How is this source different from the AppMetrica source?

This source exports raw rows: one installation or one e-commerce event per row, with its own identifiers and timestamps. The AppMetrica source exports aggregated reports, where a row is a combination of the dimensions you selected and the metrics are counts and sums. Use this source to build your own aggregations or to join app data with other sources at the device level, and the AppMetrica source for ready-made statistics.

Why is Date end set to Yesterday?

Events reach the Logs API with a delay, so the current day is always incomplete at the moment of the export. Keep **Date end** set to **Yesterday** to load whole days only, and use the **Overwrite period** to re-request the recent ones as late events arrive.

Which time zone are the dates in?

AppMetrica records events in the time zone configured for the application, under **Settings** > **Main** > **Time zone UTC** in the AppMetrica interface. The date range and the *_datetime fields follow that setting. The *_timestamp fields hold Unix time, so use them when you need a value that does not depend on the application's time zone.

Does the E-commerce report contain only purchases?

No. A row is any e-commerce event the app sends, and the ecom_type field says which one: show_screen , show_product_card , show_product_details , add_cart_item , remove_cart_item , begin_checkout , or purchase . Filter by that field to get purchases alone.

Can one pipeline export several applications?

No. The **Counters** list accepts one application. To export several applications, create a separate pipeline for each one and give each pipeline its own table name.

Why are the column names in my table so cryptic?

The picker and the destination table use the field names of the Logs API itself, such as appmetrica_device_id or ecom_product_sku . On Google BigQuery, Renta attaches the description of each field to the corresponding column, so you can read what a column means in the table schema.

AppMetrica Logs API

The AppMetrica Logs API exports the raw rows behind the reports: one installation or one e-commerce event per row, with the device identifiers and timestamps attached to it.

Authentication

Renta uses OAuth to authenticate with Yandex. You will be redirected to Yandex to grant Renta limited access to your AppMetrica applications.

Your credentials are encrypted in transit and at rest, and never stored in Renta's application database. You stay in control and can revoke access from your Yandex account settings at any time.

Connect AppMetrica Logs API source

Go to the CatalogStep 1

Navigate to the Connections > Catalog section in the left sidebar.
Open the Analytics category and click the AppMetrica Logs API card.

The AppMetrica card next to it is a different source. It exports aggregated reports built from dimensions and metrics instead of raw rows.

AppMetrica Logs API card in the Analytics category of the Renta source catalog

Authorize connectionStep 2

Click Log in to your Appmetrica Logs API account. You will be redirected to Yandex to grant access.

Authorize connection page for a new AppMetrica Logs API connection in Renta

Choose a Yandex accountStep 3

Yandex shows the sign-in screen with the list of permissions Renta requests, including access to the statistics of your applications in AppMetrica. Choose the account that has access to your applications and confirm. After that you are redirected back to Renta.

Yandex sign-in page with the account selection and the list of permissions requested by Renta

Name the connection and saveStep 4

Finish the setup:

Source name.
Specify a name for this data source. This is used exclusively in the Renta interface.
Access granted.
Verify that the account is connected successfully.

Click Save to finish.

If your Yandex authorization later changes (for example, after a password change), click Re-authorize on this source. The connection refreshes in place and every pipeline built on it keeps running.

Set up your AppMetrica Logs API connection with the source name field and the access granted block

Source createdStep 5

The new source appears in the Sources list with the Active status. You can now use it in pipelines.

Sources list with the new AppMetrica Logs API source in the Active status

Create an AppMetrica Logs API pipeline

Link your AppMetrica Logs API source to a destination and configure the pipeline.

Select AppMetrica Logs API as the sourceStep 1

In the left sidebar, click New pipeline. On the Source step, select AppMetrica Logs API under Already connected and click Next step.

Select a source step with AppMetrica Logs API under Already connected

Select your AppMetrica Logs API connectionStep 2

Choose the AppMetrica Logs API connection you created earlier and click Next step.

Select your AppMetrica Logs API connection step with the connected Yandex account

Select a destinationStep 3

On the Destination step, select your destination (for example, Google BigQuery) and click Next step.

Select a destination step with Google BigQuery under Already connected

Select the destination connectionStep 4

Choose the destination connection you want to load data into and click Next step.

