Array Indexing

    +

    Array Indexing adds the capability to create global indexes on array elements and optimizes the execution of queries involving array elements.

    This is a huge leap from the previous versions where secondary indexes could only be created and subsequently queried on whole arrays. You can now create an index of array elements ranging from plain scalar values to complex arrays or JSON objects nested deeper in the array.

    Syntax

    To create an array index, the overall syntax is the same as for a global secondary index. The distinguishing feature is the use of an array expression as an index key.

    Refer to the CREATE INDEX statement for details of the syntax.

    Index Key

    index-key ::= expr | array-expr
    Syntax diagram: refer to source code listing

    To create an array index, one index key must be an array expression. The index key containing the array expression is referred to as the array index key. The index definition may also contain other index keys which are not array expressions.

    expr

    A N1QL expression over any fields in the document. This cannot use constant expressions, aggregate functions, or sub-queries.

    array-expr

    An array expression. Refer to Array Expression below.

    Array Index Key

    Currently, the index definition for an array index may only contain one array index key. However, the array index key may index more than one field or expression within the array, as described below.

    For an UNNEST scan to use an array index, the array index key containing the appropriate array expression must be the leading key of the index definition. The UNNEST scan can generate index spans on other non-leading index keys when appropriate predicates exist.

    In order for the optimizer to select the correct array index for a SELECT, UPDATE, or DELETE statement, the query predicate which appears in the WHERE clause must be constructed to match the format of the array index key. See Format of Query Predicate for details.

    Array Expression

    array-expr ::= full-array-expr | simple-array-expr
    Syntax diagram: refer to source code listing

    The array expression can be either a full array expression, which uses the ARRAY operator to index specified fields and elements within the array; or a simple array expression, which indexes all fields and elements in the array.

    Full Array Expression

    full-array-expr ::= ( 'ALL' | 'DISTINCT' ) 'ARRAY' var-expr
                        'FOR' var ( 'IN' | 'WITHIN' ) expr
                        ( ',' var ( 'IN' | 'WITHIN' ) expr )* ( 'WHEN' cond )? 'END'
    Syntax diagram: refer to source code listing

    The ARRAY operator lets you map and filter the elements or attributes of a collection, object, or objects. It evaluates to an array of the operand expression that satisfies the WHEN clause, if specified.

    var-expr

    A function of the var variable used in the FOR clause.

    var

    Represents elements in the array specified by expr.

    expr

    Evaluates to an array of objects, elements of which are represented by the var variable.

    cond

    Specifies predicates to qualify the subset of documents to include in the index array.

    Variable Expression

    In Couchbase Server 7.1 and later, you can index one or more expressions within the array (up to maximum of 32) by using the FLATTEN_KEYS() function in the var-expr. This function flattens expressions within the array, as if they were separate index keys; and all subsequent index keys are accordingly moved to the right. Queries will be sargable and will generate spans. Refer to Format of Query Predicate below.

    The var-expr itself may be a nested array expression. This enables creating array indexes on nested array fields. Refer to Example 5 below.

    To create an array index involving multiple array elements or multiple arrays, you may construct the var-expr as a compound object constituted with different elements of the same array or multiple arrays. Refer to Example 6 below.

    Simple Array Expression

    simple-array-expr ::= ( 'ALL' | 'DISTINCT' ) expr
    Syntax diagram: refer to source code listing

    Couchbase Server 5.0 and later provides a simpler syntax for array indexing when all array elements are indexed as is, without needing to use the ARRAY operator in the index definition.

    expr

    An array field name, or an expression that can evaluate to an array. In this case, all fields and elements of the array are indexed.

    Format of Query Predicate

    In order for the optimizer to select the correct array index for a SELECT, UPDATE, or DELETE statement, the query predicate which appears in the WHERE clause must be constructed to match the format of the array index key.

