The UPDATE
statement updates rows in a table.
If you update a row that contains a column referenced by a foreign key constraint and has an ON UPDATE
action, all of the dependent rows will also be updated.
Required privileges
The user must have the SELECT
and UPDATE
privileges on the table.
Synopsis
Parameters
Parameter | Description |
---|---|
common_table_expr |
See Common Table Expressions. |
table_name |
The name of the table that contains the rows you want to update. |
AS table_alias_name |
An alias for the table name. When an alias is provided, it completely hides the actual table name. |
column_name |
The name of the column whose values you want to update. |
a_expr |
The new value you want to use, the aggregate function you want to perform, or the scalar expression you want to use. To fill columns with their default values, use DEFAULT VALUES in place of a_expr . To fill a specific column with its default value, leave the value out of the a_expr or use DEFAULT at the appropriate position. |
FROM table_ref |
Specify a table to reference, but not update, in UPDATE expressions, or in RETURNING and WHERE clauses. For more details, see Reference other tables in an update. |
select_stmt |
A selection query. Each value must match the data type of its column on the left side of = . |
WHERE a_expr |
a_expr must be a scalar expression that returns Boolean values using columns (e.g., <column> = <value> ). Update rows that return TRUE .Without a WHERE clause in your statement, UPDATE updates all rows in the table. |
sort_clause |
An ORDER BY clause. See Ordering Query Results and Ordering of rows in DML statements for more details. |
limit_clause |
A LIMIT clause. See Limit Query Results for more details. |
RETURNING target_list |
Return values based on rows updated, where target_list can be specific column names from the table, * for all columns, or computations using scalar expressions. To return nothing in the response, not even the number of rows updated, use RETURNING NOTHING . |
ONLY ... * |
Supported for compatibility with PostgreSQL table inheritance syntax. This clause is a no-op, as CockroachDB does not currently support table inheritance. |
Force index selection for updates
By using the explicit index annotation (also known as "index hinting"), you can override CockroachDB's index selection and use a specific index for updating rows of a named table.
Index selection can impact performance, but does not change the result of a query.
The syntax to force an update for a specific index is:
> UPDATE table@my_idx SET ...
This is equivalent to the longer expression:
> UPDATE table@{FORCE_INDEX=my_idx} SET ...
To view how the index hint modifies the query plan that CockroachDB follows for updating rows, use an EXPLAIN (OPT)
statement. To see all indexes available on a table, use SHOW INDEXES
.
For examples, see Update with index hints.
Reference other tables in an update
To reference values from a table other than the table being updated, add a FROM
clause that specifies one or more tables in the cluster. Values from tables specified in a FROM
clause can be used in UPDATE
expressions, and in RETURNING
and WHERE
clauses.
When executing an UPDATE
query with a FROM
clause, CockroachDB joins the target table (i.e., the table being updated) to the tables referenced in the FROM
clause. The output of this join should have the same number of rows as the rows being updated in the target table, as CockroachDB uses a single row from the join output to update a given row in the target table. If the join produces more rows than the rows being updated in the target table, there is no way to predict which row from the join output will be used to update a row in the target table.
For an example, see Update using values from a different table.
Bulk-update data
To update a large number of rows (i.e., tens of thousands of rows or more), we recommend iteratively updating subsets of the rows that you want to update, until all of the rows have been updated. You can write a script to do this, or you can write a loop into your application.
For guidance and an example, see Bulk-update Data.
