ClickHouse/docs/en/query_language/functions/array_functions.md

720 lines
22 KiB
Markdown
Raw Normal View History

# Functions for working with arrays
## empty
Returns 1 for an empty array, or 0 for a non-empty array.
The result type is UInt8.
The function also works for strings.
## notEmpty
Returns 0 for an empty array, or 1 for a non-empty array.
The result type is UInt8.
The function also works for strings.
## length {#array_functions-length}
Returns the number of items in the array.
The result type is UInt64.
The function also works for strings.
## emptyArrayUInt8, emptyArrayUInt16, emptyArrayUInt32, emptyArrayUInt64
## emptyArrayInt8, emptyArrayInt16, emptyArrayInt32, emptyArrayInt64
## emptyArrayFloat32, emptyArrayFloat64
## emptyArrayDate, emptyArrayDateTime
## emptyArrayString
Accepts zero arguments and returns an empty array of the appropriate type.
## emptyArrayToSingle
Accepts an empty array and returns a one-element array that is equal to the default value.
## range(N)
Returns an array of numbers from 0 to N-1.
Just in case, an exception is thrown if arrays with a total length of more than 100,000,000 elements are created in a data block.
## array(x1, ...), operator \[x1, ...\]
Creates an array from the function arguments.
The arguments must be constants and have types that have the smallest common type. At least one argument must be passed, because otherwise it isn't clear which type of array to create. That is, you can't use this function to create an empty array (to do that, use the 'emptyArray\*' function described above).
Returns an 'Array(T)' type result, where 'T' is the smallest common type out of the passed arguments.
## arrayConcat
Combines arrays passed as arguments.
```
arrayConcat(arrays)
```
**Parameters**
WIP on docs (#3813) * CLICKHOUSE-4063: less manual html @ index.md * CLICKHOUSE-4063: recommend markdown="1" in README.md * CLICKHOUSE-4003: manually purge custom.css for now * CLICKHOUSE-4064: expand <details> before any print (including to pdf) * CLICKHOUSE-3927: rearrange interfaces/formats.md a bit * CLICKHOUSE-3306: add few http headers * Remove copy-paste introduced in #3392 * Hopefully better chinese fonts #3392 * get rid of tabs @ custom.css * Apply comments and patch from #3384 * Add jdbc.md to ToC and some translation, though it still looks badly incomplete * minor punctuation * Add some backlinks to official website from mirrors that just blindly take markdown sources * Do not make fonts extra light * find . -name '*.md' -type f | xargs -I{} perl -pi -e 's//g' {} * find . -name '*.md' -type f | xargs -I{} perl -pi -e 's/ sql/g' {} * Remove outdated stuff from roadmap.md * Not so light font on front page too * Refactor Chinese formats.md to match recent changes in other languages * Update some links on front page * Remove some outdated comment * Add twitter link to front page * More front page links tuning * Add Amsterdam meetup link * Smaller font to avoid second line * Add Amsterdam link to README.md * Proper docs nav translation * Back to 300 font-weight except Chinese * fix docs build * Update Amsterdam link * remove symlinks * more zh punctuation * apply lost comment by @zhang2014 * Apply comments by @zhang2014 from #3417 * Remove Beijing link * rm incorrect symlink * restore content of docs/zh/operations/table_engines/index.md * CLICKHOUSE-3751: stem terms while searching docs * CLICKHOUSE-3751: use English stemmer in non-English docs too * CLICKHOUSE-4135 fix * Remove past meetup link * Add blog link to top nav * Add ContentSquare article link * Add form link to front page + refactor some texts * couple markup fixes * minor * Introduce basic ODBC driver page in docs * More verbose 3rd party libs disclaimer * Put third-party stuff into a separate folder * Separate third-party stuff in ToC too * Update links * Move stuff that is not really (only) a client library into a separate page * Add clickhouse-hdfs-loader link * Some introduction for "interfaces" section * Rewrite tcp.md * http_interface.md -> http.md * fix link * Remove unconvenient error for now * try to guess anchor instead of failing * remove symlink * Remove outdated info from introduction * remove ru roadmap.md * replace ru roadmap.md with symlink * Update roadmap.md * lost file * Title case in toc_en.yml * Sync "Functions" ToC section with en * Remove reference to pretty old ClickHouse release from docs * couple lost symlinks in fa * Close quote in proper place * Rewrite en/getting_started/index.md * Sync en<>ru getting_started/index.md * minor changes * Some gui.md refactoring * Translate DataGrip section to ru * Translate DataGrip section to zh * Translate DataGrip section to fa * Translate DBeaver section to fa * Translate DBeaver section to zh * Split third-party GUI to open-source and commercial * Mention some RDBMS integrations + ad-hoc translation fixes * Add rel="external nofollow" to outgoing links from docs * Lost blank lines * Fix class name * More rel="external nofollow" * Apply suggestions by @sundy-li * Mobile version of front page improvements * test * test 2 * test 3 * Update LICENSE * minor docs fix * Highlight current article as suggested by @sundy-li * fix link destination * Introduce backup.md (only "en" for now) * Mention INSERT+SELECT in backup.md * Some improvements for replication.md * Add backup.md to toc * Mention clickhouse-backup tool * Mention LightHouse in third-party GUI list * Introduce interfaces/third-party/proxy.md * Add clickhouse-bulk to proxy.md * Major extension of integrations.md contents * fix link target * remove unneeded file * better toc item name * fix markdown * better ru punctuation * Add yet another possible backup approach * Simplify copying permalinks to headers * Support non-eng link anchors in docs + update some deps * Generate anchors for single-page mode automatically * Remove anchors to top of pages * Remove anchors that nobody links to * build fixes * fix few links * restore css * fix some links * restore gifs * fix lost words * more docs fixes * docs fixes * NULL anchor * update urllib3 dependency * more fixes
2018-12-12 17:28:00 +00:00
- `arrays` Arbitrary number of arguments of [Array](../../data_types/array.md) type.
**Example**
``` sql
SELECT arrayConcat([1, 2], [3, 4], [5, 6]) AS res
```
```
┌─res───────────┐
│ [1,2,3,4,5,6] │
└───────────────┘
```
## arrayElement(arr, n), operator arr[n]
Get the element with the index `n` from the array `arr`. `n` must be any integer type.
Indexes in an array begin from one.
Negative indexes are supported. In this case, it selects the corresponding element numbered from the end. For example, `arr[-1]` is the last item in the array.
If the index falls outside of the bounds of an array, it returns some default value (0 for numbers, an empty string for strings, etc.).
## has(arr, elem)
Checks whether the 'arr' array has the 'elem' element.
Returns 0 if the the element is not in the array, or 1 if it is.
`NULL` is processed as a value.
```
SELECT has([1, 2, NULL], NULL)
┌─has([1, 2, NULL], NULL)─┐
│ 1 │
└─────────────────────────┘
```
## hasAll
Checks whether one array is a subset of another.
```
hasAll(set, subset)
```
**Parameters**
- `set` Array of any type with a set of elements.
- `subset` Array of any type with elements that should be tested to be a subset of `set`.
**Return values**
- `1`, if `set` contains all of the elements from `subset`.
- `0`, otherwise.
**Peculiar properties**
- An empty array is a subset of any array.
- `Null` processed as a value.
- Order of values in both of arrays doesn't matter.
**Examples**
`SELECT hasAll([], [])` returns 1.
`SELECT hasAll([1, Null], [Null])` returns 1.
`SELECT hasAll([1.0, 2, 3, 4], [1, 3])` returns 1.
`SELECT hasAll(['a', 'b'], ['a'])` returns 1.
`SELECT hasAll([1], ['a'])` returns 0.
`SELECT hasAll([[1, 2], [3, 4]], [[1, 2], [3, 5]])` returns 0.
## hasAny
Checks whether two arrays have intersection by some elements.
```
hasAny(array1, array2)
```
**Parameters**
- `array1` Array of any type with a set of elements.
- `array2` Array of any type with a set of elements.
**Return values**
- `1`, if `array1` and `array2` have one similar element at least.
- `0`, otherwise.
**Peculiar properties**
- `Null` processed as a value.
- Order of values in both of arrays doesn't matter.
**Examples**
`SELECT hasAny([1], [])` returns `0`.
`SELECT hasAny([Null], [Null, 1])` returns `1`.
