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# ParDo
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<br>
A transform for generic parallel processing. A `ParDo` transform considers each
element in the input `PCollection`, performs some processing function
(your user code) on that element, and emits zero or more elements to
an output PCollection.

See more information in the [Beam Programming Guide]({{ site.baseurl }}/documentation/programming-guide/#pardo).

## Examples
**Example 1**: Passing side inputs

```java
  // Pass side inputs to your ParDo transform by invoking .withSideInputs.
  // Inside your DoFn, access the side input by using the method DoFn.ProcessContext.sideInput.

  // The input PCollection to ParDo.
  PCollection<String> words = ...;

  // A PCollection of word lengths that we'll combine into a single value.
  PCollection<Integer> wordLengths = ...; // Singleton PCollection

  // Create a singleton PCollectionView from wordLengths using Combine.globally and View.asSingleton.
  final PCollectionView<Integer> maxWordLengthCutOffView =
     wordLengths.apply(Combine.globally(new Max.MaxIntFn()).asSingletonView());


  // Apply a ParDo that takes maxWordLengthCutOffView as a side input.
  PCollection<String> wordsBelowCutOff =
  words.apply(ParDo
      .of(new DoFn<String, String>() {
          public void processElement(ProcessContext c) {
            String word = c.element();
            // In our DoFn, access the side input.
            int lengthCutOff = c.sideInput(maxWordLengthCutOffView);
            if (word.length() <= lengthCutOff) {
              c.output(word);
            }
          }
      }).withSideInputs(maxWordLengthCutOffView)
  );
```

**Example 2**: Emitting to multiple outputs in your `DoFn`

```java
// To emit elements to multiple output PCollections, create a TupleTag object to identify each collection
// that your ParDo produces. For example, if your ParDo produces three output PCollections (the main output
// and two additional outputs), you must create three TupleTags. The following example code shows how to
// create TupleTags for a ParDo with three output PCollections.

  // Input PCollection to our ParDo.
  PCollection<String> words = ...;

  // The ParDo will filter words whose length is below a cutoff and add them to
  // the main ouput PCollection<String>.
  // If a word is above the cutoff, the ParDo will add the word length to an
  // output PCollection<Integer>.
  // If a word starts with the string "MARKER", the ParDo will add that word to an
  // output PCollection<String>.
  final int wordLengthCutOff = 10;

  // Create three TupleTags, one for each output PCollection.
  // Output that contains words below the length cutoff.
  final TupleTag<String> wordsBelowCutOffTag =
      new TupleTag<String>(){};
  // Output that contains word lengths.
  final TupleTag<Integer> wordLengthsAboveCutOffTag =
      new TupleTag<Integer>(){};
  // Output that contains "MARKER" words.
  final TupleTag<String> markedWordsTag =
      new TupleTag<String>(){};

// Passing Output Tags to ParDo:
// After you specify the TupleTags for each of your ParDo outputs, pass the tags to your ParDo by invoking
// .withOutputTags. You pass the tag for the main output first, and then the tags for any additional outputs
// in a TupleTagList. Building on our previous example, we pass the three TupleTags for our three output
// PCollections to our ParDo. Note that all of the outputs (including the main output PCollection) are
// bundled into the returned PCollectionTuple.

  PCollectionTuple results =
      words.apply(ParDo
          .of(new DoFn<String, String>() {
            // DoFn continues here.
            ...
          })
          // Specify the tag for the main output.
          .withOutputTags(wordsBelowCutOffTag,
          // Specify the tags for the two additional outputs as a TupleTagList.
                          TupleTagList.of(wordLengthsAboveCutOffTag)
                                      .and(markedWordsTag)));
```

**Example 3**: Tags for multiple outputs

```java
// Inside your ParDo's DoFn, you can emit an element to a specific output PCollection by passing in the
// appropriate TupleTag when you call ProcessContext.output.
// After your ParDo, extract the resulting output PCollections from the returned PCollectionTuple.
// Based on the previous example, this shows the DoFn emitting to the main output and two additional outputs.

  .of(new DoFn<String, String>() {
     public void processElement(ProcessContext c) {
       String word = c.element();
       if (word.length() <= wordLengthCutOff) {
         // Emit short word to the main output.
         // In this example, it is the output with tag wordsBelowCutOffTag.
         c.output(word);
       } else {
         // Emit long word length to the output with tag wordLengthsAboveCutOffTag.
         c.output(wordLengthsAboveCutOffTag, word.length());
       }
       if (word.startsWith("MARKER")) {
         // Emit word to the output with tag markedWordsTag.
         c.output(markedWordsTag, word);
       }
     }}));
```


## Related transforms 
* [MapElements]({{ site.baseurl }}/documentation/transforms/java/elementwise/mapelements)
  applies a simple 1-to-1 mapping function over each element in the collection.
* [Filter]({{ site.baseurl }}/documentation/transforms/java/elementwise/filter)
  is useful if the function is just deciding whether to output an element or not.