Please use the form below to provide your feedback. Because your feedback is valuable to us, the information you submit in this form is recorded in our issue tracking system (JIRA), which is publicly available. You can track the status of your feedback using the ticket number displayed in the dialog once you submit the form.

Data Types

  • Capella Columnar
  • reference
    +
    This topic describes the data types that Capella Columnar operates on.

    An instance of the data model can be one of the following:

    • Primitive type: BOOLEAN, STRING, BIGINT, or DOUBLE

    • Special type: NULL or MISSING

    • Composite type: OBJECT, array, or MULTISET

    The type names are case-insensitive. That is, you can use BIGINT or bigint.

    Primitive Types

    Boolean

    The Boolean data type has only two values: true and false.

    Examples
    true
false

    An expression that compares two values, such as weight > limit, might return a Boolean value or it might return one of the special values null or missing. For details, see Comparison Operators.

    String

    A string represents a sequence of characters. The total length of the sequence can be up to 2,147,483,648.

    Syntactically, a literal string is enclosed in single or double quotes.

    Examples
    "This is a string."
'Have you read "War and Peace"?'
"I don't think so."

    For more information about string literals, see Literals.

    Bigint

    A bigint is a 64-bit integer. The range of bigint is from -9223372036854775808 to 9223372036854775807.

    Examples
    45
-27900

    In general, arithmetic operations on two bigint values return a bigint result. However, SQL++ for Capella columnar provides two division operators:

    • 5 / 2 returns 2.5, a value of type double.

    • 5 div 2 returns 2, a value of type bigint, by truncating the result.

    See Arithmetic Operators.

    Double (double precision)

    The double type represents approximate numeric data values using 8 bytes. The range of a double value is from (2^(-1022)) to (2-2(-52))·2(1023) for both positive and negative numbers. Expressions that compute values outside these ranges return INF or -INF. SQL++ for Capella columnar also supports the special value NaN (not a number).

    If a numeric literal contains a decimal point or an exponent, SQL++ for Capella columnar treats it as a double.

    Examples
    45.
-2.79E4
2.79E-4

    Capella Columnar parses all numbers that are not integers in incoming JSON documents as double values.

    Temporal Data and Primitive Types

    Applications often make use of temporal data (dates, times, and timestamps). Since JSON does not provide data types for temporal data, SQL++ for Capella columnar uses the string and bigint types for this purpose. SQL++ provides a number of builtin functions, called temporal functions, that operate on string or bigint values, interpreting them as dates or times. For a list of these functions, see Temporal Functions.

    Using bigint for Temporal Data

    Some of the temporal functions take bigint values and interpret them as representing a number of milliseconds since the beginning of the Unix Epoch at 00:00:00 UTC on January 1, 1970. Two of these temporal functions, and some examples of their use, follow.

    • now_millis( ) returns the current point in time as a bigint representing Unix Epoch milliseconds.

    • date_diff_millis(t1, t2, unit) returns the difference between two points in time--t1 and t2--in terms of the designated units: years, months, weeks, days, hours, seconds, or milliseconds.

    Examples
    now_millis( ) returns 1655230396621 at the start of an experiment.
    now_millis( ) returns 1655231924715 at the end of the experiment.
    date_diff_millis(1655231924715, 1655230396621, "minute") returns 25,
    showing that the experiment lasted for 25 minutes.
    date_diff_millis(1655231924715, 1655230396621, "second") returns 1528,
    providing a finer measurement: the experiment lasted for 1528 seconds.

    Using string for Temporal Data

    A string in ISO 8601 format can represent a date, time, or timestamp. The following example shows 30.55 seconds after 15:10—​3:10pm—​on June 14, 2022 in a timezone that’s eight hours behind Coordinated Universal Time (UTC) in ISO format.

    "2022-06-14T15:10:30.55-8:00"

    When using a string to represent temporal data, you can omit parts of the ISO format. For example:

    • "2022-06-14" represents the day June 14, 2022.

    • "15:10:30" represents a time 30 seconds past 15:10 (3:10pm)

    In general, you can compare two temporal values only if they have the same components, for example, two dates or two times. Violations of this rule usually give null results.

    The following examples, which use the date_diff_str function to compare two temporal values and return the difference in a designated unit, demonstrate these rules.

    Examples
    date_diff_str("2022-06-22", "2022-06-15", "day") returns 7
    date_diff_str("09:20:00", "08:00:00", "hour") returns 1
    date_diff_str("09:20:00", "08:00:00", "minute") returns 80
    date_diff_str("2022-06-22", "10:00:00", "hour") returns null

    For more information about string formats for temporal data, see Date String Formats.

    Incomplete Information Types

    Null

    NULL is a special value that indicates that a value does not exist. It often represents an unknown value. For example, if a user doesn’t know what to enter for a field, they leave it blank or let it be null.

    Example
    { "field": null };

    The expected result is:

    { "field": null }

    Missing

    MISSING indicates that a name-value pair is not present in an object. If you access a missing name-value pair, the query returns an empty result value.

    As neither the data model nor the system enforces homogeneity for datasets or collections, items in a dataset or collection can be of heterogeneous types. A field that is present in one object might be missing in another.

    Example
    { "field": missing };

    Results in:

    {  }

    Since a field with value missing means the field is also absent, the result is an empty object.

    The query results convert a missing value to null.

    Composite Types

    Object

    An object--that is, a JSON object—​contains a set of fields. Each field is described by its name.

    Syntactically, curly braces {…​} surround object constructors.

    Example
    { "name": "Joe Blow", "rank": "Sergeant", "serialno": 1234567 }
{ "rank": "Private", "serialno": 9876543 }
{ "name": "Sally Forth", "rank": "Major", "serialno": 2345678, "gender": "F" }

    [#CompositeTypesArray]https://github.com/couchbasecloud/couchbase-cloud/pull/27045/files === Array

    An array is a container that holds a fixed number of values. An array is an ordered collection of items.

    Syntactically, brackets […​] denote array constructors.

    Example
    ["alice", 123, "bob", null]
    An array can appear in the incoming JSON, and a query can construct an array. Each SELECT statement with an ORDER BY clause returns an array.

    Multiset

    A multiset is an unordered collection of items. A multiset allows multiple instances of its elements.

    A multiset cannot appear in the incoming JSON. The query results convert a multiset into a JSON array with an undefined order of elements. The order of the items in the result might change from one query execution to another. Each SELECT statement without an ORDER BY clause returns a multiset.