Type Functions

reference

This topic describes the builtin SQL++ for Enterprise Analytics type functions.

is_array

Syntax:
```
is_array(expr)
```
Checks whether the given expression is an array value.
Arguments:
- expr : an expression of any type.
Return Value:
- a Boolean on whether the argument is an array value or not,
- a missing if the argument is a missing value,
- a null if the argument is a null value.

Example:

{
  "a": is_array(true),
  "b": is_array(false),
  "c": isarray(null),
  "d": isarray(missing),
  "e": isarray("d"),
  "f": isarray(4.0),
  "g": isarray(5),
  "h": isarray(["1", 2]),
  "i": isarray({"a":1})
};

The expected result is:

{ "a": false, "b": false, "c": null, "e": false, "f": false, "g": false, "h": true, "i": false }

The function has an alias isarray.

is_multiset

Syntax:
```
is_multiset(expr)
```
Checks whether the given expression is an multiset value.
Arguments:
- expr : an expression of any type.
Return Value:
- a Boolean on whether the argument is an multiset value or not,
- a missing if the argument is a missing value,
- a null if the argument is a null value.

Example:

{
  "a": is_multiset(true),
  "b": is_multiset(false),
  "c": is_multiset(null),
  "d": is_multiset(missing),
  "e": is_multiset("d"),
  "f": ismultiset(4.0),
  "g": ismultiset(["1", 2]),
  "h": ismultiset({"a":1}),
  "i": ismultiset({{"hello", 9328, "world", [1, 2, null]}})
};

The expected result is:

{ "a": false, "b": false, "c": null, "e": false, "f": false, "g": false, "h": false, "i": true }

The function has an alias ismultiset.

is_atomic (is_atom)

Syntax:
```
is_atomic(expr)
```
Checks whether the given expression is a value of a primitive type.
Arguments:
- expr : an expression of any type.
Return Value:
- a Boolean on whether the argument is a primitive type or not,
- a missing if the argument is a missing value,
- a null if the argument is a null value.

Example:

{
  "a": is_atomic(true),
  "b": is_atomic(false),
  "c": isatomic(null),
  "d": isatomic(missing),
  "e": isatomic("d"),
  "f": isatom(4.0),
  "g": isatom(5),
  "h": isatom(["1", 2]),
  "i": isatom({"a":1})
};

The expected result is:

{ "a": true, "b": true, "c": null, "e": true, "f": true, "g": true, "h": false, "i": false }

The function has three aliases: isatomic, is_atom, and isatom.

is_Boolean (is_bool)

Syntax:
```
is_Boolean(expr)
```
Checks whether the given expression is a Boolean value.
Arguments:
- expr : an expression of any type.
Return Value:
- a Boolean on whether the argument is a Boolean value or not,
- a missing if the argument is a missing value,
- a null if the argument is a null value.

Example:

{
  "a": isBoolean(true),
  "b": isBoolean(false),
  "c": is_Boolean(null),
  "d": is_Boolean(missing),
  "e": isbool("d"),
  "f": isbool(4.0),
  "g": isbool(5),
  "h": isbool(["1", 2]),
  "i": isbool({"a":1})
};

The expected result is:

{ "a": true, "b": true, "c": null, "e": false, "f": false, "g": false, "h": false, "i": false }

The function has three aliases: isBoolean, is_bool, and isbool.

is_number (is_num)

Syntax:
```
is_number(expr)
```
Checks whether the given expression is a numeric value.
Arguments:
- expr : an expression of any type.
Return Value:
- a Boolean on whether the argument is a smallint/tinyint/integer/bigint/float/double value or not,
- a missing if the argument is a missing value,
- a null if the argument is a null value.

Example:

{
  "a": is_number(true),
  "b": is_number(false),
  "c": isnumber(null),
  "d": isnumber(missing),
  "e": isnumber("d"),
  "f": isnum(4.0),
  "g": isnum(5),
  "h": isnum(["1", 2]),
  "i": isnum({"a":1})
};

The expected result is:

{ "a": false, "b": false, "c": null, "e": false, "f": true, "g": true, "h": false, "i": false }

The function has three aliases: isnumber, is_num, and isnum.

is_object (is_obj)

Syntax:
```
is_object(expr)
```
Checks whether the given expression is a object value.
Arguments:
- expr : an expression of any type.
Return Value:
- a Boolean on whether the argument is a object value or not,
- a missing if the argument is a missing value,
- a null if the argument is a null value.

