AppSearch

AppSearch is a high-performance on-device search solution for managing locally stored, structured data. It contains APIs for indexing data and retrieving data using full-text search. Applications can use AppSearch to offer custom in-app search capabilities, allowing users to search for content even while offline.

AppSearch provides the following features:

• A fast, mobile-first storage implementation with low I/O use
• Highly efficient indexing and querying over large data sets
• Multi-language support, such as English and Spanish
• Relevance ranking and usage scoring

Due to lower I/O use, AppSearch offers lower latency for indexing and searching over large datasets compared to SQLite. AppSearch simplifies cross-type queries by supporting single queries whereas SQLite merges results from multiple tables.

To illustrate AppSearch’s features, let’s take the example of a music application that manages users’ favorite songs and allows users to easily search for them. Users enjoy music from around the world with song titles in different languages, which AppSearch natively supports indexing and querying for. When the user searches for a song by title or artist name, the application simply passes the request to AppSearch to quickly and efficiently retrieve matching songs. The application surfaces the results, allowing its users to quickly start playing their favorite songs.

Setup

To use AppSearch in your application, add the following dependencies to your application's build.gradle file:

Groovy

dependencies {
    def appsearch_version = "1.1.0-alpha05"

    implementation "androidx.appsearch:appsearch:$appsearch_version"
    // Use kapt instead of annotationProcessor if writing Kotlin classes
    annotationProcessor "androidx.appsearch:appsearch-compiler:$appsearch_version"

    implementation "androidx.appsearch:appsearch-local-storage:$appsearch_version"
    // PlatformStorage is compatible with Android 12+ devices, and offers additional features
    // to LocalStorage.
    implementation "androidx.appsearch:appsearch-platform-storage:$appsearch_version"
}

Kotlin

dependencies {
    val appsearch_version = "1.1.0-alpha05"

    implementation("androidx.appsearch:appsearch:$appsearch_version")
    // Use annotationProcessor instead of kapt if writing Java classes
    kapt("androidx.appsearch:appsearch-compiler:$appsearch_version")

    implementation("androidx.appsearch:appsearch-local-storage:$appsearch_version")
    // PlatformStorage is compatible with Android 12+ devices, and offers additional features
    // to LocalStorage.
    implementation("androidx.appsearch:appsearch-platform-storage:$appsearch_version")
}

AppSearch concepts

The following diagram illustrates AppSearch concepts and their interactions.

Figure 1. Diagram of AppSearch concepts: AppSearch database, schema, schema types, documents, session, and search.

Database and session

An AppSearch database is a collection of documents that conforms to the database schema. Client applications create a database by providing their application context and a database name. Databases can be opened only by the application that created them. When a database is opened, a session is returned to interact with the database. The session is the entry point for calling the AppSearch APIs and remains open until it’s closed by the client application.

Schema and schema types

A schema represents the organizational structure of data within an AppSearch database.

The schema is composed of schema types that represent unique types of data. Schema types consist of properties that contain a name, data type, and cardinality. Once a schema type is added to the database schema, documents of that schema type can be created and added to the database.

Documents

In AppSearch, a unit of data is represented as a document. Each document in an AppSearch database is uniquely identified by its namespace and ID. Namespaces are used to separate data from different sources when only one source needs to be queried, such as user accounts.

Documents contain a creation timestamp, a time-to-live (TTL), and a score that can be used for ranking during retrieval. A document is also assigned a schema type that describes additional data properties the document must have.

A document class is an abstraction of a document. It contains annotated fields that represent the contents of a document. By default, the name of the document class sets the name of the schema type.

Search

Documents are indexed and can be searched by providing a query. A document is matched and included in the search results if it contains the terms in the query or matches another search specification. Results are ordered based on their score and ranking strategy. Search results are represented by pages that you can retrieve sequentially.

AppSearch offers customizations for search, such as filters, page size configuration, and snippeting.

