QueryBuilder

    +

    Description — How to use QueryBuilder to build effective queries with Couchbase Lite on Java
    Related Content — Predictive Queries | Live Queries | Indexing

    The examples used in this topic are based on the Travel Sample app and data introduced in the Couchbase Mobile Workshop tutorial

    Introduction

    Couchbase Lite for Java provides two ways to build and run database queries; the QueryBuilder API described in this topic and the SQL++ for Mobile.

    Database queries defined with the QueryBuilder API use query statements of the form shown in Example 1. The structure and semantics of the query format are based on that of Couchbase’s SQL++ query language.

    Example 1. Query Format
    SELECT ____ (1)
    FROM 'database' (2)
    WHERE ____, (3)
    JOIN ____ (4)
    GROUP BY ____ (5)
    ORDER BY ____ (6)
    Query Components
    1 The SELECT statement specifies the document properties that will be returned in the result set
    2 FROM specifies the database to query the documents from
    3 WHERE statement specifies the query criteria.
    The `SELECT`ed properties of documents matching this criteria will be returned in the result set
    4 JOIN statement specifies the criteria for joining multiple documents
    5 GROUP BY statement specifies the criteria used to group returned items in the result set
    6 ORDER BY statement specifies the criteria used to order the items in the result set
    We recommend working through the query section of the Couchbase Mobile Workshop tutorial as a good way to build your skills in this area.

    Indexing

    See the Indexing topic to learn more about indexing.

    Before we begin querying documents, let’s briefly mention the importance of having a query index. A query can only be fast if there’s a pre-existing database index it can search to narrow down the set of documents to examine — see: Example 2, which shows how to create an index, and also the Query Troubleshooting topic.

    See the Indexing topic to learn more about indexing.

    A query can only be fast if there’s a pre-existing database index it can search to narrow down the set of documents to examine — see: Example 2, which shows how to create an index and our Query Troubleshooting topic.

    However, every index has to be updated whenever a document is updated. So too many indexes can hurt performance.

    Good performance depends on designing and creating the right indexes to go along with your queries.

    Example 2. Creating a New Index

    This example creates a new index for the `type` and `name` properties in the Data Model.

    
    database.createIndex(ValueIndexConfiguration(["type", "name"]), "TypeNameIndex");
    Data Model
    [
      { (1)
        "id": "hotel123",
        "type": "hotel",
        "name": "Hotel Ghia"
      },
      { (2)
        "id": "hotel456",
        "type": "hotel",
        "name": "Hotel Deluxe",
      }
    ]

    SELECT statement

    Use the SELECT statement to specify which properties you want to return from the queried documents. You can opt to retrieve entire documents, or just the specific properties you need.

    Return All Properties

    Use the SelectResult.all() method to return all the properties of selected documents — see: Example 3.

    Example 3. Using SELECT to Retrieve All Properties

    This query shows how to retrieve all properties from all documents in your database.

    Query query = QueryBuilder
        .select(SelectResult.all())
        .from(DataSource.database(database))
        .where(Expression.property("type").equalTo(Expression.string("hotel")));

    The query.execute statement returns the results in a dictionary, where the key is the database name — see Example 4.

    Example 4. ResultSet Format from SelectResult.all()
    [
      {
        "travel-sample": { (1)
          "callsign": "MILE-AIR",
          "country": "United States",
          "iata": "Q5",
          "icao": "MLA",
          "id": 10,
          "name": "40-Mile Air",
          "type": "airline"
        }
      },
      {
        "travel-sample": { (2)
          "callsign": "ALASKAN-AIR",
          "country": "United States",
          "iata": "AA",
          "icao": "AAA",
          "id": 10,
          "name": "Alaskan Airways",
          "type": "airline"
        }
      }
    ]
    1 Here we see the result for the first document matching the query criteria.
    2 Here we see the result for the next document matching the query criteria.

    See: Result Sets for more on processing query results.

    Return Selected Properties

    To access only specific properties, specify a comma separated list of SelectResult expressions, one for each property, in the select statement of your query  — see: Example 5

    Example 5. Using SELECT to Retrieve Specific Properties

    In this query we retrieve and then print the _id, type and name properties of each document.

