Work with arrays

In GoogleSQL for BigQuery, an array is an ordered list consisting of zero or more values of the same data type. You can construct arrays of simple data types, such as INT64, and complex data types, such as STRUCTs. The current exception to this is the ARRAY data type because arrays of arrays are not supported. To learn more about the ARRAY data type, including NULL handling, see Array type.

With GoogleSQL, you can construct array literals, build arrays from subqueries using the ARRAY function, and aggregate values into an array using the ARRAY_AGG function.

You can combine arrays using functions like ARRAY_CONCAT(), and convert arrays to strings using ARRAY_TO_STRING().

Accessing array elements

Consider the following emulated table called Sequences. This table contains the column some_numbers of the ARRAY data type.

WITH
  Sequences AS (
    SELECT [0, 1, 1, 2, 3, 5] AS some_numbers UNION ALL
    SELECT [2, 4, 8, 16, 32] UNION ALL
    SELECT [5, 10]
  )
SELECT * FROM Sequences

/*---------------------*
 | some_numbers        |
 +---------------------+
 | [0, 1, 1, 2, 3, 5]  |
 | [2, 4, 8, 16, 32]   |
 | [5, 10]             |
 *---------------------*/

To access array elements in the some_numbers column, specify which type of indexing you want to use: either index or OFFSET(index) for zero-based indexes, or ORDINAL(index) for one-based indexes.

For example:

SELECT
  some_numbers,
  some_numbers[0] AS index_0,
  some_numbers[OFFSET(1)] AS offset_1,
  some_numbers[ORDINAL(1)] AS ordinal_1
FROM Sequences

/*--------------------+---------+----------+-----------*
 | some_numbers       | index_0 | offset_1 | ordinal_1 |
 +--------------------+---------+----------+-----------+
 | [0, 1, 1, 2, 3, 5] | 0       | 1        | 0         |
 | [2, 4, 8, 16, 32]  | 2       | 4        | 2         |
 | [5, 10]            | 5       | 10       | 5         |
 *--------------------+---------+----------+-----------*/

Note: OFFSET and ORDINAL will raise errors if the index is out of range. To avoid this, you can use SAFE_OFFSET or SAFE_ORDINAL to return NULL instead of raising an error.

Finding lengths

The ARRAY_LENGTH function returns the length of an array.

WITH Sequences AS
  (SELECT [0, 1, 1, 2, 3, 5] AS some_numbers
   UNION ALL SELECT [2, 4, 8, 16, 32] AS some_numbers
   UNION ALL SELECT [5, 10] AS some_numbers)
SELECT some_numbers,
       ARRAY_LENGTH(some_numbers) AS len
FROM Sequences;

/*--------------------+--------*
 | some_numbers       | len    |
 +--------------------+--------+
 | [0, 1, 1, 2, 3, 5] | 6      |
 | [2, 4, 8, 16, 32]  | 5      |
 | [5, 10]            | 2      |
 *--------------------+--------*/

Converting elements in an array to rows in a table

To convert an ARRAY into a set of rows, also known as "flattening," use the UNNEST operator. UNNEST takes an ARRAY and returns a table with a single row for each element in the ARRAY.

Because UNNEST destroys the order of the ARRAY elements, you may wish to restore order to the table. To do so, use the optional WITH OFFSET clause to return an additional column with the offset for each array element, then use the ORDER BY clause to order the rows by their offset.

Example

SELECT *
FROM UNNEST(['foo', 'bar', 'baz', 'qux', 'corge', 'garply', 'waldo', 'fred'])
  AS element
WITH OFFSET AS offset
ORDER BY offset;

/*----------+--------*
 | element  | offset |
 +----------+--------+
 | foo      | 0      |
 | bar      | 1      |
 | baz      | 2      |
 | qux      | 3      |
 | corge    | 4      |
 | garply   | 5      |
 | waldo    | 6      |
 | fred     | 7      |
 *----------+--------*/

To flatten an entire column of ARRAYs while preserving the values of the other columns in each row, use a correlated cross join to join the table containing the ARRAY column to the UNNEST output of that ARRAY column.