`SELECT hasAny([-128, 1., 512], [1])` returns `1`.
`SELECT hasAny([[1, 2], [3, 4]], ['a', 'c'])` returns `0`.
`SELECT hasAll([[1, 2], [3, 4]], [[1, 2], [1, 2]])` returns `1`.
## indexOf(arr, x)
Returns the index of the first 'x' element (starting from 1) if it is in the array, or 0 if it is not.
Example:
```
:) SELECT indexOf([1,3,NULL,NULL],NULL)
SELECT indexOf([1, 3, NULL, NULL], NULL)
┌─indexOf([1, 3, NULL, NULL], NULL)─┐
│ 3 │
└───────────────────────────────────┘
```
Elements set to `NULL` are handled as normal values.
## countEqual(arr, x)
Returns the number of elements in the array equal to x. Equivalent to arrayCount (elem -> elem = x, arr).
`NULL` elements are handled as separate values.
Example:
```
SELECT countEqual([1, 2, NULL, NULL], NULL)
┌─countEqual([1, 2, NULL, NULL], NULL)─┐
│ 2 │
└──────────────────────────────────────┘
```
## arrayEnumerate(arr) {#array_functions-arrayenumerate}
Returns the array \[1, 2, 3, ..., length (arr) \]
This function is normally used with ARRAY JOIN. It allows counting something just once for each array after applying ARRAY JOIN. Example:
``` sql
SELECT
count() AS Reaches,
countIf(num = 1) AS Hits
FROM test.hits
ARRAY JOIN
GoalsReached,
arrayEnumerate(GoalsReached) AS num
WHERE CounterID = 160656
LIMIT 10
```
```
┌─Reaches─┬──Hits─┐
│ 95606 │ 31406 │
└─────────┴───────┘
```
In this example, Reaches is the number of conversions (the strings received after applying ARRAY JOIN), and Hits is the number of pageviews (strings before ARRAY JOIN). In this particular case, you can get the same result in an easier way:
``` sql
SELECT
sum(length(GoalsReached)) AS Reaches,
count() AS Hits
FROM test.hits
WHERE (CounterID = 160656) AND notEmpty(GoalsReached)
```
```
┌─Reaches─┬──Hits─┐
│ 95606 │ 31406 │
└─────────┴───────┘
```
This function can also be used in higher-order functions. For example, you can use it to get array indexes for elements that match a condition.
## arrayEnumerateUniq(arr, ...)
Returns an array the same size as the source array, indicating for each element what its position is among elements with the same value.
For example: arrayEnumerateUniq(\[10, 20, 10, 30\]) = \[1, 1, 2, 1\].
This function is useful when using ARRAY JOIN and aggregation of array elements.
Example:
``` sql
SELECT
Goals.ID AS GoalID,
sum(Sign) AS Reaches,
sumIf(Sign, num = 1) AS Visits
FROM test.visits
ARRAY JOIN
Goals,
arrayEnumerateUniq(Goals.ID) AS num
WHERE CounterID = 160656
GROUP BY GoalID
ORDER BY Reaches DESC
LIMIT 10
```
```
┌──GoalID─┬─Reaches─┬─Visits─┐
│ 53225 │ 3214 │ 1097 │
│ 2825062 │ 3188 │ 1097 │
│ 56600 │ 2803 │ 488 │
│ 1989037 │ 2401 │ 365 │
│ 2830064 │ 2396 │ 910 │
│ 1113562 │ 2372 │ 373 │
│ 3270895 │ 2262 │ 812 │
│ 1084657 │ 2262 │ 345 │
│ 56599 │ 2260 │ 799 │
│ 3271094 │ 2256 │ 812 │
└─────────┴─────────┴────────┘
```
In this example, each goal ID has a calculation of the number of conversions (each element in the Goals nested data structure is a goal that was reached, which we refer to as a conversion) and the number of sessions. Without ARRAY JOIN, we would have counted the number of sessions as sum(Sign). But in this particular case, the rows were multiplied by the nested Goals structure, so in order to count each session one time after this, we apply a condition to the value of the arrayEnumerateUniq(Goals.ID) function.
The arrayEnumerateUniq function can take multiple arrays of the same size as arguments. In this case, uniqueness is considered for tuples of elements in the same positions in all the arrays.
