- StarRocks
- Introduction to StarRocks
- Quick Start
- Deployment
- Deployment overview
- Prepare
- Deploy
- Deploy classic StarRocks
- Deploy and use shared-data StarRocks
- Manage
- Table Design
- Data Loading
- Concepts
- Overview of data loading
- Load data from a local file system or a streaming data source using HTTP PUT
- Load data from HDFS or cloud storage
- Continuously load data from Apache Kafka®
- Bulk load using Apache Sparkâ„¢
- Load data using INSERT
- Load data using Stream Load transaction interface
- Realtime synchronization from MySQL
- Continuously load data from Apache Flink®
- Change data through loading
- Transform data at loading
- Data Unloading
- Query Data Sources
- Query Acceleration
- Gather CBO statistics
- Synchronous materialized view
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- Colocate Join
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- Query Cache
- Index
- Computing the Number of Distinct Values
- Sorted streaming aggregate
- Administration
- Management
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- Reference
- SQL Reference
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- ADD SQLBLACKLIST
- ADMIN CANCEL REPAIR TABLE
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- ADMIN REPAIR TABLE
- ADMIN SET CONFIG
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- ADMIN SHOW CONFIG
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- CREATE REPOSITORY
- CREATE RESOURCE
- CREATE TABLE AS SELECT
- CREATE TABLE LIKE
- CREATE TABLE
- CREATE VIEW
- CREATE FUNCTION
- DROP ANALYZE
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- HLL
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- DELETE
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- GROUP BY
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- REFRESH MATERIALIZED VIEW
- RESUME ROUTINE LOAD
- SELECT
- SHOW ALTER TABLE
- SHOW ALTER MATERIALIZED VIEW
- SHOW BACKUP
- SHOW CATALOGS
- SHOW CREATE CATALOG
- SHOW CREATE MATERIALIZED VIEW
- SHOW CREATE TABLE
- SHOW CREATE VIEW
- SHOW DATA
- SHOW DATABASES
- SHOW DELETE
- SHOW DYNAMIC PARTITION TABLES
- SHOW EXPORT
- SHOW LOAD
- SHOW MATERIALIZED VIEWS
- SHOW PARTITIONS
- SHOW PROPERTY
- SHOW REPOSITORIES
- SHOW RESTORE
- SHOW ROUTINE LOAD
- SHOW ROUTINE LOAD TASK
- SHOW SNAPSHOT
- SHOW TABLES
- SHOW TABLET
- SHOW TRANSACTION
- SPARK LOAD
- STOP ROUTINE LOAD
- STREAM LOAD
- SUBMIT TASK
- UPDATE
- Auxiliary Commands
- Data Types
- Keywords
- AUTO_INCREMENT
- Function Reference
- Java UDFs
- Window functions
- Lambda expression
- Aggregate Functions
- array_agg
- avg
- any_value
- approx_count_distinct
- bitmap
- bitmap_agg
- count
- grouping
- grouping_id
- hll_empty
- hll_hash
- hll_raw_agg
- hll_union
- hll_union_agg
- max
- max_by
- min
- multi_distinct_sum
- multi_distinct_count
- percentile_approx
- percentile_cont
- percentile_disc
- retention
- stddev
- stddev_samp
- sum
- variance, variance_pop, var_pop
- var_samp
- window_funnel
- Array Functions
- array_agg
- array_append
- array_avg
- array_concat
- array_contains
- array_contains_all
- array_cum_sum
- array_difference
- array_distinct
- array_filter
- array_intersect
- array_join
- array_length
- array_map
- array_max
- array_min
- array_position
- array_remove
- array_slice
- array_sort
- array_sortby
- array_sum
- arrays_overlap
- array_to_bitmap
- cardinality
- element_at
- reverse
- unnest
- Bit Functions
- Bitmap Functions
- base64_to_bitmap
- bitmap_agg
- bitmap_and
- bitmap_andnot
- bitmap_contains
- bitmap_count
- bitmap_from_string
- bitmap_empty
- bitmap_has_any
- bitmap_hash
- bitmap_intersect
- bitmap_max
- bitmap_min
- bitmap_or
- bitmap_remove
- bitmap_to_array
- bitmap_to_base64
- bitmap_to_string
- bitmap_union
- bitmap_union_count
- bitmap_union_int
- bitmap_xor
- intersect_count
- sub_bitmap
- to_bitmap
- JSON Functions
- Overview of JSON functions and operators
- JSON operators
- JSON constructor functions
- JSON query and processing functions
- Map Functions
- Binary Functions
- Conditional Functions
- Cryptographic Functions
- Date Functions
- add_months
- adddate
- convert_tz
- current_date
- current_time
- current_timestamp
- date
- date_add
- date_format
- date_slice
- date_sub, subdate
- date_trunc
- datediff
- day
- dayname
- dayofmonth
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- dayofyear
- days_add
- days_diff
- days_sub
- from_days
- from_unixtime
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- hours_add
- hours_diff
- hours_sub
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- microseconds_sub
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- minutes_add
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- minutes_sub
