New limitations in v24.1
This section describes newly identified limitations in CockroachDB v24.1.
PL/pgSQL
- It is not possible to use a variable as a target more than once in the same
INTO
clause. For example,SELECT 1, 2 INTO x, x;
. #121605 - PLpgSQL variable declarations cannot inherit the type of a table row or column using
%TYPE
or%ROWTYPE
syntax. #114676
UDFs and stored procedures
- Routines cannot be invoked with named arguments, e.g.,
SELECT foo(a => 1, b => 2);
orSELECT foo(b := 1, a := 2);
. #122264 - Routines cannot be created if they reference temporary tables. #121375
- Routines cannot be created with unnamed
INOUT
parameters. For example,CREATE PROCEDURE p(INOUT INT) AS $$ BEGIN NULL; END; $$ LANGUAGE PLpgSQL;
. #121251 - Routines cannot be created if they return fewer columns than declared. For example,
CREATE FUNCTION f(OUT sum INT, INOUT a INT, INOUT b INT) LANGUAGE SQL AS $$ SELECT (a + b, b); $$;
. #121247 - A
RECORD
-returning UDF cannot be created without aRETURN
statement in the root block, which would restrict the wildcard type to a concrete one. #122945
Physical cluster replication cut back to primary cluster
When you cut back to a cluster that was previously the primary cluster, you should cut over to the LATEST
timestamp. Using a historical timestamp may lead to the cutback failing.
#117984
Limitations from v23.2 and earlier
This section describes limitations from previous CockroachDB versions that still impact v24.1.
SQL statements
Syntax and behavior differences from PostgreSQL
CockroachDB supports the PostgreSQL wire protocol and the majority of its syntax. For a list of known differences in syntax and behavior between CockroachDB and PostgreSQL, see Features that differ from PostgreSQL.
AS OF SYSTEM TIME
does not support placeholders
CockroachDB does not support placeholders in AS OF SYSTEM TIME
. The time value must be embedded in the SQL string. #30955
COPY
syntax not supported by CockroachDB
CockroachDB does not yet support the following COPY
syntax:
IMPORT INTO
limitations
IMPORT INTO
has the following limitations:
- While importing into an existing table, the table is taken offline.
- After importing into an existing table, constraints will be un-validated and need to be re-validated.
- Imported rows must not conflict with existing rows in the table or any unique secondary indexes.
IMPORT INTO
works for only a single existing table.IMPORT INTO
can sometimes fail with a "context canceled" error, or can restart itself many times without ever finishing. If this is happening, it is likely due to a high amount of disk contention. This can be mitigated by setting thekv.bulk_io_write.max_rate
cluster setting to a value below your max disk write speed. For example, to set it to 10MB/s, execute:SET CLUSTER SETTING kv.bulk_io_write.max_rate = '10MB';
ALTER VIEW
limitations
ALTER VIEW
does not currently support:
- Changing the
SELECT
statement executed by a view. Instead, you must drop the existing view and create a new view. - Renaming a view that other views depend on. This feature may be added in the future. #10083
Row-Level TTL limitations
- Any queries you run against tables with Row-Level TTL enabled (or against tables that have foreign keys that reference TTL-enabled tables) do not filter out expired rows from the result set (this includes
UPDATE
s andDELETE
s). This feature may be added in a future release. For now, follow the instructions in Filter out expired rows from a selection query. - Enabling Row-Level TTL on a table with multiple secondary indexes can have negative performance impacts on a cluster, including increased latency and contention. This is particularly true for large tables with terabytes of data and billions of rows that are split up into multiple ranges across separate nodes.
- Increased latency may occur because secondary indexes aren't necessarily stored on the same underlying ranges as a table's primary indexes. Further, the secondary indexes' ranges may have leaseholders located on different nodes than the primary index.
- Increased contention may occur because intents must be written as part of performing the deletions.
- Finally, secondary indexes can also have a negative impact on the overall performance of TTL jobs. According to internal testing, the TTL job processing rate is worse on tables with secondary indexes. If you encounter this situation, decreasing the
ttl_delete_batch_size
storage parameter may help by decreasing the number of ranges that need to be accessed by the job.