``` sql
SELECT arrayEnumerateUniq([1, 1, 1, 2, 2, 2], [1, 1, 2, 1, 1, 2]) AS res
```
```
┌─res───────────┐
│ [1,2,1,1,2,1] │
└───────────────┘
```
This is necessary when using ARRAY JOIN with a nested data structure and further aggregation across multiple elements in this structure.
## arrayPopBack
Removes the last item from the array.
```
arrayPopBack(array)
```
**Parameters**
- `array` Array.
**Example**
``` sql
SELECT arrayPopBack([1, 2, 3]) AS res
```
```
┌─res───┐
│ [1,2] │
└───────┘
```
## arrayPopFront
Removes the first item from the array.
```
arrayPopFront(array)
```
**Parameters**
- `array` Array.
**Example**
``` sql
SELECT arrayPopFront([1, 2, 3]) AS res
```
```
┌─res───┐
│ [2,3] │
└───────┘
```
## arrayPushBack
Adds one item to the end of the array.
```
arrayPushBack(array, single_value)
```
**Parameters**
- `array` Array.
- `single_value` A single value. Only numbers can be added to an array with numbers, and only strings can be added to an array of strings. When adding numbers, ClickHouse automatically sets the `single_value` type for the data type of the array. For more information about the types of data in ClickHouse, see "[Data types](../../data_types/index.md#data_types)". Can be `NULL`. The function adds a `NULL` element to an array, and the type of array elements converts to `Nullable`.
**Example**
``` sql
SELECT arrayPushBack(['a'], 'b') AS res
```
2018-04-23 06:20:21 +00:00
```
┌─res───────┐
│ ['a','b'] │
└───────────┘
```
## arrayPushFront
Adds one element to the beginning of the array.
```
arrayPushFront(array, single_value)
```
**Parameters**
- `array` Array.
- `single_value` A single value. Only numbers can be added to an array with numbers, and only strings can be added to an array of strings. When adding numbers, ClickHouse automatically sets the `single_value` type for the data type of the array. For more information about the types of data in ClickHouse, see "[Data types](../../data_types/index.md#data_types)". Can be `NULL`. The function adds a `NULL` element to an array, and the type of array elements converts to `Nullable`.
**Example**
``` sql
SELECT arrayPushBack(['b'], 'a') AS res
```
```
┌─res───────┐
│ ['a','b'] │
└───────────┘
```
## arrayResize
Changes the length of the array.
```
arrayResize(array, size[, extender])
```
**Parameters:**
- `array` — Array.
- `size` — Required length of the array.
- If `size` is less than the original size of the array, the array is truncated from the right.
- If `size` is larger than the initial size of the array, the array is extended to the right with `extender` values or default values for the data type of the array items.
- `extender` — Value for extending an array. Can be `NULL`.
**Returned value:**
An array of length `size`.
**Examples of calls**
```
SELECT arrayResize([1], 3)
┌─arrayResize([1], 3)─┐
│ [1,0,0] │
└─────────────────────┘
```
```
SELECT arrayResize([1], 3, NULL)
┌─arrayResize([1], 3, NULL)─┐
│ [1,NULL,NULL] │
└───────────────────────────┘
```
## arraySlice
Returns a slice of the array.
```
arraySlice(array, offset[, length])
```
**Parameters**
- `array` Array of data.
2018-03-25 02:04:22 +00:00
- `offset` Indent from the edge of the array. A positive value indicates an offset on the left, and a negative value is an indent on the right. Numbering of the array items begins with 1.
- `length` - The length of the required slice. If you specify a negative value, the function returns an open slice `[offset, array_length - length)`. If you omit the value, the function returns the slice `[offset, the_end_of_array]`.
**Example**
``` sql
SELECT arraySlice([1, 2, NULL, 4, 5], 2, 3) AS res
```
```
┌─res────────┐
│ [2,NULL,4] │
└────────────┘
```
Array elements set to `NULL` are handled as normal values.
2019-04-23 19:43:20 +00:00
## arraySort(\[func,\] arr, ...) {#array_functions-reverse-sort}
2019-04-19 15:18:57 +00:00
2019-04-23 19:43:20 +00:00
Sorts the elements of the `arr` array in ascending order. If the `func` function is specified, sorting order is determined by the result of the `func` function applied to the elements of the array. If `func` accepts multiple arguments, the `arraySort` function is passed several arrays that the arguments of `func` will correspond to. Detailed examples are shown at the end of `arraySort` description.
