Export Firebase Crashlytics data to BigQuery

You can export your Firebase Crashlytics data into BigQuery for further analysis. BigQuery lets you analyze the data using BigQuery SQL, export it to another cloud provider, and use it for visualization and custom dashboards with Google Data Studio.

Enable export to BigQuery

Note: Make sure that you have the required level of access to view or manage settings for data export to BigQuery.

1. In the Firebase console, go to the Integrations page.

2. In the BigQuery card, click Link.

3. Follow the on-screen instructions to enable export to BigQuery.

   If you want near real-time access to your Crashlytics data in BigQuery, then consider upgrading to streaming export.

What happens when you enable export?

• You select the dataset location. After the dataset is created, the 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, see Change the location for existing exports.

  This location is only applicable for the data exported into BigQuery, and it does not impact the location of data stored for use in the Crashlytics dashboard of the Firebase console or in Android Studio.

  Note: The capability to select and change the location for data export is only available if you enabled export after mid-October 2024 or if you upgrade to the new export infrastructure.

• By default, all apps in your project are linked to BigQuery and any apps that you later add to the project are automatically linked to BigQuery. You can manage which apps send data.

• Firebase sets up daily syncs of your data to BigQuery.

  • After you link your project, you usually need to wait until the next day's sync for your first set of data to be exported to BigQuery.

  • The daily sync happens once per day, regardless of any scheduled export that you might have set up in BigQuery. 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.

• Firebase exports a copy of your existing data to BigQuery. The initial propagation of data for export may take up to 48 hours.

  • For each linked app, this export includes a batch table containing the data from the daily sync.

  • You can manually schedule data backfills for the batch table up to the past 30 days or for the most recent date when you enabled export to BigQuery (whichever is most recent).

  Note that if you enabled export of Crashlytics data before mid-October 2024, you can also backfill 30 days prior to the day you enabled export.

• If you enable Crashlytics streaming export to BigQuery, all linked apps will also have a realtime table containing constantly updating data.

To deactivate export to BigQuery, unlink your project in the Firebase console.

What data is exported to BigQuery?

Firebase Crashlytics data is exported into a BigQuery dataset named firebase_crashlytics. By default, individual tables will be created inside the Crashlytics dataset for each app in your project. Firebase names the tables based on the app's identifier, with periods converted to underscores, and a platform name appended to the end.

For example, data for an Android app with the package name com.google.test would be in a table named com_google_test_ANDROID. This batch table is updated once every day. If you enable Crashlytics streaming export to BigQuery, then Crashlytics data will also be streamed in realtime to a table named com_google_test_ANDROID_REALTIME.

Note: You may also choose to opt out of exporting data into BigQuery for specific apps in your project from within the Firebase console.

Each row in a table represents an event that occurred in the app, including crashes, non-fatal errors, and ANRs.

Crashlytics streaming export to BigQuery

You can stream your Crashlytics data in realtime with BigQuery streaming. You can use it 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.

Note: Crashlytics streaming export to BigQuery is not available for BigQuery sandbox.

When you enable Crashlytics streaming export to BigQuery, in addition to the batch table you will also have a realtime table. Here are the differences you should be aware of between the tables:

Batch table	Realtime table
Data is exported once daily. Events are durably stored before batch writing to BigQuery. Data can be backfilled up to 30 days prior*.	Data is exported in real time. No backfilling is available.

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 to BigQuery, and so it is ideal for live dashboards and custom alerts. These two tables can be combined with a stitching query to get the benefits of both.

By default, the realtime table has a partition expiration time of 30 days. To learn how to modify this, see Set the partition expiration in the BigQuery documentation.

^{* See details about backfill support in Upgrade to the new export infrastructure.}

Enable Crashlytics streaming export to BigQuery

1. In the Firebase console, go to the Integrations page.

2. In the BigQuery card, click Manage.

3. Select the Include streaming checkbox.

This action enables streaming for all of your linked apps.

What can you do with the exported data?

Exports to BigQuery contain raw crash data including device type, operating system, exceptions (Android apps) or errors (Apple apps), and Crashlytics logs, as well as other data.