Example:

{
  "a": is_object(true),
  "b": is_object(false),
  "c": isobject(null),
  "d": isobject(missing),
  "e": isobj("d"),
  "f": isobj(4.0),
  "g": isobj(5),
  "h": isobj(["1", 2]),
  "i": isobj({"a":1})
};

The expected result is:

{ "a": false, "b": false, "c": null, "e": false, "f": false, "g": false, "h": false, "i": true }

The function has three aliases: isobject, is_obj, and isobj.

is_string (is_str)

Syntax:
```
is_string(expr)
```
Checks whether the given expression is a string value.
Arguments:
- expr : an expression of any type.
Return Value:
- a Boolean on whether the argument is a string value or not,
- a missing if the argument is a missing value,
- a null if the argument is a null value.

Example:

{
  "a": is_string(true),
  "b": isstring(false),
  "c": isstring(null),
  "d": isstr(missing),
  "e": isstr("d"),
  "f": isstr(4.0),
  "g": isstr(5),
  "h": isstr(["1", 2]),
  "i": isstr({"a":1})
};

The expected result is:

{ "a": false, "b": false, "c": null, "e": true, "f": false, "g": false, "h": false, "i": false }

The function has three aliases: isstring, is_str, and isstr.

is_null

Syntax:
```
is_null(expr)
```
Checks whether the given expression is a null value.
Arguments:
- expr : an expression of any type.
Return Value:
- a Boolean on whether the variable is a null or not,
- a missing if the input is missing.

Example:

{ "v1": is_null(null), "v2": is_null(1), "v3": is_null(missing) };

The expected result is:
```
{ "v1": true, "v2": false }
```

The function has an alias isnull.

is_missing

Syntax:
```
is_missing(expr)
```
Checks whether the given expression is a missing value.
Arguments:
- expr : an expression of any type.
Return Value:
- a Boolean on whether the variable is a missing or not.

Example:

{ "v1": is_missing(null), "v2": is_missing(1), "v3": is_missing(missing) };

The expected result is:

{ "v1": false, "v2": false, "v3": true }

The function has an alias ismissing.

is_unknown

Syntax:
```
is_unknown(expr)
```
Checks whether the given variable is a null value or a missing value.
Arguments:
- expr : an expression of any type.
Return Value:
- a boolean on whether the variable is a null/missing value (true) or not (`false).

Example:

{ "v1": is_unknown(null), "v2": is_unknown(1), "v3": is_unknown(missing) };

The expected result is:
```
{ "v1": true, "v2": false, "v3": true }
```

The function has an alias isunknown.

to_array

Syntax:
```
to_array(expr)
```
Converts input value to an array value
Arguments:
- expr : an expression
Return Value:
- missing if the argument is missing
- null if the argument is null
- if the argument is of array type then it is returned as is
- if the argument is of multiset type then it is returned as an array with elements in an undefined order
- otherwise an array containing the input expression as its single item is returned

Example:

{
  "v1": to_array("asterix"),
  "v2": to_array(["asterix"]),
};

The expected result is:

{ "v1": ["asterix"], "v2": ["asterix"] }

The function has an alias toarray.

to_atomic (to_atom)

Syntax:
```
to_atomic(expr)
```
Converts input value to a primitive value
Arguments:
- expr : an expression
Return Value:
- missing if the argument is missing
- null if the argument is null
- if the argument is of primitive type then it is returned as is
- if the argument is of array or multiset type and has only one element then the result of invoking to_atomic() on that element is returned
- if the argument is of object type and has only one field then the result of invoking to_atomic() on the value of that field is returned
- otherwise null is returned

Example:

{
  "v1": to_atomic("asterix"),
  "v2": to_atomic(["asterix"]),
  "v3": to_atomic([0, 1]),
  "v4": to_atomic({"value": "asterix"}),
  "v5": to_number({"x": 1, "y": 2})
};

The expected result is:

{ "v1": "asterix", "v2": "asterix", "v3": null, "v4": "asterix", "v5": null }

The function has three aliases: toatomic, to_atom, and toatom.

to_boolean (to_bool)

Syntax:
```
to_boolean(expr)
```
Converts input value to a boolean value
Arguments:
- expr : an expression
Return Value:
- missing if the argument is missing
- null if the argument is null
- if the argument is of boolean type then it is returned as is
- if the argument is of numeric type then false if it’s 0 or NaN, otherwise true
- if the argument is of string type then false if it’s empty, otherwise true
- if the argument is of array or multiset type then false if its size is 0, otherwise true
- if the argument is of object type then false if it has no fields, otherwise true
- a type error results for all other input types

Example:

{
  "v1": to_boolean(0),
  "v2": to_boolean(1),
  "v3": to_boolean(""),
  "v4": to_boolean("asterix")
};

The expected result is:

{ "v1": false, "v2": true, "v3": false, "v4": true }

The function has three aliases: toboolean, to_bool, and tobool.

