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Integrations

Google BigQuery
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Data Warehouse

How it works

Given that you are already sending data from your app(s) to mParticle, you can enable BigQuery in your project in Google Cloud Platform, and complete BigQuery configuration on the mParticle UI. Then your app data will be continuously streamed into BigQuery.

In general, mParticle back-end services will perform the following actions in your BigQuery dataset.

  1. Store each app’s data in a separate set of tables.
  2. Create a table for each custom event name as well as each eCommerce event name that has occurred at least once in the last 30 days. All other message types (e.g., session start, session end, screen views, etc.) will be put into a single table called [Table Prefix]_“otherevents”.
  3. Stream data into each table accordingly. Loaded data should be available for analysis within a few seconds of streaming insertion into a table.
  4. Set expiration time according to the data retention policy configured on the mParticle UI.

Note that mParticle begins loading current data into BigQuery from the time the integration is enabled. You can work with mParticle customer support team to load historical data.

BigQuery Configuration

To load data, please complete the following steps.

  1. Enable BigQuery in your project in Google Cloud Platform.
  2. From the IAM page for your project, add mparticle-gcp-clientfacing@gcp-prod-170221.iam.gserviceaccount.com as a member with the BigQuery Job User and Project Viewer roles.

  3. From the BigQuery page for your project:

    • Create a dataset to load your app into.
    • Click on Share Dataset on the dataset page.
    • Add mparticle-gcp-clientfacing@gcp-prod-170221.iam.gserviceaccount.com with the BigQuery Data Editor and Project Viewer roles.
      medium
  4. Log into mParticle platform, and navigate to the BigQuery page.
  • Enter your BigQuery projectId (note that it may be different from your project name) and the datasetId of the dataset created in step 3.

  • Enter your BigQuery table prefix
  • Choose from the dropdown your preferred partition time granularity. None is set by default and it will use weekly sharding tables. If you choose any other option, that value will be used as it’s time-unit partitioning using the event timestamp and clustering will be applied to that same column.
  • Optionally, you may configure a data retention policy that will apply at table level for sharding or partition level for partions.
  1. Connect individual inputs to the BigQuery output from the Connections page. You must connect every input you want to store data for.

mParticle Setup

After adding Google BigQuery from the integrations Directory, you can find the settings UI at Setup > Data Warehouse.

From the main page for your Google BigQuery configuration, select the Settings tab to provide the necessary settings to get your Google BigQuery integration working.

To forward data subject erasure requests to Google BigQuery, set the Forwarding Status toggle to Active and select I understand after reading the disclaimer. Once the status has been set to Active, erasure requests are sent to Google BigQuery immediately upon being received by mParticle.

Connection Settings

Setting Name Data Type Default Value Platform Description
BigQuery Table Name string Out of Band Table name for this partner feed. If not set, the partner name will be used. Only applicable to feeds inputs, no effect on apps inputs. If “Split Partner Feed Data by Event Name” checkbox is enabled, this setting is not used.
Split Partner Feed Data by Event Name boolean False Out of Band If enabled, split partner feed data by event name. Otherwise load data into the same table.
Send Batches without Events boolean True All If enabled, an event batch that contains no events will be forwarded.

Optional Steps

You can upload your own JSON BigQuery service account credentials using the Google Service Account Key JSON (Optional) field in the Data Warehouse > Settings page. If you do not provide your custom credentials, mParticle’s Google service account credentials will used. The image below shows a sample JSON configuration file.

After successfully saving the configurations, data loading should start within a few minutes, and you can view the data load status on the mParticle BigQuery page.

BigQuery Schema

All of your data is stored in one single BigQuery dataset.

Each app has its own set of tables. Each table name has a table name prefix. This will be the name of your app, except for data from Feeds, for which you can customize the prefix in the Connection Settings.

By default, each custom event name and eCommerce event name have their own table in BigQuery dataset, and all other event names (e.g., session-start, session-end) are stored in a single table. The naming conversion of the table names are as follows.

  • A custom event name will have a table named [Table Prefix]_event_[event type]_[event name]. For example, a Navigation type event named SignUp from an app named “my cool app” will have a table named mycoolapp_event_navigation_signup.
  • An eCommerce event name will have a table named [Table Prefix]_ecomm_[event name].
  • All other events are stored in a table named [Table Prefix]_otherevents.