Review exactly what Crashlytics data is exported and its table schema later in this page.

Use a Data Studio template

To enable realtime data in your Data Studio template, follow the instructions in Visualizing exported Crashlytics data with Data Studio.

Create views

You can transform queries into views using the BigQuery UI. For detailed instructions, see Create views in the BigQuery documentation.

Run queries

The following examples demonstrate queries that you can run on your Crashlytics data to generate reports that aggregate crash event data into more easily-understood summaries. Since these types of reports aren't available in the Crashlytics dashboard of the Firebase console, they can supplement your analysis and understanding of crash data.

Example 1: Crashes by day

After working to fix as many bugs as possible, you think your team is finally ready to launch your new photo-sharing app. Before you do, you want to check the number of crashes per day for the past month, to be sure your bug-bash made the app more stable over time.

Here's an example query for an Android app. For an iOS app, use its bundle ID and IOS (instead of package name and ANDROID).

SELECT
  COUNT(DISTINCT event_id) AS number_of_crashes,
  FORMAT_TIMESTAMP("%F", event_timestamp) AS date_of_crashes
FROM
 `PROJECT_ID.firebase_crashlytics.PACKAGE_NAME_ANDROID`
GROUP BY
  date_of_crashes
ORDER BY
  date_of_crashes DESC
LIMIT 30;

Example 2: Find the most pervasive crashes

To properly prioritize production plans, you want to find the top 10 most pervasive crashes in your app. You produce a query that provides the pertinent points of data.

Here's an example query for an Android app. For an iOS app, use its bundle ID and IOS (instead of package name and ANDROID).

SELECT
  DISTINCT issue_id,
  COUNT(DISTINCT event_id) AS number_of_crashes,
  COUNT(DISTINCT installation_uuid) AS number_of_impacted_user,
  blame_frame.file,
  blame_frame.line
FROM
  `PROJECT_ID.firebase_crashlytics.PACKAGE_NAME_ANDROID`
WHERE
  event_timestamp >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(),INTERVAL 168 HOUR)
  AND event_timestamp < CURRENT_TIMESTAMP()
GROUP BY
  issue_id,
  blame_frame.file,
  blame_frame.line
ORDER BY
  number_of_crashes DESC
LIMIT 10;

Example 3: Top 10 crashing devices

Fall is new phone season! Your company knows that this also means it's new device-specific issues season — especially for Android. To get ahead of the looming compatibility concerns, you put together a query that identifies the 10 devices that experienced the most crashes in the past week (168 hours).

Here's an example query for an Android app. For an iOS app, use its bundle ID and IOS (instead of package name and ANDROID).

SELECT
  device.model,
COUNT(DISTINCT event_id) AS number_of_crashes
FROM
  `PROJECT_ID.firebase_crashlytics.PACKAGE_NAME_ANDROID`
WHERE
  event_timestamp >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 168 HOUR)
  AND event_timestamp < CURRENT_TIMESTAMP()
GROUP BY
  device.model
ORDER BY
  number_of_crashes DESC
LIMIT 10;

Example 4: Filter by custom key

You're a game developer who wants to know which level of your game experiences the most crashes.

To help track that stat, you set a custom Crashlytics key called current_level, and update it every time the user reaches a new level.

Swift

Crashlytics.sharedInstance().setIntValue(3, forKey: "current_level");

Objective-C

CrashlyticsKit setIntValue:3 forKey:@"current_level";

Java

Crashlytics.setInt("current_level", 3);

With that key in your export to BigQuery, you can then write a query to report the distribution of current_level values associated with each crash event.

Here's an example query for an Android app. For an iOS app, use its bundle ID and IOS (instead of package name and ANDROID).

SELECT
COUNT(DISTINCT event_id) AS num_of_crashes,
  value
FROM
  `PROJECT_ID.firebase_crashlytics.PACKAGE_NAME_ANDROID`
UNNEST(custom_keys)
WHERE
  key = "current_level"
GROUP BY
  key,
  value
ORDER BY
  num_of_crashes DESC

Example 5: User ID extraction

You have an Android app in early access. Most of your users love it, but three have experienced an unusual number of crashes. To get to the bottom of the problem, you write a query that pulls all the crash events for those users, using their user IDs.