With a correlated join, the UNNEST operator references the ARRAY typed column from each row in the source table, which appears previously in the FROM clause. For each row N in the source table, UNNEST flattens the ARRAY from row N into a set of rows containing the ARRAY elements, and then the cross join joins this new set of rows with the single row N from the source table.

Examples

The following example uses UNNEST to return a row for each element in the array column. Because of the CROSS JOIN, the id column contains the id values for the row in Sequences that contains each number.

WITH Sequences AS
  (SELECT 1 AS id, [0, 1, 1, 2, 3, 5] AS some_numbers
   UNION ALL SELECT 2 AS id, [2, 4, 8, 16, 32] AS some_numbers
   UNION ALL SELECT 3 AS id, [5, 10] AS some_numbers)
SELECT id, flattened_numbers
FROM Sequences
CROSS JOIN UNNEST(Sequences.some_numbers) AS flattened_numbers;

/*------+-------------------*
 | id   | flattened_numbers |
 +------+-------------------+
 |    1 |                 0 |
 |    1 |                 1 |
 |    1 |                 1 |
 |    1 |                 2 |
 |    1 |                 3 |
 |    1 |                 5 |
 |    2 |                 2 |
 |    2 |                 4 |
 |    2 |                 8 |
 |    2 |                16 |
 |    2 |                32 |
 |    3 |                 5 |
 |    3 |                10 |
 *------+-------------------*/

Note that for correlated cross joins the UNNEST operator is optional and the CROSS JOIN can be expressed as a comma cross join. Using this shorthand notation, the previous example is consolidated as follows:

WITH Sequences AS
  (SELECT 1 AS id, [0, 1, 1, 2, 3, 5] AS some_numbers
   UNION ALL SELECT 2 AS id, [2, 4, 8, 16, 32] AS some_numbers
   UNION ALL SELECT 3 AS id, [5, 10] AS some_numbers)
SELECT id, flattened_numbers
FROM Sequences, Sequences.some_numbers AS flattened_numbers;

/*------+-------------------*
 | id   | flattened_numbers |
 +------+-------------------+
 |    1 |                 0 |
 |    1 |                 1 |
 |    1 |                 1 |
 |    1 |                 2 |
 |    1 |                 3 |
 |    1 |                 5 |
 |    2 |                 2 |
 |    2 |                 4 |
 |    2 |                 8 |
 |    2 |                16 |
 |    2 |                32 |
 |    3 |                 5 |
 |    3 |                10 |
 *------+-------------------*/

Querying nested arrays

If a table contains an ARRAY of STRUCTs, you can flatten the ARRAY to query the fields of the STRUCT. You can also flatten ARRAY type fields of STRUCT values.

Querying STRUCT elements in an array

The following example uses UNNEST with CROSS JOIN to flatten an ARRAY of STRUCTs.

WITH Races AS (
  SELECT "800M" AS race,
    [STRUCT("Rudisha" AS name, [23.4, 26.3, 26.4, 26.1] AS laps),
     STRUCT("Makhloufi" AS name, [24.5, 25.4, 26.6, 26.1] AS laps),
     STRUCT("Murphy" AS name, [23.9, 26.0, 27.0, 26.0] AS laps),
     STRUCT("Bosse" AS name, [23.6, 26.2, 26.5, 27.1] AS laps),
     STRUCT("Rotich" AS name, [24.7, 25.6, 26.9, 26.4] AS laps),
     STRUCT("Lewandowski" AS name, [25.0, 25.7, 26.3, 27.2] AS laps),
     STRUCT("Kipketer" AS name, [23.2, 26.1, 27.3, 29.4] AS laps),
     STRUCT("Berian" AS name, [23.7, 26.1, 27.0, 29.3] AS laps)]
       AS participants)
SELECT
  race,
  participant
FROM Races AS r
CROSS JOIN UNNEST(r.participants) AS participant;