    Consider the following expressions used in a CREATE INDEX statement:

    C1
    DISTINCT ARRAY f(x) FOR x IN expr1 END;
    C2
    DISTINCT ARRAY f(x) FOR x WITHIN expr1 END;

    And the following expressions used in the SELECT statement WHERE clause:

    Q1
    ANY x IN expr2 SATISFIES g(x) END;
    Q2
    ANY x WITHIN expr2 SATISFIES g(x) END;

    The following dependencies must be satisfied for the Query service to consider the array index:

    • The index keys used in CREATE INDEX must be used in the WHERE clause. (The query can use different variable names from those used in the array index definition.)

    • The expr2 in Q1 and Q2 must be equivalent to the expr1 in C1 and C2. This is a formal notion of equivalence. For example, they must be the same expressions, or equivalent arithmetic expressions such as (x+y) and (y+x).

    • Usually, g(x) in Q1 and Q2 must be sargable for f(x) in C1 and C2. In other words, if there were a scalar index with key f(x), then that index would be applicable to the predicate g(x). For example, the predicate UPPER(x) LIKE "John%" is sargable for the index key UPPER(x).

    Flatten Keys

    Now consider the following variants of C1 and C2, in which the index key f(x) uses the FLATTEN_KEYS() function to flatten expressions within the array:

    C3
    DISTINCT ARRAY
      FLATTEN_KEYS(f1(x) ASC, f2(x) DESC)
      FOR x IN expr1 END;
    C4
    DISTINCT ARRAY
      FLATTEN_KEYS(f1(x) ASC, f2(x) DESC)
      FOR x WITHIN expr1 END;
    • The index keys C3 and C4 flatten expressions within the array, as if they were separate index keys; and all subsequent index keys are accordingly moved to the right. Queries will be sargable and will generate spans.

    • In order to select an array index defined using C3 or C4, the predicate g(x) in Q1 and Q2 must be sargable for one of the arguments of the FLATTEN_KEYS() function — f1(x) or f2(x).

    IN vs. WITHIN
    • Index key C1 can be used for query predicate Q1. Index key C2 can be used for both query predicates Q1 and Q2.

    • Index key C2 is strictly more expensive than index key C1, for both index maintenance and query processing. Index key C2 and query predicate Q2 are very powerful. They can efficiently index and query recursive trees of arbitrary depth.

    Examples

    The following examples use the travel-sample bucket that is shipped with Couchbase Server.

    Example 1. Array index of distinct elements
    Index: Create an index on all schedules
    CREATE INDEX idx_sched
    ON `travel-sample`.inventory.route
    ( DISTINCT ARRAY v.flight FOR v IN schedule END );
    Query: Find the list of scheduled 'UA' flights
    SELECT * FROM `travel-sample`.inventory.route
    WHERE ANY v IN schedule SATISFIES v.flight LIKE 'UA%' END;
    Example 2. Partial array index

    Create a partial index (with WHERE clause) of individual attributes from selected elements (using WHEN clause) of an array.

    Index: Create an index on flights from San Francisco scheduled in the first 4 days of the week
    CREATE INDEX idx_flight_sfo
    ON `travel-sample`.inventory.route
    ( ALL ARRAY v.flight FOR v IN schedule WHEN v.day < 4 END )
    WHERE sourceairport = "SFO";
    Query: Find the list of scheduled 'UA' flights on day 1
    SELECT * FROM `travel-sample`.inventory.route
    WHERE sourceairport = "SFO" (1)
    AND ANY v IN schedule SATISFIES (v.flight LIKE 'UA%') (2)
    AND (v.day=1) END; (3)

    In this example, the Index qualifies for the Query because:

    1 The Query predicate sourceairport = "SFO" matches that of the partial index WHERE clause.
    2 The ANY operator uses the index key v.flight on which the Index is defined.
    3 The ANY-SATISFIES condition v.day=1 in the Query is sargable to that in the index definition WHEN clause v.day < 4.
    Example 3. Flattened array index
    Index: Create an index on day and flight from schedule array
    CREATE INDEX ixf_sched
      ON `travel-sample`.inventory.route
      (ALL ARRAY FLATTEN_KEYS(s.day DESC, s.flight) FOR s IN schedule END,
      sourceairport, destinationairport, stops);
    Query A: Find the weekday Delta flights FROM SFO to ATL
    SELECT META(r).id
      FROM `travel-sample`.inventory.route AS r
      WHERE r.sourceairport = "SFO" (1)
        AND r.destinationairport = "ATL" (2)
        AND ANY s IN r.schedule SATISFIES s.day BETWEEN 1 AND 5 (3)
        AND s.flight LIKE "DL%" END; (4)

    In this example, Query A is able to use the ixf_sched index defined by the Index, pass all the predicate information to index scan, and cover the query.

    Partial Explain Plan
    "spans": [
                 {
                     "exact": true,
                     "range": [
                         {
                             "high": "5",
                             "inclusion": 3,
                             "index_key": "(`s`.`day`)", (3)
                             "low": "1"
                         },
                         {
                             "high": "\"DM\"",
                             "inclusion": 1,
                             "index_key": "(`s`.`flight`)", (4)
                             "low": "\"DL\""
                         },
                         {
                             "high": "\"SFO\"",
                             "inclusion": 3,
                             "index_key": "`sourceairport`", (1)
                             "low": "\"SFO\""
                         },
                         {
                             "high": "\"ATL\"",
                             "inclusion": 3,
                             "index_key": "`destinationairport`", (2)
                             "low": "\"ATL\""
                         }
    
                     ]
                 }
             ]
    1 r.sourceairport = "SFO" is able to match and pass to IndexScan.
    2 r.destinationairport = "ATL" is able to match and pass to IndexScan.
    3 ARRAY predicate s.day BETWEEN 1 AND 5 is able to match and pass to IndexScan.
    4 ARRAY predicate s.flight LIKE "DL%" is able to match and pass to IndexScan.
    Query B: Find the weekday Delta flights from SFO to ATL
    SELECT  s.day, s.flight,r.sourceairport, r.destinationairport, r.stops
    FROM `travel-sample`.inventory.route AS r
    UNNEST r.schedule AS s
    WHERE r.sourceairport = "SFO" AND r.destinationairport = "ATL"
          AND s.day BETWEEN 1 AND 5 AND s.flight LIKE "DL%"
    ORDER BY s.day DESC
    OFFSET 2
    LIMIT 3;

    This query performs a covering UNNEST IndexScan, by applying all the predicates, using the ixf_sched index defined by the Index. Even though the ORDER BY key uses an array index key, it can use index order, and pass LIMIT and OFFSET to the indexer.

    Example 4. Composite array index
    Index: Create an index on individual elements of an array and other non-array fields
    CREATE INDEX idx_flight_stops
    ON `travel-sample`.inventory.route
        ( stops, DISTINCT ARRAY v.flight FOR v IN schedule END );
    Query: Find the list of scheduled 'FL' flights that have one or more stops
    SELECT * FROM `travel-sample`.inventory.route
    WHERE stops >=1
    AND ANY v IN schedule SATISFIES v.flight LIKE 'FL%' END;
    Example 5. Nested array index
    Please note that the example below will alter the data in your sample buckets. To restore your sample data, remove and reinstall the travel-sample bucket. Refer to Sample Buckets for details.
    Update: Create a nested array
    UPDATE `travel-sample`.inventory.route
    SET schedule[0] = {"day" : 7, "special_flights" :
                   [ {"flight" : "AI444", "utc" : "4:44:44"},
                     {"flight" : "AI333", "utc" : "3:33:33"}
                   ] }
    WHERE destinationairport = "CDG" AND sourceairport = "TLV";

    Use the DISTINCT ARRAY clause in a nested fashion to index specific attributes of a document when the array contains other arrays or documents that contain arrays.

