- 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
- Asynchronous materialized view
- Colocate Join
- Lateral Join
- Query Cache
- Index
- Computing the Number of Distinct Values
- Sorted streaming aggregate
- Administration
- Management
- Data recovery
- User Privilege and Authentication
- Performance Tuning
- Reference
- SQL Reference
- User Account Management
- Cluster Management
- ADD SQLBLACKLIST
- ADMIN CANCEL REPAIR TABLE
- ADMIN CHECK TABLET
- ADMIN REPAIR TABLE
- ADMIN SET CONFIG
- ADMIN SET REPLICA STATUS
- ADMIN SHOW CONFIG
- ADMIN SHOW REPLICA DISTRIBUTION
- ADMIN SHOW REPLICA STATUS
- ALTER RESOURCE GROUP
- ALTER SYSTEM
- CANCEL DECOMMISSION
- CREATE FILE
- CREATE RESOURCE GROUP
- DELETE SQLBLACKLIST
- DROP FILE
- DROP RESOURCE GROUP
- EXPLAIN
- INSTALL PLUGIN
- KILL
- SET
- SHOW BACKENDS
- SHOW BROKER
- SHOW COMPUTE NODES
- SHOW FILE
- SHOW FRONTENDS
- SHOW FULL COLUMNS
- SHOW INDEX
- SHOW PLUGINS
- SHOW PROC
- SHOW PROCESSLIST
- SHOW RESOURCE GROUP
- SHOW SQLBLACKLIST
- SHOW TABLE STATUS
- SHOW VARIABLES
- UNINSTALL PLUGIN
- DDL
- ALTER DATABASE
- ALTER MATERIALIZED VIEW
- ALTER TABLE
- ALTER VIEW
- ALTER RESOURCE
- ANALYZE TABLE
- BACKUP
- CANCEL ALTER TABLE
- CANCEL BACKUP
- CANCEL RESTORE
- CREATE ANALYZE
- CREATE DATABASE
- CREATE EXTERNAL CATALOG
- CREATE INDEX
- CREATE MATERIALIZED VIEW
- CREATE REPOSITORY
- CREATE RESOURCE
- CREATE TABLE AS SELECT
- CREATE TABLE LIKE
- CREATE TABLE
- CREATE VIEW
- CREATE FUNCTION
- DROP ANALYZE
- DROP STATS
- DROP CATALOG
- DROP DATABASE
- DROP INDEX
- DROP MATERIALIZED VIEW
- DROP REPOSITORY
- DROP RESOURCE
- DROP TABLE
- DROP VIEW
- DROP FUNCTION
- HLL
- KILL ANALYZE
- RECOVER
- REFRESH EXTERNAL TABLE
- RESTORE
- SET CATALOG
- SHOW ANALYZE JOB
- SHOW ANALYZE STATUS
- SHOW META
- SHOW RESOURCES
- SHOW FUNCTION
- TRUNCATE TABLE
- USE
- DML
- ALTER LOAD
- ALTER ROUTINE LOAD
- BROKER LOAD
- CANCEL LOAD
- CANCEL EXPORT
- CANCEL REFRESH MATERIALIZED VIEW
- CREATE ROUTINE LOAD
- DELETE
- EXPORT
- GROUP BY
- INSERT
- PAUSE ROUTINE LOAD
- 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
- dayofweek
- dayofyear
- days_add
- days_diff
- days_sub
- from_days
- from_unixtime
- hour
- hours_add
- hours_diff
- hours_sub
- microseconds_add
- microseconds_sub
- minute
- minutes_add
- minutes_diff
- minutes_sub
- month
- monthname
- months_add
- months_diff
- months_sub
- now
- quarter
- second
- seconds_add
- seconds_diff
- seconds_sub
- str_to_date
- str2date
- time_slice
- time_to_sec
- timediff
- timestamp
- timestampadd
- timestampdiff
- to_date
- to_days
- unix_timestamp
- utc_timestamp
- week
- week_iso
- weekofyear
- 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
- FAQ
- Benchmark
- Developers
- Contribute to StarRocks
- Code Style Guides
- Use the debuginfo file for debugging
- Development Environment
- Trace Tools
- Integration
UPDATE
Modifies rows in a Primary Key table. In versions earlier than version 3.0, the UPDATE statement only supports simple syntax, such as UPDATE <table_name> SET <column_name>=<expression> WHERE <where_condition>
. Starting from version 3.0, StarRocks enriches the syntax to support multi-table joins and common table expressions (CTEs). If you need to join the table to be updated with other tables in the database, you can reference these other tables in the FROM clause or CTE.