Platform Storage vs Local Storage

AppSearch offers two storage solutions: LocalStorage and PlatformStorage. With LocalStorage, your application manages an app-specific index that lives in your application data directory. With PlatformStorage, your application contributes to a system-wide central index. Data access within the central index is restricted to data your application has contributed and data that has been explicitly shared with you by another application. Both LocalStorage and PlatformStorage share the same API and can be interchanged based on a device's version:

Kotlin

if (BuildCompat.isAtLeastS()) {
    appSearchSessionFuture.setFuture(
        PlatformStorage.createSearchSession(
            PlatformStorage.SearchContext.Builder(mContext, DATABASE_NAME)
               .build()
        )
    )
} else {
    appSearchSessionFuture.setFuture(
        LocalStorage.createSearchSession(
            LocalStorage.SearchContext.Builder(mContext, DATABASE_NAME)
                .build()
        )
    )
}

Java

if (BuildCompat.isAtLeastS()) {
    mAppSearchSessionFuture.setFuture(PlatformStorage.createSearchSession(
            new PlatformStorage.SearchContext.Builder(mContext, DATABASE_NAME)
                    .build()));
} else {
    mAppSearchSessionFuture.setFuture(LocalStorage.createSearchSession(
            new LocalStorage.SearchContext.Builder(mContext, DATABASE_NAME)
                    .build()));
}

Using PlatformStorage, your application can securely share data with other applications to allow them to search over your app's data as well. Read-only application data sharing is granted via a certificate handshake to ensure that the other application has permission to read the data. Read more about this API in the documentation for setSchemaTypeVisibilityForPackage().

Additionally, data that is indexed can be displayed on System UI surfaces. Applications can opt out of some or all of their data being displayed on System UI surfaces. Read more about this API in the documentation for setSchemaTypeDisplayedBySystem().

Features	LocalStorage (compatible with Android 4.0+)	PlatformStorage (compatible with Android 12+)
Efficient full-text search
Multi-language support
Reduced binary size
Application-to-application data sharing
Capability to display data on System UI surfaces
Unlimited document size and count can be indexed
Faster operations without additional binder latency

There are additional trade-offs to consider when choosing between LocalStorage and PlatformStorage. Because PlatformStorage wraps Jetpack APIs over the AppSearch system service, the APK size impact is minimal compared to using LocalStorage. However, this also means AppSearch operations incur additional binder latency when calling the AppSearch system service. With PlatformStorage, AppSearch limits the number of documents and size of documents an application can index to ensure an efficient central index.

Get started with AppSearch

The example in this section showcases how to use AppSearch APIs to integrate with a hypothetical note-keeping application.

Write a document class

The first step to integrate with AppSearch is to write a document class to describe the data to insert into the database. Mark a class as a document class by using the @Document annotation.You can use instances of the document class to put documents in and retrieve documents from the database.

The following code defines a Note document class with a @Document.StringProperty annotated field for indexing a Note object’s text.

Kotlin

@Document
public data class Note(

    // Required field for a document class. All documents MUST have a namespace.
    @Document.Namespace
    val namespace: String,

    // Required field for a document class. All documents MUST have an Id.
    @Document.Id
    val id: String,

    // Optional field for a document class, used to set the score of the
    // document. If this is not included in a document class, the score is set
    // to a default of 0.
    @Document.Score
    val score: Int,

    // Optional field for a document class, used to index a note's text for this
    // document class.
    @Document.StringProperty(indexingType = AppSearchSchema.StringPropertyConfig.INDEXING_TYPE_PREFIXES)
    val text: String
)

Java

@Document
public class Note {

  // Required field for a document class. All documents MUST have a namespace.
  @Document.Namespace
  private final String namespace;

  // Required field for a document class. All documents MUST have an Id.
  @Document.Id
  private final String id;

  // Optional field for a document class, used to set the score of the
  // document. If this is not included in a document class, the score is set
  // to a default of 0.
  @Document.Score
  private final int score;

  // Optional field for a document class, used to index a note's text for this
  // document class.
  @Document.StringProperty(indexingType = StringPropertyConfig.INDEXING_TYPE_PREFIXES)
  private final String text;

  Note(@NonNull String id, @NonNull String namespace, int score, @NonNull String text) {
    this.id = Objects.requireNonNull(id);
    this.namespace = Objects.requireNonNull(namespace);
    this.score = score;
    this.text = Objects.requireNonNull(text);
  }

  @NonNull
  public String getNamespace() {
    return namespace;
  }

  @NonNull
  public String getId() {
    return id;
  }

  public int getScore() {
    return score;
  }

  @NonNull
  public String getText() {
     return text;
  }
}

Open a database

You must create a database before working with documents. The following code creates a new database with the name notes_app and gets a ListenableFuture for an AppSearchSession, which represents the connection to the database and provides the APIs for database operations.