    Query query = QueryBuilder
        .select(
            SelectResult.expression(Meta.id),
            SelectResult.property("name"),
            SelectResult.property("type"))
        .from(DataSource.database(database))
        .where(Expression.property("type").equalTo(Expression.string("hotel")))
        .orderBy(Ordering.expression(Meta.id));
    
    try {
        for (Result result : query.execute()) {
            Log.i("Sample", String.format("hotel id -> %s", result.getString("id")));
            Log.i("Sample", String.format("hotel name -> %s", result.getString("name")));
        }
    } catch (CouchbaseLiteException e) {
        Log.e("Sample", e.getLocalizedMessage());
    }

    The query.execute statement returns one or more key-value pairs, one for each SelectResult expression, with the property-name as the key — see Example 6

    Example 6. Select Result Format
    [
      { (1)
        "id": "hotel123",
        "type": "hotel",
        "name": "Hotel Ghia"
      },
      { (2)
        "id": "hotel456",
        "type": "hotel",
        "name": "Hotel Deluxe",
      }
    ]
    1 Here we see the result for the first document matching the query criteria.
    2 Here we see the result for the next document matching the query criteria.

    See: Result Sets for more on processing query results.

    WHERE statement

    In this section

    Comparison Operators  |   Collection Operators  |   Like Operator  |   Regex Operator  |   Deleted Document

    Like SQL, you can use the WHERE statement to choose which documents are returned by your query. The select statement takes in an Expression. You can chain any number of Expressions in order to implement sophisticated filtering capabilities.

    Comparison Operators

    The Expression Comparators can be used in the WHERE statement to specify on which property to match documents. In the example below, we use the equalTo operator to query documents where the type property equals "hotel".

    [
      { (1)
        "id": "hotel123",
        "type": "hotel",
        "name": "Hotel Ghia"
      },
      { (2)
        "id": "hotel456",
        "type": "hotel",
        "name": "Hotel Deluxe",
      }
    ]
    Example 7. Using Where
    Query query = QueryBuilder
        .select(SelectResult.all())
        .from(DataSource.database(database))
        .where(Expression.property("type").equalTo(Expression.string("hotel")))
        .limit(Expression.intValue(10));
    for (Result result : query.execute()) {
        Dictionary all = result.getDictionary(DATABASE_NAME);
        Log.i("Sample", String.format("name -> %s", all.getString("name")));
        Log.i("Sample", String.format("type -> %s", all.getString("type")));
    }

    Collection Operators

    ArrayFunction Collection Operators are useful to check if a given value is present in an array.

    CONTAINS Operator

    The following example uses the ArrayFunction to find documents where the public_likes array property contains a value equal to "Armani Langworth".

    {
        "_id": "hotel123",
        "name": "Apple Droid",
        "public_likes": ["Armani Langworth", "Elfrieda Gutkowski", "Maureen Ruecker"]
    }
    Query query = QueryBuilder
        .select(
            SelectResult.expression(Meta.id),
            SelectResult.property("name"),
            SelectResult.property("public_likes"))
        .from(DataSource.database(database))
        .where(Expression.property("type").equalTo(Expression.string("hotel"))
            .and(ArrayFunction
                .contains(Expression.property("public_likes"), Expression.string("Armani Langworth"))));
    for (Result result : query.execute()) {
        Log.i(
            "Sample",
            String.format("public_likes -> %s", result.getArray("public_likes").toList()));
    }

    IN Operator

    The IN operator is useful when you need to explicitly list out the values to test against. The following example looks for documents whose first, last or username property value equals "Armani".

    Expression[] values = new Expression[] {
        Expression.property("first"),
        Expression.property("last"),
        Expression.property("username")
    };
    
    Query query = QueryBuilder.select(SelectResult.all())
        .from(DataSource.database(database))
        .where(Expression.string("Armani").in(values));

    Like Operator

    In this section

    String Matching  |   Wildcard Match  |   Wildcard Character Match

    String Matching

    The Like() operator can be used for string matching — see Example 8

    The like operator performs case sensitive matches.
    To perform case insensitive matching, use Function.lower or Function.upper to ensure all comparators have the same case, thereby removing the case issue.