Additionaly, the partition time granularity setting will impact in how data is physically stored and how table names are resolved. On top of what’s mentioned above:

  • If set to None (default value) data is stored by week using a sharding approach and thus each table name has a date value as an appendix. The date value is the date of the Sunday of a week. For example, you’ll see table names like mycoolapp_event_navigation_signup20160424, mycoolapp_event_navigation_signup20160417, mycoolapp_event_navigation_signup20160410, etc.
  • Otherwise, for any other option, the choosen time frame will be used to enable the bigquery time partitioning over the event timestamp column and also clustering optimizations on that column. The choosen option will be appended as a constant literal at the end of the table. If you choose Day it will end up being mycoolapp_event_navigation_signup_day or mycoolapp_event_navigation_signup_month for Month, etc. That allows to update the partition time granularity setting with the overdraw that it’s sent to a new different table since it’s not allowed to update the configuration in an existing table.

Any update on the data retention policy setting after a table creation would not have effect on the existing tables. When using sharding that implies that the change will take effect on the next weekly table creation. In the case of partitioned tables, it will only have effect if the table prefix or partition time granularity is updated too which may lead into a new table creation (if it does not exist yet). For updates on your existing tables you will need to do a manual update from your BigQuery console.

Each table has the following fields.

Field Name Data Type Data Mode Description
appid INTEGER NULLABLE mParticle app Id
appplatformid INTEGER NULLABLE mParticle AppPlatformId, e.g., Google Now app has iOS platform and Android platform, and each platform has an unique mParticle AppPlatformId
appname STRING NULLABLE App name
appversion STRING NULLABLE App version
packagename STRING NULLABLE App package name
apparchitecture STRING NULLABLE App architecture
ispirated BOOLEAN NULLABLE Is the device pirated?
applicationbuildnumber STRING NULLABLE Application build number
isdebugsigning BOOLEAN NULLABLE Is the app debug signing?
upgradedate TIMESTAMP NULLABLE App upgrade timestamp
appenvironment STRING NULLABLE App environment, debug or production
installreferrer STRING NULLABLE Install referrer
brand STRING NULLABLE Device brand
product STRING NULLABLE Device product
devicename STRING NULLABLE Device name
deviceudid STRING NULLABLE Device UDID
manufacturer STRING NULLABLE Device manufacturer
platform STRING NULLABLE Device platform
osversion STRING NULLABLE Device OS version
devicemodel STRING NULLABLE Device model
localecountry STRING NULLABLE Device’s locale country
localelanguage STRING NULLABLE Device’s locale language
networkcountry STRING NULLABLE Network country
networkcarrier STRING NULLABLE Network carrier name
screenheight INTEGER NULLABLE Device’s screen height
screenwidth INTEGER NULLABLE Device’s screen width
screendpi INTEGER NULLABLE Device’s screen dpi
deviceutcoffset INTEGER NULLABLE Device UTC offset
osversionint INTEGER NULLABLE Android OS version int
idfa STRING NULLABLE iOS IDFA
googleaid STRING NULLABLE Android Google Advertising ID
architecture STRING NULLABLE Device architecture
istablet BOOLEAN NULLABLE Is the device a tablet?
vendoridentifier STRING NULLABLE iOS vendor identifier
pushtoken STRING NULLABLE Push token
attributionserviceprovider STRING NULLABLE Attribution service provider name
attributionpublisher STRING NULLABLE Attributed publisher name
attributioncampaign STRING NULLABLE Attributed campaign name
mparticleuserid INTEGER NULLABLE UserId assigned by mParticle
customerid STRING NULLABLE User’s customerID, usually this is the unique userId in your system
facebookid STRING NULLABLE User’s Facebook user Id
twitterid STRING NULLABLE User’s Twitter ID
googleuserid STRING NULLABLE User’s Google ID
microsoftuserid STRING NULLABLE User’s Microsoft ID
yahoouserid STRING NULLABLE User’s Yahoo ID
email STRING NULLABLE User’s email
otheruserid STRING NULLABLE “Other” type user identity
otheruserid2 STRING NULLABLE “Other2” type user identity
otheruserid3 STRING NULLABLE “Other3” type user identity
otheruserid4 STRING NULLABLE “Other4” type user identity
isdebug BOOLEAN NULLABLE True for debug environment and false for production environment
batchid INTEGER NULLABLE A unique ID of the batch
batchtimestamp TIMESTAMP NULLABLE Batch timestamp
sdkversion STRING NULLABLE mParticle SDK version
clientip STRING NULLABLE Client IP address
accumulatedltvvalue FLOAT NULLABLE Accumulated LTV value of a user
entrypointtype INTEGER NULLABLE Type of incoming data, 1 means from SDK and 128 means from S2S
countrycode STRING NULLABLE Country code
cityname STRING NULLABLE City name
postalcode STRING NULLABLE Postal code
regioncode STRING NULLABLE Geo region code
latitude FLOAT NULLABLE Geo latitude
longitude FLOAT NULLABLE Geo longitude
accuracy FLOAT NULLABLE Geo accuracy
sessionid INTEGER NULLABLE A unique ID of the session
sessionstarttimestamp TIMESTAMP NULLABLE Session start timestamp
eventid INTEGER NULLABLE A unique ID of the event
eventtimestamp TIMESTAMP NULLABLE Event timestamp
messagetypeid INTEGER NULLABLE Message Type Id
eventstarttimestamp TIMESTAMP NULLABLE Event start timestamp
eventname STRING NULLABLE Event name
eventtypeid INTEGER NULLABLE Event type Id
eventlength INTEGER NULLABLE How long did the event take? Represents session length in milliseonds on session end events
eventltvvalue FLOAT NULLABLE Monetary value extracted from the event
dataconnectiontype STRING NULLABLE Data connection type
exceptionhandled BOOLEAN NULLABLE Handled exception or crash
firstseentimestamp TIMESTAMP NULLABLE Timestamp of the first event on this user
isfirstrunevent BOOLEAN NULLABLE Is this a first run event?
isupgradeevent BOOLEAN NULLABLE Is this an app upgrade event?
successfullyclosed BOOLEAN NULLABLE Is the last session successfully closed? Will be false if app is forcefully killed
applicationtransitiontypeid INTEGER NULLABLE Applicaiton Transition TypeId
