Amplitude Extract
Overview
The Amplitude Extract component calls the Amplitude API to retrieve and store data to be either referenced by an external table or loaded into a table, depending on your cloud data warehouse. You can then use transformation components to enrich and manage the data in permanent tables.
Using this component may return structured data that requires flattening. For help with flattening such data, we recommend using the following components:
- Extract Nested Data for Snowflake or Google BigQuery.
- Nested Data Load for Amazon Redshift.
Properties
Name = string
A human-readable name for the component.
Data Source = drop-down
Select an Amplitude data source. Available options are Event Types and Events.
API Key = string
A valid Amplitude API key. For help acquiring your Amplitude API key, read Amplitude Extract authentication guide.
Secret Key = string
A valid Amplitude secret key. For help acquiring your Amplitude secret key, read Amplitude Extract authentication guide. Store the secret key in the component, or create a managed entry for the secret key using Manage Passwords (recommended).
Start Time = datetime
Designate a start time. The format, without whitespace, is YYYYMMDDT00.
T00, T01, T02...T23 indicate the hour (there is no T24). Select only one hour. Only required when using the Events data source.
End Time = datetime
Designate an end time. The format, without whitespace, is YYYYMMDDT00.
T00, T01, T02...T23 indicate the hour (there is no T24). Select only one hour. Only required when using the Events data source.
Location = filepath
Provide an Amazon S3 bucket path, Google Cloud Storage (GCS) bucket path, or Azure Blob Storage path that will be used to store the data. The data can then be referenced by an external table. A folder will be created at this location with the same name as the target table.
Integration = drop-down
(GCP only) Choose your Google Cloud Storage Integration. Integrations are required to permit Snowflake to read data from and write to a Google Cloud Storage bucket. Integrations must be set up in advance of selecting them in Matillion ETL. To learn more about setting up a storage integration, read our Storage Integration setup guide.
Warehouse = drop-down
The Snowflake warehouse used to run the queries. The special value, [Environment Default], will use the warehouse defined in the environment. Read Overview of Warehouses to learn more.
Database = drop-down
The Snowflake database. The special value, [Environment Default], will use the database defined in the environment. Read Databases, Tables and Views - Overview to learn more.
Schema = drop-down
The Snowflake schema. The special value, [Environment Default], will use the schema defined in the environment. Read Database, Schema, and Share DDL to learn more.
Target Table = string
A name for the new table. Upon running the job, this table will be recreated and will drop any existing table of the same name.
Name = string
A human-readable name for the component.
Data Source = drop-down
Select an Amplitude data source. Available options are Event Types and Events.
API Key = string
A valid Amplitude API key. For help acquiring your Amplitude API key, read Amplitude Extract authentication guide.
Secret Key = string
A valid Amplitude secret key. For help acquiring your Amplitude secret key, read Amplitude Extract authentication guide. Store the secret key in the component, or create a managed entry for the secret key using Manage Passwords (recommended).
Start Time = datetime
Designate a start time. The format, without whitespace, is YYYYMMDDT00.
T00, T01, T02...T23 indicate the hour (there is no T24). Select only one hour. Only required when using the Events data source.
End Time = datetime
Designate an end time. The format, without whitespace, is YYYYMMDDT00.
T00, T01, T02...T23 indicate the hour (there is no T24). Select only one hour. Only required when using the Events data source.
Location = filepath
Provide an Amazon S3 bucket path that will be used to store the data. The data can then be referenced by an external table. A folder will be created at this location with the same name as the target table.
Type = drop-down
- External: The data will be put into your chosen S3 bucket and referenced by an external table.
- Standard: The data will be staged on your chosen S3 bucket before being loaded into a table. This is the default setting.
Standard Schema = drop-down
The Redshift schema. The special value, [Environment Default], will use the schema defined in the Matillion ETL environment.
External Schema = drop-down
The table's external schema. Read Getting Started with Amazon Redshift Spectrum to learn more.
Target Table = string
A name for the new table. Upon running the job, this table will be recreated and will drop any existing table of the same name.
Name = string
A human-readable name for the component.
Data Source = drop-down
Select an Amplitude data source. Available options are Event Types and Events.
API Key = string
A valid Amplitude API key. For help acquiring your Amplitude API key, read Amplitude Extract authentication guide.
Secret Key = string
A valid Amplitude secret key. For help acquiring your Amplitude secret key, read Amplitude Extract authentication guide. Store the secret key in the component, or create a managed entry for the secret key using Manage Passwords (recommended).
Start Time = datetime
Designate a start time. The format, without whitespace, is YYYYMMDDT00.
T00, T01, T02...T23 indicate the hour (there is no T24). Select only one hour. Only required when using the Events data source.
End Time = datetime
Designate an end time. The format, without whitespace, is YYYYMMDDT00.
T00, T01, T02...T23 indicate the hour (there is no T24). Select only one hour. Only required when using the Events data source.
Table Type = drop-down
Select whether the table is Native (by default in BigQuery) or an external table.
Project = drop-down
Select the Google Cloud project. The special value, [Environment Default], will use the project defined in the environment. For more information, read Creating and managing projects.
Dataset = drop-down
Select the Google BigQuery dataset to load data into. The special value, [Environment Default], will use the dataset defined in the environment. For more information, read Introduction to datasets.
Target Table = string
A name for the new table. Upon running the job, this table will be recreated and will drop any existing table of the same name.
New Target Table = string
A name for the new external table. Only available when the table type is External.
Cloud Storage Staging Area = Google Cloud Storage bucket
The URL and path of the target Google Cloud Storage bucket to be used for staging the queried data. Only available when the table type is Native.
Location = Google Cloud Storage bucket
The URL and path of the target Google Cloud Storage bucket. Only available when the table type is External.
Load Options = multiple drop-downs
- Clean Cloud Storage Files: Destroy staged files on Google Cloud Storage after loading data. Default is On.
- Cloud Storage File Prefix: Give staged file names a prefix of your choice. The default setting is an empty field.
- Recreate Target Table: Choose whether the component recreates its target table before the data load. If Off, the component will use an existing table or create one if it does not exist. Default is On.
- Use Grid Variable: Check this checkbox to use a grid variable. This box is unchecked by default.
| Snowflake | Delta Lake on Databricks | Amazon Redshift | Google BigQuery | Azure Synapse Analytics |
|---|---|---|---|---|
| ✅ | ❌ | ✅ | ✅ | ❌ |