    This query returns landmark type documents where the name matches the string "Royal Engineers Museum", regardless of how it is capitalized (so, it selects "royal engineers museum", "ROYAL ENGINEERS MUSEUM" and so on).

    Example 8. Like with case-insensitive matching
    Query query = QueryBuilder
        .select(
            SelectResult.expression(Meta.id),
            SelectResult.property("country"),
            SelectResult.property("name"))
        .from(DataSource.database(database))
        .where(Expression.property("type").equalTo(Expression.string("landmark"))
            .and(Function.lower(Expression.property("name")).like(Function.Expression.string("royal engineers museum")))));
    for (Result result : query.execute()) {
        Log.i("Sample", String.format("name -> %s", result.getString("name")));
    }

    Note the use of Function.lower to transform name values to the same case as the literal comparator.

    Wildcard Match

    We can use % sign within a like expression to do a wildcard match against zero or more characters. Using wildcards allows you to have some fuzziness in your search string.

    In Example 9 below, we are looking for documents of type "landmark" where the name property matches any string that begins with "eng" followed by zero or more characters, the letter "e", followed by zero or more characters. Once again, we are using Function.lower to make the search case insensitive.

    So "landmark" documents with names such as "Engineers", "engine", "english egg" and "England Eagle". Notice that the matches may span word boundaries.

    Example 9. Wildcard Matches
    Query query = QueryBuilder
        .select(
            SelectResult.expression(Meta.id),
            SelectResult.property("country"),
            SelectResult.property("name"))
        .from(DataSource.database(database))
        .where(Expression.property("type").equalTo(Expression.string("landmark"))
        .and(Function.lower(Expression.property("name")).like(Expression.string("eng%e%"))));
    for (Result result : query.execute()) {
        Log.i("Sample", String.format("name -> %s", result.getString("name"))); }

    Wildcard Character Match

    We can use an _ sign within a like expression to do a wildcard match against a single character.

    In Example 10 below, we are looking for documents of type "landmark" where the name property matches any string that begins with "eng" followed by exactly 4 wildcard characters and ending in the letter "r". The query returns "landmark" type documents with names such as "Engineer", "engineer" and so on.

    Example 10. Wildcard Character Matching
    Query query = QueryBuilder
        .select(
            SelectResult.expression(Meta.id),
            SelectResult.property("country"),
            SelectResult.property("name"))
        .from(DataSource.database(database))
        .where(Expression.property("type").equalTo(Expression.string("landmark"))
        .and(Function.lower(Expression.property("name")).like(Expression.string("eng____r"))));
    for (Result result : query.execute()) {
        Log.i("Sample", String.format("name -> %s", result.getString("name"))); }

    Regex Operator

    Similar to the wildcards in like expressions, regex based pattern matching allow you to introduce an element of fuzziness in your search string — see the code shown in Example 11.

    The regex operator is case sensitive, use upper or lower functions to mitigate this if required.
    Example 11. Using Regular Expressions

    This example returns documents with a `type` of "landmark" and a `name` property that matches any string that begins with "eng" and ends in the letter "e".

    Query query = QueryBuilder
        .select(
            SelectResult.expression(Meta.id),
            SelectResult.property("country"),
            SelectResult.property("name"))
        .from(DataSource.database(database))
        .where(Expression.property("type").equalTo(Expression.string("landmark"))
        .and(Function.lower(Expression.property("name")).regex(Expression.string("\\beng.*r\\b"))));            ResultSet rs = query.execute();
    for (Result result : query.execute()) {
        Log.i("Sample", String.format("name -> %s", result.getString("name"))); }
    1 The \b specifies that the match must occur on word boundaries.
    For more on the regex spec used by Couchbase Lite see cplusplus regex reference page

    Deleted Document

    You can query documents that have been deleted (tombstones) [1] as shown in Example 12.

    Example 12. Query to select Deleted Documents

    This example shows how to query deleted documents in the database. It returns is an array of key-value pairs.