samplingpercentage INTEGER NULLABLE Not used
ecommercescreenname STRING NULLABLE eCommerce screen name
ecommerceisnoninteractive BOOLEAN NULLABLE Is eCommerce action interactive?
productactiontypeid INTEGER NULLABLE eCommerce Product Action Type Id
0 = unknown
1 = add_to_cart
2 = remove_from_cart
3 = checkout
4 = checkout_option
5 = click
6 = view_detail
7 = purchase
8 = refund
9 = add_to_wishlist
10 = remove_from_wishlist
promotionactiontypeid INTEGER NULLABLE Promotion Action Type Id
0 = unknown
1 = view
2 = click
attauthorizationstatus STRING NULLABLE iOS 14 ATT Authorization status
atttimestamp TIMESTAMP NULLABLE iOS 14 ATT Authorization status timestamp
httpheaderuseragent STRING NULLABLE User-Agent field from the HTTP Header
mparticledeviceid STRING NULLABLE mParticle Device Stamp
eventattributes RECORD REPEATED A repeated field containing a list of event attribute key value pairs
eventattributes.attributename STRING NULLABLE Event attribute name
eventattributes.attributevalue STRING NULLABLE Event attribute value
userattributes RECORD REPEATED A repeated field containing a list of user attribute key value pairs
userattributes.attributename STRING NULLABLE User attribute name
userattributes.attributevalue STRING NULLABLE User attribute value
jailbroken RECORD REPEATED Device’s jailbroken status
jailbroken.attributename STRING NULLABLE Jailbroken attribute name
jailbroken.attributevalue STRING NULLABLE Jailbroken attribute value
eventcustomflags RECORD REPEATED Event custom flags
eventcustomflags.attributename STRING NULLABLE Custom flag attribute name
eventcustomflags.attributevalue STRING NULLABLE Custom flag attribute value
audiencemembership RECORD REPEATED A repeated field containing mParticle segment ID’s the user was a member of at the time of the event
audiencemembership.audienceid INTEGER NULLABLE mParticle segment ID
productimpressions RECORD REPEATED A repeated field containing a list of product impressions
productimpressions.productimpressionlist STRING NULLABLE Product impression list name
productimpressions.product_id STRING NULLABLE Product Id
productimpressions.product_name STRING NULLABLE Product name
productimpressions.product_brand STRING NULLABLE Product brand
productimpressions.product_category STRING NULLABLE Product category
productimpressions.product_variant STRING NULLABLE Product variant
productimpressions.product_position INTEGER NULLABLE Product position
productimpressions.product_price FLOAT NULLABLE Product price
productimpressions.product_quantity FLOAT NULLABLE Product quantity
productimpressions.product_couponcode STRING NULLABLE Product coupon code
productimpressions.product_attributes STRING NULLABLE JSON string of all product attributes
productimpressions.product_addedtocarttimestamp TIMESTAMP NULLABLE Added to cart timestamp
productimpressions.product_totalproductamount FLOAT NULLABLE Total product amount
productaction RECORD NULLABLE Product action information
productaction.actiontype INTEGER NULLABLE eCommerce Product Action Type Id
0 = unknown
1 = add_to_cart
2 = remove_from_cart
3 = checkout
4 = checkout_option
5 = click
6 = view_detail
7 = purchase
8 = refund
9 = add_to_wishlist
10 = remove_from_wishlist
productaction.checkoutstep INTEGER NULLABLE Checkout step
productaction.checkoutoptions STRING NULLABLE Checkout options
productaction.productactionlist STRING NULLABLE Product action list
productaction.productlistsource STRING NULLABLE Product list source
productaction.transactionid STRING NULLABLE Transaction id
productaction.affiliation STRING NULLABLE Transaction affiliation
productaction.totalamount FLOAT NULLABLE Transaction total amount
productaction.taxamount FLOAT NULLABLE Transaction tax amount
productaction.shippingamount FLOAT NULLABLE Transaction shipping amount
productaction.couponcode STRING NULLABLE Transaction coupon code
productactionproducts RECORD REPEATED A repeated field containing a list of products associate with a product action
productactionproducts.product_id STRING NULLABLE Product Id
productactionproducts.product_name STRING NULLABLE Product name
productactionproducts.product_brand STRING NULLABLE Product brand
productactionproducts.product_category STRING NULLABLE Product category
productactionproducts.product_variant STRING NULLABLE Product variant
productactionproducts.product_position INTEGER NULLABLE Product position
productactionproducts.product_price FLOAT NULLABLE Product price
productactionproducts.product_quantity FLOAT NULLABLE Prodict quantity
productactionproducts.product_couponcode STRING NULLABLE Product coupon code
productactionproducts.product_attributes STRING NULLABLE JSON string of all product attributes
productactionproducts.product_addedtocarttimestamp TIMESTAMP NULLABLE Added to cart timestamp
productactionproducts.product_totalproductamount FLOAT NULLABLE Total product amount
promotionaction RECORD REPEATED A repeated field containing a list of eCommerce product promotions
promotionaction.promotion_action_type INTEGER NULLABLE eCommerce Promotion Action Type Id
0 = unknown
1 = view
2 = click
promotionaction.promotion_id STRING NULLABLE Promotion Id
promotionaction.promotion_name STRING NULLABLE Promotion name
promotionaction.promotion_creative STRING NULLABLE Promotion creative
promotionaction.promotion_position STRING NULLABLE Promotion position
shoppingcart RECORD REPEATED A repeated field containing a list of products in a shopping cart
shoppingcart.product_id STRING NULLABLE Product Id
shoppingcart.product_name STRING NULLABLE Product name
shoppingcart.product_brand STRING NULLABLE Product brand
shoppingcart.product_category STRING NULLABLE Product category
shoppingcart.product_variant STRING NULLABLE Product variant
shoppingcart.product_position INTEGER NULLABLE Product position
shoppingcart.product_price FLOAT NULLABLE Product price
shoppingcart.product_quantity FLOAT NULLABLE Prodict quantity
shoppingcart.product_couponcode STRING NULLABLE Product coupon code
shoppingcart.product_attributes STRING NULLABLE JSON string of all product attributes
shoppingcart.product_addedtocarttimestamp TIMESTAMP NULLABLE Added to cart timestamp
shoppingcart.product_totalproductamount FLOAT NULLABLE Total product amount