Here's an example query for an Android app. For an iOS app, use its bundle ID and IOS (instead of package name and ANDROID).

SELECT *
FROM
  `PROJECT_ID.firebase_crashlytics.PACKAGE_NAME_ANDROID`
WHERE
  user.id IN ("USER_ID_1", "USER_ID_2", "USER_ID_3")
ORDER BY
  user.id
 

Example 6: Find all users facing a particular crash issue

Your team has accidentally released a critical bug to a group of beta testers. Your team was able to use the query from the "Find most pervasive crashes" example above to identify the specific crash issue ID. Now your team would like to run a query to extract the list of app users who were impacted by this crash.

Here's an example query for an Android app. For an iOS app, use its bundle ID and IOS (instead of package name and ANDROID).

SELECT user.id as user_id
FROM
  `PROJECT_ID.firebase_crashlytics.PACKAGE_NAME_ANDROID`
WHERE
  issue_id = "ISSUE_ID"
  AND application.display_version = "APP_VERSION"
  AND user.id != ""
ORDER BY
  user.id;

Example 7: Number of users impacted by a crash issue, broken down by country

Your team has detected a critical bug during the rollout of a new release. You were able to use the query from the "Find most pervasive crashes" example above to identify the specific crash issue ID. Your team would now like to see if this crash has spread to users in different countries around the world.

To write this query, your team will need to do the following:

1. Enable export of Google Analytics data to BigQuery. See Export project data to BigQuery.

2. Update your app to pass a user ID into both the Google Analytics SDK and the Crashlytics SDK.

   Swift

   Crashlytics.sharedInstance().setUserIdentifier("123456789");
   Analytics.setUserID("123456789");
   

   Objective-C

   CrashlyticsKit setUserIdentifier:@"123456789";
   FIRAnalytics setUserID:@"12345678 9";
   

   Java

   Crashlytics.setUserIdentifier("123456789");
   mFirebaseAnalytics.setUserId("123456789");
   

3. Write a query that uses the user ID field to join events in the Google Analytics dataset with crashes in the Crashlytics dataset.

   Here's an example query for an Android app. For an iOS app, use its bundle ID and IOS (instead of package name and ANDROID).

   SELECT DISTINCT c.issue_id, a.geo.country, COUNT(DISTINCT c.user.id) as num_users_impacted
   FROM `PROJECT_ID.firebase_crashlytics.PACKAGE_NAME_ANDROID` c
   INNER JOIN  `PROJECT_ID.analytics_TABLE_NAME.events_*` a on c.user.id = a.user_id
   WHERE
     c.issue_id = "ISSUE_ID"
     AND a._TABLE_SUFFIX BETWEEN '20190101'
     AND '20200101'
   GROUP BY
     c.issue_id,
     a.geo.country,
     c.user.id

Example 8: Top 5 issues so far today

Note: This example requires enabling Crashlytics streaming export to BigQuery.

Here's an example query for an Android app. For an iOS app, use its bundle ID and IOS (instead of package name and ANDROID).

SELECT
  issue_id,
  COUNT(DISTINCT event_id) AS events
FROM
  `PROJECT_ID.firebase_crashlytics.PACKAGE_NAME_ANDROID_REALTIME`
WHERE
  DATE(event_timestamp) = CURRENT_DATE()
GROUP BY
  issue_id
ORDER BY
  events DESC
LIMIT
  5;

Example 9: Top 5 issues since DATE, including today

Note: This example requires enabling Crashlytics streaming export to BigQuery.

You can also combine the batch and realtime tables with a stitching query to add realtime information to the reliable batch data. Since event_id is a primary key, you can use DISTINCT event_id to dedupe any common events from the two tables.

Here's an example query for an Android app. For an iOS app, use its bundle ID and IOS (instead of package name and ANDROID).