Select your Google BigQuery connection step with the dataset and project identifiers

Pipeline configuration

On the final step, choose which AppMetrica data to export and how Renta loads it.

Report configuration

Point the pipeline at the application and choose the report type.

AppMetrica Logs API application and report type selection on the pipeline settings step

Counters Choose the application to export data from. The list contains the applications available to the connected Yandex account, shown by application name. One pipeline exports one application.

Report Types Choose what to export. One pipeline exports one report type.

Report type	What one row contains
Installation report	One installation: the install and click timestamps, the attribution block (tracker, campaign, publisher, match type, re-attribution and re-installation flags), device identifiers, and the device, network, geography, and app attributes.
E-commerce report	One e-commerce event: its type and the screen, product, cart, order, and referrer attributes, together with the event identity, device identifiers, and the device, network, geography, and app attributes.

Parameters

Select the fields to include in the destination table. Your dataset schema is defined by the parameters you choose here.

Report type

Name	API name	Description
ecom_type text	`ecom_type`	Purchase event type. Possible values: show_screen, show_product_card, show_product_details, add_cart_item, remove_cart_item, begin_checkout, purchase.
ecom_screen_name text	`ecom_screen_name`	Screen name.
ecom_screen_search_query text	`ecom_screen_search_query`	Search query.
ecom_screen_category_path_1 text	`ecom_screen_category_path_1`	Screen category. Level 1.
ecom_screen_category_path_2 text	`ecom_screen_category_path_2`	Screen category. Level 2.
ecom_screen_category_path_3 text	`ecom_screen_category_path_3`	Screen category. Level 3.
ecom_screen_category_path_4 text	`ecom_screen_category_path_4`	Screen category. Level 4.
ecom_screen_category_path_5 text	`ecom_screen_category_path_5`	Screen category. Level 5.
ecom_screen_category_path_6 text	`ecom_screen_category_path_6`	Screen category. Level 6.
ecom_screen_category_path_7 text	`ecom_screen_category_path_7`	Screen category. Level 7.
ecom_screen_category_path_8 text	`ecom_screen_category_path_8`	Screen category. Level 8.
ecom_screen_category_path_9 text	`ecom_screen_category_path_9`	Screen category. Level 9.
ecom_screen_category_path_10 text	`ecom_screen_category_path_10`	Screen category. Level 10.
ecom_product_name text	`ecom_product_name`	Product name.
ecom_product_sku text	`ecom_product_sku`	Product ID.
ecom_product_promocodes array_string	`ecom_product_promocodes`	Product promo codes. JSON array of strings.
ecom_product_category_path_1 text	`ecom_product_category_path_1`	Product category. Level 1.
ecom_product_category_path_2 text	`ecom_product_category_path_2`	Product category. Level 2.
ecom_product_category_path_3 text	`ecom_product_category_path_3`	Product category. Level 3.
ecom_product_category_path_4 text	`ecom_product_category_path_4`	Product category. Level 4.
ecom_product_category_path_5 text	`ecom_product_category_path_5`	Product category. Level 5.
ecom_product_category_path_6 text	`ecom_product_category_path_6`	Product category. Level 6.
ecom_product_category_path_7 text	`ecom_product_category_path_7`	Product category. Level 7.
ecom_product_category_path_8 text	`ecom_product_category_path_8`	Product category. Level 8.
ecom_product_category_path_9 text	`ecom_product_category_path_9`	Product category. Level 9.
ecom_product_category_path_10 text	`ecom_product_category_path_10`	Product category. Level 10.
ecom_product_actual_price_fiat_unit_type text	`ecom_product_actual_price_fiat_unit_type`	Currency of the actual product price.