Partner Feed Data

Events from each connected Partner Feed will be stored under a single table unless the Split Partner Feed Data by Event Name checkbox is enabled. You can choose the table name for each Feed in the Connection Settings. If you do not provide a name, mParticle will use the name of the Partner.

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Device Application Stamp Forwarding

Events can be forwarded with a Device Application Stamp stored in the device ID column. You can enable this in the settings page for your data warehouse configuration by toggling the Store Device Stamp checkbox.

Best Practices

  1. Query a specific table whenever possible. Doing this lowers your BigQuery bill since BigQuery charges by how much data is queried.
  2. For the same reason as above, only include the fields you really want in a query whenever possible.
  3. When counting number of distinct elements, BigQuery use estimation by HyperLogLog by default. To get an exact count, use “count(distinct fieldName, n)”, which tells BigQuery to use estimation only if there are more than n number of unique elements.

  4. When dealing with more than one repeated field, use FLATTEN operator. When using FLATTEN operator and table wildcard functions together, reference the following example:

    -- calculate daily signups from facebook US users
SELECT
  DATE(EventTimestamp),
  COUNT(*)
FROM
  FLATTEN((
    SELECT
      *
    FROM
      TABLE_QUERY([myproject:mydataset], 'table_id contains "mycoolapp"')), eventattributes)
WHERE
  EventName = 'SignUp'
  AND EventAttributes.attributename = 'Sign Up Method'
  AND EventAttributes.attributevalue = 'Facebook'
  AND UserAttributes.attributename = 'Country'
  AND UserAttributes.attributevalue = 'US'
GROUP BY 1
ORDER BY 1

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