/*------+---------------------------------------*
 | race | participant                           |
 +------+---------------------------------------+
 | 800M | {Rudisha, [23.4, 26.3, 26.4, 26.1]}   |
 | 800M | {Makhloufi, [24.5, 25.4, 26.6, 26.1]} |
 | 800M | {Murphy, [23.9, 26, 27, 26]}          |
 | 800M | {Bosse, [23.6, 26.2, 26.5, 27.1]}     |
 | 800M | {Rotich, [24.7, 25.6, 26.9, 26.4]}    |
 | 800M | {Lewandowski, [25, 25.7, 26.3, 27.2]} |
 | 800M | {Kipketer, [23.2, 26.1, 27.3, 29.4]}  |
 | 800M | {Berian, [23.7, 26.1, 27, 29.3]}      |
 *------+---------------------------------------*/

You can find specific information from repeated fields. For example, the following query returns the fastest racer in an 800M race.

Note: This example does not involve flattening an array, but does represent a common way to get information from a repeated field.

Example

WITH Races AS (
  SELECT "800M" AS race,
    [STRUCT("Rudisha" AS name, [23.4, 26.3, 26.4, 26.1] AS laps),
     STRUCT("Makhloufi" AS name, [24.5, 25.4, 26.6, 26.1] AS laps),
     STRUCT("Murphy" AS name, [23.9, 26.0, 27.0, 26.0] AS laps),
     STRUCT("Bosse" AS name, [23.6, 26.2, 26.5, 27.1] AS laps),
     STRUCT("Rotich" AS name, [24.7, 25.6, 26.9, 26.4] AS laps),
     STRUCT("Lewandowski" AS name, [25.0, 25.7, 26.3, 27.2] AS laps),
     STRUCT("Kipketer" AS name, [23.2, 26.1, 27.3, 29.4] AS laps),
     STRUCT("Berian" AS name, [23.7, 26.1, 27.0, 29.3] AS laps)]
       AS participants)
SELECT
  race,
  (SELECT name
   FROM UNNEST(participants)
   ORDER BY (
     SELECT SUM(duration)
     FROM UNNEST(laps) AS duration) ASC
   LIMIT 1) AS fastest_racer
FROM Races;

/*------+---------------*
 | race | fastest_racer |
 +------+---------------+
 | 800M | Rudisha       |
 *------+---------------*/

Querying ARRAY-type fields in a struct

You can also get information from nested repeated fields. For example, the following statement returns the runner who had the fastest lap in an 800M race.

WITH Races AS (
 SELECT "800M" AS race,
   [STRUCT("Rudisha" AS name, [23.4, 26.3, 26.4, 26.1] AS laps),
    STRUCT("Makhloufi" AS name, [24.5, 25.4, 26.6, 26.1] AS laps),
    STRUCT("Murphy" AS name, [23.9, 26.0, 27.0, 26.0] AS laps),
    STRUCT("Bosse" AS name, [23.6, 26.2, 26.5, 27.1] AS laps),
    STRUCT("Rotich" AS name, [24.7, 25.6, 26.9, 26.4] AS laps),
    STRUCT("Lewandowski" AS name, [25.0, 25.7, 26.3, 27.2] AS laps),
    STRUCT("Kipketer" AS name, [23.2, 26.1, 27.3, 29.4] AS laps),
    STRUCT("Berian" AS name, [23.7, 26.1, 27.0, 29.3] AS laps)]
    AS participants)
SELECT
race,
(SELECT name
 FROM UNNEST(participants),
   UNNEST(laps) AS duration
 ORDER BY duration ASC LIMIT 1) AS runner_with_fastest_lap
FROM Races;

/*------+-------------------------*
 | race | runner_with_fastest_lap |
 +------+-------------------------+
 | 800M | Kipketer                |
 *------+-------------------------*/

Notice that the preceding query uses the comma operator (,) to perform an implicit CROSS JOIN. It is equivalent to the following example, which uses an explicit CROSS JOIN.

