Import BigQuery Data into Amplitude

With Amplitude's BigQuery integration, you can ingest BigQuery data directly into your Amplitude project.

Prerequisites¶

To get started with importing from BigQuery, you need to take care of a few prerequisites.

• You need a table (or tables) in BigQuery. This is where you want to import data from.
• Create a GCS bucket. Amplitude recommends one dedicated to this purpose. The ingestion process must offload data to a GCS bucket before ingesting it into Amplitude. This is due to BigQuery's limited export options.
• Create a Service Account with permissions granted for the bucket and tables you want to ingest, then get the service account key. The Service Account must have the following roles granted to it:
  • BigQuery:
    • BigQuery Job User at the project level.
    • BigQuery Data Viewer at the resource level necessary to access your data to be ingested. If your data is in a single table, just grant the service account BigQuery Data Viewer for that table resource. If the query requires multiple tables or datasets, grant BigQuery Data Viewer on all tables or datasets in the query.
  • Cloud Storage:
    • Storage Admin on the GCS bucket you're using for ingestion.

• Depending on your company's network policy, you may need to add the following IP addresses to your allowlist to allow Amplitude's servers to access your BigQuery instance:

  • Amplitude US IP addresses:
    • 52.33.3.219
    • 35.162.216.242
    • 52.27.10.221
  • Amplitude EU IP addresses:
    • 3.124.22.25
    • 18.157.59.125
    • 18.192.47.195

Add BigQuery as a source¶

To add BigQuery as a data source in your Amplitude project, follow these steps.

1. In Amplitude Data, click Catalog and select the Sources tab.
2. In the Warehouse Sources section, click BigQuery.
3. Add the service account key and specify a GCS bucket name.
4. Click Next to test the connection to make sure it's working.
5. After you confirm your credentials, click Next to select data. You have several configuration options to choose from here:
   • Type of data: This tells Amplitude whether you're ingesting event data, user property or group property data.
   • Type of import:
     • Full Sync: Amplitude periodically imports the entire dataset, regardless of whether the data is already imported. This is good for data sets where the row data changes over time, but there is no easy way to tell which rows have changed. Otherwise, the more efficient option would be a time-based import. This option isn't supported for ingesting event data.
     • Time-based: Amplitude periodically ingests the most recent rows in the data, as determined by the provided Timestamp column. The first import ingests all available data, and later imports ingest any data with timestamps after the time of the most recent import. To use this option, include the timestamp column in the output of your SQL statement.
   • Frequency: Choose from several scheduling options ranging from five minutes to one month (when this is selected, ingestion happens on the first of the month).
   • SQL query: This is the code for the query Amplitude uses to ingest the right data.
6. After you've set your configuration options, click Test SQL to see how the data is coming through from your BigQuery instance. If there are any errors, they appear under the Test SQL button.
7. If there are no errors, click Finish. You get a notification indicating you've successfully enabled the new BigQuery source. Finally, you're redirected to the Sources listing page, where you can see the newly created BigQuery source.

If you have any issues or questions while following this flow, contact the Amplitude team.

Time-based import¶

For Amplitude's time-based import option, it's best practice to use a monotonically increasing timestamp value. This value should indicate when the record was loaded into the source table the SQL configuration is querying from (often referred to as a "server upload time"). The warehouse import tool brings data into Amplitude is by continually updating the maximum value of the column referenced in the Timestamp Column Name input within the Import Config UI with each subsequent import.

Mandatory data fields¶

Include the mandatory fields for the data type when you create the SQL query. These tables outline the mandatory and optional fields for each data type. Find a list of other supported fields for events in the HTTP V2 API documentation and for user properties in the Identify API documentation. Add any columns not in those lists to either event_properties or user_properties, otherwise it's ignored.

Events¶

Find other supported fields in the HTTP V2 API documentation.

User properties¶

Find other supported fields in the Identify API documentation.

Group properties¶

Each group property in group_properties would be applied to every group in groups

Update your BigQuery service account key¶

To update the Service Account used for your BigQuery Source, select the existing BigQuery Source within the Sources section of Data and click the ⚙️ (gear) icon. Within the modal, upload the new Service Account Key you want Amplitude to use moving forward.

BigQuery SQL helper¶

Properties fields¶

Many Amplitude features are powered by "properties" fields, which are composed of property keys and property values. The most common of these properties fields are event_properties and user_properties.

In order for these sets of keys and values to be correctly ingested into Amplitude, they must be exported from BigQuery as raw JSON, not as JSON strings. BigQuery doesn't have great support for JSON, but the following describes how to make sure your data is exported from BigQuery and imported to Amplitude without errors.

The properties fields are sourced from columns with a STRUCT type. The struct type is the field type that represents a key-value structure and is exported from BigQuery in raw JSON format.

If your source table doesn't have the event or user properties organized in a struct type column, you can create it in your select SQL. For example, if your event properties are all flattened into their own columns, you can compose your event_properties into a struct like so:

SELECT STRUCT(

    event_property_column_1 AS event_property_name_1,

    event_property_column_2 AS event_property_name_2

) as event_properties

FROM your_table;

Properties from a JSON string field¶

If you have your event or user properties formatted as JSON as a string field, you still must reconstruct the properties field in the select SQL as a STRUCT. BigQuery exports String fields as String even if the contents are JSON. Amplitude's event validation rejects these.

You can extract values from your JSON String field, though, to use in your properties STRUCT. Use the JSON_EXTRACT_SCALAR function to access the values in your string as follows. If your EVENT_PROPERTIES column in the table contains a JSON String like:

"{\"record count\":\"50\",\"region\":\"eu-central-1\"}" which is shown in the BigQuery UI like {"record count":"50","region":"eu-central-1"}), then you can extract the values from the JSON String like this:

SELECT STRUCT(

    JSON_EXTRACT_SCALAR(EVENT_PROPERTIES, "$.record count") AS record_count,

   JSON_EXTRACT_SCALAR(EVENT_PROPERTIES, "$.region") AS region

) as event_properties

FROM your_table;

String literals¶

Be aware that, unlike other data warehouse products, BigQuery treats "double-quoted strings" as string literals. This means that you can't use them to quote identifiers like column names or table names, or the SQL fails to execute in BigQuery.