Usage notes
[ WITH <with_query> [, ...] ]
UPDATE <table_name>
SET <column_name> = <expression> [, ...]
[ FROM <from_item> [, ...] ]
WHERE <where_condition>
Parameters
with_query
One or more CTEs that can be referenced by name in an UPDATE statement. CTEs are temporary result sets that can improve the readability of complex statements.
table_name
The name of the table to be updated.
column_name
The name of the column to be updated. It cannot include the table name. For example, 'UPDATE t1 SET col = 1' is not valid.
expression
The expression that assigns new values to the column.
from_item
One or more other tables in the database. These tables can be joined with the table to be updated based on the condition specified in the WHERE clause. The values of the rows in the result set are used to update the values for the specified columns in the matched rows in the table to be updated. For example, if the FROM clause is FROM t1 WHERE t0.pk = t1.pk
, StarRocks converts the table expression in the FROM clause to t0 JOIN t1 ON t0.pk=t1.pk
when executing the UPDATE statement.
where_condition
The condition based on which you want to update rows. Only rows that meet the WHERE condition can be updated. This parameter is required, because it helps prevent you from accidentally updating the entire table. If you want to update the entire table, you can use 'WHERE true'.
Examples
For example, there are two tables employees
and accounts
in StarRocks. The table employees
records employee information, and the table accounts
records account information.
CREATE TABLE Employees (
EmployeeID INT,
Name VARCHAR(50),
Salary DECIMAL(10, 2)
)
PRIMARY KEY (EmployeeID)
DISTRIBUTED BY HASH (EmployeeID) BUCKETS 1
PROPERTIES ("replication_num" = "3");
INSERT INTO Employees VALUES
(1, 'John Doe', 5000),
(2, 'Jane Smith', 6000),
(3, 'Robert Johnson', 5500),
(4, 'Emily Williams', 4500),
(5, 'Michael Brown', 7000);
If you need to give a 10% raise to all employees, you can execute the following statement:
UPDATE Employees
SET Salary = Salary * 1.1 -- Increase the salary by 10%.
WHERE true;
If you need to give a 10% raise to employees with salaries lower than the average salary, you can execute the following statement:
UPDATE Employees
SET Salary = Salary * 1.1 -- Increase the salary by 10%.
WHERE Salary < (SELECT AVG(Salary) FROM Employees);
You can also use a CTE to rewrite the above statement to improve readability.
WITH AvgSalary AS (
SELECT AVG(Salary) AS AverageSalary
FROM Employees
)
UPDATE Employees
SET Salary = Salary * 1.1 -- Increase the salary by 10%.
FROM AvgSalary
WHERE Employees.Salary < AvgSalary.AverageSalary;
Multi-table UPDATE
Create a table Accounts
to record account information and insert three data rows into the table.
CREATE TABLE Accounts (
Accounts_id BIGINT NOT NULL,
Name VARCHAR(26) NOT NULL,
Sales_person VARCHAR(50) NOT NULL
)
PRIMARY KEY (Accounts_id)
DISTRIBUTED BY HASH (Accounts_id) BUCKETS 1
PROPERTIES ("replication_num" = "3");
INSERT INTO employees VALUES (1,100),(2,1000);
CREATE TABLE accounts
(
accounts_id BIGINT NOT NULL,
name VARCHAR(26) NOT NULL,
sales_person INT NOT NULL
)
PRIMARY KEY (accounts_id)
DISTRIBUTED BY HASH(accounts_id) BUCKETS 1
PROPERTIES ("replication_num" = "3");
INSERT INTO accounts VALUES (1,'Acme Corporation',2),(2,'Acme Corporation',3),(3,'Corporation',3);
If you need to increase the sales count of salespersons that manage Acme Corporation's account in the employees
table by 1, you can execute the following statement:
UPDATE employees
SET sales_count = sales_count + 1
FROM accounts
WHERE accounts.name = 'Acme Corporation'
AND employees.id = accounts.sales_person;
You can also use a CTE to rewrite the above statement to improve readability.
WITH acme_accounts as (
SELECT * from accounts
WHERE accounts.name = 'Acme Corporation'
)
UPDATE employees SET sales_count = sales_count + 1
FROM acme_accounts
WHERE employees.id = acme_accounts.sales_person;