WITH Races AS (
 SELECT "800M" AS race,
   [STRUCT("Rudisha" AS name, [23.4, 26.3, 26.4, 26.1] AS laps),
    STRUCT("Makhloufi" AS name, [24.5, 25.4, 26.6, 26.1] AS laps),
    STRUCT("Murphy" AS name, [23.9, 26.0, 27.0, 26.0] AS laps),
    STRUCT("Bosse" AS name, [23.6, 26.2, 26.5, 27.1] AS laps),
    STRUCT("Rotich" AS name, [24.7, 25.6, 26.9, 26.4] AS laps),
    STRUCT("Lewandowski" AS name, [25.0, 25.7, 26.3, 27.2] AS laps),
    STRUCT("Kipketer" AS name, [23.2, 26.1, 27.3, 29.4] AS laps),
    STRUCT("Berian" AS name, [23.7, 26.1, 27.0, 29.3] AS laps)]
    AS participants)
SELECT
race,
(SELECT name
 FROM UNNEST(participants)
 CROSS JOIN UNNEST(laps) AS duration
 ORDER BY duration ASC LIMIT 1) AS runner_with_fastest_lap
FROM Races;

/*------+-------------------------*
 | race | runner_with_fastest_lap |
 +------+-------------------------+
 | 800M | Kipketer                |
 *------+-------------------------*/

Flattening arrays with a CROSS JOIN excludes rows that have empty or NULL arrays. If you want to include these rows, use a LEFT JOIN.

WITH Races AS (
 SELECT "800M" AS race,
   [STRUCT("Rudisha" AS name, [23.4, 26.3, 26.4, 26.1] AS laps),
    STRUCT("Makhloufi" AS name, [24.5, 25.4, 26.6, 26.1] AS laps),
    STRUCT("Murphy" AS name, [23.9, 26.0, 27.0, 26.0] AS laps),
    STRUCT("Bosse" AS name, [23.6, 26.2, 26.5, 27.1] AS laps),
    STRUCT("Rotich" AS name, [24.7, 25.6, 26.9, 26.4] AS laps),
    STRUCT("Lewandowski" AS name, [25.0, 25.7, 26.3, 27.2] AS laps),
    STRUCT("Kipketer" AS name, [23.2, 26.1, 27.3, 29.4] AS laps),
    STRUCT("Berian" AS name, [23.7, 26.1, 27.0, 29.3] AS laps),
    STRUCT("Nathan" AS name, ARRAY<FLOAT64>[] AS laps),
    STRUCT("David" AS name, NULL AS laps)]
    AS participants)
SELECT
  name, sum(duration) AS finish_time
FROM Races CROSS JOIN Races.participants LEFT JOIN participants.laps AS duration
GROUP BY name;

/*-------------+--------------------*
 | name        | finish_time        |
 +-------------+--------------------+
 | Murphy      | 102.9              |
 | Rudisha     | 102.19999999999999 |
 | David       | NULL               |
 | Rotich      | 103.6              |
 | Makhloufi   | 102.6              |
 | Berian      | 106.1              |
 | Bosse       | 103.4              |
 | Kipketer    | 106                |
 | Nathan      | NULL               |
 | Lewandowski | 104.2              |
 *-------------+--------------------*/

Constructing arrays

You can construct an array using array literals or array functions. To learn more about constructing arrays, see Array type.

Creating arrays from subqueries

A common task when working with arrays is turning a subquery result into an array. In GoogleSQL, you can accomplish this using the ARRAY() function.