ecom_product_actual_price_fiat_value float	`ecom_product_actual_price_fiat_value`	Actual product price.
ecom_product_original_price_fiat_unit_type text	`ecom_product_original_price_fiat_unit_type`	Currency of the base product price.
ecom_product_original_price_fiat_value float	`ecom_product_original_price_fiat_value`	Base product price.
ecom_cart_item_price_fiat_unit_type text	`ecom_cart_item_price_fiat_unit_type`	Price currency for the item in the cart.
ecom_cart_item_price_fiat_value float	`ecom_cart_item_price_fiat_value`	Price of the item in the cart.
ecom_cart_item_quantity int	`ecom_cart_item_quantity`	Number of items in the cart.
ecom_referrer_type text	`ecom_referrer_type`	Traffic source type.
ecom_referrer_id text	`ecom_referrer_id`	Traffic source ID.
ecom_order_id text	`ecom_order_id`	Purchase ID.
event_datetime datetime	`event_datetime`	Date and time of the event in yyyy-mm-dd hh:mm:ss format.
event_name text	`event_name`	Name of the event (as passed to the SDK).
event_receive_datetime datetime	`event_receive_datetime`	Date and time the event was received on the server side.
event_receive_timestamp int	`event_receive_timestamp`	Time when the event was received on the server side in Unix time format.
event_timestamp int	`event_timestamp`	Time of the event in Unix time format.
session_id text	`session_id`	Session ID.
installation_id text	`installation_id`	Installation ID.
appmetrica_device_id text	`appmetrica_device_id`	A unique device identifier detected by the AppMetrica service.
city text	`city`	The name of the city where the click was made (in English).
connection_type text	`connection_type`	Type of connection. Possible values: wifi \| cell \| unknown.
country_iso_code text	`country_iso_code`	ISO country code.
device_ipv6 text	`device_ipv6`	The IP address at the time of the event in IPv6 format.
device_locale text	`device_locale`	The language on the device.
device_manufacturer text	`device_manufacturer`	The device manufacturer detected by the AppMetrica service.
device_model text	`device_model`	The device model detected by the AppMetrica service.
device_type text	`device_type`	The device type detected by the AppMetrica service. Possible values: phone \| tablet \| unknown.
google_aid text	`google_aid`	The device's Google AID.
ios_ifa text	`ios_ifa`	The device's IFA.
ios_ifv text	`ios_ifv`	IFV for the app.
mcc text	`mcc`	Mobile country code.
mnc text	`mnc`	Mobile network code.
operator_name text	`operator_name`	Name of the mobile operator.
original_device_model text	`original_device_model`	Factory model of the device.
os_version text	`os_version`	The version of the operating system on the user's device.
profile_id text	`profile_id`	User profile ID.
windows_aid text	`windows_aid`	The device's Windows AID.
app_build_number text	`app_build_number`	App build number.
app_package_name text	`app_package_name`	The package name for Android, or the Bundle ID for iOS.
app_version_name text	`app_version_name`	The app version in the format specified by the developer.
Today date	`date_today`	Today's date
Year text	`year`	Year of the date
Year of week (Sun-Sat) text	`yearofweek`	Year of week for US weeks
Year of week (Mon-Sun) text	`yearofweekiso`	Year of week for ISO weeks
Year & month text	`yearmonth`	Year and month combined
Quarter text	`quarter`	Quarter of the year
Month text	`month`	Month of the year
Year & week (Sun-Sat) text	`yearweek`	Year and week for US weeks
Year & week (Mon-Sun) text	`yearweekiso`	Year and week for ISO weeks
Week (Sun-Sat) text	`week`	US week number
Week (Mon-Sun) text	`weekiso`	ISO week number
Day of week (Sun-Sat) text	`dayOfWeekName`	Day of week name for US weeks
Day of week text	`dayOfWeekNameIso`	Day of week name for ISO weeks (Mon-Sun)
Day of month text	`dayOfMonth`	Day of the month
Date date	`date`	Specific date