CAST
expressions containing a subquery with an ENUM
target are not supported
Casting subqueries to ENUMs in views and UDFs is not supported. #108184
Statements containing multiple modification subqueries of the same table are disallowed
Statements containing multiple modification subqueries mutating the same row could cause corruption. These statements are disallowed by default, but you can enable multiple modification subqueries with one the following:
- Set the
sql.multiple_modifications_of_table.enabled
cluster setting totrue
. - Use the
enable_multiple_modifications_of_table
session variable.
If multiple mutations inside the same statement affect different tables with FOREIGN KEY
relations and ON CASCADE
clauses between them, the results will be different from what is expected in PostgreSQL. #70731
Using default_int_size
session variable in batch of statements
When setting the default_int_size
session variable in a batch of statements such as SET default_int_size='int4'; SELECT 1::IN
, the default_int_size
variable will not take effect until the next statement. Statement parsing is asynchronous with statement execution.
As a workaround, set default_int_size
via your database driver, or ensure that SET default_int_size
is in its own statement. #32846
Overload resolution for collated strings
Many string operations are not properly overloaded for collated strings, for example:
> SELECT 'string1' || 'string2';
?column?
------------------
string1string2
(1 row)
> SELECT ('string1' collate en) || ('string2' collate en);
pq: unsupported binary operator: <collatedstring{en}> || <collatedstring{en}>
Current sequence value not checked when updating min/max value
Altering the minimum or maximum value of a series does not check the current value of a series. This means that it is possible to silently set the maximum to a value less than, or a minimum value greater than, the current value. #23719
null_ordered_last
does not produce correct results with tuples
By default, CockroachDB orders NULL
s before all other values. For compatibility with PostgreSQL, the null_ordered_last
session variable was added, which changes the default to order NULL
values after all other values. This works in most cases, due to some transformations CockroachDB makes in the optimizer to add extra ordering columns. However, it does not work when the ordering column is a tuple. #93558
Functions and procedures
PL/pgSQL support
- PL/pgSQL arguments cannot be referenced with ordinals (e.g.,
$1
,$2
). #114701 - The following statements are not supported:
- PL/pgSQL exception blocks cannot catch transaction retry errors. #111446
RAISE
statements cannot be annotated with names of schema objects related to the error (i.e., usingCOLUMN
,CONSTRAINT
,DATATYPE
,TABLE
, orSCHEMA
). #106237RAISE
statements message the client directly, and do not produce log output. #117750ASSERT
debugging checks are not supported. #117744RECORD
parameters and variables are not supported in user-defined functions. #105713- Variable shadowing (e.g., declaring a variable with the same name in an inner block) is not supported in PL/pgSQL. #117508
- Syntax for accessing members of composite types without parentheses is not supported. #114687
NOT NULL
variable declarations are not supported. #105243- Cursors opened in PL/pgSQL execute their queries on opening, affecting performance and resource usage. #111479
- Cursors in PL/pgSQL cannot be declared with arguments. #117746
OPEN FOR EXECUTE
is not supported for opening cursors. #117744
UDF and stored procedure support
DDL statements (e.g.,
CREATE TABLE
,CREATE INDEX
) are not allowed within UDFs or stored procedures. #110080User-defined functions are not currently supported in:
User-defined functions cannot call themselves recursively. #93049
Common table expressions (CTE), recursive or non-recursive, are not supported in user-defined functions (UDF). That is, you cannot use a
WITH
clause in the body of a UDF. #92961The
setval
function cannot be resolved when used inside UDF bodies. #110860
Transactions
Read Committed features and performance
Read Committed isolation has the following limitations:
- Schema changes (e.g.,
CREATE TABLE
,CREATE SCHEMA
,CREATE INDEX
) cannot be performed within explicitREAD COMMITTED
transactions, and will cause transactions to abort. As a workaround, set the transaction's isolation level toSERIALIZABLE
. #114778 READ COMMITTED
transactions performingINSERT
,UPDATE
, orUPSERT
cannot accessREGIONAL BY ROW
tables in whichUNIQUE
andPRIMARY KEY
constraints exist, the region is not included in the constraint, and the region cannot be computed from the constraint columns.- Multi-column-family checks during updates are not supported under
READ COMMITTED
isolation. #112488 - Because locks acquired by foreign key checks,
SELECT FOR UPDATE
, andSELECT FOR SHARE
are fully replicated underREAD COMMITTED
isolation, some queries experience a delay for Raft replication. - Foreign key checks are not performed in parallel under
READ COMMITTED
isolation. SELECT FOR UPDATE
andSELECT FOR SHARE
statements are less optimized underREAD COMMITTED
isolation than underSERIALIZABLE
isolation. UnderREAD COMMITTED
isolation,SELECT FOR UPDATE
andSELECT FOR SHARE
usually perform an extra lookup join for every locked table when compared to the same queries underSERIALIZABLE
. In addition, some optimization steps (such as de-correlation of correlated subqueries) are not currently performed on these queries.- Regardless of isolation level,
SELECT FOR UPDATE
andSELECT FOR SHARE
statements in CockroachDB do not prevent insertion of new rows matching the search condition (i.e., phantom reads). This matches PostgreSQL behavior at all isolation levels. #120673
Follower reads
Exact staleness reads and long-running writes
Long-running write transactions will create write intents with a timestamp near when the transaction began. When an exact staleness follower read encounters a write intent, it will often end up in a "transaction wait queue", waiting for the operation to complete; however, this runs counter to the benefit exact staleness reads provide.