For example, consider the following operation on the Sequences table:

WITH Sequences AS
  (SELECT [0, 1, 1, 2, 3, 5] AS some_numbers
  UNION ALL SELECT [2, 4, 8, 16, 32] AS some_numbers
  UNION ALL SELECT [5, 10] AS some_numbers)
SELECT some_numbers,
  ARRAY(SELECT x * 2
        FROM UNNEST(some_numbers) AS x) AS doubled
FROM Sequences;

/*--------------------+---------------------*
 | some_numbers       | doubled             |
 +--------------------+---------------------+
 | [0, 1, 1, 2, 3, 5] | [0, 2, 2, 4, 6, 10] |
 | [2, 4, 8, 16, 32]  | [4, 8, 16, 32, 64]  |
 | [5, 10]            | [10, 20]            |
 *--------------------+---------------------*/

This example starts with a table named Sequences. This table contains a column, some_numbers, of type ARRAY<INT64>.

The query itself contains a subquery. This subquery selects each row in the some_numbers column and uses UNNEST to return the array as a set of rows. Next, it multiplies each value by two, and then re-combines the rows back into an array using the ARRAY() operator.

Filtering arrays

The following example uses a WHERE clause in the ARRAY() operator's subquery to filter the returned rows.

Note: In the following examples, the resulting rows are not ordered.

WITH Sequences AS
  (SELECT [0, 1, 1, 2, 3, 5] AS some_numbers
   UNION ALL SELECT [2, 4, 8, 16, 32] AS some_numbers
   UNION ALL SELECT [5, 10] AS some_numbers)
SELECT
  ARRAY(SELECT x * 2
        FROM UNNEST(some_numbers) AS x
        WHERE x < 5) AS doubled_less_than_five
FROM Sequences;

/*------------------------*
 | doubled_less_than_five |
 +------------------------+
 | [0, 2, 2, 4, 6]        |
 | [4, 8]                 |
 | []                     |
 *------------------------*/

Notice that the third row contains an empty array, because the elements in the corresponding original row ([5, 10]) did not meet the filter requirement of x < 5.

You can also filter arrays by using SELECT DISTINCT to return only unique elements within an array.

WITH Sequences AS
  (SELECT [0, 1, 1, 2, 3, 5] AS some_numbers)
SELECT ARRAY(SELECT DISTINCT x
             FROM UNNEST(some_numbers) AS x) AS unique_numbers
FROM Sequences;

/*-----------------*
 | unique_numbers  |
 +-----------------+
 | [0, 1, 2, 3, 5] |
 *-----------------*/

You can also filter rows of arrays by using the IN keyword. This keyword filters rows containing arrays by determining if a specific value matches an element in the array.

WITH Sequences AS
  (SELECT [0, 1, 1, 2, 3, 5] AS some_numbers
   UNION ALL SELECT [2, 4, 8, 16, 32] AS some_numbers
   UNION ALL SELECT [5, 10] AS some_numbers)
SELECT
   ARRAY(SELECT x
         FROM UNNEST(some_numbers) AS x
         WHERE 2 IN UNNEST(some_numbers)) AS contains_two
FROM Sequences;

/*--------------------*
 | contains_two       |
 +--------------------+
 | [0, 1, 1, 2, 3, 5] |
 | [2, 4, 8, 16, 32]  |
 | []                 |
 *--------------------*/

Notice again that the third row contains an empty array, because the array in the corresponding original row ([5, 10]) did not contain 2.

Scanning arrays

To check if an array contains a specific value, use the IN operator with UNNEST. To check if an array contains a value matching a condition, use the EXISTS operator with UNNEST.

Scanning for specific values

To scan an array for a specific value, use the IN operator with UNNEST.

Example

The following example returns true if the array contains the number 2.

SELECT 2 IN UNNEST([0, 1, 1, 2, 3, 5]) AS contains_value;

/*----------------*
 | contains_value |
 +----------------+
 | true           |
 *----------------*/

To return the rows of a table where the array column contains a specific value, filter the results of IN UNNEST using the WHERE clause.

Example

The following example returns the id value for the rows where the array column contains the value 2.