Name	API name	Description
application_id int	`application_id`	Unique numerical identifier of the application in AppMetrica.
installation_id text	`installation_id`	Installation identifier.
attributed_touch_type text	`attributed_touch_type`	Type of advertising interaction. Possible values: click, impression, unknown.
click_datetime datetime	`click_datetime`	Date and time of the click/impression in the format yyyy-mm-dd hh:mm:ss.
click_id text	`click_id`	Identifier of the click/impression or an empty string if not available.
click_ipv6 text	`click_ipv6`	IP address at the time of the click/impression in IPv6 format (e.g., 2a02:6b8::40c:6676:baff:fea6:53d8, ::ffff:5.255.232.147).
click_timestamp int	`click_timestamp`	Timestamp of the click/impression in UNIX-time in seconds.
click_url_parameters text	`click_url_parameters`	Parameters as represented in the link. Special characters should be escaped (e.g., ?param1%3D1%26param2%3D2...).
click_user_agent text	`click_user_agent`	User-agent of the click/impression.
profile_id text	`profile_id`	Identifier of the user profile.
publisher_id int	`publisher_id`	Partner ID in AppMetrica. It can be used to identify the partner in AppMetrica reports.
publisher_name text	`publisher_name`	Name of the AppMetrica partner. If unattributed postbacks are enabled for the tracker, the value will be empty.
tracker_name text	`tracker_name`	Name of the tracker added in the AppMetrica interface. If unattributed postbacks are enabled, the value will be empty.
tracking_id int	`tracking_id`	Tracker ID in AppMetrica. It can be used to identify the partner in reports. If unattributed postbacks are enabled, the value will be 0.
install_datetime datetime	`install_datetime`	Date and time of installation in the format yyyy-mm-dd hh:mm:ss.
install_ipv6 text	`install_ipv6`	IP address at the time of installation in IPv6 format (e.g., 2a02:6b8::40c:6676:baff:fea6:53d8, ::ffff:5.255.232.147).
install_receive_datetime datetime	`install_receive_datetime`	Date and time when the server received the installation event. May differ from install_datetime due to network delays or the user's offline status.
install_receive_timestamp int	`install_receive_timestamp`	Server reception timestamp of the installation event in UNIX-time.
install_timestamp int	`install_timestamp`	Timestamp of the installation in UNIX-time in seconds.
is_reattribution bool	`is_reattribution`	Indicates reattribution of the installation to a new source. Possible values: true, false.
is_reinstallation bool	`is_reinstallation`	Indicates whether the application was reinstalled. Possible values: true, false.
match_type text	`match_type`	Attribution method: fingerprint, referrer, identifier, or an empty string.
appmetrica_device_id int	`appmetrica_device_id`	Unique device identifier assigned by AppMetrica.
city text	`city`	City name in English where the click occurred.
connection_type text	`connection_type`	Device connection type. Possible values: wifi, cell, unknown.
country_iso_code text	`country_iso_code`	ISO code of the country.
device_locale text	`device_locale`	Device interface language.
device_manufacturer text	`device_manufacturer`	Device manufacturer, determined by AppMetrica (e.g., Apple, Samsung).
device_model text	`device_model`	Device model, determined by AppMetrica (e.g., Galaxy S6).
device_type text	`device_type`	Device type determined by AppMetrica. Possible values: phone, tablet, unknown.
google_aid text	`google_aid`	Google AID of the device as received from the device.
oaid text	`oaid`	Huawei OAID of the device as received from the device.
ios_ifa text	`ios_ifa`	IFA of the device as received from the device.
ios_ifv text	`ios_ifv`	IFV for the application as received from the device.
mcc int	`mcc`	Mobile country code.
mnc int	`mnc`	Mobile network code.
operator_name text	`operator_name`	Name of the mobile operator.
os_name text	`os_name`	Operating system on the user's device: ios, android, windows.
os_version text	`os_version`	Version of the operating system on the user's device.
windows_aid text	`windows_aid`	Windows AID of the device as received from the device.
app_package_name text	`app_package_name`	Package name for Android or Bundle ID for iOS (e.g., ru.yandex.metro).
app_version_name text	`app_version_name`	Application version as specified by the developer.
Today date	`date_today`	Today's date
Year text	`year`	Year of the date
Year of week (Sun-Sat) text	`yearofweek`	Year of week for US weeks
Year of week (Mon-Sun) text	`yearofweekiso`	Year of week for ISO weeks
Year & month text	`yearmonth`	Year and month combined
Quarter text	`quarter`	Quarter of the year
Month text	`month`	Month of the year
Year & week (Sun-Sat) text	`yearweek`	Year and week for US weeks
Year & week (Mon-Sun) text	`yearweekiso`	Year and week for ISO weeks
Week (Sun-Sat) text	`week`	US week number
Week (Mon-Sun) text	`weekiso`	ISO week number
Day of week (Sun-Sat) text	`dayOfWeekName`	Day of week name for US weeks
Day of week text	`dayOfWeekNameIso`	Day of week name for ISO weeks (Mon-Sun)
Day of month text	`dayOfMonth`	Day of the month
Date date	`date`	Specific date

The Parameters list is a single flat list of the fields available for the selected report type, named exactly as they are named in the Logs API: installation_id, appmetrica_device_id, ecom_product_sku. The search box is the quickest way to a specific field. Select All checks the entire list.