    // Query documents that have been deleted
    Where query = QueryBuilder
        .select(SelectResult.expression(Meta.id))
        .from(DataSource.database(database))
        .where(Meta.deleted);

    JOIN statement

    The JOIN clause enables you to select data from multiple documents that have been linked by criteria specified in the JOIN statement. For example to combine airline details with route details, linked by the airline id — see Example 13.

    Example 13. Using JOIN to Combine Document Details

    This example JOINS the document of type route with documents of type airline using the document ID (id) on the _airline document and airlineid on the route document.

    Query query = QueryBuilder.select(
        SelectResult.expression(Expression.property("name").from("airline")),
        SelectResult.expression(Expression.property("callsign").from("airline")),
        SelectResult.expression(Expression.property("destinationairport").from("route")),
        SelectResult.expression(Expression.property("stops").from("route")),
        SelectResult.expression(Expression.property("airline").from("route")))
        .from(DataSource.database(database).as("airline"))
        .join(Join.join(DataSource.database(database).as("route"))
            .on(Meta.id.from("airline").equalTo(Expression.property("airlineid").from("route"))))
        .where(Expression.property("type").from("route").equalTo(Expression.string("route"))
            .and(Expression.property("type").from("airline").equalTo(Expression.string("airline")))
            .and(Expression.property("sourceairport").from("route").equalTo(Expression.string("RIX"))));
    for (Result result : query.execute()) {
             Log.w("Sample", String.format("%s", result.toMap().toString()));
    }

    GROUP BY statement

    You can perform further processing on the data in your result set before the final projection is generated.

    The following example looks for the number of airports at an altitude of 300 ft or higher and groups the results by country and timezone.

    Data Model for Example
    {
        "_id": "airport123",
        "type": "airport",
        "country": "United States",
        "geo": { "alt": 456 },
        "tz": "America/Anchorage"
    }
    Example 14. Query using GroupBy

    This example shows a query that selects all airports with an altitude above 300ft. The output (a count, $1) is grouped by country, within timezone.

    Query query = QueryBuilder.select(
        SelectResult.expression(Function.count(Expression.string(""))),
        SelectResult.property("country"),
        SelectResult.property("tz"))
        .from(DataSource.database(database))
        .where(Expression.property("type").equalTo(Expression.string("airport"))
            .and(Expression.property("geo.alt").greaterThanOrEqualTo(Expression.intValue(300))))
        .groupBy(
            Expression.property("country"),
            Expression.property("tz"))
        .orderBy(Ordering.expression(Function.count(Expression.string(""))).descending());
    for (Result result : query.execute()) {
        Log.i(
            "Sample",
            String.format(
                "There are %d airports on the %s timezone located in %s and above 300ft",
                result.getInt("$1"),
                result.getString("tz"),
                result.getString("country")));
    }

    The query shown in Example 14 generates the following output:

    There are 138 airports on the Europe/Paris timezone located in France and above 300 ft
    There are 29 airports on the Europe/London timezone located in United Kingdom and above 300 ft
    There are 50 airports on the America/Anchorage timezone located in United States and above 300 ft
    There are 279 airports on the America/Chicago timezone located in United States and above 300 ft
    There are 123 airports on the America/Denver timezone located in United States and above 300 ft

    ORDER BY statement

    It is possible to sort the results of a query based on a given expression result — see Example 15

    Example 15. Query using OrderBy

    This example shows a query that returns documents of type equal to "hotel" sorted in ascending order by the value of the title property.

    Query query = QueryBuilder
        .select(
            SelectResult.expression(Meta.id),
            SelectResult.property("name"))
        .from(DataSource.database(database))
        .where(Expression.property("type").equalTo(Expression.string("hotel")))
        .orderBy(Ordering.property("name").ascending())
        .limit(Expression.intValue(10));
    For (Result result : query.execute()) {
        Log.i("Sample", String.format("%s", result.toMap()));
    }

    The query shown in Example 15 generates the following output:

    Aberdyfi
    Achiltibuie
    Altrincham
    Ambleside
    Annan
    Ardèche
    Armagh
    Avignon

    Date/Time Functions

    Couchbase Lite documents support a date type that internally stores dates in ISO 8601 with the GMT/UTC timezone.

