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Upgrade to Version 2 of the SDK
Getting Started
Identity
Web
Alexa
Overview
Step 1. Create an input
Step 2. Verify your input
Step 3. Set up your output
Step 4. Create a connection
Step 5. Verify your connection
Step 6. Track events
Step 7. Track user data
Step 8. Create a data plan
Step 9. Test your local app
Overview
Step 1. Create an input
Step 2. Verify your input
Step 3. Set up your output
Step 4. Create a connection
Step 5. Verify your connection
Step 6. Track events
Step 7. Track user data
Step 8. Create a data plan
Step 1. Create an input
Step 2. Create an output
Step 3. Verify output
Node SDK
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Migrate from Segment to mParticle
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Segment-to-mParticle Migration Reference
Rules Developer Guide
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The Developer's Guided Journey to mParticle
Create an Input
Start capturing data
Connect an Event Output
Create an Audience
Connect an Audience Output
Transform and Enhance Your Data
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For Clauses
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Introduction
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Introduction
Introduction
Introduction
Rudderstack
Google Tag Manager
Segment
Advanced Data Warehouse Settings
AWS Kinesis (Snowplow)
AWS Redshift (Define Your Own Schema)
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AWS S3 (Snowplow Schema)
BigQuery (Snowplow Schema)
BigQuery Firebase Schema
BigQuery (Define Your Own Schema)
GCP BigQuery Export
Snowflake (Snowplow Schema)
Snowplow Schema Overview
Snowflake (Define Your Own Schema)
Aliasing
Audience
Audience
Event
Event
Feed
Event
Audience
Cookie Sync
Event
Audience
Audience
Audience
Feed
Event
Event
Event
Event
Audience
Data Warehouse
Event
Event
Event
Audience
Event
Event
Event
Event
Event
Event
Event
Event
Audience
Event
Feed
Event
Event
Audience
Feed
Event
Event
Event
Custom Feed
Data Warehouse
Event
Audience
Event
Audience
Event
Audience
Audience
Event
Event
Event
Event
Event
Audience
Audience
Event
Audience
Data Warehouse
Event
Event
Event
Event
Audience
Cookie Sync
Event
Event
Event
Feed
Feed
Event
Event
Event
Audience
Event
Event
Audience
Event
Event
Feed
Audience
Event
Event
Event
Audience
Audience
Event
Audience
Audience
Audience
Event
Audience
Event
Event
Event
Event
Feed
Event
Event
Event
Event
Event
Feed
Audience
Event
Event
Event
Event
Event
Event
Event
Event
Feed
Audience
Event
Event
Custom Pixel
Feed
Event
Event
Event
Event
Event
Audience
Event
Event
Data Warehouse
Event
Event
Audience
Audience
Event
Audience
Audience
Audience
Cookie Sync
Audience
Event
Feed
Audience
Event
Event
Audience
Audience
Event
Event
Event
Event
Audience
Cookie Sync
Audience
Cookie Sync
Feed
Audience
Feed
mParticle’s Data Warehouse integration with Snowflake forwards all your incoming data to a Snowflake cluster, allowing you to query the raw data directly.
The integration creates a table in your Snowflake database for each custom event name and each eCommerce event name with a volume above a defined threshold. Less common events are recorded in a single table, labeled otherevents
.
By default, the integration begins loading current data into Snowflake from the time it is enabled. You can work with your mParticle Customer Service Manager to load historical data.
All setup tasks can be accomplished from a Snowflake Worksheet.
Note that you can use any names you choose for your warehouse, database, schema, role, and user, as long as you provide the correct names to mParticle in the integration settings. Also note that we currently don’t support Snowflake’s double-quoted identifiers (https://docs.snowflake.net/manuals/sql-reference/identifiers-syntax.html#double-quoted-identifiers), and thus please make sure no double quotes are used when you create your warehouse, database, schema, role, and user.
-- Create a warehouse and choose the appropriate size. We use AUTO_SUSPEND of 10 minutes (600 seconds) as an example. Please adjust accordingly if needed.
CREATE WAREHOUSE mPTravelWarehouse WITH WAREHOUSE_SIZE = 'XSMALL' AUTO_SUSPEND = 600 AUTO_RESUME = TRUE;
-- Create database
CREATE DATABASE mPTravelDatabase;
-- Create schema
CREATE SCHEMA mPTravelSchema WITH managed access;
Once your database is ready, you need to create a dedicated role with permissions to manage the database.
-- Create new role:
CREATE ROLE data_loader;
-- Grant access to your warehouse, database and schema
GRANT USAGE ON WAREHOUSE mPTravelWarehouse TO ROLE data_loader;
GRANT USAGE ON DATABASE mPTravelDatabase TO ROLE data_loader;
GRANT ALL ON SCHEMA mPTravelSchema TO ROLE data_loader;
-- Create user with your new role. Make sure to set your new user as a LEGACY_SERVICE user to avoid Snowflake's MFA requirement.
CREATE USER mparticle_user
MUST_CHANGE_PASSWORD = FALSE
DEFAULT_ROLE = data_loader
PASSWORD = "STRONG_PASSWORD_HERE"
TYPE = LEGACY_SERVICE;
GRANT ROLE data_loader TO USER mparticle_user;
After adding Snowflake from the integrations Directory, you can find the settings UI at Setup > Data Warehouse.
From the main page for your Snowflake configuration, select the Settings tab to provide the necessary settings to get your Snowflake integration working.
Your full account name may include region. For example, xy12345.us-east-1
.
To forward data subject erasure requests to Snowflake, 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 Snowflake immediately upon being received by mParticle.