Examples
Setup
To follow along, run cockroach demo
to start a temporary, in-memory cluster with the movr
sample dataset preloaded:
$ cockroach demo
Update a single column in a single row
> SELECT * FROM users LIMIT 10;
id | city | name | address | credit_card
+--------------------------------------+-----------+--------------------+--------------------------------+-------------+
c28f5c28-f5c2-4000-8000-000000000026 | amsterdam | Maria Weber | 14729 Karen Radial | 5844236997
c7ae147a-e147-4000-8000-000000000027 | amsterdam | Tina Miller | 97521 Mark Extensions | 8880478663
cccccccc-cccc-4000-8000-000000000028 | amsterdam | Taylor Cunningham | 89214 Jennifer Well | 5130593761
d1eb851e-b851-4800-8000-000000000029 | amsterdam | Kimberly Alexander | 48474 Alfred Hollow | 4059628542
19999999-9999-4a00-8000-000000000005 | boston | Nicole Mcmahon | 11540 Patton Extensions | 0303726947
1eb851eb-851e-4800-8000-000000000006 | boston | Brian Campbell | 92025 Yang Village | 9016427332
23d70a3d-70a3-4800-8000-000000000007 | boston | Carl Mcguire | 60124 Palmer Mews Apt. 49 | 4566257702
28f5c28f-5c28-4600-8000-000000000008 | boston | Jennifer Sanders | 19121 Padilla Brooks Apt. 12 | 1350968125
80000000-0000-4000-8000-000000000019 | chicago | Matthew Clay | 49220 Lisa Junctions | 9132291015
851eb851-eb85-4000-8000-00000000001a | chicago | Samantha Coffey | 6423 Jessica Underpass Apt. 87 | 9437219051
(10 rows)
> UPDATE users SET address = '201 E Randolph St' WHERE id = '851eb851-eb85-4000-8000-00000000001a';
> SELECT * FROM users LIMIT 10;
id | city | name | address | credit_card
+--------------------------------------+-----------+--------------------+------------------------------+-------------+
c28f5c28-f5c2-4000-8000-000000000026 | amsterdam | Maria Weber | 14729 Karen Radial | 5844236997
c7ae147a-e147-4000-8000-000000000027 | amsterdam | Tina Miller | 97521 Mark Extensions | 8880478663
cccccccc-cccc-4000-8000-000000000028 | amsterdam | Taylor Cunningham | 89214 Jennifer Well | 5130593761
d1eb851e-b851-4800-8000-000000000029 | amsterdam | Kimberly Alexander | 48474 Alfred Hollow | 4059628542
19999999-9999-4a00-8000-000000000005 | boston | Nicole Mcmahon | 11540 Patton Extensions | 0303726947
1eb851eb-851e-4800-8000-000000000006 | boston | Brian Campbell | 92025 Yang Village | 9016427332
23d70a3d-70a3-4800-8000-000000000007 | boston | Carl Mcguire | 60124 Palmer Mews Apt. 49 | 4566257702
28f5c28f-5c28-4600-8000-000000000008 | boston | Jennifer Sanders | 19121 Padilla Brooks Apt. 12 | 1350968125
80000000-0000-4000-8000-000000000019 | chicago | Matthew Clay | 49220 Lisa Junctions | 9132291015
851eb851-eb85-4000-8000-00000000001a | chicago | Samantha Coffey | 201 E Randolph St | 9437219051
(10 rows)
Update multiple columns in a single row
> UPDATE rides SET (end_address, revenue) = ('201 E Randolph St', 25.00) WHERE id = '851eb851-eb85-4000-8000-000000000104';
> SELECT * FROM rides WHERE rider_id = '851eb851-eb85-4000-8000-00000000001a';
id | city | vehicle_city | rider_id | vehicle_id | start_address | end_address | start_time | end_time | revenue
+--------------------------------------+---------+--------------+--------------------------------------+--------------------------------------+-------------------------------+-----------------------------+---------------------------+---------------------------+---------+