    Index I: Create a partial index on a nested array
    CREATE INDEX idx_nested ON `travel-sample`.inventory.route
        (DISTINCT ARRAY
            (DISTINCT ARRAY y.flight (1)
            FOR y IN x.special_flights END)
        FOR x IN schedule END);
    1 In this case, the inner ARRAY construct is used as the var_expr for the outer ARRAY construct in the N1QL Syntax above.
    Query A: Use nested ANY operator to use the index
    SELECT count(*) FROM `travel-sample`.inventory.route
    WHERE ANY x in schedule SATISFIES
        (ANY y in x.special_flights SATISFIES y.flight IS NOT NULL END)
    END;

    This query uses the index idx_nested defined by Index I. It returns 3 results, as there are 3 routes with special flights.

    Query B: Use UNNEST operators to use the index
    SELECT count(*) FROM `travel-sample`.inventory.route
    UNNEST schedule AS x
    UNNEST x.special_flights AS y
    WHERE y.flight IS NOT NULL;

    This query uses the index idx_nested defined by Index I. It returns 6 results, as there are 3 routes with 2 special flights each.

    Index II: Create a flattened index on a nested array
    CREATE INDEX ixf_sched_nested ON `travel-sample`.inventory.route
        (ALL ARRAY
            (ALL ARRAY FLATTEN_KEYS(s.day, sf.flight)
             FOR sf IN s.special_flights END)
        FOR s IN schedule END);
    Query C: Use nested ANY operator to use the index
    SELECT RAW count(1)
    FROM `travel-sample`.inventory.route AS r
    WHERE ANY s IN schedule
          SATISFIES (ANY sf IN s.special_flights
                     SATISFIES sf.flight IS NOT NULL AND s.day = 7
                     END)
          END;

    This query performs a covering UNNEST IndexScan, by applying the predicates on both levels of the ARRAY, using the index ixf_sched_nested defined by Index II.

    Query D: Use UNNEST operators to use the index
    SELECT RAW count(1)
    FROM `travel-sample`.inventory.route AS r
    UNNEST r.schedule AS s
    UNNEST s.special_flights AS sf
    WHERE sf.flight IS NOT NULL AND s.day = 7;

    This query performs a covering UNNEST IndexScan, by applying the predicates on both levels of the ARRAY, using the index ixf_sched_nested defined by Index II; and uses index aggregation.

    Example 6. Array index on compound object
    Index: Create an index on multiple elements of an array
    CREATE INDEX idx_flight_day ON `travel-sample`.inventory.route
        (DISTINCT ARRAY [v.flight, v.day] FOR v IN schedule END);
    Query: Find the list of scheduled 'US681' flights on day 2
    SELECT meta().id FROM `travel-sample`.inventory.route
    WHERE ANY v in schedule SATISFIES [v.flight, v.day] = ["US681", 2] END;
    Example 7. Simplified array index
    Index: Create an index on all schedules using simplified array index syntax
    CREATE INDEX idx_sched_simple
    ON `travel-sample`.inventory.route (ALL schedule);

    The following queries find details of all route documents matching a specific schedule.

    Query A: Use ANY operator to use the index
    SELECT * FROM `travel-sample`.inventory.route
    WHERE ANY v IN schedule
    SATISFIES v = {"day":2, "flight": "US681", "utc": "19:20:00"} END; (1)
    1 Elements of the schedule array are objects, and hence the right side value of the predicate condition should be a similarly structured object.
    Query B: Use UNNEST operator to use the index
    SELECT * FROM `travel-sample`.inventory.route t
    UNNEST schedule sch
    WHERE sch = {"day":2, "flight": "US681", "utc": "19:20:00"};

    This is a variant of Query A using UNNEST in the SELECT statement.

    Query C: Alternative using a flattened array index
    SELECT META(r).id
    FROM `travel-sample`.inventory.route AS r
    WHERE ANY v IN r.schedule SATISFIES v.day = 2 AND v.flight = "US681" END;

    For comparison, this query performs a covering index scan, by applying all the predicates, using ixf_sched defined by the Index in Example 3. The query syntax is more intuitive than Query A and Query B, since the multiple fields within the array have not required complex indexing.

