Complex data types
About complex types
In Devo, complex data types provide flexible and powerful structures for querying and manipulatingdata logs. These types include set, map, array, and tuple, each with unique properties allowing users to efficiently handle diverse data operations. This article outlines the key characteristics and operations associated with each data type.
Type | Description | Example |
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Unordered, unique collection of values |
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Key-value pairs, unique keys |
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Ordered collection, allows duplicates |
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Ordered, immutable collection, mixed types |
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Key-value pairs, unordered, unique keys, mixed types |
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These complex data types provide the flexibility for handling structured and unstructured data in Devo, enabling efficient queries and operations across vast datasets. Users can effectively manipulate and analyze data within the Devo environment by leveraging sets, maps, arrays, and tuples.
The JSON type is not considered a complex type but it is included in this documentation for similarity purposes. Currently, it is not possible to cast JSON natively from/to a complex type.
Set
A set in Devo represents an unordered collection of unique values, meaning no duplicates are allowed. The order of elements in a set is not guaranteed, making it ideal for operations where uniqueness is more important than sequence.
Example:
{1, 2, 3}
Key Characteristics:
Unordered: Elements do not follow a specific order.
Unique: No duplicates are allowed.
Related operations:
Operation | Description | Syntax | Example | Result Value | Result Type |
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creates a set from elements | mkset (ele_1, ... ,ele_n) | mkset (1.33,2,3,4) | {1.33, 2, 3, 4} | set(float) | |
Checks if a set is empty | isempty (set) | isempty ({1, 2, 3}) | false | bool | |
Returns the length of a set | length (set) | length ({1, 20, 3, 4, 20, 20}) | 4 | int | |
Checks the occurrence of | has (set, ele) | has ({31, 2, 77}, 77) | true | bool | |
Checks the occurrence of | `in` (ele, set) | `in` (77, {30, 2, 77}) | true | bool | |
Checks whether a set | has (set_1, set_2) | has ({1, 2 , 3, 4}, {2, 1}) | true | bool | |
Checks whether a set | `in` (set_1, set_2) | `in` ({1, 2 , 3, 4}, {2, 1}) | false | bool | |
Adds some value to a set | add (set, ele) | add ({30, "Peter", 77}, “Ann") | {30, Peter, 77, Ann} | set(str) | |
Union of two sets | add (set_1, set_2) | add ({5, "Peter", 77}, {77, "Ann", 400}) | {5, Peter, 77, Ann, 400] | set(str) | |
Joins the strings of a given | join (set_str) | join ({1, "Peter", 77, 77, "Ann"}) | 1Ann77Peter | str | |
Intersection of two sets | band (set_1, set_2) | band ({30, 2, 77}, {77, 400}) | {77} | set(int) | |
Deletes a value from a set | sub (set, ele) | sub ({30, 2, 77}, 400) | {30, 2, 77} | •set(int) | |
Difference of two sets | sub (set_1, set_2) | sub ({30, 2, 77}, {400, 30}) | {2, 77} | set(int) |
Common Operations:
from siem.logtrust.web.activity
Create a set from values:
select mkset(srcHost, params) as mkset_string
Convert an array to a set:
Check if a set contains a specific value:
Add values to a set:
Get distinct values in a set out of a grouped field
Get distinct values in a set out of a grouped field
Test them together in Data Search
Map
A map in Devo is a collection of key-value pairs where each key is unique, but values can be duplicated. Maps allow for efficient lookups by keys and are useful when working with datasets that need to associate properties or attributes to specific items.
Example:
Key Characteristics:
Key-Value Structure: Each pair associates a key with a value.
Unique Keys: Each key must be unique, though values can repeat.
