Working with Arrays in Standard SQL

In 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: arrays of arrays are not supported.

With BigQuery, 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().

Constructing arrays

Using array literals

You can build an array literal in BigQuery using brackets ([ and ]). Each element in an array is separated by a comma.

SELECT [1, 2, 3] as numbers;

SELECT ["apple", "pear", "orange"] as fruit;

SELECT [true, false, true] as booleans;

You can also create arrays from any expressions that have compatible types. For example:

SELECT [a, b, c]
FROM
  (SELECT 5 AS a,
          37 AS b,
          406 AS c);

SELECT [a, b, c]
FROM
  (SELECT CAST(5 AS INT64) AS a,
          CAST(37 AS FLOAT64) AS b,
          406 AS c);

Notice that the second example contains three expressions: one that returns an INT64, one that returns a FLOAT64, and one that declares a literal. This expression works because all three expressions share FLOAT64 as a supertype.

To declare a specific data type for an array, use angle brackets (< and >). For example:

SELECT ARRAY<FLOAT64>[1, 2, 3] as floats;

Arrays of most data types, such as INT64 or STRING, don't require that you declare them first.

SELECT [1, 2, 3] as numbers;

You can write an empty array of a specific type using ARRAY<type>[]. You can also write an untyped empty array using [], in which case BigQuery attempts to infer the array type from the surrounding context. If BigQuery cannot infer a type, the default type ARRAY<INT64> is used.

Using generated values

You can also construct an ARRAY with generated values.

Generating arrays of integers

GENERATE_ARRAY generates an array of values from a starting and ending value and a step value. For example, the following query generates an array that contains all of the odd integers from 11 to 33, inclusive:

SELECT GENERATE_ARRAY(11, 33, 2) AS odds;

+--------------------------------------------------+
| odds                                             |
+--------------------------------------------------+
| [11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33] |
+--------------------------------------------------+

You can also generate an array of values in descending order by giving a negative step value:

SELECT GENERATE_ARRAY(21, 14, -1) AS countdown;

+----------------------------------+
| countdown                        |
+----------------------------------+
| [21, 20, 19, 18, 17, 16, 15, 14] |
+----------------------------------+

Generating arrays of dates

GENERATE_DATE_ARRAY generates an array of DATEs from a starting and ending DATE and a step INTERVAL.

You can generate a set of DATE values using GENERATE_DATE_ARRAY. For example, this query returns the current DATE and the following DATEs at 1 WEEK intervals up to and including a later DATE:

SELECT
  GENERATE_DATE_ARRAY('2017-11-21', '2017-12-31', INTERVAL 1 WEEK)
    AS date_array;
+--------------------------------------------------------------------------+
| date_array                                                               |
+--------------------------------------------------------------------------+
| [2017-11-21, 2017-11-28, 2017-12-05, 2017-12-12, 2017-12-19, 2017-12-26] |
+--------------------------------------------------------------------------+

Accessing Array Elements

Consider the following table, sequences:

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

This table contains the column some_numbers of the ARRAY data type. To access elements from the arrays in this column, you must specify which type of indexing you want to use: either OFFSET, for zero-based indexes, or ORDINAL, for one-based indexes.

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,
       some_numbers[OFFSET(1)] AS offset_1,
       some_numbers[ORDINAL(1)] AS ordinal_1
FROM sequences;

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

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      |
+--------------------+--------+

Flattening arrays

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 CROSS JOIN to join the table containing the ARRAY column to the UNNEST output of that ARRAY column.

This is a correlated cross join: the UNNEST operator references the column of ARRAYs 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.

Example

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 |
+------+-------------------+

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 splits),
     STRUCT("Makhloufi" as name, [24.5, 25.4, 26.6, 26.1] as splits),
     STRUCT("Murphy" as name, [23.9, 26.0, 27.0, 26.0] as splits),
     STRUCT("Bosse" as name, [23.6, 26.2, 26.5, 27.1] as splits),
     STRUCT("Rotich" as name, [24.7, 25.6, 26.9, 26.4] as splits),
     STRUCT("Lewandowski" as name, [25.0, 25.7, 26.3, 27.2] as splits),
     STRUCT("Kipketer" as name, [23.2, 26.1, 27.3, 29.4] as splits),
     STRUCT("Berian" as name, [23.7, 26.1, 27.0, 29.3] as splits)]
       AS participants)
SELECT
  race,
  participant
FROM races 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.

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

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

Note that 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 splits),
    STRUCT("Makhloufi" as name, [24.5, 25.4, 26.6, 26.1] as splits),
    STRUCT("Murphy" as name, [23.9, 26.0, 27.0, 26.0] as splits),
    STRUCT("Bosse" as name, [23.6, 26.2, 26.5, 27.1] as splits),
    STRUCT("Rotich" as name, [24.7, 25.6, 26.9, 26.4] as splits),
    STRUCT("Lewandowski" as name, [25.0, 25.7, 26.3, 27.2] as splits),
    STRUCT("Kipketer" as name, [23.2, 26.1, 27.3, 29.4] as splits),
    STRUCT("Berian" as name, [23.7, 26.1, 27.0, 29.3] as splits),
    STRUCT("Nathan" as name, ARRAY<FLOAT64>[] as splits),
    STRUCT("David" as name, NULL as splits)]
    AS participants)
SELECT
  name, sum(duration) AS finish_time
FROM races, races.participants LEFT JOIN participants.splits 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              |
+-------------+--------------------+

Creating Arrays From Subqueries

A common task when working with arrays is turning a subquery result into an array. In BigQuery, 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 recombines 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 function 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 BigQuery, 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) x) AS sums
FROM sequences s;

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

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

WITH aggregate_example 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 aggregate_example;

+--------------------------------------------------+
| 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 greetings AS
  (SELECT ["Hello", "World"] AS greeting)
SELECT ARRAY_TO_STRING(greeting, " ") AS greetings
FROM greetings;


+-------------+
| 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]                               |
+--------------------------------------------------+

Building arrays of arrays

BigQuery 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                                        |
+----------------------------------------------------+
| [{[1, 5]}, {[2, 8]}, {[3, 7]}, {[4, 1]}, {[5, 7]}] |
+----------------------------------------------------+

Constructing arrays

Using array literals

Using generated values

Generating arrays of integers

Generating arrays of dates

Accessing Array Elements

Finding Lengths

Flattening arrays

Querying Nested Arrays

Querying STRUCT elements in an ARRAY

Querying ARRAY-type fields in a STRUCT

Creating Arrays From Subqueries

Filtering Arrays

Scanning Arrays

Scanning for specific values

Scanning for values that satisfy a condition

Scanning for STRUCT field values that satisfy a condition

Arrays and Aggregation

Converting Arrays to Strings

Combining Arrays

Building arrays of arrays

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