    Covering Array Index

    Covering indexes are an efficient method of using an Index for a particular query, whereby the index itself can completely cover the query in terms of providing all data required for the query. Basically, it avoids the fetch phase of the query processing and related overhead in fetching the required documents from data-service nodes. For more details, see Covering Indexes.

    Array indexing requires special attention to create covering array indexes. In general, the array field itself should be included as one of the index keys in the CREATE INDEX definition. For instance, in Example 1, the Index does not cover the Query because the Query projection list includes * which needs to fetch the document from the Data Service.

    Example 8. Covering Array Index
    Index I: Creating a Covering Array Index
    CREATE INDEX idx_sched_cover ON `travel-sample`.inventory.route
        (DISTINCT ARRAY v.flight FOR v IN schedule END, schedule);

    The index keys of an index must be used in the WHERE clause of a DML statement to use the index for that query. In the SELECT or DML WHERE clause, Covering Array Indexes can be used by the following operators:

    Query A: Covering Array Index using the ANY clause
    EXPLAIN SELECT meta().id FROM `travel-sample`.inventory.route
    USE INDEX (idx_sched_cover) (1)
    WHERE ANY v IN schedule SATISFIES v.flight LIKE 'UA%' END;
    1 In this example, Query A needs Index I to cover it because the query predicate refers to the array schedule in the ANY operator.
    Result
    [
      {
        "plan": {
          "#operator": "Sequence",
          "~children": [
            {
              "#operator": "DistinctScan",
              "scan": {
                "#operator": "IndexScan3",
                "bucket": "travel-sample",
                "covers": [
                  "cover ((distinct (array (`v`.`flight`) for `v` in (`route`.`schedule`) end)))",
                  "cover ((`route`.`schedule`))",
                  "cover ((meta(`route`).`id`))"
                ],
                "filter": "cover (any `v` in (`route`.`schedule`) satisfies ((`v`.`flight`) like \"UA%\") end)",
                "filter_covers": {
                  "cover (any `v` in (`route`.`schedule`) satisfies ((\"UA\" <= (`v`.`flight`)) and ((`v`.`flight`) < \"UB\")) end)": true,
                  "cover (any `v` in (`route`.`schedule`) satisfies ((`v`.`flight`) like \"UA%\") end)": true
                },
                "index": "idx_sched_cover",
              // ...
              }
            }
          ]
        }
      }
    ]
    Query B: Covering Array Index using the ANY AND EVERY clause
    EXPLAIN SELECT meta().id FROM `travel-sample`.inventory.route
    USE INDEX (idx_sched_cover)
    WHERE ANY AND EVERY v IN schedule SATISFIES v.flight LIKE 'UA%' END;
    Result
    [
      {
        "plan": {
          "#operator": "Sequence",
          "~children": [
            {
              "#operator": "DistinctScan",
              "scan": {
                "#operator": "IndexScan3",
                "bucket": "travel-sample",
                "covers": [
                  "cover ((distinct (array (`v`.`flight`) for `v` in (`route`.`schedule`) end)))",
                  "cover ((`route`.`schedule`))",
                  "cover ((meta(`route`).`id`))"
                ],
                "filter": "any and every `v` in cover ((`route`.`schedule`)) satisfies ((`v`.`flight`) like \"UA%\") end",
                "index": "idx_sched_cover",
              // ...
              }
            }
          ]
        }
      }
    ]
    Query C: Covering Array Index using the UNNEST clause and aliasing
    EXPLAIN SELECT meta(t).id FROM `travel-sample`.inventory.route t
    USE INDEX (idx_sched_cover)
    UNNEST schedule v
    WHERE v.flight LIKE 'UA%';
    Result
    [
      {
        "plan": {
          "#operator": "Sequence",
          "~children": [
            {
              "#operator": "DistinctScan",
              "scan": {
                "#operator": "IndexScan3",
                "as": "t",
                "bucket": "travel-sample",
                "covers": [
                  "cover ((distinct (array (`v`.`flight`) for `v` in (`t`.`schedule`) end)))",
                  "cover ((`t`.`schedule`))",
                  "cover ((meta(`t`).`id`))"
                ],
                "filter": "is_array(cover ((`t`.`schedule`)))",
                "index": "idx_sched_cover",
              // ...
              }
            }
          ]
        }
      }
    ]

    In this example, Query A has the following limitation: the collection operator EVERY cannot use array indexes or covering array indexes because the EVERY operator needs to apply the SATISFIES predicate to all elements in the array, including the case where an array has zero elements.