2019-04-19 15:18:57 +00:00
2019-04-23 12:56:22 +00:00
Example of integer values sorting:
2019-04-19 15:18:57 +00:00
``` sql
2019-04-23 12:56:22 +00:00
SELECT arraySort([1, 3, 3, 0]);
2019-04-19 15:18:57 +00:00
```
```
┌─arraySort([1, 3, 3, 0])─┐
│ [0,1,3,3] │
└─────────────────────────┘
```
2019-04-23 12:56:22 +00:00
Example of string values sorting:
2019-04-19 15:55:23 +00:00
``` sql
2019-04-23 12:56:22 +00:00
SELECT arraySort(['hello', 'world', '!']);
2019-04-19 15:55:23 +00:00
```
```
┌─arraySort(['hello', 'world', '!'])─┐
│ ['!','hello','world'] │
└────────────────────────────────────┘
```
2019-04-23 12:56:22 +00:00
Consider the following sorting order for the `NULL`, `NaN` and `Inf` values:
``` sql
SELECT arraySort([1, nan, 2, NULL, 3, nan, -4, NULL, inf, -inf]);
```
```
┌─arraySort([1, nan, 2, NULL, 3, nan, -4, NULL, inf, -inf])─┐
│ [-inf,-4,1,2,3,inf,nan,nan,NULL,NULL] │
└───────────────────────────────────────────────────────────┘
```
- `-Inf` values are first in the array.
- `NULL` values are last in the array.
- `NaN` values are right before `NULL`.
- `Inf` values are right before `NaN`.
2019-04-23 19:54:32 +00:00
Note that `arraySort` is a [higher-order function](higher_order_functions.md). You can pass a lambda function to it as the first argument. In this case, sorting order is determined by the result of the lambda function applied to the elements of the array.
Let's consider the following example:
2019-04-23 12:56:22 +00:00
2019-04-19 15:18:57 +00:00
``` sql
2019-04-23 19:43:20 +00:00
SELECT arraySort((x) -> -x, [1, 2, 3]) as res;
```
```
┌─res─────┐
│ [3,2,1] │
└─────────┘
```
2019-04-24 21:08:49 +00:00
For each element of the source array, the lambda function returns the sorting key, that is, [1 > -1, 2 > -2, 3 > -3]. Since the `arraySort` function sorts the keys in ascending order, the result is [3, 2, 1]. Thus, the `(x) > -x` lambda function sets the [descending order](#array_functions-reverse-sort) in a sorting.
2019-04-23 19:43:20 +00:00
2019-04-24 21:08:49 +00:00
The lambda function can accept multiple arguments. In this case, you need to pass the `arraySort` function several arrays of identical length that the arguments of lambda function will correspond to. The resulting array will consist of elements from the first input array; elements from the next input array(s) specify the sorting keys. For example:
2019-04-23 19:43:20 +00:00
``` sql
SELECT arraySort((x, y) -> y, ['hello', 'world'], [2, 1]) as res;
2019-04-23 12:56:22 +00:00
```
2019-04-19 15:18:57 +00:00
```
2019-04-23 12:56:22 +00:00
┌─res────────────────┐
│ ['world', 'hello'] │
└────────────────────┘
```
2019-04-24 21:08:49 +00:00
Here, the elements that are passed in the second array ([2, 1]) define a sorting key for the corresponding element from the source array (['hello', 'world']), that is, ['hello' > 2, 'world' > 1]. Since the lambda function doesn't use `x`, actual values of the source array don't affect the order in the result. So, 'hello' will be the second element in the result, and 'world' will be the first.
2019-04-23 12:56:22 +00:00
2019-04-24 21:08:49 +00:00
Other examples are shown below.
