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Fused in 5 Minutes

Welcome to Fused! This tutorial will get you up and running in just 5 minutes with three simple examples that demonstrate the core concepts of User Defined Functions (UDFs).

What is a UDF?​

A User Defined Function (UDF) is a Python function decorated with @fused.udf that can be run anywhere - in the cloud, on your local machine, or embedded in web applications. Read more about why UDFs.

Example 1: Hello World UDF​

Let's start with the simplest possible UDF:

import fused

@fused.udf
def udf(x: int = 1):
    return f"Hello world {x + x}"

fused.run(udf)

What this does:

Try it:

  1. Copy this code into Fused Workbench
  2. Click "Run" to execute it
  3. You'll see the output: "Hello world 2"

Example 2: Simple Data UDF​

Now let's create a UDF that returns structured data:

@fused.udf
def udf(x: int = 5):
    import pandas as pd
    return pd.DataFrame({"x": range(x)})

What this does:

  • Creates a pandas DataFrame with numbers from 0 to x-1
  • Returns structured data that can be visualized or processed further
  • Default value creates a DataFrame with 5 rows

Try it:

  1. Paste this code into a new UDF in Workbench
  2. Run it to see a table with values 0, 1, 2, 3, 4
  3. Try changing the parameter x to see different amounts of data

Example 3: Simple Data File UDF​

Finally, let's read real data from a file:

@fused.udf
def udf(x: int = 10):
    import pandas as pd
    # Read from a public dataset
    df = pd.read_parquet("s3://fused-asset/infra/building_msft_us.parquet")
    return df.head(x)

What this does:

  • Reads a parquet file from cloud storage (S3)
  • Returns the first x rows of the dataset
  • This example uses Microsoft building footprint data

Try it:

  1. Paste this code into Workbench
  2. Run it to see building data
  3. Try the File Explorer in Workbench to browse other available datasets

Next Steps​

Congratulations! You've just created your first three UDFs. Here's what you can explore next:

  • File Explorer: Browse available datasets in the Fused catalog
  • Map View: Visualize geospatial data on an interactive map
  • Sharing: Share your UDFs with others using shareable URLs
  • Advanced Features: Explore caching, async operations, and more complex data transformations

Key Concepts Learned​

✅ UDF Decorator: @fused.udf transforms any Python function into a distributed, scalable function
✅ Type Hints: Parameters should have type hints and default values
✅ Data Returns: UDFs can return strings, DataFrames, or other data structures
✅ Cloud Integration: Easily read from cloud storage like S3

Ready to build more complex UDFs? Check out our Core Concepts and Examples sections!