To counteract this, you can issue all follower reads in explicit transactions set with HIGH
priority:
BEGIN PRIORITY HIGH AS OF SYSTEM TIME follower_read_timestamp();
SELECT ...
SELECT ...
COMMIT;
Exact staleness read timestamps must be far enough in the past
If an exact staleness read is not using an AS OF SYSTEM TIME
value far enough in the past, CockroachDB cannot perform a follower read. Instead, the read must access the leaseholder replica. This adds network latency if the leaseholder is not the closest replica to the gateway node. Most users will use the follower_read_timestamp()
function to get a timestamp far enough in the past that there is a high probability of getting a follower read.
Bounded staleness read limitations
Bounded staleness reads have the following limitations:
- They must be used in a single-statement (aka implicit) transaction.
- They must read from a single row.
- They must not require an index join. In other words, the index used by the read query must be either a primary index, or some other index that covers the entire query by
STORING
all columns.
For example, let's look at a read query that cannot be served as a bounded staleness read. We will use a demo cluster, which automatically loads the MovR dataset.
cockroach demo
SELECT code FROM promo_codes AS OF SYSTEM TIME with_max_staleness('10s') LIMIT 1;
ERROR: unimplemented: cannot use bounded staleness for queries that may touch more than one row or require an index join
SQLSTATE: 0A000
HINT: You have attempted to use a feature that is not yet implemented.
See: https://go.crdb.dev/issue-v/67562/v23.2
As noted by the error message, this query cannot be served as a bounded staleness read because in this case it would touch more than one row. Even though we used a LIMIT 1
clause, the query would still have to touch more than one row in order to filter out the additional results.
We can verify that more than one row would be touched by issuing EXPLAIN
on the same query, but without the AS OF SYSTEM TIME
clause:
EXPLAIN SELECT code FROM promo_codes LIMIT 5;
info
-------------------------------------------------------------------------------
distribution: full
vectorized: true
• scan
estimated row count: 1 (0.10% of the table; stats collected 1 minute ago)
table: promo_codes@primary
spans: LIMITED SCAN
limit: 1
(8 rows)
The output verifies that this query performs a scan of the primary index on the promo_codes
table, which is why it cannot be used for a bounded staleness read.
For an example showing how to successfully perform a bounded staleness read, see Run queries that use bounded staleness follower reads.
SELECT FOR UPDATE
locks are dropped on lease transfers and range splits/merges
By default under SERIALIZABLE
isolation, locks acquired using SELECT ... FOR UPDATE
and SELECT ... FOR SHARE
are implemented as fast, in-memory unreplicated locks. If a lease transfer or range split/merge occurs on a range held by an unreplicated lock, the lock is dropped. The following behaviors can occur:
- The desired ordering of concurrent accesses to one or more rows of a table expressed by your use of
SELECT ... FOR UPDATE
may not be preserved (that is, a transaction B against some table T that was supposed to wait behind another transaction A operating on T may not wait for transaction A). - The transaction that acquired the (now dropped) unreplicated lock may fail to commit, leading to transaction retry errors with code
40001
and therestart transaction
error message.
When running under SERIALIZABLE
isolation, SELECT ... FOR UPDATE
and SELECT ... FOR SHARE
locks should be thought of as best-effort, and should not be relied upon for correctness. Note that serialization is preserved despite this limitation. This limitation is fixed when the enable_durable_locking_for_serializable
session setting is set to true
.
This limitation does not apply to READ COMMITTED
transactions.