2019-04-23 12:56:22 +00:00
``` sql
2019-04-23 19:43:20 +00:00
SELECT arraySort((x, y) -> y, [0, 1, 2], ['c', 'b', 'a']) as res;
2019-04-19 15:18:57 +00:00
```
2019-04-23 12:56:22 +00:00
``` sql
┌─res─────┐
2019-04-23 19:43:20 +00:00
│ [2,1,0] │
2019-04-23 12:56:22 +00:00
└─────────┘
2019-04-19 15:18:57 +00:00
```
2019-04-23 19:54:32 +00:00
``` sql
SELECT arraySort((x, y) -> -y, [0, 1, 2], [1, 2, 3]) as res;
```
``` sql
┌─res─────┐
│ [2,1,0] │
└─────────┘
```
2019-04-23 19:43:20 +00:00
!!! note
To improve sorting efficiency, the [Schwartzian transform](https://en.wikipedia.org/wiki/Schwartzian_transform) is used.
2019-04-19 15:55:23 +00:00
2019-04-23 19:43:20 +00:00
## arrayReverseSort([func,] arr, ...) {#array_functions-reverse-sort}
2019-04-19 15:55:23 +00:00
2019-04-23 19:43:20 +00:00
Sorts the elements of the `arr` array in descending order. If the `func` function is specified, `arr` is sorted according to the result of the `func` function applied to the elements of the array, and then the sorted array is reversed. If `func` accepts multiple arguments, the `arrayReverseSort` function is passed several arrays that the arguments of `func` will correspond to. Detailed examples are shown at the end of `arrayReverseSort` description.
2019-04-23 12:56:22 +00:00
Example of integer values sorting:
2019-04-19 15:18:57 +00:00
2019-04-19 15:55:23 +00:00
``` sql
2019-04-23 12:56:22 +00:00
SELECT arrayReverseSort([1, 3, 3, 0]);
2019-04-19 15:55:23 +00:00
```
```
┌─arrayReverseSort([1, 3, 3, 0])─┐
│ [3,3,1,0] │
└────────────────────────────────┘
```
2019-04-23 12:56:22 +00:00
Example of string values sorting:
2019-04-19 16:04:45 +00:00
2019-04-19 15:55:23 +00:00
``` sql
2019-04-23 12:56:22 +00:00
SELECT arrayReverseSort(['hello', 'world', '!']);
2019-04-19 15:55:23 +00:00
```
```
┌─arrayReverseSort(['hello', 'world', '!'])─┐
│ ['world','hello','!'] │
└───────────────────────────────────────────┘
```
2019-04-19 15:18:57 +00:00
2019-04-23 12:56:22 +00:00
Consider the following sorting order for the `NULL`, `NaN` and `Inf` values:
2019-04-19 15:18:57 +00:00
``` sql
2019-04-23 12:56:22 +00:00
SELECT arrayReverseSort([1, nan, 2, NULL, 3, nan, -4, NULL, inf, -inf]) as res;
```
``` sql
┌─res───────────────────────────────────┐
│ [inf,3,2,1,-4,-inf,nan,nan,NULL,NULL] │
└───────────────────────────────────────┘
2019-04-19 15:18:57 +00:00
```
2019-04-23 12:56:22 +00:00
- `Inf` values are first in the array.
- `NULL` values are last in the array.
- `NaN` values are right before `NULL`.
- `-Inf` values are right before `NaN`.
2019-04-23 19:54:32 +00:00
Note that the `arrayReverseSort` is a [higher-order function](higher_order_functions.md). You can pass a lambda function to it as the first argument. Example is shown below.
2019-04-23 19:43:20 +00:00
``` sql
SELECT arrayReverseSort((x) -> -x, [1, 2, 3]) as res;
```
```
┌─res─────┐
│ [1,2,3] │
└─────────┘
```
The array is sorted in the following way:
1. At first, the source array ([1, 2, 3]) is sorted according to the result of the lambda function applied to the elements of the array. The result is an array [3, 2, 1].