849ba5e3-53f7-4000-8000-000000000103 | chicago | chicago | 851eb851-eb85-4000-8000-00000000001a | 88888888-8888-4800-8000-000000000008 | 77630 Steven Road Suite 60 | 74140 Andrew Spur | 2018-12-30 03:04:05+00:00 | 2018-12-31 08:04:05+00:00 | 20.00
851eb851-eb85-4000-8000-000000000104 | chicago | chicago | 851eb851-eb85-4000-8000-00000000001a | 88888888-8888-4800-8000-000000000008 | 76707 Timothy Square | 201 E Randolph St | 2018-12-15 03:04:05+00:00 | 2018-12-17 07:04:05+00:00 | 25.00
86a7ef9d-b22d-4000-8000-000000000107 | chicago | chicago | 851eb851-eb85-4000-8000-00000000001a | 88888888-8888-4800-8000-000000000008 | 28532 Kevin Villages Suite 90 | 27493 Ortega Radial Apt. 60 | 2018-12-08 03:04:05+00:00 | 2018-12-09 03:04:05+00:00 | 36.00
92f1a9fb-e76c-4800-8000-00000000011f | chicago | chicago | 851eb851-eb85-4000-8000-00000000001a | 88888888-8888-4800-8000-000000000008 | 56955 Edward Walks | 53193 Jerry Village | 2019-01-01 03:04:05+00:00 | 2019-01-01 15:04:05+00:00 | 35.00
94fdf3b6-45a1-4800-8000-000000000123 | chicago | chicago | 851eb851-eb85-4000-8000-00000000001a | 88888888-8888-4800-8000-000000000008 | 63820 Robinson Fields | 89245 Eric Orchard | 2018-12-14 03:04:05+00:00 | 2018-12-16 10:04:05+00:00 | 80.00
(5 rows)
> UPDATE rides SET end_address = '10000 W OHare Ave', revenue = 60.00 WHERE id = '94fdf3b6-45a1-4800-8000-000000000123';
> SELECT * FROM rides WHERE rider_id = '851eb851-eb85-4000-8000-00000000001a';
id | city | vehicle_city | rider_id | vehicle_id | start_address | end_address | start_time | end_time | revenue
+--------------------------------------+---------+--------------+--------------------------------------+--------------------------------------+-------------------------------+-----------------------------+---------------------------+---------------------------+---------+
849ba5e3-53f7-4000-8000-000000000103 | chicago | chicago | 851eb851-eb85-4000-8000-00000000001a | 88888888-8888-4800-8000-000000000008 | 77630 Steven Road Suite 60 | 74140 Andrew Spur | 2018-12-30 03:04:05+00:00 | 2018-12-31 08:04:05+00:00 | 20.00
851eb851-eb85-4000-8000-000000000104 | chicago | chicago | 851eb851-eb85-4000-8000-00000000001a | 88888888-8888-4800-8000-000000000008 | 76707 Timothy Square | 201 E Randolph St | 2018-12-15 03:04:05+00:00 | 2018-12-17 07:04:05+00:00 | 25.00
86a7ef9d-b22d-4000-8000-000000000107 | chicago | chicago | 851eb851-eb85-4000-8000-00000000001a | 88888888-8888-4800-8000-000000000008 | 28532 Kevin Villages Suite 90 | 27493 Ortega Radial Apt. 60 | 2018-12-08 03:04:05+00:00 | 2018-12-09 03:04:05+00:00 | 36.00
92f1a9fb-e76c-4800-8000-00000000011f | chicago | chicago | 851eb851-eb85-4000-8000-00000000001a | 88888888-8888-4800-8000-000000000008 | 56955 Edward Walks | 53193 Jerry Village | 2019-01-01 03:04:05+00:00 | 2019-01-01 15:04:05+00:00 | 35.00
94fdf3b6-45a1-4800-8000-000000000123 | chicago | chicago | 851eb851-eb85-4000-8000-00000000001a | 88888888-8888-4800-8000-000000000008 | 63820 Robinson Fields | 10000 W OHare Ave | 2018-12-14 03:04:05+00:00 | 2018-12-16 10:04:05+00:00 | 60.00
(5 rows)
Update using SELECT
statement
> UPDATE rides SET (revenue, start_address) =
(SELECT revenue, end_address FROM rides WHERE id = '94fdf3b6-45a1-4800-8000-000000000123')
WHERE id = '851eb851-eb85-4000-8000-000000000104';
> SELECT * FROM rides WHERE rider_id = '851eb851-eb85-4000-8000-00000000001a';