Related operations:
Operation | Description | Syntax | Example | Result Value | Result Type |
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Creates a map from | mkmap (key_1, val_1, ... , key_n, val_n) | mkmap (10, 1001, 20, 1.33) | {10:1001, 20:1.33} | map(int, float) | |
collectdistinct() (aggr) | Creates a map of distinct values after an aggregation | collectdistinct(aggr_field) | {{1, 3, 20, 4}} | map(int, int,int,int) | |
Checks if a map is empty | isempty (map) | isempty ({1:10, 2:20, 3:30}) | false | bool | |
Returns the length of a map | length (map) | length ({1:"a", 2:"b", 3:"c"}) | 3 | int | |
Checks the | has (map, key) | has ({1:"aaa", 2:"bbb", 77:"ccc"}, 77) | true | bool | |
Checks the | `in` (key, map) | `in` (77, {1:"aaa", 2:"bbb", 77:"ccc"}) | true | bool | |
Adds some key-value | add (map, key, value) | add ({5:“Peter", 10:“Ann"}, 4, “xxx") | {5=Peter, 10=Ann, 4=xxx} | map(int, str) | |
Concatenation of two | add (map_1, map_2) | add ({5:"Peter", 10:"Ann"}, {4:"xxx"}) | {5=Peter, 10=Ann, 4=xxx} | map(int, str) | |
Given a map, returns the | at (map, key) | at ({"Hello":77, 4:4000}, "Hello") | 77 | int | |
Intersection of two maps : | band (map_1, map_2) | band ({5:"Five", 2:"Two"}, {2:"xxx"}) | {2=Two} | map(int, str) | |
Restrict a map to a set of | band (map, set) | band ({5:"Five", 2:"Two", 6:"Six"}, {6, 2}) | {2=Two, 6=Six} | map(int, str) | |
Deletes the key-value pair | sub (map, key) | sub ({5:"Five", 2:"Two", 6:"Six"}, 5) | {2:“Two", 6:“Six"} | map(int, str) | |
Deletes the key-value pairs | sub (map, set) | sub ({5:"Five", 2:"Two", 6:"Six"}, {2, 5, 10}) | {6=Six} | map(int, str) | |
Difference of two maps | sub (map_1, map_2) | sub ({5:"Five", 2:"Two", 6:"Six"} {5:“xxx"}) | {2:“Two", 6:“Six"} | map(int, str) | |
Returns the set of keys of a given map | keys (map) | keys ({"Hello":77, 4:4000}) | {Hello, 4} | set(str) | |
Returns the array of values of a given map | values (map) | values ({"Hello":77, 4:4000}) | [77, 4000] | array(int) |
Common Operations:
Create a map:
Check if a map is empty:
Get the length of a map (number of key-value pairs):
Access a value by key:
Append new key-value pairs:
Subtract pairs
Return the value of a give key
Return all keys or values from a map:
Test them together in Data Search
Array
An array is an ordered collection of elements where duplicates are allowed. Arrays are especially useful for performing a range of operations such as sorting, summing, and filtering. Unlike sets, arrays preserve the order of elements, making them essential for ordered data manipulation.
Example:
Key Characteristics:
Ordered: Elements follow a specific sequence.
Allows Duplicates: Identical elements can appear multiple times.
Related operations:
Operation | Description | Syntax | Example | Result Value | Result Type |
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Creates an array from elements | mkarray (ele_1, … ,ele_n) | mkarray (1.33,2,3,4) mkarray (“One", "two", "Number 3“) [ “One", 77 ] mkarray (domain, responseTime) | [1.33, 2, 3, 4] | array(float) array(str) array(str) array(str) | |
Creates an array by splitting a string field | split (string, string) |
| [1, 2, 3, 4] | array | |
Checks if an array is empty | isempty (array) | isempty ([1, 2, 3]) isempty ([ ]) | false true | bool | |
Returns the length of an array | length (array) | length ([1, 2, 3, 4, 5, 6]) | 6 | Int | |
Checks the occurrence of a specified value in a given array | •has (array, ele) •array -> ele | has ([30, 2, 77], 77) [30, 2, 77] -> 77 | true true | bool | |
Checks the occurrence of a specified value in a given array | `in` (ele, array) ele <- array | `in` (77, [30, 2, 77]) 77 <- [30, 2, 77] | true true | bool | |
Appends some value to the end of an array | add (array, ele) | add ([30, "Peter", 77], "Ann") | [30, Peter, 77, Ann] | array(str) | |
Concatenates two arrays | add (array_1, array_2) | add ([5, "Peter", 77], [77, "Ann", 400]) | [5, Peter, 77, 77, Ann, 400] | array(str) | |
Joins the strings of a given | join (array_str) | join ([1, "Peter", 77, 77, "Ann"]) | 1Peter7777Ann | str | |
Returns the n-th element of | at (array, n) | at ([10, 20, 3.33, 40], 1) | 20 | float | |
Returns a subarray between | at (array, from, to) | at ([10, 20, 30, 40], 1, 3) | [20, 30] | array(int) | |
Returns the index of the first | indexof (array, ele) | indexof ([10, 20, 3.33, 40], 3.33) | 2 | int | |
Drops null elements of a given array | dropnulls (array) | dropnulls ([3, null, 77, null]) | [3, 77] | array(int) | |
Sorts the elements of a | sort (array) | sort ([3, 77, 30, 1) | [1, 3, 30, 77] | array(int) | |
Reverses the elements of | reverse | reverse ([3, 77, 30, 1) | [1, 30, 77, 3] | array(int) | |
Sums the values of a | sum (array) | sum([1,2,3,4]) | 10 | Int |