Kotlin

val context: Context = getApplicationContext()
val sessionFuture = LocalStorage.createSearchSession(
    LocalStorage.SearchContext.Builder(context, /*databaseName=*/"notes_app")
    .build()
)

Java

Context context = getApplicationContext();
ListenableFuture<AppSearchSession> sessionFuture = LocalStorage.createSearchSession(
       new LocalStorage.SearchContext.Builder(context, /*databaseName=*/ "notes_app")
               .build()
);

Set a schema

You must set a schema before you can put documents in and retrieve documents from the database. The database schema consists of different types of structured data, referred to as "schema types." The following code sets the schema by providing the document class as a schema type.

Kotlin

val setSchemaRequest = SetSchemaRequest.Builder().addDocumentClasses(Note::class.java)
    .build()
val setSchemaFuture = Futures.transformAsync(
    sessionFuture,
    { session ->
        session?.setSchema(setSchemaRequest)
    }, mExecutor
)

Java

SetSchemaRequest setSchemaRequest = new SetSchemaRequest.Builder().addDocumentClasses(Note.class)
       .build();
ListenableFuture<SetSchemaResponse> setSchemaFuture =
       Futures.transformAsync(sessionFuture, session -> session.setSchema(setSchemaRequest), mExecutor);

Put a document in the database

Once a schema type is added, you can add documents of that type to the database. The following code builds a document of schema type Note using the Note document class builder. It sets the document namespace user1 to represent an arbitrary user of this sample. The document is then inserted into the database and a listener is attached to process the result of the put operation.

Kotlin

val note = Note(
    namespace="user1",
    id="noteId",
    score=10,
    text="Buy fresh fruit"
)

val putRequest = PutDocumentsRequest.Builder().addDocuments(note).build()
val putFuture = Futures.transformAsync(
    sessionFuture,
    { session ->
        session?.put(putRequest)
    }, mExecutor
)

Futures.addCallback(
    putFuture,
    object : FutureCallback<AppSearchBatchResult<String, Void>?> {
        override fun onSuccess(result: AppSearchBatchResult<String, Void>?) {

            // Gets map of successful results from Id to Void
            val successfulResults = result?.successes

            // Gets map of failed results from Id to AppSearchResult
            val failedResults = result?.failures
        }

        override fun onFailure(t: Throwable) {
            Log.e(TAG, "Failed to put documents.", t)
        }
    },
    mExecutor
)

Java

Note note = new Note(/*namespace=*/"user1", /*id=*/
                "noteId", /*score=*/ 10, /*text=*/ "Buy fresh fruit!");

PutDocumentsRequest putRequest = new PutDocumentsRequest.Builder().addDocuments(note)
       .build();
ListenableFuture<AppSearchBatchResult<String, Void>> putFuture =
       Futures.transformAsync(sessionFuture, session -> session.put(putRequest), mExecutor);

Futures.addCallback(putFuture, new FutureCallback<AppSearchBatchResult<String, Void>>() {
   @Override
   public void onSuccess(@Nullable AppSearchBatchResult<String, Void> result) {

     // Gets map of successful results from Id to Void
     Map<String, Void> successfulResults = result.getSuccesses();

     // Gets map of failed results from Id to AppSearchResult
     Map<String, AppSearchResult<Void>> failedResults = result.getFailures();
   }

   @Override
   public void onFailure(@NonNull Throwable t) {
      Log.e(TAG, "Failed to put documents.", t);
   }
}, mExecutor);

Search

You can search documents that are indexed using the search operations covered in this section. The following code performs queries for the term "fruit" over the database for documents that belong to the user1 namespace.

Kotlin

val searchSpec = SearchSpec.Builder()
    .addFilterNamespaces("user1")
    .build();

val searchFuture = Futures.transform(
    sessionFuture,
    { session ->
        session?.search("fruit", searchSpec)
    },
    mExecutor
)
Futures.addCallback(
    searchFuture,
    object : FutureCallback<SearchResults> {
        override fun onSuccess(searchResults: SearchResults?) {
            iterateSearchResults(searchResults)
        }

        override fun onFailure(t: Throwable?) {
            Log.e("TAG", "Failed to search notes in AppSearch.", t)
        }
    },
    mExecutor
)

Java

SearchSpec searchSpec = new SearchSpec.Builder()
       .addFilterNamespaces("user1")
       .build();

ListenableFuture<SearchResults> searchFuture =
       Futures.transform(sessionFuture, session -> session.search("fruit", searchSpec),
       mExecutor);

Futures.addCallback(searchFuture,
       new FutureCallback<SearchResults>() {
           @Override
           public void onSuccess(@Nullable SearchResults searchResults) {
               iterateSearchResults(searchResults);
           }

           @Override
           public void onFailure(@NonNull Throwable t) {
               Log.e(TAG, "Failed to search notes in AppSearch.", t);
           }
       }, mExecutor);

Iterate through SearchResults

Searches return a SearchResults instance, which gives access to the pages of SearchResult objects. Each SearchResult holds its matched GenericDocument, the general form of a document that all documents are converted to. The following code gets the first page of search results and converts the result back into a Note document.