WITH Sequences AS
  (SELECT 1 AS id, [0, 1, 1, 2, 3, 5] AS some_numbers
   UNION ALL SELECT 2 AS id, [2, 4, 8, 16, 32] AS some_numbers
   UNION ALL SELECT 3 AS id, [5, 10] AS some_numbers)
SELECT id AS matching_rows
FROM Sequences
WHERE 2 IN UNNEST(Sequences.some_numbers)
ORDER BY matching_rows;

/*---------------*
 | matching_rows |
 +---------------+
 | 1             |
 | 2             |
 *---------------*/

Scanning for values that satisfy a condition

To scan an array for values that match a condition, use UNNEST to return a table of the elements in the array, use WHERE to filter the resulting table in a subquery, and use EXISTS to check if the filtered table contains any rows.

Example

The following example returns the id value for the rows where the array column contains values greater than 5.

WITH
  Sequences AS (
    SELECT 1 AS id, [0, 1, 1, 2, 3, 5] AS some_numbers
    UNION ALL
    SELECT 2 AS id, [2, 4, 8, 16, 32] AS some_numbers
    UNION ALL
    SELECT 3 AS id, [5, 10] AS some_numbers
  )
SELECT id AS matching_rows
FROM Sequences
WHERE EXISTS(SELECT * FROM UNNEST(some_numbers) AS x WHERE x > 5);

/*---------------*
 | matching_rows |
 +---------------+
 | 2             |
 | 3             |
 *---------------*/

Scanning for STRUCT field values that satisfy a condition

To search an array of STRUCTs for a field whose value matches a condition, use UNNEST to return a table with a column for each STRUCT field, then filter non-matching rows from the table using WHERE EXISTS.

Example

The following example returns the rows where the array column contains a STRUCT whose field b has a value greater than 3.

WITH
  Sequences AS (
    SELECT 1 AS id, [STRUCT(0 AS a, 1 AS b)] AS some_numbers
    UNION ALL
    SELECT 2 AS id, [STRUCT(2 AS a, 4 AS b)] AS some_numbers
    UNION ALL
    SELECT 3 AS id, [STRUCT(5 AS a, 3 AS b), STRUCT(7 AS a, 4 AS b)] AS some_numbers
  )
SELECT id AS matching_rows
FROM Sequences
WHERE EXISTS(SELECT 1 FROM UNNEST(some_numbers) WHERE b > 3);

/*---------------*
 | matching_rows |
 +---------------+
 | 2             |
 | 3             |
 *---------------*/

Arrays and aggregation

With GoogleSQL, you can aggregate values into an array using ARRAY_AGG().

WITH Fruits AS
  (SELECT "apple" AS fruit
   UNION ALL SELECT "pear" AS fruit
   UNION ALL SELECT "banana" AS fruit)
SELECT ARRAY_AGG(fruit) AS fruit_basket
FROM Fruits;

/*-----------------------*
 | fruit_basket          |
 +-----------------------+
 | [apple, pear, banana] |
 *-----------------------*/

The array returned by ARRAY_AGG() is in an arbitrary order, since the order in which the function concatenates values is not guaranteed. To order the array elements, use ORDER BY. For example:

WITH Fruits AS
  (SELECT "apple" AS fruit
   UNION ALL SELECT "pear" AS fruit
   UNION ALL SELECT "banana" AS fruit)
SELECT ARRAY_AGG(fruit ORDER BY fruit) AS fruit_basket
FROM Fruits;

/*-----------------------*
 | fruit_basket          |
 +-----------------------+
 | [apple, banana, pear] |
 *-----------------------*/

You can also apply aggregate functions such as SUM() to the elements in an array. For example, the following query returns the sum of array elements for each row of the Sequences table.

WITH Sequences AS
  (SELECT [0, 1, 1, 2, 3, 5] AS some_numbers
   UNION ALL SELECT [2, 4, 8, 16, 32] AS some_numbers
   UNION ALL SELECT [5, 10] AS some_numbers)
SELECT some_numbers,
  (SELECT SUM(x)
   FROM UNNEST(s.some_numbers) AS x) AS sums
FROM Sequences AS s;

/*--------------------+------*
 | some_numbers       | sums |
 +--------------------+------+
 | [0, 1, 1, 2, 3, 5] | 12   |
 | [2, 4, 8, 16, 32]  | 62   |
 | [5, 10]            | 15   |
 *--------------------+------*/

GoogleSQL also supports an aggregate function, ARRAY_CONCAT_AGG(), which concatenates the elements of an array column across rows.