SET
does not ROLLBACK
in a transaction
SET
does not properly apply ROLLBACK
within a transaction. For example, in the following transaction, showing the TIME ZONE
variable does not return 2
as expected after the rollback:
SET TIME ZONE +2;
BEGIN;
SET TIME ZONE +3;
ROLLBACK;
SHOW TIME ZONE;
timezone
------------
3
ROLLBACK TO SAVEPOINT
in high-priority transactions containing DDL
1
Transactions with priority HIGH
that contain DDL and ROLLBACK TO SAVEPOINT
are not supported, as they could result in a deadlock. For example:
> BEGIN PRIORITY HIGH; SAVEPOINT s; CREATE TABLE t(x INT); ROLLBACK TO SAVEPOINT s;
ERROR: unimplemented: cannot use ROLLBACK TO SAVEPOINT in a HIGH PRIORITY transaction containing DDL
SQLSTATE: 0A000
HINT: You have attempted to use a feature that is not yet implemented.
See: https://github.com/cockroachdb/cockroach/issues/46414
CANCEL JOB
limitations
To avoid transaction states that cannot properly roll back, the following statements cannot be cancelled with
CANCEL JOB
:DROP
statements (e.g.,DROP TABLE
).ALTER ... RENAME
statements (e.g.,ALTER TABLE ... RENAME TO
).CREATE TABLE ... AS
statements.ALTER TYPE
statements, except for those that drop values.
When an Enterprise
RESTORE
is canceled, partially restored data is properly cleaned up. This can have a minor, temporary impact on cluster performance.
SQL cursor support
CockroachDB implements SQL cursor support with the following limitations:
DECLARE
only supports forward cursors. Reverse cursors created withDECLARE SCROLL
are not supported. #77102FETCH
supports forward, relative, and absolute variants, but only for forward cursors. #77102BINARY CURSOR
, which returns data in the Postgres binary format, is not supported. #77099WITH HOLD
, which allows keeping a cursor open for longer than a transaction by writing its results into a buffer, is accepted as valid syntax within a single transaction but is not supported. It acts as a no-op and does not actually perform the function ofWITH HOLD
, which is to make the cursor live outside its parent transaction. Instead, if you are usingWITH HOLD
, you will be forced to close that cursor within the transaction it was created in. #77101This syntax is accepted (but does not have any effect):
BEGIN; DECLARE test_cur CURSOR WITH HOLD FOR SELECT * FROM foo ORDER BY bar; CLOSE test_cur; COMMIT;
This syntax is not accepted, and will result in an error:
BEGIN; DECLARE test_cur CURSOR WITH HOLD FOR SELECT * FROM foo ORDER BY bar; COMMIT; -- This will fail with an error because CLOSE test_cur was not called inside the transaction.
Scrollable cursor (also known as reverse
FETCH
) is not supported. #77102SELECT ... FOR UPDATE
with a cursor is not supported. #77103Respect for
SAVEPOINT
s is not supported. Cursor definitions do not disappear properly if rolled back to aSAVEPOINT
from before they were created. #77104
Materialized views inside transactions
CockroachDB cannot refresh materialized views inside explicit transactions. Trying to refresh a materialized view inside an explicit transaction will result in an error.
Start
cockroach demo
with the samplebank
data set:cockroach demo bank
Create the materialized view described in Usage.
Start a new multi-statement transaction with
BEGIN TRANSACTION
:BEGIN TRANSACTION;
Inside the open transaction, attempt to refresh the view. This will result in an error.
REFRESH MATERIALIZED VIEW overdrawn_accounts;
ERROR: cannot refresh view in an explicit transaction SQLSTATE: 25000
Schemas and indexes
Online schema change limitations
Schema changes within transactions
Most schema changes should not be performed within an explicit transaction with multiple statements, as they do not have the same atomicity guarantees as other SQL statements. Execute schema changes either as single statements (as an implicit transaction), or in an explicit transaction consisting of the single schema change statement. There are some exceptions to this, detailed below.
Schema changes keep your data consistent at all times, but they do not run inside [transactions][txns] in the general case. Making schema changes transactional would mean requiring a given schema change to propagate across all the nodes of a cluster. This would block all user-initiated transactions being run by your application, since the schema change would have to commit before any other transactions could make progress. This would prevent the cluster from servicing reads and writes during the schema change, requiring application downtime.