id | city | vehicle_city | rider_id | vehicle_id | start_address | end_address | start_time | end_time | revenue
+--------------------------------------+---------+--------------+--------------------------------------+--------------------------------------+-------------------------------+-----------------------------+---------------------------+---------------------------+---------+
849ba5e3-53f7-4000-8000-000000000103 | chicago | chicago | 851eb851-eb85-4000-8000-00000000001a | 88888888-8888-4800-8000-000000000008 | 77630 Steven Road Suite 60 | 74140 Andrew Spur | 2018-12-30 03:04:05+00:00 | 2018-12-31 08:04:05+00:00 | 20.00
851eb851-eb85-4000-8000-000000000104 | chicago | chicago | 851eb851-eb85-4000-8000-00000000001a | 88888888-8888-4800-8000-000000000008 | 10000 W OHare Ave | 201 E Randolph St | 2018-12-15 03:04:05+00:00 | 2018-12-17 07:04:05+00:00 | 60.00
86a7ef9d-b22d-4000-8000-000000000107 | chicago | chicago | 851eb851-eb85-4000-8000-00000000001a | 88888888-8888-4800-8000-000000000008 | 28532 Kevin Villages Suite 90 | 27493 Ortega Radial Apt. 60 | 2018-12-08 03:04:05+00:00 | 2018-12-09 03:04:05+00:00 | 36.00
92f1a9fb-e76c-4800-8000-00000000011f | chicago | chicago | 851eb851-eb85-4000-8000-00000000001a | 88888888-8888-4800-8000-000000000008 | 56955 Edward Walks | 53193 Jerry Village | 2019-01-01 03:04:05+00:00 | 2019-01-01 15:04:05+00:00 | 35.00
94fdf3b6-45a1-4800-8000-000000000123 | chicago | chicago | 851eb851-eb85-4000-8000-00000000001a | 88888888-8888-4800-8000-000000000008 | 63820 Robinson Fields | 10000 W OHare Ave | 2018-12-14 03:04:05+00:00 | 2018-12-16 10:04:05+00:00 | 60.00
(5 rows)
Update with default values
> UPDATE users SET address = DEFAULT WHERE id = '19999999-9999-4a00-8000-000000000005';
> SELECT * FROM users LIMIT 5;
id | city | name | address | credit_card
+--------------------------------------+-----------+--------------------+-----------------------+-------------+
c28f5c28-f5c2-4000-8000-000000000026 | amsterdam | Maria Weber | 14729 Karen Radial | 5844236997
c7ae147a-e147-4000-8000-000000000027 | amsterdam | Tina Miller | 97521 Mark Extensions | 8880478663
cccccccc-cccc-4000-8000-000000000028 | amsterdam | Taylor Cunningham | 89214 Jennifer Well | 5130593761
d1eb851e-b851-4800-8000-000000000029 | amsterdam | Kimberly Alexander | 48474 Alfred Hollow | 4059628542
19999999-9999-4a00-8000-000000000005 | boston | Nicole Mcmahon | NULL | 0303726947
(5 rows)
Update using values from a different table
> UPDATE rides SET revenue = NULL FROM vehicles WHERE rides.rider_id=vehicles.owner_id AND rides.vehicle_id=vehicles.id;
> SELECT * FROM rides WHERE revenue IS NULL LIMIT 5;
id | city | vehicle_city | rider_id | vehicle_id | start_address | end_address | start_time | end_time | revenue
---------------------------------------+-----------+--------------+--------------------------------------+--------------------------------------+--------------------------------+-----------------------------+---------------------------+---------------------------+----------
ab020c49-ba5e-4800-8000-00000000014e | amsterdam | amsterdam | c28f5c28-f5c2-4000-8000-000000000026 | aaaaaaaa-aaaa-4800-8000-00000000000a | 1905 Christopher Locks Apt. 77 | 66037 Belinda Plaza Apt. 93 | 2018-12-13 03:04:05+00:00 | 2018-12-14 08:04:05+00:00 | NULL