Select at least one field: a pipeline with an empty Parameters list cannot be created.

The list of the Installation report covers attribution (tracker_name, publisher_name, click_datetime, attributed_touch_type, is_reattribution), install timestamps, device identifiers (appmetrica_device_id, google_aid, ios_ifa, oaid), and the device, network, geography, and app attributes.

The list of the E-commerce report follows the funnel instead: the event type in ecom_type, then the screen, product, cart, and order fields, plus the event identity (event_name, event_datetime, session_id) and the same device and app attributes.

In the destination table, column names repeat the field names of the Logs API as they are. On Google BigQuery, Renta also attaches the description of each field to the corresponding column.

Date parameters

The list also contains date fields calculated by Renta: Date and Today, plus calendar fields such as Year, Quarter, Month, Week, and Day of week. Renta derives them from the installation date in the Installation report and from the event date in the E-commerce report.

Include the Date parameter in the report. With it, the destination table is partitioned by the date column and Renta loads data incrementally. It also enables the Overwrite period setting, which appears below the date range once the parameter is selected. Without it, Renta reloads the whole date range on every run.

Table name and date range

Name the pipeline and set the historical period to load.

Integration name.
The name of the pipeline. It is used exclusively in the Renta interface.
Table name.
The destination table name. You can keep the auto-generated name or enter your own.
Date start.
The first date of the extraction period.
Date end.
The last date of the extraction period. Set it to Yesterday.

Leave Date end set to Yesterday. Events reach the Logs API with a delay, so an export that includes the current day returns it incomplete, and the run records a partial day as if it were final.

AppMetrica prepares each export on its side before it can be downloaded, and Renta waits for it. The first run over a long history therefore takes noticeably longer than the following daily runs, which pick up a day or two at a time.

Overwrite period

The overwrite period defines how many recent days Renta reloads on every run. The setting appears once the Date parameter is selected in Parameters.

On each run, Renta re-fetches the data starting from the date of the last successful run minus the overwrite period. The affected days are deleted from the destination table and inserted again, while older data stays untouched.

Installations keep being matched to clicks after the install itself: AppMetrica attributes a click for 10 days by default, and up to 30 days depending on the tracker settings. Rows already exported can therefore get their attribution filled in later. Set the overwrite period to cover the attribution window you use.

Schedule

Choose how often the pipeline runs.

Schedule type	Description
Manual	The pipeline runs only when triggered manually through the interface or via API.
Daily	The pipeline runs once a day at the specified update time.
Interval	The pipeline runs at specified time intervals.
Cron Expression	The pipeline runs on a schedule defined by a cron expression.

For Daily schedules, set the Update time, the exact time each run starts, then click Create pipeline.

AppMetrica Logs API update time selection and the Create pipeline button

Renta also supports API triggers and integration with external orchestrators such as Apache Airflow, Dagster, and Prefect. See the full scheduling documentation for details.

The new pipeline appears in the Pipelines section under the ETL tab, where you can track its runs, progress, and the destination table name.

Pipelines list with the new AppMetrica Logs API integration in the Completed status

Sync strategy

The synchronization strategy depends on whether the report includes the Date parameter.

Strategy	Supported report types	Description
Incremental	Installation report, E-commerce report (with the Date or Today parameter selected)	Each row carries its date, and the destination table is partitioned by the `date` column. On every run Renta requests the window from the last successful run minus the overwrite period to the end of the date range: the affected daily partitions are deleted and inserted again, and older partitions stay untouched.
Full reload	Installation report, E-commerce report (without a date parameter)	The table has no date column to partition by, so Renta requests the whole configured date range and replaces the dataset on every run.

Changing the selected parameters updates the table schema, so the next run after the change reloads the entire date range.

Frequently asked questions

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