    Couchbase Lite’s Query Builder API [1] includes four functions for date comparisons.

    Function.StringToMillis(Expression.Property("date_time"))

    The input to this will be a validly formatted ISO 8601 date_time string. The end result will be an expression (with a numeric content) that can be further input into the query builder.

    Function.StringToUTC(Expression.Property("date_time"))

    The input to this will be a validly formatted ISO 8601 date_time string. The end result will be an expression (with string content) that can be further input into the query builder.

    Function.MillisToString(Expression.Property("date_time"))

    The input for this is a numeric value representing milliseconds since the Unix epoch. The end result will be an expression (with string content representing the date and time as an ISO 8601 string in the device’s timezone) that can be further input into the query builder.

    Function.MillisToUTC(Expression.Property("date_time"))

    The input for this is a numeric value representing milliseconds since the Unix epoch. The end result will be an expression (with string content representing the date and time as a UTC ISO 8601 string) that can be further input into the query builder.

    Result Sets

    Processing

    This section shows how to handle the returned result sets for different types of SELECT statements.

    The result set format and its handling varies slightly depending on the type of SelectResult statements used. The result set formats you may encounter include those generated by :

    To process the results of a query, you first need to execute it using Query.execute.

    The execution of a Couchbase Lite for Java’s database query typically returns an array of results, a result set.

    • The result set of an aggregate, count-only, query is a key-value pair — see Select Count-only — which you can access using the count name as its key.

    • The result set of a query returning document properties is an array.
      Each array row represents the data from a document that matched your search criteria (the WHERE statements) The composition of each row is determined by the combination of SelectResult expressions provided in the SELECT statement. To unpack these result sets you need to iterate this array.

    Select All Properties

    Query

    The Select statement for this type of query, which returns all document properties for each document matching the query criteria, is fairly straightforward — see Example 16

    Example 16. Query selecting All Properties
      try {
        this_Db = new Database("hotels");
      } catch (CouchbaseLiteException e) {
        e.printStackTrace();
      }
    
    Query listQuery = QueryBuilder.select(SelectResult.all())
            .from(DataSource.database(this_Db));

    Result Set Format

    The result set returned by queries using SelectResult.all is an array of dictionary objects — one for each document matching the query criteria.

    For each result object, the key is the database name and the 'value' is a dictionary representing each document property as a key-value pair — see: Example 17.

    Example 17. Format of Result Set (All Properties)
    [
      {
        "travel-sample": { (1)
          "callsign": "MILE-AIR",
          "country": "United States",
          "iata": "Q5",
          "icao": "MLA",
          "id": 10,
          "name": "40-Mile Air",
          "type": "airline"
        }
      },
      {
        "travel-sample": { (2)
          "callsign": "ALASKAN-AIR",
          "country": "United States",
          "iata": "AA",
          "icao": "AAA",
          "id": 10,
          "name": "Alaskan Airways",
          "type": "airline"
        }
      }
    ]
    1 Here we see the result for the first document matching the query criteria.
    2 Here we see the result for the next document matching the query criteria.

    Result Set Access

    In this case access the retrieved document properties by converting each row’s value, in turn, to a dictionary — as shown in Example 18.

    Example 18. Using Document Properties (All)
    try {
        for (Result result : listQuery.execute().allResults()) {
                         // get the k-v pairs from the 'hotel' key's value into a dictionary
            thisDocsProps = result.getDictionary(0)); (1)
            thisDocsId = thisDocsProps.getString("id");
            thisDocsName = thisDocsProps.getString("Name");
            thisDocsType = thisDocsProps.getString("Type");
            thisDocsCity = thisDocsProps.getString("City");
    
            // Alternatively, access results value dictionary directly
            final Hotel hotel = new Hotel();
            hotel.Id = result.getDictionary(0).getString("id"); (2)
            hotel.Type = result.getDictionary(0).getString("Type");
            hotel.Name = result.getDictionary(0).getString("Name");
            hotel.City = result.getDictionary(0).getString("City");
            hotel.Country= result.getDictionary(0).getString("Country");
            hotel.Description = result.getDictionary(0).getString("Description");
            hotels.put(hotel.Id, hotel);
    
        }
    } catch (CouchbaseLiteException e) {
        e.printStackTrace();
    }
    1 Here we get the dictionary of document properties using the database name as the key. You can add this dictionary to an array of returned matches, for processing elsewhere in the app.
    2 Alternatively you can access the document properties here, by using the property names as keys to the dictionary object.