ac083126-e978-4800-8000-000000000150 | amsterdam | amsterdam | c28f5c28-f5c2-4000-8000-000000000026 | aaaaaaaa-aaaa-4800-8000-00000000000a | 50217 Victoria Fields Apt. 44 | 56217 Wilson Spring | 2018-12-07 03:04:05+00:00 | 2018-12-07 10:04:05+00:00 | NULL
af9db22d-0e56-4800-8000-000000000157 | amsterdam | amsterdam | c28f5c28-f5c2-4000-8000-000000000026 | aaaaaaaa-aaaa-4800-8000-00000000000a | 20937 Gibson River | 50480 Steven Row | 2018-12-23 03:04:05+00:00 | 2018-12-25 11:04:05+00:00 | NULL
b22d0e56-0418-4000-8000-00000000015c | amsterdam | amsterdam | bd70a3d7-0a3d-4000-8000-000000000025 | bbbbbbbb-bbbb-4800-8000-00000000000b | 36054 Ward Crescent Suite 35 | 7745 John Run | 2018-12-09 03:04:05+00:00 | 2018-12-10 18:04:05+00:00 | NULL
b53f7ced-9168-4000-8000-000000000162 | amsterdam | amsterdam | bd70a3d7-0a3d-4000-8000-000000000025 | bbbbbbbb-bbbb-4800-8000-00000000000b | 86091 Mcdonald Motorway | 1652 Robert Ford | 2018-12-05 03:04:05+00:00 | 2018-12-05 06:04:05+00:00 | NULL
(5 rows)
Update all rows
If you do not use the WHERE
clause to specify the rows to be updated, the values for all rows will be updated.
sql_safe_updates
session variable is set to true
, the client will prevent the update. sql_safe_updates
is set to true
by default.
> UPDATE rides SET revenue = 7.00;
pq: rejected: UPDATE without WHERE clause (sql_safe_updates = true)
You can use a SET
statement to set session variables.
> SET sql_safe_updates = false;
> UPDATE rides SET revenue = 7.00;
> SELECT * FROM rides LIMIT 5;
id | city | vehicle_city | rider_id | vehicle_id | start_address | end_address | start_time | end_time | revenue
+--------------------------------------+-----------+--------------+--------------------------------------+--------------------------------------+--------------------------------+-----------------------------------+---------------------------+---------------------------+---------+
c0000000-0000-4000-8000-000000000177 | amsterdam | amsterdam | c28f5c28-f5c2-4000-8000-000000000026 | cccccccc-cccc-4000-8000-00000000000c | 65738 Williams Summit | 72424 Thomas Field Suite 82 | 2018-12-31 03:04:05+00:00 | 2019-01-01 03:04:05+00:00 | 7.00
c083126e-978d-4000-8000-000000000178 | amsterdam | amsterdam | cccccccc-cccc-4000-8000-000000000028 | cccccccc-cccc-4000-8000-00000000000c | 53613 Johnson Terrace | 12667 Monica Hollow | 2018-12-16 03:04:05+00:00 | 2018-12-17 15:04:05+00:00 | 7.00
c10624dd-2f1a-4000-8000-000000000179 | amsterdam | amsterdam | c7ae147a-e147-4000-8000-000000000027 | cccccccc-cccc-4000-8000-00000000000c | 61921 Brittany Orchard Apt. 85 | 81157 Stephanie Court Suite 96 | 2018-12-30 03:04:05+00:00 | 2019-01-01 07:04:05+00:00 | 7.00
c189374b-c6a7-4000-8000-00000000017a | amsterdam | amsterdam | cccccccc-cccc-4000-8000-000000000028 | cccccccc-cccc-4000-8000-00000000000c | 75456 Gray View | 69175 Christopher Shoals Suite 47 | 2018-12-23 03:04:05+00:00 | 2018-12-23 03:04:05+00:00 | 7.00
c20c49ba-5e35-4000-8000-00000000017b | amsterdam | amsterdam | cccccccc-cccc-4000-8000-000000000028 | cccccccc-cccc-4000-8000-00000000000c | 38892 Joseph Summit Suite 86 | 89582 Melissa Streets | 2018-12-27 03:04:05+00:00 | 2018-12-28 18:04:05+00:00 | 7.00
(5 rows)
Update and return values
In this example, the RETURNING
clause returns the id
value of the row updated. The language-specific versions assume that you have installed the relevant client drivers.