to_bigint

Syntax:
```
to_bigint(expr)
```
Converts input value to an integer value
Arguments:
- expr : an expression
Return Value:
- missing if the argument is missing
- null if the argument is null
- if the argument is of boolean type, 1 if it’s true, 0 if it’s false
- if the argument is of numeric integer type then it is returned as the same value of bigint type
- if the argument is of numeric float/double type then it is converted to bigint type
- if the argument is of string type and can be parsed as integer then that integer value is returned, otherwise null
- null if the argument is of array/multiset/object type
- a type error results for all other input types

Example:

{
  "v1": to_bigint(false),
  "v2": to_bigint(true),
  "v3": to_bigint(10),
  "v4": to_bigint(float("1e100")),
  "v5": to_bigint(double("1e1000")),
  "v6": to_bigint("20")
};

The expected result is:

{ "v1": 0, "v2": 1, "v3": 10, "v4": 9223372036854775807, "v5": 9223372036854775807, "v6": 20 }

The function has an alias tobigint.

to_double

Syntax:
```
to_double(expr)
```
Converts input value to a double value
Arguments:
- expr : an expression
Return Value:
- missing if the argument is missing
- null if the argument is null
- if the argument is of boolean type, 1.0 if it is true, 0.0 if it is false
- if the argument is of numeric type then it is returned as the value of double type
- if the argument is of string type and can be parsed as double then that double value is returned, otherwise null
- null if the argument is of array/multiset/object type
- a type error results for all other input types

Example:

{
  "v1": to_double(false),
  "v2": to_double(true),
  "v3": to_double(10),
  "v4": to_double(11.5),
  "v5": to_double("12.5")
};

The expected result is:

{ "v1": 0.0, "v2": 1.0, "v3": 10.0, "v4": 11.5, "v5": 12.5 }

The function has an alias todouble.

to_number (to_num)

Syntax:
```
to_number(expr)
```
Converts input value to a numeric value
Arguments:
- expr : an expression
Return Value:
- missing if the argument is missing
- null if the argument is null
- if the argument is of numeric type then it is returned as is
- if the argument is of boolean type, 1 if it is true, 0 if it is false
- if the argument is of string type and can be parsed as bigint then that bigint value is returned, otherwise if it can be parsed as double then that double value is returned, otherwise null
- null if the argument is of array/multiset/object type
- a type error results for all other input types

Example:

{
  "v1": to_number(false),
  "v2": to_number(true),
  "v3": to_number(10),
  "v4": to_number(11.5),
  "v5": to_number("12.5")
};

The expected result is:

{ "v1": 0, "v2": 1, "v3": 10, "v4": 11.5, "v5": 12.5 }

The function has three aliases: tonumber, to_num, and tonum.

to_object (to_obj)

Syntax:
```
to_object(expr)
```
Converts input value to an object value
Arguments:
- expr : an expression
Return Value:
- missing if the argument is missing
- null if the argument is null
- if the argument is of object type then it is returned as is
- otherwise an empty object is returned

Example:

{
  "v1": to_object({"value": "asterix"}),
  "v2": to_object("asterix")
};

The expected result is:

{ "v1": {"value": "asterix"}, "v2": {} }

The function has three aliases: toobject, to_obj, and toobj.

to_string (to_str)

Syntax:
```
to_string(expr)
```
Converts input value to a string value
Arguments:
- expr : an expression
Return Value:
- missing if the argument is missing
- null if the argument is null
- if the argument is of boolean type then "true" is returned if it is true, "false" if it is false
- if the argument is of numeric type then its string representation is returned
- if the argument is of string type then it is returned as is
- if the argument is of array/multiset/object type then null is returned
- a type error results for all other input types

Example:

{
  "v1": to_string(false),
  "v2": to_string(true),
  "v3": to_string(10),
  "v4": to_string(11.5),
  "v5": to_string("asterix")
};

The expected result is:

{ "v1": "false", "v2": "true", "v3": "10", "v4": "11.5", "v5": "asterix" }

The function has three aliases: tostring, to_str, and tostr.

typename

Syntax:
```
typename(expr)
```
Returns the type of an expression.
Arguments:
- expr: an expression.
Return Value:
- Returns a string, depending on the type of expr: number, string, array, object, or boolean.
- Returns NULL if expr is NULL.

Example:

{"v1": typename(123),
 "v2": typename("abc"),
 "v3": typename([1, 2, 3]),
 "v4": typename({"abc": 123}),
 "v5": typename(true)};

The expected result is:

{
  "v1": "number",
  "v2": "string",
  "v3": "array",
  "v4": "object",
  "v5": "boolean"
}

array_infer_schema

Syntax:

array_infer_schema(collection[, parameters])

Infers the schema of an array or multiset, for example the structure of the elements, data types of various attributes, sample values, and so on. Since an array or multiset can contain items with varying structures, the result of this function is statistical in nature rather than deterministic.