    Select Specific Properties

    Query

    Here we use SelectResult.expression(property("<property-name>"))) to specify the document properties we want our query to return — see: Example 19.

    Example 19. Query selecting Specific Properties
    try {
      this_Db = new Database("hotels");
    } catch (CouchbaseLiteException e) {
      e.printStackTrace();
    }
    
    Query listQuery =
            QueryBuilder.select(SelectResult.expression(Meta.id),
                    SelectResult.property("name"),
                    SelectResult.property("Name"),
                    SelectResult.property("Type"),
                    SelectResult.property("City"))
                    .from(DataSource.database(this_Db));

    Result Set Format

    The result set returned when selecting only specific document properties is an array of dictionary objects — one for each document matching the query criteria.

    Each result object comprises a key-value pair for each selected document property — see Example 20

    Example 20. Format of Result Set (Specific Properties)
    [
      { (1)
        "id": "hotel123",
        "type": "hotel",
        "name": "Hotel Ghia"
      },
      { (2)
        "id": "hotel456",
        "type": "hotel",
        "name": "Hotel Deluxe",
      }
    ]
    1 Here we see the result for the first document matching the query criteria.
    2 Here we see the result for the next document matching the query criteria.

    Result Set Access

    Access the retrieved properties by converting each row into a dictionary — as shown in Example 21.

    Example 21. Using Returned Document Properties (Specific Properties)
    
    try {
        for (Result result : listQuery.execute().allResults()) {
    
            // get data direct from result k-v pairs
            final Hotel hotel = new Hotel();
            hotel.Id = result.getString("id");
            hotel.Type = result.getString("Type");
            hotel.Name = result.getString("Name");
            hotel.City = result.getString("City");
    
            // Store created hotel object in a hashmap of hotels
            hotels.put(hotel.Id, hotel);
    
            // Get result k-v pairs into a 'dictionary' object
            Map <String, Object> thisDocsProps = result.toMap();
            thisDocsId =
                    thisDocsProps.getOrDefault("id",null).toString();
            thisDocsName =
                    thisDocsProps.getOrDefault("Name",null).toString();
            thisDocsType =
                    thisDocsProps.getOrDefault("Type",null).toString();
            thisDocsCity =
                    thisDocsProps.getOrDefault("City",null).toString();
    
        }
    } catch (CouchbaseLiteException e) {
        e.printStackTrace();
    }

    Select Document Id Only

    Query

    You would typically use this type of query if retrieval of document properties directly would consume excessive amounts of memory and-or processing time — see: Example 22.

    Example 22. Query selecting only Doc Id
    try {
      this_Db = new Database("hotels");
    } catch (CouchbaseLiteException e) {
      e.printStackTrace();
    }
    
    Query listQuery =
            QueryBuilder.select(SelectResult.expression(Meta.id).as("metaID"))
                    .from(DataSource.database(this_Db));

    Result Set Format

    The result set returned by queries using a SelectResult expression of the form SelectResult.expression(meta.id) is an array of dictionary objects — one for each document matching the query criteria. Each result object has id as the key and the ID value as its value — -see Example 23.

    Example 23. Format of Result Set (Doc Id only)
    [
      {
        "id": "hotel123"
      },
      {
        "id": "hotel456"
      },
    ]

    Result Set Access

    In this case, access the required document’s properties by unpacking the id and using it to get the document from the database — see: Example 24.

