public class View
extends java.lang.Object
PCollectionViews from PCollections (to read them as side inputs).
 While a PCollection<ElemT> has many values of type ElemT per
 window, a PCollectionView<ViewT> has a single value of type ViewT for each window. It can be thought of as a mapping from windows to values of type ViewT. The transforms here represent ways of converting the ElemT values in a window
 into a ViewT for that window.
 
When a ParDo transform is processing a main input element in a window w and a
 PCollectionView is read via DoFn.ProcessContext.sideInput(org.apache.beam.sdk.values.PCollectionView<T>), the value of the view
 for w is returned.
 
The SDK supports viewing a PCollection, per window, as a single value, a List,
 an Iterable, a Map, or a multimap (iterable-valued Map).
 
For a PCollection that contains a single value of type T per window, such as
 the output of Combine.globally(org.apache.beam.sdk.transforms.SerializableFunction<java.lang.Iterable<V>, V>), use asSingleton() to prepare it for use as a
 side input:
 
 PCollectionView<T> output = someOtherPCollection
     .apply(Combine.globally(...))
     .apply(View.<T>asSingleton());
 For a small PCollection with windows that can fit entirely in memory, use asList() to prepare it for use as a List. When read as a side input, the entire
 list for a window will be cached in memory.
 
 PCollectionView<List<T>> output =
    smallPCollection.apply(View.<T>asList());
 If a PCollection of KV<K, V> is known to have a single value per window for
 each key, then use asMap() to view it as a Map<K, V>:
 
 PCollectionView<Map<K, V> output =
     somePCollection.apply(View.<K, V>asMap());
 Otherwise, to access a PCollection of KV<K, V> as a Map<K,
 Iterable<V>> side input, use asMultimap():
 
 PCollectionView<Map<K, Iterable<V>> output =
     somePCollection.apply(View.<K, Iterable<V>>asMultimap());
 To iterate over an entire window of a PCollection via side input, use asIterable():
 
 PCollectionView<Iterable<T>> output =
     somePCollection.apply(View.<T>asIterable());
 Both asMultimap() and asMap() are useful for implementing lookup
 based "joins" with the main input, when the side input is small enough to fit into memory.
 
For example, if you represent a page on a website via some Page object and have some
 type UrlVisits logging that a URL was visited, you could convert these to more fully
 structured PageVisit objects using a side input, something like the following:
 
PCollection<Page> pages = ... // pages fit into memory PCollection<UrlVisit> urlVisits = ... // very large collection final PCollectionView<Map<URL, Page>> urlToPageView = pages .apply(WithKeys.of( ... )) // extract the URL from the page .apply(View.<URL, Page>asMap()); PCollection<PageVisit> pageVisits = urlVisits .apply(ParDo.withSideInputs(urlToPageView) .of(new DoFn<UrlVisit, PageVisit>(){@Override void processElement(ProcessContext context) { UrlVisit urlVisit = context.element(); Map<URL, Page> urlToPage = context.sideInput(urlToPageView); Page page = urlToPage.get(urlVisit.getUrl()); c.output(new PageVisit(page, urlVisit.getVisitData())); }}));
See ParDo.SingleOutput.withSideInputs(org.apache.beam.sdk.values.PCollectionView<?>...) for details on how to access this variable
 inside a ParDo over another PCollection.
| Modifier and Type | Class and Description | 
|---|---|
| static class  | View.AsIterable<T>For internal use only; no backwards-compatibility guarantees. | 
| static class  | View.AsList<T>For internal use only; no backwards-compatibility guarantees. | 
| static class  | View.AsMap<K,V>For internal use only; no backwards-compatibility guarantees. | 
| static class  | View.AsMultimap<K,V>For internal use only; no backwards-compatibility guarantees. | 
| static class  | View.AsSingleton<T>For internal use only; no backwards-compatibility guarantees. | 
| static class  | View.CreatePCollectionView<ElemT,ViewT>For internal use only; no backwards-compatibility guarantees. | 
| static class  | View.ToListViewDoFn<T>Provides an index to value mapping using a random starting index and also provides an offset
 range for each window seen. | 
| Modifier and Type | Method and Description | 
|---|---|
| static <T> View.AsIterable<T> | asIterable()Returns a  View.AsIterabletransform that takes aPCollectionas input and
 produces aPCollectionViewmapping each window to anIterableof the values in
 that window. | 
| static <T> View.AsList<T> | asList()Returns a  View.AsListtransform that takes aPCollectionand returns aPCollectionViewmapping each window to aListcontaining all of the elements in the
 window. | 
| static <K,V> View.AsMap<K,V> | asMap()Returns a  View.AsMaptransform that takes aPCollection<KV<K,
 V>>as input and produces aPCollectionViewmapping each window to aMap<K, V>. | 
| static <K,V> View.AsMultimap<K,V> | asMultimap()Returns a  View.AsMultimaptransform that takes aPCollection<KV<K, V>>as input and produces aPCollectionViewmapping each
 window to its contents as aMap<K, Iterable<V>>for use as a side
 input. | 
| static <T> View.AsSingleton<T> | asSingleton()Returns a  View.AsSingletontransform that takes aPCollectionwith a single value
 per window as input and produces aPCollectionViewthat returns the value in the main
 input window when read as a side input. | 
public static <T> View.AsSingleton<T> asSingleton()
View.AsSingleton transform that takes a PCollection with a single value
 per window as input and produces a PCollectionView that returns the value in the main
 input window when read as a side input.
 
 PCollection<InputT> input = ...
 CombineFn<InputT, OutputT> yourCombineFn = ...
 PCollectionView<OutputT> output = input
     .apply(Combine.globally(yourCombineFn))
     .apply(View.<OutputT>asSingleton());
 If the input PCollection is empty, throws NoSuchElementException
 in the consuming DoFn.
 
If the input PCollection contains more than one element, throws IllegalArgumentException in the consuming DoFn.
public static <T> View.AsList<T> asList()
View.AsList transform that takes a PCollection and returns a PCollectionView mapping each window to a List containing all of the elements in the
 window.
 This view should only be used if random access and/or size of the PCollection is required.
 asIterable() will perform significantly better for sequential access.
 
Some runners may require that the view fits in memory.
public static <T> View.AsIterable<T> asIterable()
View.AsIterable transform that takes a PCollection as input and
 produces a PCollectionView mapping each window to an Iterable of the values in
 that window.
 Some runners may require that the view fits in memory.
public static <K,V> View.AsMap<K,V> asMap()
View.AsMap transform that takes a PCollection<KV<K,
 V>> as input and produces a PCollectionView mapping each window to a Map<K, V>. It is required that each key of the input be associated with a single value,
 per window. If this is not the case, precede this view with Combine.perKey, as in the
 example below, or alternatively use asMultimap().
 
 PCollection<KV<K, V>> input = ...
 CombineFn<V, OutputT> yourCombineFn = ...
 PCollectionView<Map<K, OutputT>> output = input
     .apply(Combine.perKey(yourCombineFn))
     .apply(View.<K, OutputT>asMap());
 Some runners may require that the view fits in memory.
public static <K,V> View.AsMultimap<K,V> asMultimap()
View.AsMultimap transform that takes a PCollection<KV<K, V>> as input and produces a PCollectionView mapping each
 window to its contents as a Map<K, Iterable<V>> for use as a side
 input. In contrast to asMap(), it is not required that the keys in the input
 collection be unique.
 
 PCollection<KV<K, V>> input = ... // maybe more than one occurrence of a some keys
 PCollectionView<Map<K, Iterable<V>>> output = input.apply(View.<K, V>asMultimap());
 Some runners may require that the view fits in memory.