query()
method for statements that return results and an exec()
method for statements that do not (e.g., Go), it's likely necessary to use the query()
method for UPDATE
statements with RETURNING
.> UPDATE vehicles SET status = 'available' WHERE city = 'new york' RETURNING id;
id
+--------------------------------------+
00000000-0000-4000-8000-000000000000
11111111-1111-4100-8000-000000000001
(2 rows)
# Import the driver.
import psycopg2
# Connect to the "bank" database.
conn = psycopg2.connect(
database='movr',
user='root',
host='localhost',
port=26257
)
# Make each statement commit immediately.
conn.set_session(autocommit=True)
# Open a cursor to perform database operations.
cur = conn.cursor()
# Update a row in the "vehicles" table
# and return the "id" value.
cur.execute(
"UPDATE vehicles SET status = 'available' WHERE city = 'new york' RETURNING id;"
)
# Print out the returned value.
rows = cur.fetchall()
print('IDs:')
for row in rows:
print([str(cell) for cell in row])
# Close the database connection.
cur.close()
conn.close()
The printed value would look like:
IDs:
['00000000-0000-4000-8000-000000000000']
['11111111-1111-4100-8000-000000000001']
# Import the driver.
require 'pg'
# Connect to the "bank" database.
conn = PG.connect(
user: 'root',
dbname: 'movr',
host: 'localhost',
port: 26257
)
# Update a row in the "vehicles" table
# and return the "id" value.
conn.exec(
"UPDATE vehicles SET status = 'available' WHERE city = 'new york' RETURNING id;"
) do |res|
# Print out the returned value.
puts "IDs:"
res.each do |row|
puts row
end
end
# Close communication with the database.
conn.close()
The printed value would look like:
IDs:
{"id"=>"00000000-0000-4000-8000-000000000000"}
{"id"=>"11111111-1111-4100-8000-000000000001"}
package main
import (
"database/sql"
"fmt"
"log"
_ "github.com/lib/pq"
)
func main() {
//Connect to the "bank" database.
db, err := sql.Open(
"postgres",
"postgresql://root@localhost:26257/movr?sslmode=disable",
)
if err != nil {
log.Fatal("error connecting to the database: ", err)
}
// Update a row in the "vehicles" table
// and return the "id" value.
rows, err := db.Query(
"UPDATE vehicles SET status = 'available' WHERE city = 'new york' RETURNING id;",
)
if err != nil {
log.Fatal(err)
}
// Print out the returned value.
defer rows.Close()
fmt.Println("IDs:")
for rows.Next() {
var id string
if err := rows.Scan(&id); err != nil {
log.Fatal(err)
}
fmt.Printf("%s\n", id)
}
}
The printed value would look like:
IDs:
00000000-0000-4000-8000-000000000000
11111111-1111-4100-8000-000000000001
var async = require('async')
var pg = require('pg')
// Config to connect to the "movr" database.