This function is the equivalent to the SQL++ for Query INFER statement.

You can infer the schema of a collection by applying this function to a subquery which returns the documents in that collection, or a representative sample of them. The subquery must use the SELECT VALUE clause to avoid an additional layer of nesting in the result of the subquery.

Arguments:
- collection: An array or multiset, or an expression that evaluates to an array or multiset.
- parameters: Optional. An object, which may contain one or more of the following fields to guide the function.
  - similarity_metric: Optional. A number, or an expression that evaluates to a number, between 0 and 1. This indicates the percentage match of attributes required for two schemas to have the same flavor. If omitted, it defaults to 0.6.
  - num_sample_values: Optional. An integer, or an expression that evaluates to an integer. This indicates the maximum number of sample values to be returned for each attribute, providing examples of the data format. If omitted, it defaults to 5.
Return Value:
- An array of one or more objects, each of which contains an inferred schema in JSON Schema format. For details of the schema, refer to the SQL++ for Query INFER statement.
- Returns an empty array if collection is MISSING or NULL.
- Returns an error if collection is not an array or multiset.
- Returns an error if parameters is not an object.
- Returns a warning if similarity_metric is not a number.
- Returns a warning if num_sample_values is not a number.
- Returns a warning if the argument name provided is not recognized by array_infer_schema

Example 1:

Infer schemas from an array or multiset.

array_infer_schema([{"a": 1},{"a":"aval"},{"a":[1,2]}], {"similarity_metric": 0.6});

The expected result is:

[
  {
    "#docs": 1,
    "%docs": 33.33333333333333,
    "type": "object",
    "Flavor": "",
    "properties": {
      "a": {
        "#docs": 1,
        "%docs": 100,
        "type": "array",
        "samples": [
          [
            1,
            2
          ]
        ],
        "maxItems": 2,
        "minItems": 2,
        "items": "number"
      }
    }
  },
  {
    "#docs": 1,
    "%docs": 33.33333333333333,
    "type": "object",
    "Flavor": "'a' = \"aval\"",
    "properties": {
      "a": {
        "#docs": 1,
        "%docs": 100,
        "type": "string",
        "samples": [
          "aval"
        ]
      }
    }
  },
  {
    "#docs": 1,
    "%docs": 33.33333333333333,
    "type": "object",
    "Flavor": "'a' = 1",
    "properties": {
      "a": {
        "#docs": 1,
        "%docs": 100,
        "type": "number",
        "samples": [
          1
        ]
      }
    }
  }
]

The function detects that the input data has three flavors of document: one where a is 1, one where a is "aval", and one where a is an array. All documents are objects, and each document only has the a property.

Example 2:

Infer the schema of the customers collection using a subquery.

array_infer_schema((SELECT VALUE c FROM customers as c), {"num_sample_values": 3});

The expected result is:

[
  {
    "#docs": 7,
    "%docs": 100,
    "type": "object",
    "Flavor": "",
    "properties": {
      "address": {
        "#docs": 7,
        "%docs": 100,
        "type": "object",
        "samples": [
          {
            "street": "690 River St.",
            "city": "Hanover, MA",
            "zipcode": "02340"
          },
          {
            "street": "201 Main St.",
            "city": "St. Louis, MO",
            "zipcode": "63101"
          },
          {
            "street": "120 Harbor Blvd.",
            "city": "Boston, MA",
            "zipcode": "02115"
          }
        ],
        "properties": {
          "city": {
            "#docs": 7,
            "%docs": 100,
            "type": "string",
            "samples": [
              "Boston, MA",
              "Hanover, MA",
              "St. Louis, MO"
            ]
          },
          "street": {
            "#docs": 7,
            "%docs": 100,
            "type": "string",
            "samples": [
              "201 Main St.",
              "690 River St.",
              "120 Harbor Blvd."
            ]
          },
          "zipcode": {
            "#docs": 6,
            "%docs": 85.71428571428571,
            "type": "string",
            "samples": [
              "02115",
              "02340",
              "63101"
            ]
          }
        }
      },
      "custid": {
        "#docs": 7,
        "%docs": 100,
        "type": "string",
        "samples": [
          "C13",
          "C25",
          "C37"
        ]
      },
      "name": {
        "#docs": 7,
        "%docs": 100,
        "type": "string",
        "samples": [
          "T. Cody",
          "T. Henry",
          "M. Sinclair"
        ]
      },
      "rating": {
        "#docs": 6,
        "%docs": 85.71428571428571,
        "type": "number",
        "samples": [
          640,
          690,
          750
        ]
      }
    }
  }
]

The function detects that this collection has only one flavor of document. All documents are objects, and each document has the following properties: custid (string), name (string), rating (number), and address (object), which in turn contains the properties city (string), street (string), and zipcode (string).