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- monthname
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- months_sub
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- str2date
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- to_date
- to_days
- unix_timestamp
- utc_timestamp
- week
- week_iso
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- weeks_add
- weeks_diff
- weeks_sub
- year
- years_add
- years_diff
- years_sub
- Geographic Functions
- Math Functions
- String Functions
- append_trailing_char_if_absent
- ascii
- char
- char_length
- character_length
- concat
- concat_ws
- ends_with
- find_in_set
- group_concat
- hex
- hex_decode_binary
- hex_decode_string
- instr
- lcase
- left
- length
- locate
- lower
- lpad
- ltrim
- money_format
- null_or_empty
- parse_url
- repeat
- replace
- reverse
- right
- rpad
- rtrim
- space
- split
- split_part
- starts_with
- strleft
- strright
- substring
- trim
- ucase
- unhex
- upper
- Pattern Matching Functions
- Percentile Functions
- Scalar Functions
- Utility Functions
- cast function
- hash function
- System variables
- User-defined variables
- Error code
- System limits
- SQL Reference
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- Benchmark
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- Use the debuginfo file for debugging
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- Integration
array_agg
Description
Aggregates values (including NULL
) in a column into an array (multiple rows to one row), and optionally order the elements by specific columns. From v3.0, array_agg() supports using ORDER BY to sort elements.
Syntax
ARRAY_AGG(col [order by col0 [desc | asc] [nulls first | nulls last] ...])
Parameters
col
: the column whose values you want to aggregate. Supported data types are BOOLEAN, TINYINT, SMALLINT, INT, BIGINT, LARGEINT, FLOAT, DOUBLE, VARCHAR, CHAR, DATETIME, and DATE.col0
: the column which decides the order ofcol
. There may be more than one ORDER BY column.[desc | asc]
: specifies whether to sort the elements in ascending order (default) or descending order ofcol0
.[nulls first | nulls last]
: specifies whether null values are placed at the first or last place.
Return value
Returns a value of the ARRAY type, optionally sorted by col0
.
Usage notes
- The order of the elements in an array is random, which means it may be different from the order of the values in the column if no ORDER BY columns or no sorted by order by columns are specified.
- The data type of the elements in the returned array is the same as the data type of the values in the column.
- Returns
NULL
if the input is empty and without group-by columns.
Examples
Take the following data table as an example:
mysql> select * from t;
+------+------+------+
| a | name | pv |
+------+------+------+
| 11 | | 33 |
| 2 | NULL | 334 |
| 1 | fzh | 3 |
| 1 | fff | 4 |
| 1 | fff | 5 |
+------+------+------+
Example 1: Group the values in column a
and aggregate values in column pv
into an array by ordering a
by name
.
mysql> select a, array_agg(pv order by name nulls first) from t group by a;
+------+---------------------------------+
| a | array_agg(pv ORDER BY name ASC) |
+------+---------------------------------+
| 2 | [334] |
| 11 | [33] |
| 1 | [4,5,3] |
+------+---------------------------------+
-- Aggregate values with no order.
mysql> select a, array_agg(pv) from t group by a;
+------+---------------+
| a | array_agg(pv) |
+------+---------------+
| 11 | [33] |
| 2 | [334] |
| 1 | [3,4,5] |
+------+---------------+
3 rows in set (0.03 sec)
Example 2: Aggregate values in column pv
into an array with ordering by name
.
mysql> select array_agg(pv order by name desc nulls last) from t;
+----------------------------------+
| array_agg(pv ORDER BY name DESC) |
+----------------------------------+
| [3,4,5,33,334] |
+----------------------------------+
1 row in set (0.02 sec)
-- Aggregate values with no order.
mysql> select array_agg(pv) from t;
+----------------+
| array_agg(pv) |
+----------------+
| [3,4,5,33,334] |
+----------------+
1 row in set (0.03 sec)
Example 3: Aggregate values in column pv
using the WHERE clause. If no data in pv
meets the filter condition, a NULL
value is returned.
mysql> select array_agg(pv order by name desc nulls last) from t where a < 0;
+----------------------------------+
| array_agg(pv ORDER BY name DESC) |
+----------------------------------+
| NULL |
+----------------------------------+
1 row in set (0.02 sec)
-- Aggregate values with no order.
mysql> select array_agg(pv) from t where a < 0;
+---------------+
| array_agg(pv) |
+---------------+
| NULL |
+---------------+
1 row in set (0.03 sec)
Keywords
ARRAY_AGG, ARRAY