I've linked BigQuery to one of our organizations Firebase projects. I used my free trial of Google Cloud Platform for this test. I didn't want to use BQ anymore, thus I deactived the link between Firebase and BQ. I also degraded our account from Blaze back to Spark. I assumed that, with the deactivation of the Blaze subscription and link between Firebase and BQ, no queries would be ran in BQ. This happened almost a week ago. However, this did not happen; the last query ran yesterday. I am not sure if I will be billed for these queries.
How do I cancel all queries in BQ in the future? I can't seem to find a(n easy) way to do that.
THanks in advance.
I have some simple weekly aggregates from Google analytics that i'd like to store somewhere. The reason for storing is because if I run a query against too much data in google analytics, it becomes sampled and I want it to be totally accurate.
What is the best way to solve this?
My thoughts are:
1) Write a process in bigquery to append the data each week to a permanent dataset
2) Use an API that gets the data each week and stores the data in a google spreadsheet (appending a line each time)
What is the best recommendation for my problem - and how do I go about executing it?
Checking your previous questions, we see that you already use Bigquery.
When you run a query against the Google Analytics tables that is not sampled, as that has all the data in it. There is no need to store as you can query every time you need.
In case if you want to store, and pay for the addition table, you can go ahead store in a destination table.
If you want to access quickly, try creating a view.
I suggest the following:
1) make a roll-up table for your weekly data - you can do that either by writing a query for it and running manually or with a script in a Google Spreadsheet that uses the same query (using the API) and is scheduled to run every week. I tried a bunch of the tutorials out there and this one is the simplest to implement
2) depending on the data points you want, you can even use the Google Analytics API without having to go through BigQuery for this request, try pulling this report of yours from here . If it works there are a bunch of Google Sheets extensions that can make it a lot quicker to set up a weekly report. Or you can just code it yourself
Would that work for you?
thks!