SELECT
  issue_id,
  COUNT(DISTINCT event_id) AS events
FROM (
  SELECT
    issue_id,
    event_id,
    event_timestamp
  FROM
    `PROJECT_ID.firebase_crashlytics.PACKAGE_NAME_ANDROID_REALTIME`
  UNION ALL
  SELECT
    issue_id,
    event_id,
    event_timestamp
  FROM
    `PROJECT_ID.firebase_crashlytics.PACKAGE_NAME_ANDROID`)
WHERE
  event_timestamp >= "YYYY_MM_DD"
GROUP BY
  issue_id
ORDER BY
  events DESC
LIMIT
  5;

Understand the Crashlytics schema in BigQuery

When you set up Crashlytics data export to BigQuery, Firebase exports recent events (crashes, non-fatal errors, and ANRs), including events from up to two days before the link, with the option to backfill up to 30 days.

From that point until you deactivate the export, Firebase exports Crashlytics events on a daily basis. It can take a few minutes for the data to be available in BigQuery after each export.

Datasets

Crashlytics creates a new dataset in BigQuery for Crashlytics data. The dataset covers your entire project, even if it has multiple apps.

Tables

Crashlytics creates a table in the dataset for each app in your project, unless you've opted out of exporting data for that app. Firebase names the tables based on the app's identifier, with periods converted to underscores, and a platform name appended to the end.

For example, data for an Android app with the package name com.google.test would be in a table named com_google_test_ANDROID, and realtime data (if enabled) would be in a table named com_google_test_ANDROID_REALTIME

Tables contain a standard set of Crashlytics data in addition to any custom Crashlytics keys defined by you in your app.

Rows

Each row in a table represents an error the app encountered.

Columns

The columns in a table are identical for crashes, non-fatal errors, and ANRs. If Crashlytics streaming export to BigQuery is enabled, then the realtime table will have the same columns as the batch table. Note that you may have columns in rows that represent events that don't have stack traces.

The columns within the export are listed in this table:

Field name	Data type	Description
platform	STRING	The platform of the app as registered in the Firebase project (valid values: IOS or ANDROID)
bundle_identifier	STRING	The unique identifier for the app as registered in the Firebase project (for example, com.google.gmail) For Apple platform apps, this is the bundle ID of the app. For Android apps, this is the package name of the app.
event_id	STRING	The unique ID for the event
is_fatal	BOOLEAN	This field is deprecated. Use error_type instead. Whether the app crashed
error_type	STRING	The error type of the event (for example, FATAL, NON_FATAL, ANR, etc.)
issue_id	STRING	The issue associated with the event
variant_id	STRING	The issue variant associated with this event Note that not all events have an associated issue variant.
event_timestamp	TIMESTAMP	When the event occurred
device	RECORD	The device the event occurred on
device.manufacturer	STRING	The device manufacturer
device.model	STRING	The device model
device.architecture	STRING	For example, X86_32, X86_64, ARMV7, ARM64, ARMV7S, or ARMV7K
memory	RECORD	The device's memory status
memory.used	INT64	Bytes of memory used
memory.free	INT64	Bytes of memory remaining
storage	RECORD	The device's persistent storage
storage.used	INT64	Bytes of storage used
storage.free	INT64	Bytes of storage remaining
operating_system	RECORD	The details of the OS on the device
operating_system.display_version	STRING	The version of the OS on the device
operating_system.name	STRING	The name of the OS on the device
operating_system.modification_state	STRING	Whether the device has been modified (for example, a jailbroken app is MODIFIED and a rooted app is UNMODIFIED)
operating_system.type	STRING	(Apple apps only) The type of OS running on the device (for example, IOS, MACOS, etc.)
operating_system.device_type	STRING	The type of device (for example, MOBILE, TABLET, TV, etc.); also known as "device category"
application	RECORD	The app that generated the event
application.build_version	STRING	The app's build version
application.display_version	STRING
user	RECORD	(Optional) Info collected about the app's user
user.name	STRING	This field is deprecated; do not use this field. (Optional) The user's name
user.email	STRING	This field is deprecated; do not use this field. (Optional) The user's email address
user.id	STRING	(Optional) An app-specific ID associated with the user
custom_keys	REPEATED RECORD	Developer-defined key-value pairs
custom_keys.key	STRING	A developer-defined key
custom_keys.value	STRING	A developer-defined value
installation_uuid	STRING	An ID that identifies a unique app and device installation
crashlytics_sdk_versions	STRING	The Crashlytics SDK version that generated the event
app_orientation	STRING	For example, PORTRAIT, LANDSCAPE, FACE_UP, FACE_DOWN, etc.
device_orientation	STRING	For example, PORTRAIT, LANDSCAPE, FACE_UP, FACE_DOWN, etc.
process_state	STRING	BACKGROUND or FOREGROUND
logs	REPEATED RECORD	Timestamped log messages generated by the Crashlytics logger, if enabled
logs.timestamp	TIMESTAMP	When the log was made
logs.message	STRING	The logged message
breadcrumbs	REPEATED RECORD	Timestamped Google Analytics breadcrumbs, if enabled
breadcrumbs.timestamp	TIMESTAMP	The timestamp associated with the breadcrumb
breadcrumbs.name	STRING	The name associated with the breadcrumb
breadcrumbs.params	REPEATED RECORD	Parameters associated with the breadcrumb
breadcrumbs.params.key	STRING	A parameter key associated with the breadcrumb
breadcrumbs.params.value	STRING	A parameter value associated with the breadcrumb
blame_frame	RECORD	The frame identified as the root cause of the crash or error
blame_frame.line	INT64	The line number of the file of the frame
blame_frame.file	STRING	The name of the frame file
blame_frame.symbol	STRING	The hydrated symbol, or raw symbol if it's unhydrateable
blame_frame.offset	INT64	The byte offset into the binary image that contains the code Unset for Java exceptions
blame_frame.address	INT64	The address in the binary image which contains the code Unset for Java frames
blame_frame.library	STRING	The display name of the library that includes the frame
blame_frame.owner	STRING	For example, DEVELOPER, VENDOR, RUNTIME, PLATFORM, or SYSTEM
blame_frame.blamed	BOOLEAN	Whether Crashlytics determined that this frame is the cause of the crash or error
exceptions	REPEATED RECORD	(Android only) Exceptions that occurred during this event. Nested exceptions are presented in reverse chronological order, which means that the last record is the first exception thrown
exceptions.type	STRING	The exception type (for example, java.lang.IllegalStateException)
exceptions.exception_message	STRING	A message associated with the exception
exceptions.nested	BOOLEAN	True for all but the last-thrown exception (meaning the first record)
exceptions.title	STRING	The title of the thread
exceptions.subtitle	STRING	The subtitle of the thread
exceptions.blamed	BOOLEAN	True if Crashlytics determines the exception is responsible for the error or crash
exceptions.frames	REPEATED RECORD	The frames associated with the exception