    Example 24. Using Returned Document Properties (Document Id)
    
    try {
        for (Result result : listQuery.execute().allResults()) {
    
            // get the ID form the result's k-v pair array
            thisDocsId = result.getString("metaID"); (1)
    
            // Get document from DB using retrieved ID
            Document thisDoc = this_Db.getDocument(thisDocsId);
    
            // Process document as required
            thisDocsName = thisDoc.getString("Name");
    
        }
    } catch (CouchbaseLiteException e) {
        e.printStackTrace();
    }
    1 Extract the Id value from the dictionary and use it to get the document from the database

    Select Count-only

    Query

    Example 25. Query selecting a Count-only
    Query listQuery = QueryBuilder.select(
            SelectResult.expression(Function.count(Expression.string("*"))).as("mycount")) (1)
            .from(DataSource.database(this_Db));
    1 The alias name, mycount, is used to access the count value.

    Result Set Format

    The result set returned by a count such as Select.expression(Function.count(Expression.all))) is a key-value pair. The key is the count name, as defined using SelectResult.as — see: Example 26 for the format and Example 25 for the query.

    Example 26. Format of Result Set (Count)
    {
      "mycount": 6
    }
    1 Here we see the key-value pair returned by a count.

    Result Set Access

    Access the count using its alias name (mycount in this example) — see Example 27

    Example 27. Using Returned Document Properties (Count)
    try {
        for (Result result : listQuery.execute()) {
    
            // Retrieve count using key 'mycount'
            Integer altDocId = result.getInt("mycount");
    
            // Alternatively, use the index
            Integer orDocId = result.getInt(0);
        }
        // Or even miss out the for-loop altogether
        Integer resultCount = listQuery.execute().next().getInt("mycount");
    
    } catch (CouchbaseLiteException e) {
        e.printStackTrace();
    }
    1 Get the count using the SelectResult.as alias, which is used as its key.

    Handling Pagination

    One way to handle pagination in high-volume queries is to retrieve the results in batches. Use the limit and offset feature, to return a defined number of results starting from a given offset — see: Example 28.

    Example 28. Query Pagination
    try {
      this_Db = new Database("hotels");
    } catch (CouchbaseLiteException e) {
      e.printStackTrace();
    }
    
    int thisOffset = 0;
    int thisLimit = 20;
    
    Query listQuery =
    QueryBuilder
    .select(SelectResult.all())
    .from(DataSource.database(this_Db))
    .limit(Expression.intValue(thisLimit),
    Expression.intValue(thisOffset)); (1)
    1 Return a maximum of limit results starting from result number offset
    For more on using the QueryBuilder API, see our blog: Introducing the Query Interface in Couchbase Mobile

    JSON Result Sets

    Couchbase Lite for Java provides a convenience API to convert query results to JSON strings.

    Example 29. Using JSON Results

    Use Result.toJSON() to transform your result string into a JSON string, which can easily be serialized or used as required in your application. See <> for a working example.

    // Uses Jackson JSON processor
    
    ArrayList<Hotel> hotels = new ArrayList<Hotel>();
    HashMap<String, Object> dictFromJSONstring;
    for (Result result : listQuery.execute()) {
    
      // Get result as JSON string
      String thisJsonString = result.toJSON(); (1)
    
            // Get Java  Hashmap from JSON string
      HashMap<String, Object> dictFromJSONstring =
              mapper.readValue(thisJsonString, HashMap.class); (2)
    
    
      // Use created hashmap
      String hotelId = dictFromJSONstring.get("id").toString();
      String hotelType = dictFromJSONstring.get("type").toString();
      String hotelname = dictFromJSONstring.get("name").toString();
    
    
      // Get custom object from Native 'dictionary' object
      Hotel thisHotel =
              mapper.readValue(thisJsonString, Hotel.class); (3)
      hotels.add(thisHotel);
    
    }
    1 Get the Query result as a JSON string — see JSON String Format
    2 Get a native object from the JSON string
    3 Populate your custom object from the dictionary created from JSON data
    JSON String Format

    If your query selects ALL then the JSON format will be:

    {
      database-name: {
        key1: "value1",
        keyx: "valuex"
      }
    }

    If your query selects a sub-set of available properties then the JSON format will be:

    {
      key1: "value1",
      keyx: "valuex"
    }

    Predictive Query

    Enterprise Edition only
    Predictive Query is an Enterprise Edition feature.

