This action enables export of session data for all of your linked apps. If you
have streaming export enabled, this will start exporting session data in
realtime as well.
This action enables streaming for all of your linked apps. If you have
Firebase sessions export enabled, this will enable streaming export for session
data as well.
Unlink fromBigQuery
Unlinking fromBigQuerystops the corresponding dataset(s) inBigQueryfrom being populated.
Be aware of the following:
Any data already exported intoBigQuerywill persist for the allowed
retention time, and storage and query charges may still apply. You can
manually delete your dataset(s) to prevent any further billing.
If you haveBigQuerydata stored in other services, that data might
be governed by different terms for data persistence.
You can unlink fromBigQueryat the Firebase project level, at the
product-level, or at the app-level for a specific product.
Firebase exports data to the dataset location you selected during setup.
This location applies to both theCrashlyticsdataset and the
Firebase sessions dataset (if sessions data is enabled for export).
This location is only applicable for the data exported intoBigQuery, and it does not impact the location of data stored for
use in theCrashlyticsdashboard of theFirebaseconsole or in
Android Studio.
After a dataset is created, its location can't be changed, but you can
copy the dataset to a different location or manually move (recreate) the
dataset in a different location. To learn more, seeChange the location for existing exports.
Firebase sets up daily syncs of your batch data toBigQuery.
After linking toBigQuery, it may take up to 48 hours for theinitialbatch data export.
The daily sync happens once per day, regardless of any scheduled export
that you might have set up inBigQuery. Note that the timing and
duration of the sync job can change, so we don't recommend scheduling
downstream operations or jobs based on a specific timing of the export.
For each linked app, this export includes a batch table containing the data
from the daily sync.
You canmanually schedule data backfillsfor the batch table up to the past 30 daysorfor the most recent date
when you enabled export toBigQuery(whichever is most recent).
Note that if you enabled export ofCrashlyticsdatabeforemid-October 2024, you can also backfill 30 days prior to the day you enabled
export.
Each linked app will also have its own realtime table containing constantly
updating data (in addition to the app's batch table for daily batch export).
After enabling streaming, it may take up to 1 hour for data to begin
streaming.
Are you not seeing data in your realtime table?
Make sure that you've sent at least two events from your app toCrashlyticsand waited a couple minutes after sending them.
Make sure your Firebase project is on the pay-as-you-go Blaze pricing plan. You can check this by looking in the bottom-left corner of theFirebaseconsole.
If there's still no data in your realtime table after sending two events and
waiting a couple minutes:
Make sure the service accountservice-PROJECT_NUMBER@gcp-sa-crashlytics.iam.gserviceaccount.comis in your Firebase project and has theFirebase Crashlytics Service Agentrole. You can check this in theIAMpage of theGoogle Cloudconsole(make sure to select the checkbox forInclude Google-provided role grants).
Send at least two events toCrashlyticsand wait a couple minutes.
By default, data is exported toBigQueryin a daily batch export.
Additionally, you can stream yourCrashlyticsdata and Firebase sessions in
realtime withBigQuerystreaming.
You can use streamed data for any purpose that requires live data, such as
presenting information in a live dashboard, watching a rollout live, or
monitoring application problems that trigger alerts and custom workflows.
When you enable streaming export toBigQuery, you'll also have
realtime tables (in addition to batch tables). Both types of tables will have
the samedataset schema,
but here some important differences between batch tables and realtime tables:
Batch table
Realtime table
Data is exported once daily.
Events are durably stored before batch writing toBigQuery.
The batch table is ideal for long-term analysis and identifying trends over time
because we durably store events before writing them, and they can be backfilled
to the table for up to 30 days*. When we write data to your realtime table, we
immediately write it toBigQuery, and so it is ideal for live
dashboards and custom alerts. These two tables can becombined with a stitching queryto get the benefits of both.
By default, the realtime table has a partition expiration time of 30 days. To
learn how to modify this, seeSet the partition expirationin theBigQuerydocumentation.
If your Firebase project is on the no-cost Spark pricing plan, you can use theBigQuerysandbox,
which provides no-cost access toBigQuery. For information about theBigQuerysandbox and its capabilities, seeUsing theBigQuerysandbox.
If your Firebase project is on the pay-as-you-go Blaze pricing plan, you can use all the
features ofBigQuery. Your use ofBigQueryis subject toBigQuerypricing,
which includes limited no-cost use.
Upgrade to the new export infrastructure forBigQuery
In mid-October 2024,Crashlyticslaunched a new infrastructure forbatchexport ofCrashlyticsdata intoBigQuery.
If you enabled batch exportafterOctober 2024, then your Firebase
project is automatically using the new export infrastructure.No action is
needed.
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