    As items cannot be indexed, it is not possible to index MISSING items, so the EVERY operator is evaluated in the N1QL engine and cannot leverage the array index scan.

    For example, Query D below uses the primary index def_inventory_route_primary ignoring the USE INDEX hint to use the array indexes. (Note that in this example, Index I defines a DISTINCT array index while Index II defines an ALL array index, and both are ignored).

    Index II: Non-array index with an ALL array index
    CREATE INDEX idx_sched_cover_all ON `travel-sample`.inventory.route
        (ALL ARRAY v.flight FOR v IN schedule END, schedule);
    Query D: Non-array index with an ALL array index
    EXPLAIN SELECT meta().id FROM `travel-sample`.inventory.route
    USE INDEX (idx_sched_cover_all, idx_sched_cover)
    WHERE EVERY v IN schedule SATISFIES v.flight LIKE 'UA%' END;
    Result
    [
      {
        "plan": {
          "#operator": "Sequence",
          "~children": [
            {
              "#operator": "PrimaryScan3",
              "bucket": "travel-sample",
              "index": "def_inventory_route_primary",
            // ...
            }
          ]
        }
      }
    ]

    Implicit Covering Array Index

    N1QL supports simplified Implicit Covering Array Index syntax in certain cases where the mandatory array index-key requirement is relaxed to create a covering array-index. This special optimization applies to those queries and DML which have WHERE clause predicates that can be exactly and completely pushed to the indexer during the array index scan. For example:

    Example 9. ANY operator with an =, <, >, and LIKE predicate in the SATISFIES clause

    Note that the GSI indexes are tree structures that support exact match and range matches. And the ANY predicate returns true as long as it finds at least one matching item in the index. Hence, an item found in the index can cover the query. Furthermore, this is covered by both ALL and DISTINCT array indexes.

    Index: Creating an Implicit Covering Array Index with DISTINCT
    CREATE INDEX idx_sched_cover_simple ON `travel-sample`.inventory.route
        (DISTINCT ARRAY v.flight FOR v IN schedule END);
    Query: Implicit Covering Array Index using the ANY clause
    EXPLAIN SELECT meta().id FROM `travel-sample`.inventory.route
    USE INDEX (idx_sched_cover_simple)
    WHERE ANY v IN schedule SATISFIES v.flight LIKE 'UA%' END;
    Result
    [
      {
        "plan": {
          "#operator": "Sequence",
          "~children": [
            {
              "#operator": "DistinctScan",
              "scan": {
                "#operator": "IndexScan3",
                "bucket": "travel-sample",
                "covers": [
                  "cover ((distinct (array (`v`.`flight`) for `v` in (`route`.`schedule`) end)))",
                  "cover ((meta(`route`).`id`))"
                ],
                "filter": "cover (any `v` in (`route`.`schedule`) satisfies ((`v`.`flight`) like \"UA%\") end)",
                "filter_covers": {
                  "cover (any `v` in (`route`.`schedule`) satisfies ((\"UA\" <= (`v`.`flight`)) and ((`v`.`flight`) < \"UB\")) end)": true,
                  "cover (any `v` in (`route`.`schedule`) satisfies ((`v`.`flight`) like \"UA%\") end)": true
                },
                "index": "idx_sched_cover_simple",
              // ...
              }
            }
          ]
        }
      }
    ]
    Example 10. UNNEST operator with =, <, >, or LIKE predicate in the WHERE clause

    This applies to only ALL array indexes because, for such index, all array elements are indexed in the array index, and the UNNEST operation needs all the elements to reconstruct the array. Note that the array cannot be reconstructed if on DISTINCT elements of the array are indexed.