    Predictive Query enables Couchbase Lite queries to use machine learning, by providing query functions that can process document data (properties or blobs) via trained ML models.

    Let’s consider an image classifier model that takes a picture as input and outputs a label and probability.

    predictive diagram

    To run a predictive query with a model as the one shown above, you must implement the following steps.

    Integrate the Model

    To integrate a model with Couchbase Lite, you must implement the PredictiveModel interface which has only one function called predict() — see: Example 30.

    Example 30. Integrating a predictive model
    // tensorFlowModel is a fake implementation
    // this would be the implementation of the ml model you have chosen
    class ImageClassifierModel implements PredictiveModel {
        @Override
        public Dictionary predict(@NonNull Dictionary input) {
            Blob blob = input.getBlob("photo");
            if (blob == null) { return null; }
    
            // tensorFlowModel is a fake implementation
            // this would be the implementation of the ml model you have chosen
            return new MutableDictionary(TensorFlowModel.predictImage(blob.getContent())); (1)
        }
    }
    
    class TensorFlowModel {
        public static Map<String, Object> predictImage(byte[] data) {
            return null;
        }
    }
    1 The predict(input) -> output method provides the input and expects the result of using the machine learning model. The input and output of the predictive model is a DictionaryObject. Therefore, the supported data type will be constrained by the data type that the DictionaryObject supports.

    Register the Model

    To register the model you must create a new instance and pass it to the Database.prediction.registerModel static method.

    Example 31. Registering a predictive model
    Database.prediction.registerModel("ImageClassifier", new ImageClassifierModel());

    Create an Index

    Creating an index for a predictive query is highly recommended. By computing the predictions during writes and building a prediction index, you can significantly improve the speed of prediction queries (which would otherwise have to be computed during reads).

    There are two types of indexes for predictive queries:

    Value Index

    The code below creates a value index from the "label" value of the prediction result. When documents are added or updated, the index will call the prediction function to update the city value in the index.

    Example 32. Creating a value index
    ValueIndex index = IndexBuilder.valueIndex(ValueIndexItem.expression(Expression.property("label")));
    database.createIndex("value-index-image-classifier", index);

    Predictive Index

    Predictive Index is a new index type used for predictive query. It differs from the value index in that it caches the predictive results and creates a value index from that cache when the predictive results values are specified.

    Example 33. Creating a predictive index

    Here we create a predictive index from the label value of the prediction result.

    Map<String, Object> inputMap = new HashMap<>();
    inputMap.put("numbers", Expression.property("photo"));
    Expression input = Expression.map(inputMap);
    
    PredictiveIndex index = IndexBuilder.predictiveIndex("ImageClassifier", input, null);
    database.createIndex("predictive-index-image-classifier", index);

    Run a Prediction Query

    The code below creates a query that calls the prediction function to return the "label" value for the first 10 results in the database.

    Example 34. Creating a value index
    Map<String, Object> inputProperties = new HashMap<>();
    inputProperties.put("photo", Expression.property("photo"));
    Expression input = Expression.map(inputProperties);
    PredictionFunction prediction = PredictiveModel.predict("ImageClassifier", input); (1)
    
    Query query = QueryBuilder
        .select(SelectResult.all())
        .from(DataSource.database(database))
        .where(Expression.property("label").equalTo(Expression.string("car"))
            .and(Expression.property("probability").greaterThanOrEqualTo(Expression.doubleValue(0.8))));
    
    // Run the query.
    ResultSet result = query.execute();
    Log.d(TAG, "Number of rows: " + result.allResults().size());
    1 The PredictiveModel.predict() method returns a constructed Prediction Function object which can be used further to specify a property value extracted from the output dictionary of the PredictiveModel.predict() function.
    The null value returned by the prediction method will be interpreted as MISSING value in queries.

    Deregister the Model

    To deregister the model you must call the Database.prediction.unregisterModel static method.

    Example 35. Deregister a value index
    Database.prediction.unregisterModel("ImageClassifier");

    1. Starting in Couchbase Lite 2.5