exceptions.frames.line	INT64	The line number of the file of the frame
exceptions.frames.file	STRING	The name of the frame file
exceptions.frames.symbol	STRING	The hydrated symbol, or raw symbol if it's unhydrateable
exceptions.frames.offset	INT64	The byte offset into the binary image that contains the code Unset for Java exceptions
exceptions.frames.address	INT64	The address in the binary image which contains the code Unset for Java frames
exceptions.frames.library	STRING	The display name of the library that includes the frame
exceptions.frames.owner	STRING	For example, DEVELOPER, VENDOR, RUNTIME, PLATFORM, or SYSTEM
exceptions.frames.blamed	BOOLEAN	Whether Crashlytics determined that this frame is the cause of the crash or error
error	REPEATED RECORD	(Apple apps only) non-fatal errors
error.queue_name	STRING	The queue the thread was running on
error.code	INT64	Error code associated with the app's custom logged NSError
error.title	STRING	The title of the thread
error.subtitle	STRING	The subtitle of the thread
error.blamed	BOOLEAN	Whether Crashlytics determined that this frame is the cause of the error
error.frames	REPEATED RECORD	The frames of the stacktrace
error.frames.line	INT64	The line number of the file of the frame
error.frames.file	STRING	The name of the frame file
error.frames.symbol	STRING	The hydrated symbol, or raw symbol if it's unhydrateable
error.frames.offset	INT64	The byte offset into the binary image that contains the code
error.frames.address	INT64	The address in the binary image which contains the code
error.frames.library	STRING	The display name of the library that includes the frame
error.frames.owner	STRING	For example, DEVELOPER, VENDOR, RUNTIME, PLATFORM, or SYSTEM
error.frames.blamed	BOOLEAN	Whether Crashlytics determined that this frame is the cause of the error
threads	REPEATED RECORD	Threads present at the time of the event
threads.crashed	BOOLEAN	Whether the thread crashed
threads.thread_name	STRING	The thread's name
threads.queue_name	STRING	(Apple apps only) The queue the thread was running on
threads.signal_name	STRING	The name of the signal that caused the app to crash, only present on crashed native threads
threads.signal_code	STRING	The code of the signal that caused the app to crash; only present on crashed native threads
threads.crash_address	INT64	The address of the signal that caused the application to crash; only present on crashed native threads
threads.code	INT64	(Apple apps only) Error code of the application's custom logged NSError
threads.title	STRING	The title of the thread
threads.subtitle	STRING	The subtitle of the thread
threads.blamed	BOOLEAN	Whether Crashlytics determined that this frame is the cause of the crash or error
threads.frames	REPEATED RECORD	The frames of the thread
threads.frames.line	INT64	The line number of the file of the frame
threads.frames.file	STRING	The name of the frame file
threads.frames.symbol	STRING	The hydrated symbol, or raw symbol if it's unhydreatable
threads.frames.offset	INT64	The byte offset into the binary image that contains the code
threads.frames.address	INT64	The address in the binary image which contains the code
threads.frames.library	STRING	The display name of the library that includes the frame
threads.frames.owner	STRING	For example, DEVELOPER, VENDOR, RUNTIME, PLATFORM, or SYSTEM
threads.frames.blamed	BOOLEAN	Whether Crashlytics determined that this frame is the cause of the error
unity_metadata.unity_version	STRING	The version of Unity running on this device
unity_metadata.debug_build	BOOLEAN	If this is a debug build
unity_metadata.processor_type	STRING	The type of processor
unity_metadata.processor_count	INT64	The number of processors (cores)
unity_metadata.processor_frequency_mhz	INT64	The frequency of the processor(s) in MHz
unity_metadata.system_memory_size_mb	INT64	The size of the system's memory in Mb
unity_metadata.graphics_memory_size_mb	INT64	The graphics memory in MB
unity_metadata.graphics_device_id	INT64	The identifier of the graphics device
unity_metadata.graphics_device_vendor_id	INT64	The identifier of the graphics processor's vendor
unity_metadata.graphics_device_name	STRING	The name of the graphics device
unity_metadata.graphics_device_vendor	STRING	The vendor of the graphics device
unity_metadata.graphics_device_version	STRING	The version of the graphics device
unity_metadata.graphics_device_type	STRING	The type of the graphics device
unity_metadata.graphics_shader_level	INT64	The shader level of the graphics
unity_metadata.graphics_render_target_count	INT64	The number of graphical rendering targets
unity_metadata.graphics_copy_texture_support	STRING	Support for copying graphics texture as defined in the Unity API
unity_metadata.graphics_max_texture_size	INT64	The maximum size dedicated to rendering texture
unity_metadata.screen_size_px	STRING	The size of the screen in pixels, formatted as width x height
unity_metadata.screen_resolution_dpi	STRING	The DPI of the screen as a floating point number
unity_metadata.screen_refresh_rate_hz	INT64	The refresh rate of the screen in Hz