Kotlin

Futures.transform(
    searchResults?.nextPage,
    { page: List<SearchResult>? ->
        // Gets GenericDocument from SearchResult.
        val genericDocument: GenericDocument = page!![0].genericDocument
        val schemaType = genericDocument.schemaType
        val note: Note? = try {
            if (schemaType == "Note") {
                // Converts GenericDocument object to Note object.
                genericDocument.toDocumentClass(Note::class.java)
            } else null
        } catch (e: AppSearchException) {
            Log.e(
                TAG,
                "Failed to convert GenericDocument to Note",
                e
            )
            null
        }
        note
    },
    mExecutor
)

Java

Futures.transform(searchResults.getNextPage(), page -> {
  // Gets GenericDocument from SearchResult.
  GenericDocument genericDocument = page.get(0).getGenericDocument();
  String schemaType = genericDocument.getSchemaType();

  Note note = null;

  if (schemaType.equals("Note")) {
    try {
      // Converts GenericDocument object to Note object.
      note = genericDocument.toDocumentClass(Note.class);
    } catch (AppSearchException e) {
      Log.e(TAG, "Failed to convert GenericDocument to Note", e);
    }
  }

  return note;
}, mExecutor);

Remove a document

When the user deletes a note, the application deletes the corresponding Note document from the database. This ensures the note will no longer be surfaced in queries. The following code makes an explicit request to remove the Note document from the database by Id.

Kotlin

val removeRequest = RemoveByDocumentIdRequest.Builder("user1")
    .addIds("noteId")
    .build()

val removeFuture = Futures.transformAsync(
    sessionFuture, { session ->
        session?.remove(removeRequest)
    },
    mExecutor
)

Java

RemoveByDocumentIdRequest removeRequest = new RemoveByDocumentIdRequest.Builder("user1")
       .addIds("noteId")
       .build();

ListenableFuture<AppSearchBatchResult<String, Void>> removeFuture =
       Futures.transformAsync(sessionFuture, session -> session.remove(removeRequest), mExecutor);

Persist to disk

Updates to a database should be periodically persisted to disk by calling requestFlush(). The following code calls requestFlush() with a listener to determine if the call was successful.

Kotlin

val requestFlushFuture = Futures.transformAsync(
    sessionFuture,
    { session -> session?.requestFlush() }, mExecutor
)

Futures.addCallback(requestFlushFuture, object : FutureCallback<Void?> {
    override fun onSuccess(result: Void?) {
        // Success! Database updates have been persisted to disk.
    }

    override fun onFailure(t: Throwable) {
        Log.e(TAG, "Failed to flush database updates.", t)
    }
}, mExecutor)

Java

ListenableFuture<Void> requestFlushFuture = Futures.transformAsync(sessionFuture,
        session -> session.requestFlush(), mExecutor);

Futures.addCallback(requestFlushFuture, new FutureCallback<Void>() {
    @Override
    public void onSuccess(@Nullable Void result) {
        // Success! Database updates have been persisted to disk.
    }

    @Override
    public void onFailure(@NonNull Throwable t) {
        Log.e(TAG, "Failed to flush database updates.", t);
    }
}, mExecutor);

Close a session

An AppSearchSession should be closed when an application will no longer be calling any database operations. The following code closes the AppSearch session that was opened previously and persists all updates to disk.

Kotlin

val closeFuture = Futures.transform<AppSearchSession, Unit>(sessionFuture,
    { session ->
        session?.close()
        Unit
    }, mExecutor
)

Java

ListenableFuture<Void> closeFuture = Futures.transform(sessionFuture, session -> {
   session.close();
   return null;
}, mExecutor);

Additional resources

To learn more about AppSearch, see the following additional resources:

Samples

• Android AppSearch Sample (Kotlin), a note taking app that uses AppSearch to index a user's notes and allows users to search over their notes.

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