Time-Window Aggregation Functions Reference

Time-window aggregation functions are built-in functions that are used by defining an Aggregation object in a Batch Feature View or a Stream Feature View.

• Example of using a time-window aggregation function in a Batch Feature View

• Example of using a time-window aggregation function in a Stream Feature View

This page is a reference that contains the available time-window aggregation functions.

count

An aggregation function that returns, for a materialization time window, the number of row values for a column, per entity value (such as a user_id value). Null values are excluded.

Supported Data Platforms

• Tecton on Spark (Databricks and EMR)
• Tecton on Snowflake

Input column types

• Tecton on Spark: All types
• Tecton on Snowflake: All types

Output column types

• Int64

Usage

To use this aggregation, define an Aggregation object, using function="count", in a Batch Feature View or a Stream Feature View.

Example

Aggregation(column="transaction_id", function="count", time_window=timedelta(days=1))

last_distinct(n)

An aggregation function that returns, for a materialization time window, the last N distinct row values for a column, per entity value (such as a user_id value).

For example, if the last 2 distinct row values for a column, in the materialization time window, are 10 and 20, then the function returns [10,20].

note

The output sequence is in ascending order based on the timestamp.

Supported data platforms

• Tecton on Spark (Databricks and EMR)

Input column types

• String

Output column type

• Array[String]

Usage

To use this aggregation, define an Aggregation object, using function=last_distinct(n), where n is an integer > 0 and <= 1000, in a Batch Feature View or a Stream Feature View.

Example

Aggregation(column="amt", function=last_distinct(2), time_window=timedelta(days=1))

max

An aggregation function that returns, for a materialization time window, the maximum of the row values for a column, per entity value (such as a user_id value).

Supported data platforms

• Tecton on Spark (Databricks and EMR)
• Tecton on Snowflake

Input column types

• Int64, Int32, Float64, String

Output column type

• Int64, Float64, String

Usage

To use this aggregation, define an Aggregation object, using function="max", in a Batch Feature View or a Stream Feature View.

Example

Aggregation(column="amt", function="max", time_window=timedelta(days=1))

mean

An aggregation function that returns, for a materialization time window, the mean of the row values for a column, per entity value (such as a user_id value).

Supported data platforms

• Tecton on Spark (Databricks and EMR)
• Tecton on Snowflake

Input column types

• Int64, Int32, Float64

Output column type

• Float64

Usage

To use this aggregation, define an Aggregation object, using function="mean", in a Batch Feature View or a Stream Feature View.

Example

Aggregation(column="amt", function="mean", time_window=timedelta(days=1))

min

An aggregation function that returns, for a materialization time window, the minimum of the row values for a column, per entity value (such as a user_id value).

Supported data platforms

• Tecton on Spark (Databricks and EMR)
• Tecton on Snowflake

Input column types

• Int64, Int32, Float64, String

Output column type

• Int64, Float64, String

Usage

To use this aggregation, define an Aggregation object, using function="min", in a Batch Feature View or a Stream Feature View.

Example

Aggregation(column="amt", function="min", time_window=timedelta(days=1))

stddev_pop

An aggregation function that returns, for a materialization time window, the standard deviation of the row values for a column around the population mean, per entity value (such as a user_id value).

Supported data platforms

• Tecton on Spark (Databricks and EMR)
• Tecton on Snowflake

Input column types

• Int64, Int32, Float64

Output column type

• Float64

Usage

To use this aggregation, define an Aggregation object, using function="stddev_pop", in a Batch Feature View or a Stream Feature View.

Example

Aggregation(column="amt", function="stddev_pop", time_window=timedelta(days=1))

stddev_samp

An aggregation function that returns, for a materialization time window, the standard deviation of the row values for a column around the sample mean, per entity value (such as a user_id value).

Supported data platforms

• Tecton on Spark (Databricks and EMR)
• Tecton on Snowflake

Input column types

• Int64, Int32, Float64

Output column type

• Float64

Usage

To use this aggregation, define an Aggregation object, using function="stddev_samp", in a Batch Feature View or a Stream Feature View.

Example

Aggregation(column="amt", function="stddev_samp", time_window=timedelta(days=1))

sum

An aggregation function that returns, for a materialization time window, the sum of the row values for a column, per entity value (such as a user_id value).

Supported data platforms

• Tecton on Spark (Databricks and EMR)
• Tecton on Snowflake

Input column types

• Int64, Int32, Float64

Output column type

• Int64 or Float64

Usage

To use this aggregation, define an Aggregation object, using function="sum", in a Batch Feature View or a Stream Feature View.

Example

Aggregation(column="amt", function="sum", time_window=timedelta(days=1))

var_pop

An aggregation function that returns, for a materialization time window, the variance of the row values for a column around the population mean, per entity value (such as a user_id value).

Supported data platforms

• Tecton on Spark (Databricks and EMR)
• Tecton on Snowflake

Input column types

• Int64, Int32, Float64

Output column type

• Float64

Usage

To use this aggregation, define an Aggregation object, using function="var_pop", in a Batch Feature View or a Stream Feature View.

Example

Aggregation(column="amt", function="var_pop", time_window=timedelta(days=1))

var_samp

An aggregation function that returns, for a materialization time window, the variance of the row values for a column around the sample mean, per entity value (such as a user_id value).

Supported data platforms

• Tecton on Spark (Databricks and EMR)
• Tecton on Snowflake

Input column types

• Int64, Int32, Float64

Output column type

• Float64

Usage

To use this aggregation, define an Aggregation object, using function="var_samp", in a Batch Feature View or a Stream Feature View.

Example

Aggregation(column="amt", function="var_samp", time_window=timedelta(days=1))