Setting Name | Data Type | Default Value | Description |
---|---|---|---|
Account | string |
Your Snowflake account name. Your full account name may include region. | |
Database Name | string |
The database name created in your Snowflake setup. | |
Data Warehouse Name | string |
The warehouse name created in your Snowflake setup. | |
User ID | string |
User ID for the user you created in your Snowflake setup. These credentials will be used to manage the schema and load data. | |
User Password | string |
The password for the user created in your Snowflake setup. | |
Schema Name | string |
The name of the schema created in your Snowflake setup. | |
Events Threshold | number |
10000 | The number of times a custom or commerce event name must be received in a 30 day period for mParticle to create a dedicated table for that event. |
Single Table Mode | boolean |
false | If enabled, events will be saved in a single table and the Events Threshold setting will not be applied. |
Configuration Name | string |
The name you are giving to this configuration. | |
Delay Between Loading Sessions in Minutes | number |
15 | Allows you to adjust how often you want to load data into the data warehouse. Note that the minimum time is 1 minute and the maximum time is 24 hours (60 minutes x 24). |
If you check the Use same settings for Development and Production box, the same configuration is used for both development and production environments.
Once your Data Warehouse integration is configured, connect individual inputs to the Snowflake output from the Connections page. You must connect every input for which you want to store data.
Setting Name | Data Type | Default Value | Platform | Description |
---|---|---|---|---|
Snowflake Table Name | string |
Feed | 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 | Feed | 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. |
All tables created in Snowflake have the same schema, consisting of a single column of type variant
(a dedicated Snowflake type to efficiently handle JSON data) with the name "data"
. Each row in a table is a JSON string with multiple key/value pairs.
For example:
{
"accumulatedltvvalue": 0,
"accuracy": 2,
"appenvironment": "Development",
"appid": 4245,
"applicationbuildnumber": "2",
"appname": "Acme testing",
"appplatformid": 8140,
"appversion": "2.0",
"audiencemembership": ["123", "456", "789"],
"batchid": -6520741417792989986,
"batchtimestamp": 1553009917073,
"brand": "google",
"cityname": "Sierra View",
"clientip": "75.154.15.95",
"clientipv6": "75.154.15.95",
"countrycode": "US",
"customerid": "9172349@gmail.com",
"dataconnectiontype": "wifi",
"devicemodel": "Nexus 7",
"devicename": "Unknown",
"deviceutcoffset": -5,
"email": "7309226@acme.com",
"entrypointtype": 128,
"eventattributes": {
"$Amount": "5.37769004487325",
"Navigation 0 Attr 0": "12.3",
"another new attribute": "value",
"first_name": "First",
"last_name": "Last",
"newattribute": "value",
"yet another new attribute": "value"
},
"eventdate": "2019-03-19",
"eventhour": "2019-03-19 15:00:00",
"eventid": 351939524822094163,
"eventlength": 0,
"eventltvvalue": 5.37769004487325,
"eventname": "Navigation 0",
"eventstarttimestamp": 1553009774253,
"eventtimestamp": 1553009774253,
"eventtypeid": 1,
"firstseentimestamp": 1553009917073,
"googleaid": "9a8cd090-1a4f-4cb9-b76f-1bbca598d985",
"isdebug": true,
"latitude": 41.033192,
"localecountry": "US",
"localelanguage": "EN",
"longitude": -75.449047,
"manufacture": "LGE",
"messagetypeid": 4,
"mparticleuserid": -5045766802590845105,
"networkcarrier": "Sprint",
"networkcountry": "US",
"osversion": "4.2.1",
"osversionint": 0,
"packagename": "com.mparticle.demo",
"platform": "Android",
"product": "occam",
"regioncode": "PA",
"screendpi": 160,
"screenheight": 736,
"screenwidth": 1280,
"sdkversion": "5.1.0",
"sessionid": 3021067757087817833,
"sessionstarttimestamp": 1553009774253,
"upgradedate": 0,
"userattributes": {
"$Age": "85",
"$Gender": "male",
"$Zip": "95450",
"LiveInNewYork": "true",
"another new user attribute": "56",
"status": "gold"
},
"workspaceid": 4254,
"yahoouserid": "1940141@yahoo.com"
}
mParticle also creates two types of views under the schema:
mp_vw_{tableName}
is created that allows you to run regular SQL queries against each table. For example, to query workspaceid
from each table, instead of using data:workspaceid
to query the table, you can use workspaceid
to query the view. Each user attribute and event attribute has its own column in the view. For user attribute named Some Sample User Attribute
and event attribute named Some Sample Event Attribute
, the column name in the view is "ua Some Sample User Attribute"
and "ea Some Sample Event Attribute"
, respectively. Attribute column names have double quotes and are case sensitive.eventsview
that unions all per table views to give you easy access to all data under the schema.Use syntax data:key_name
. Here are some sample queries:
-- select some "columns" to look at, if querying the table directly
select data:appid, data:eventname, data:eventtimestamp, data:customerid, data:mparticleuserid
from sample_table
limit 10
-- select some "columns" to look at, if querying the view
select appid, eventname, eventtimestamp, customerid, mparticleuserid
from mp_vw_sample_table
limit 10
-- count unique eventid's by hour by event name
select date_trunc('hour', to_timestamp(cast(data:eventtimestamp / 1000 as int))), data:eventname, count(distinct data:eventid)
from sample_table
group by 1, 2
order by 3 desc
If you have chosen to create an IP whitelist as part of your Snowflake Network Policy, you can access a current list of IP addresses used by mParticle here.
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.
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.
mParticle loads data into Snowflake via Amazon S3 and can tolerate the Snowflake cluster being unavailable for up to 30 days, depending on data volume. In the event of extended downtime on your cluster, a data replay can be arranged.