var config = {
user: 'root',
host: 'localhost',
database: 'movr',
port: 26257
}
// Create pool
var pool = new pg.Pool(config)
pool.connect(function (err, client, done) {
// Close communication with the database and exit.
var finish = function () {
done()
process.exit()
}
if (err) {
console.error('could not connect to cockroachdb', err);
finish()
}
async.waterfall([function (next) {
client.query(
`UPDATE vehicles SET status = 'available' WHERE city = 'new york' RETURNING id;`,
next
)
}
],
function (err, results) {
if (err) {
console.error('error updating and selecting from users', err);
finish()
}
// Print out the returned value.
console.log('IDs:')
results.rows.forEach(function (row) {
console.log(row)
})
finish()
})
})
The printed value would like:
IDs:
{ id: '00000000-0000-4000-8000-000000000000' }
{ id: '11111111-1111-4100-8000-000000000001' }
Update with index hints
Suppose that you create a multi-column index on the users
table with the name
and city
columns.
> CREATE INDEX ON users (name, city);
Now suppose you want to update a couple rows in the table, based on their contents. You can use the EXPLAIN (OPT)
command to see how the cost-based optimizer decides to perform the UPDATE
statement:
> EXPLAIN (opt) UPDATE users SET name='Patricia Smith (there are two)' WHERE name='Patricia Smith';
text
------------------------------------------------------------------------------------
update users
└── project
├── index-join users
│ └── scan users@users_name_city_idx
│ └── constraint: /10/9/8: [/'Patricia Smith' - /'Patricia Smith']
└── projections
└── 'Patricia Smith (there are two)'
(7 rows)
The output of the EXPLAIN
statement shows that the optimizer scans the newly-created users_name_city_idx
index when performing the update. This makes sense, as you are performing an update based on the name
column.
Although users_name_city_idx
is likely the most efficient index for the table scan, you may want to assess the performance difference between scanning on users_name_city_idx
and scanning on the primary index. You can provide an index hint (i.e., force the index selection) to use the primary key of the users
table:
> EXPLAIN (opt) UPDATE users@users_pkey SET name='Patricia Smith (there are two)' WHERE name='Patricia Smith';
text
---------------------------------------------------
update users
└── project
├── select
│ ├── scan users
│ │ └── flags: force-index=primary
│ └── filters
│ └── name = 'Patricia Smith'
└── projections
└── 'Patricia Smith (there are two)'
(9 rows)
Limit the size of rows
To help you avoid failures arising from misbehaving applications that bloat the size of rows, you can specify the behavior when a row or individual column family larger than a specified size is written to the database. Use the cluster settings sql.guardrails.max_row_size_log
to discover large rows and sql.guardrails.max_row_size_err
to reject large rows.
When you write a row that exceeds sql.guardrails.max_row_size_log
:
INSERT
,UPSERT
,UPDATE
,CREATE TABLE AS
,CREATE INDEX
,ALTER TABLE
,ALTER INDEX
,IMPORT
, orRESTORE
statements will log aLargeRow
to theSQL_PERF
channel.SELECT
,DELETE
,TRUNCATE
, andDROP
are not affected.
When you write a row that exceeds sql.guardrails.max_row_size_err
:
INSERT
,UPSERT
, andUPDATE
statements will fail with a code54000 (program_limit_exceeded)
error.CREATE TABLE AS
,CREATE INDEX
,ALTER TABLE
,ALTER INDEX
,IMPORT
, andRESTORE
statements will log aLargeRowInternal
event to theSQL_INTERNAL_PERF
channel.SELECT
,DELETE
,TRUNCATE
, andDROP
are not affected.
You cannot update existing rows that violate the limit unless the update shrinks the size of the
row below the limit. You can select, delete, alter, back up, and restore such rows. We
recommend using the accompanying setting sql.guardrails.max_row_size_log
in conjunction with
SELECT pg_column_size()
queries to detect and fix any existing large rows before lowering
sql.guardrails.max_row_size_err
.