2019-04-24 21:08:49 +00:00
2. Array that is obtained on the previous step, is reversed. So, the final result is [1, 2, 3].
2019-04-23 19:43:20 +00:00
2019-04-24 21:08:49 +00:00
The lambda function can accept multiple arguments. In this case, you need to pass the `arrayReverseSort` function several arrays of identical length that the arguments of lambda function will correspond to. The resulting array will consist of elements from the first input array; elements from the next input array(s) specify the sorting keys. For example:
2019-04-23 12:56:22 +00:00
``` sql
2019-04-23 19:43:20 +00:00
SELECT arrayReverseSort((x, y) -> y, ['hello', 'world'], [2, 1]) as res;
2019-04-19 15:18:57 +00:00
```
2019-04-23 12:56:22 +00:00
``` sql
┌─res───────────────┐
│ ['hello','world'] │
└───────────────────┘
2019-04-19 15:18:57 +00:00
```
2019-04-23 19:43:20 +00:00
In this example, the array is sorted in the following way:
2019-04-23 12:56:22 +00:00
2019-04-24 21:08:49 +00:00
1. At first, the source array (['hello', 'world']) is sorted according to the result of the lambda function applied to the elements of the arrays. The elements that are passed in the second array ([2, 1]), define the sorting keys for corresponding elements from the source array. The result is an array ['world', 'hello'].
2019-04-23 19:43:20 +00:00
2. Array that was sorted on the previous step, is reversed. So, the final result is ['hello', 'world'].
2019-04-23 12:56:22 +00:00
2019-04-24 21:08:49 +00:00
Other examples are shown below.
2019-04-23 12:56:22 +00:00
``` sql
2019-04-23 19:43:20 +00:00
SELECT arrayReverseSort((x, y) -> y, [4, 3, 5], ['a', 'b', 'c']) AS res;
2019-04-23 12:56:22 +00:00
```
``` sql
┌─res─────┐
2019-04-23 19:43:20 +00:00
│ [5,3,4] │
2019-04-23 12:56:22 +00:00
└─────────┘
```
2019-04-23 19:54:32 +00:00
``` sql
SELECT arrayReverseSort((x, y) -> -y, [4, 3, 5], [1, 2, 3]) AS res;
```
``` sql
┌─res─────┐
│ [4,3,5] │
└─────────┘
```
2019-04-19 15:18:57 +00:00
## arrayUniq(arr, ...)
If one argument is passed, it counts the number of different elements in the array.
If multiple arguments are passed, it counts the number of different tuples of elements at corresponding positions in multiple arrays.
If you want to get a list of unique items in an array, you can use arrayReduce('groupUniqArray', arr).
## arrayJoin(arr) {#array_functions-join}
A special function. See the section ["ArrayJoin function"](array_join.md#functions_arrayjoin).
## arrayDifference(arr)
Takes an array, returns an array with the difference between all pairs of neighboring elements. For example:
```sql
SELECT arrayDifference([1, 2, 3, 4])
```
```
┌─arrayDifference([1, 2, 3, 4])─┐
│ [0,1,1,1] │
└───────────────────────────────┘
```
## arrayDistinct(arr)
Takes an array, returns an array containing the different elements in all the arrays. For example:
```sql
SELECT arrayDistinct([1, 2, 2, 3, 1])
```
```
┌─arrayDistinct([1, 2, 2, 3, 1])─┐
│ [1,2,3] │
└────────────────────────────────┘
```
## arrayEnumerateDense(arr)
2019-04-12 16:32:03 +00:00
Returns an array of the same size as the source array, indicating where each element first appears in the source array. For example: arrayEnumerateDense([10,20,10,30]) = [1,2,1,3].
## arrayIntersect(arr)
Takes an array, returns the intersection of all array elements. For example:
```sql
SELECT
arrayIntersect([1, 2], [1, 3], [2, 3]) AS no_intersect,
arrayIntersect([1, 2], [1, 3], [1, 4]) AS intersect
```
```
┌─no_intersect─┬─intersect─┐
│ [] │ [1] │
└──────────────┴───────────┘
```
## arrayReduce(agg_func, arr1, ...)
Applies an aggregate function to array and returns its result.If aggregate function has multiple arguments, then this function can be applied to multiple arrays of the same size.
arrayReduce('agg_func', arr1, ...) - apply the aggregate function `agg_func` to arrays `arr1...`. If multiple arrays passed, then elements on corresponding positions are passed as multiple arguments to the aggregate function. For example: SELECT arrayReduce('max', [1,2,3]) = 3
## arrayReverse(arr)
Returns an array of the same size as the source array, containing the result of inverting all elements of the source array.
[Original article](https://clickhouse.yandex/docs/en/query_language/functions/array_functions/) <!--hide-->