# Apache Beam: Partition Transform

## Overview

If you want to split a PCollection into multiple PCollections based on a function, use the `Partition` transform.

## When You Should Use the Keys Transform

When you want to split the input PCollection into multiple PCollections. You might want to partition a collection of strings based on their length. Then, truncate the longer strings into smaller sizes, but keep the shorter strings the same.

## How to Use the Keys Transform

Just apply the builtin Transform to a PCollection with the following arguments:

1. Number of Partitions
    
2. Partition function - This function must return an integer between 0 and the number of partitions
    

## Example: Partition based on Percentile

```java
    // Provide an int value with the desired number of result partitions, and a
    // PartitionFn that represents the
    // partitioning function. In this example, we define the PartitionFn in-line.
    // Returns a PCollectionList
    // containing each of the resulting partitions as individual PCollection
    // objects.
    PCollection<Student> students =
        pipeline.apply(
            Create.of(
                Student.of("Amy", 88),
                Student.of("Bob", 87),
                Student.of("Chris", 49),
                Student.of("Dylan", 62),
                Student.of("Ellen", 78),
                Student.of("Francis", 53)));
    // Split students up into 10 partitions, by percentile:
    PCollectionList<Student> studentsByPercentile =
        students.apply(
            Partition.of(
                10,
                new Partition.PartitionFn<Student>() {
                  @Override
                  public int partitionFor(Student student, int numPartitions) {
                    return student.getPercentile() // 0..99
                        * numPartitions
                        / 100;
                  }
                }));

    // You can extract each partition from the PCollectionList using the get method,
    // as follows:
    PCollection<Student> fortiethPercentile = studentsByPercentile.get(4);
    fortiethPercentile.apply(ParDo.of(new LogOutput<>("Fortieth percentile: ")));
    pipeline.run();
  }

  
```

## Conclusion

Check out other useful transforms from the [official Apache Beam documentation](https://beam.apache.org/documentation/transforms/java/overview/).