WITH Aggregates AS
  (SELECT [1,2] AS numbers
   UNION ALL SELECT [3,4] AS numbers
   UNION ALL SELECT [5, 6] AS numbers)
SELECT ARRAY_CONCAT_AGG(numbers) AS count_to_six_agg
FROM Aggregates;

/*--------------------------------------------------*
 | count_to_six_agg                                 |
 +--------------------------------------------------+
 | [1, 2, 3, 4, 5, 6]                               |
 *--------------------------------------------------*/

Note: The array returned by ARRAY_CONCAT_AGG() is non-deterministic, since the order in which the function concatenates values is not guaranteed.

Converting arrays to strings

The ARRAY_TO_STRING() function allows you to convert an ARRAY<STRING> to a single STRING value or an ARRAY<BYTES> to a single BYTES value where the resulting value is the ordered concatenation of the array elements.

The second argument is the separator that the function will insert between inputs to produce the output; this second argument must be of the same type as the elements of the first argument.

Example:

WITH Words AS
  (SELECT ["Hello", "World"] AS greeting)
SELECT ARRAY_TO_STRING(greeting, " ") AS greetings
FROM Words;

/*-------------*
 | greetings   |
 +-------------+
 | Hello World |
 *-------------*/

The optional third argument takes the place of NULL values in the input array.

• If you omit this argument, then the function ignores NULL array elements.

• If you provide an empty string, the function inserts a separator for NULL array elements.

Example:

SELECT
  ARRAY_TO_STRING(arr, ".", "N") AS non_empty_string,
  ARRAY_TO_STRING(arr, ".", "") AS empty_string,
  ARRAY_TO_STRING(arr, ".") AS omitted
FROM (SELECT ["a", NULL, "b", NULL, "c", NULL] AS arr);

/*------------------+--------------+---------*
 | non_empty_string | empty_string | omitted |
 +------------------+--------------+---------+
 | a.N.b.N.c.N      | a..b..c.     | a.b.c   |
 *------------------+--------------+---------*/

Combining arrays

In some cases, you might want to combine multiple arrays into a single array. You can accomplish this using the ARRAY_CONCAT() function.

SELECT ARRAY_CONCAT([1, 2], [3, 4], [5, 6]) AS count_to_six;

/*--------------------------------------------------*
 | count_to_six                                     |
 +--------------------------------------------------+
 | [1, 2, 3, 4, 5, 6]                               |
 *--------------------------------------------------*/

Updating arrays

Consider the following table called arrays_table. The first column in the table is an array of integers and the second column contains two nested arrays of integers.

WITH arrays_table AS (
  SELECT
    [1, 2] AS regular_array,
    STRUCT([10, 20] AS first_array, [100, 200] AS second_array) AS nested_arrays
  UNION ALL SELECT
    [3, 4] AS regular_array,
    STRUCT([30, 40] AS first_array, [300, 400] AS second_array) AS nested_arrays
)
SELECT * FROM arrays_table;

/*---------------*---------------------------*----------------------------*
 | regular_array | nested_arrays.first_array | nested_arrays.second_array |
 +---------------+---------------------------+----------------------------+
 | [1, 2]        | [10, 20]                  | [100, 200]                 |
 | [3, 4]        | [30, 40]                  | [130, 400]                 |
 *---------------*---------------------------*----------------------------*/

You can update arrays in a table by using the UPDATE statement. The following example inserts the number 5 into the regular_array column, and inserts the elements from the first_array field of the nested_arrays column into the second_array field:

UPDATE
  arrays_table
SET
  regular_array = ARRAY_CONCAT(regular_array, [5]),
  nested_arrays.second_array = ARRAY_CONCAT(nested_arrays.second_array,
                                            nested_arrays.first_array)
WHERE TRUE;
SELECT * FROM arrays_table;

/*---------------*---------------------------*----------------------------*
 | regular_array | nested_arrays.first_array | nested_arrays.second_array |
 +---------------+---------------------------+----------------------------+
 | [1, 2, 5]     | [10, 20]                  | [100, 200, 10, 20]         |
 | [3, 4, 5]     | [30, 40]                  | [130, 400, 30, 40]         |
 *---------------*---------------------------*----------------------------*/

Zipping arrays

Given two arrays of equal size, you can merge them into a single array consisting of pairs of elements from input arrays, taken from their corresponding positions. This operation is sometimes called zipping.

You can zip arrays with UNNEST and WITH OFFSET. In this example, each value pair is stored as a STRUCT in an array.

WITH
  Combinations AS (
    SELECT
      ['a', 'b'] AS letters,
      [1, 2, 3] AS numbers
  )
SELECT
  ARRAY(
    SELECT AS STRUCT
      letters[SAFE_OFFSET(index)] AS letter,
      numbers[SAFE_OFFSET(index)] AS number
    FROM Combinations
    CROSS JOIN
      UNNEST(
        GENERATE_ARRAY(
          0,
          LEAST(ARRAY_LENGTH(letters), ARRAY_LENGTH(numbers)) - 1)) AS index
    ORDER BY index
  );

/*------------------------------*
 | pairs                        |
 +------------------------------+
 | [{ letter: "a", number: 1 }, |
 |  { letter: "b", number: 2 }] |
 *------------------------------*/

You can use input arrays of different lengths as long as the first array is equal to or less than the length of the second array. The zipped array will be the length of the shortest input array.

To get a zipped array that includes all the elements even when the input arrays are different lengths, change LEAST to GREATEST. Elements of either array that have no associated element in the other array will be paired with NULL.

WITH
  Combinations AS (
    SELECT
      ['a', 'b'] AS letters,
      [1, 2, 3] AS numbers
  )
SELECT
  ARRAY(
    SELECT AS STRUCT
      letters[SAFE_OFFSET(index)] AS letter,
      numbers[SAFE_OFFSET(index)] AS number
    FROM Combinations
    CROSS JOIN
      UNNEST(
        GENERATE_ARRAY(
          0,
          GREATEST(ARRAY_LENGTH(letters), ARRAY_LENGTH(numbers)) - 1)) AS index
    ORDER BY index
  );

/*-------------------------------*
 | pairs                         |
 +-------------------------------+
 | [{ letter: "a", number: 1 },  |
 |  { letter: "b", number: 2 },  |
 |  { letter: null, number: 3 }] |
 *-------------------------------*/

Building arrays of arrays

GoogleSQL does not support building arrays of arrays directly. Instead, you must create an array of structs, with each struct containing a field of type ARRAY. To illustrate this, consider the following Points table:

/*----------*
 | point    |
 +----------+
 | [1, 5]   |
 | [2, 8]   |
 | [3, 7]   |
 | [4, 1]   |
 | [5, 7]   |
 *----------*/

Now, let's say you wanted to create an array consisting of each point in the Points table. To accomplish this, wrap the array returned from each row in a STRUCT, as shown below.

WITH Points AS
  (SELECT [1, 5] AS point
   UNION ALL SELECT [2, 8] AS point
   UNION ALL SELECT [3, 7] AS point
   UNION ALL SELECT [4, 1] AS point
   UNION ALL SELECT [5, 7] AS point)
SELECT ARRAY(
  SELECT STRUCT(point)
  FROM Points)
  AS coordinates;

/*-------------------*
 | coordinates       |
 +-------------------+
 | [{point: [1,5]},  |
 |  {point: [2,8]},  |
 |  {point: [5,7]},  |
 |  {point: [3,7]},  |
 |  {point: [4,1]}]  |
 *-------------------*/