    In this example, Query A can be covered with the ALL index idx_sched_cover_simple_all defined by the Index, but Query B is not covered when using the DISTINCT index idx_sched_cover_simple defined by the Index in Example 9.

    Index: UNNEST covered with the ALL index
    CREATE INDEX idx_sched_cover_simple_all ON `travel-sample`.inventory.route
        (ALL ARRAY v.flight FOR v IN schedule END);
    Query A: UNNEST covered with the ALL index
    EXPLAIN SELECT meta(t).id FROM `travel-sample`.inventory.route t
    USE INDEX (idx_sched_cover_simple_all)
    UNNEST schedule v
    WHERE v.flight LIKE 'UA%';
    Result
    [
      {
        "plan": {
          "#operator": "Sequence",
          "~children": [
            {
              "#operator": "IndexScan3",
              "as": "t",
              "bucket": "travel-sample",
              "covers": [
                "cover ((`v`.`flight`))",
                "cover ((meta(`t`).`id`))"
              ],
              "filter": "cover (is_array((`t`.`schedule`)))",
              "filter_covers": {
                "cover (((`t`.`schedule`) < {}))": true,
                "cover (([] <= (`t`.`schedule`)))": true,
                "cover (is_array((`t`.`schedule`)))": true
              },
              "index": "idx_sched_cover_simple_all",
              "index_id": "de0704c3fdb45b07",
              "keyspace": "route",
              "namespace": "default",
              "scope": "inventory",
              "spans": [
                {
                  "exact": true,
                  "range": [
                    {
                      "high": "\"UB\"",
                      "inclusion": 1,
                      "low": "\"UA\""
                    }
                  ]
                }
              ],
              "using": "gsi"
            },
          // ...
          ]
        }
      }
    ]
    Query B: UNNEST not covered when using the DISTINCT index
    EXPLAIN SELECT meta(t).id FROM `travel-sample`.inventory.route t
    USE INDEX (idx_sched_cover_simple)
    UNNEST schedule v
    WHERE v.flight LIKE 'UA%';
    Result
    [
      {
        "plan": {
          "#operator": "Sequence",
          "~children": [
            {
              "#operator": "DistinctScan",
              "scan": {
                "#operator": "IndexScan3",
                "as": "t",
                "bucket": "travel-sample",
                "index": "idx_sched_cover_simple",
                "index_id": "198a2bc8b0a3ea55",
                "index_projection": {
                  "primary_key": true
                },
                "keyspace": "route",
                "namespace": "default",
                "scope": "inventory",
                "spans": [
                  {
                    "exact": true,
                    "range": [
                      {
                        "high": "\"UB\"",
                        "inclusion": 1,
                        "low": "\"UA\""
                      }
                    ]
                  }
                ],
                "using": "gsi"
              }
            // ...
            }
          ]
        }
      }
    ]

    Summary

    The following table summarizes N1QL-supported collection operators in the DML WHERE clause for different kinds of array index features:

    Table 1. N1QL-supported collection operators
    Operator in the SELECT/DML WHERE clause Array Index Covering Array Index (with explicit array index-key) Implicit Covering Array Index (without explicit array index-key)

    ANY

    ✓ (both ALL & DISTINCT)

    ✓ (both ALL & DISTINCT)

    ✓ (both ALL & DISTINCT)

    UNNEST

    ✓ (only ALL, with array as leading index-key)

    ✓ (only ALL, with array as leading index-key)

    ✓ (only ALL, with array as leading index-key)

    ANY AND EVERY

    ✓ (both ALL & DISTINCT)

    ✓ (both ALL & DISTINCT)

    EVERY

    In Couchbase Server 6.5 and later, you can use any arbitrary alias for the right side of an UNNEST — the alias does not have to be the same as the ARRAY index variable name in order to use that index.