Visualize exported Crashlytics data with Data Studio

Google Data Studio turns your Crashlytics datasets in BigQuery into reports that are easier to read, easier to share, and fully customizable.

To learn more about using Data Studio, try the Data Studio quickstart guide, Welcome to Data Studio.

Use a Crashlytics report template

Data Studio has a sample report for Crashlytics that includes a comprehensive set of dimensions and metrics from the exported Crashlytics BigQuery schema. If you have enabled Crashlytics streaming export to BigQuery, then you can view that data on the Realtime trends page of the Data Studio template.You can use the sample as a template to quickly create new reports and visualizations based on your own app's raw crash data:

1. Open the Crashlytics Data Studio Dashboard template.

2. Click Use Template in the upper-right corner.

3. In the New Data Source drop down, select Create New Data Source.

4. Click Select on the BigQuery card.

5. Select a table containing exported Crashlytics data by choosing My Projects > PROJECT_ID > firebase_crashlytics > TABLE_NAME.

   Your batch table is always available to select. If Crashlytics streaming export to BigQuery is enabled, then you can select your realtime table instead.

6. Under Configuration, set Crashlytics Template level to Default.

7. Click Connect to create the new data source.

8. Click Add to Report to return to the Crashlytics template.

9. Finally, click Create Report to create your copy of the Crashlytics Data Studio Dashboard template.

Note: If you linked Crashlytics to BigQuery before December 6, 2018, then your dataset is named My Projects > PROJECT_ID > crashlytics > TABLE_NAME.

Upgrade to the new export infrastructure

In mid-October 2024, Crashlytics launched a new infrastructure for exporting Crashlytics data into BigQuery. For now, upgrading to this new infrastructure is optional.

Note: Your Crashlytics data export uses the new export infrastructure if your "data transfer config" in the Cloud console is labeled as Firebase Crashlytics with Multi-Region Support.

This new infrastructure supports Crashlytics dataset locations outside the United States.

• If you enabled export before mid-October 2024, you can now optionally change the location for data export to any BigQuery-supported dataset location.

• If you enabled export in mid-October 2024 or later, then you can select any BigQuery-supported dataset location during setup.

Another difference in the new infrastructure is that it doesn't support backfills of data from before you enabled export. (With the old infrastructure, you could backfill up to 30 days prior to the enablement date.) The new infrastructure supports backfills up to the past 30 days or for the most recent date when you enabled export to BigQuery (whichever is most recent).

Prerequisite for upgrading

Before upgrading to the new infrastructure, confirm that you meet the following prerequisite: Your current batch BigQuery tables have matching identifiers to the bundle IDs or package names set for your registered Firebase Apps.

For example:

• If you have a BigQuery table named com_yourcompany_yourproject_IOS, then you should have a Firebase iOS+ App registered in your Firebase project with the bundle ID com.yourcompany.yourproject.

• If you have a BigQuery table named com_yourcompany_yourproject_ANDROID, then you should have a Firebase Android App registered in your Firebase project with the package name com.yourcompany.yourproject.

Here's how to find all the Firebase Apps registered in your Firebase project:

1. In the Firebase console, go to your Project settings.

2. Scroll down to the Your apps card, then click on the desired Firebase App to view the app's information, including its identifier.

Note: BigQuery streaming tables that end with REALTIME are not affected by the new export infrastructure and can be ignored in this case.

The new export infrastructure will export each app's data based on the package name or bundle ID set for the registered Firebase App. In order to not disrupt your BigQuery workflow, it's important to make sure your current batch tables already have the correct names so that the new infrastructure can append all new data to the existing tables. If you have batch table names that do not match your registered Firebase Apps, but you still want to upgrade, reach out to Firebase Support.

How to upgrade to the new infrastructure

If you've already enabled export, you can upgrade to the new infrastructure simply by toggling Crashlytics data export off and then on again in the Firebase console.

Here are the detailed steps:

1. In the Firebase console, go to the Integrations page.

2. In the BigQuery card, click Manage.

3. Toggle off the Crashlytics slider to disable export. When prompted, confirm that you want data export to stop.

4. Immediately toggle on again the Crashlytics slider to re-enable export. When prompted, confirm that you want to export data.

   Your Crashlytics data export to BigQuery is now using the new export infrastructure.