Common Operations:
Create an array:
Convert a set to an array:
Check if an array contains a value:
Add a value to an array:
Reverse an array:
Drop null values from an array:
Sum numeric arrays:
length of an array
Test them together in Data Search
Tuple
A tuple in Devo is an ordered collection of elements that can be of mixed types (e.g., strings, numbers, booleans). Unlike arrays, tuples maintain the individual types of each element and are immutable, meaning that once created, the elements cannot be changed.
Example:
Key Characteristics:
Ordered: Elements are stored in a specific sequence.
Immutable: The values in a tuple cannot be modified after creation.
Allows Duplicates: Identical elements can appear more than once.
Allows Mixed Types: Elements can be of any type (e.g., string, integer, boolean).
Related operations:
Operation | Description | Syntax | Example | Result Value | Result Type |
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Creates a tuple with specified elements. |
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Tuple literal | Creates a tuple using parentheses. |
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Access by index | Access tuple elements using index. Supports negative indexing. |
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| First element Last element | Matches element type |
Access tuple elements by index using a function. |
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| First element | Matches element type | |
Filter by type | Filters tuple elements based on data type or pattern. |
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| Matches filtered criteria |
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Filter by value | Filters tuple elements based on value comparison. |
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| Matches filtered criteria |
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Sub-query (key lookup) | Finds the occurrence of a key in another dataset during the same period. |
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| Matched key occurrence | Matches key type |
Sub-query (field lookup) | Returns a field from another table matching a condition. |
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| Matches field type |
Sub-query (tuple matching) | Returns a tuple from another table matching specified conditions. |
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Common Operations:
Create a tuple:
Access tuple elements by index:
Filter tuples by type:
SUB-QUERY: find the occurrence of a specific IP in another table during the same period of time
SUB-QUERY: return the "origin" field in another table matching by user email
SUB-QUERY: return the tuple (userEmail, count()) from another table matching by the tuple (email, level)
Test them together in Data Search
JSON
Then JSON format is fully supported in Devo. It is useful for representing structured data in an unordered format, enabling flexible data storage and manipulation.
In Data Search: you can use the "pretty-print" view to inspect the content of JSON cells and extract the values that you need. How?
Example:
Key Characteristics:
Unordered: The sequence of keys is not guaranteed.
Unique Keys: Each key must be unique within the object.
Mixed Types: Values can be strings, numbers, booleans, arrays, or other JSON objects.
Flexible: Supports nested objects and arrays for complex structures.
Operation | Description | Syntax | Example | Result | Result Type |
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Extracts values from JSON objects using a |
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| Extracted value from JSON | Matches field type | |
Compiles a string as a |
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| A compiled |
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Returns the data type of a value inside a JSON object. |
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Converts a string field to a JSON data type. |
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| JSON object |
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Converts a JSON object or other data type to a string. |
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| Extracted value as a string |
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Given a map, returns the | at (json, key) |
| Extract a value from a key | Matches field type | |
Converts a JSON object (json data type) into string data type. | stringify(json_type) | stringify(json_type) | {“a“: 1, “b“: ”c”} |
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Common Operations:
Parse String to JSON
Extract a Property Value
Convert a JSON to a string
Determine Data Type of a JSON Value