New in v24.1: Some tools and applications may be able to workaround CockroachDB's lack of transactional schema changes by enabling a setting that automatically commits before running schema changes inside transactions.
Some schema change operations can be run within explicit, multiple statement transactions. CREATE TABLE
and CREATE INDEX
statements can be run within the same transaction with the same atomicity guarantees as other SQL statements. There are no performance or rollback issues when using these statements within a multiple statement transaction.
Within a single transaction:
- You can run schema changes inside the same transaction as a
CREATE TABLE
statement. For more information, see Run schema changes inside a transaction withCREATE TABLE
. However, aCREATE TABLE
statement containingFOREIGN KEY
clauses cannot be followed by statements that reference the new table. - Schema change DDL statements inside a multi-statement transaction can fail while other statements succeed.
DROP COLUMN
can result in data loss if one of the other schema changes in the transaction fails or is canceled. To work around this, move theDROP COLUMN
statement to its own explicit transaction or run it in a single statement outside the existing transaction.
If a schema change within a transaction fails, manual intervention may be needed to determine which statement has failed. After determining which schema change(s) failed, you can then retry the schema change.
Schema change DDL statements inside a multi-statement transaction can fail while other statements succeed
Most schema change DDL statements that run inside a multi-statement transaction with non-DDL statements can fail at COMMIT
time, even if other statements in the transaction succeed. This leaves such transactions in a "partially committed, partially aborted" state that may require manual intervention to determine whether the DDL statements succeeded.
Some DDL statements do not have this limitation. CREATE TABLE
and CREATE INDEX
statements have the same atomicity guarantees as other statements within a transaction.
If such a failure occurs, CockroachDB will emit a CockroachDB-specific error code, XXA00
, and the following error message:
transaction committed but schema change aborted with error: <description of error>
HINT: Some of the non-DDL statements may have committed successfully, but some of the DDL statement(s) failed.
Manual inspection may be required to determine the actual state of the database.
If you must execute schema change DDL statements inside a multi-statement transaction, we strongly recommend checking for this error code and handling it appropriately every time you execute such transactions.
This error will occur in various scenarios, including but not limited to:
- Creating a unique index fails because values aren't unique.
- The evaluation of a computed value fails.
- Adding a constraint (or a column with a constraint) fails because the constraint is violated for the default/computed values in the column.
To see an example of this error, start by creating the following table.
CREATE TABLE T(x INT);
INSERT INTO T(x) VALUES (1), (2), (3);
Then, enter the following multi-statement transaction, which will trigger the error.
BEGIN;
ALTER TABLE t ADD CONSTRAINT unique_x UNIQUE(x);
INSERT INTO T(x) VALUES (3);
COMMIT;
pq: transaction committed but schema change aborted with error: (23505): duplicate key value (x)=(3) violates unique constraint "unique_x"
HINT: Some of the non-DDL statements may have committed successfully, but some of the DDL statement(s) failed.
Manual inspection may be required to determine the actual state of the database.
In this example, the INSERT
statement committed, but the ALTER TABLE
statement adding a UNIQUE
constraint failed. We can verify this by looking at the data in table t
and seeing that the additional non-unique value 3
was successfully inserted.
SELECT * FROM t;
x
+---+
1
2
3
3
(4 rows)
No online schema changes if primary key change in progress
You cannot start an online schema change on a table if a primary key change is currently in progress on the same table.
No online schema changes between executions of prepared statements
When the schema of a table targeted by a prepared statement changes after the prepared statement is created, future executions of the prepared statement could result in an error. For example, adding a column to a table referenced in a prepared statement with a SELECT *
clause will result in an error:
CREATE TABLE users (id INT PRIMARY KEY);
PREPARE prep1 AS SELECT * FROM users;
ALTER TABLE users ADD COLUMN name STRING;
INSERT INTO users VALUES (1, 'Max Roach');
EXECUTE prep1;
ERROR: cached plan must not change result type
SQLSTATE: 0A000
It's therefore recommended to explicitly list result columns instead of using SELECT *
in prepared statements, when possible.
Adding a column with sequence-based DEFAULT
values
It is currently not possible to add a column to a table when the column uses a sequence as the DEFAULT
value, for example:
> CREATE TABLE t (x INT);
> INSERT INTO t(x) VALUES (1), (2), (3);
> CREATE SEQUENCE s;
> ALTER TABLE t ADD COLUMN y INT DEFAULT nextval('s');
ERROR: nextval(): unimplemented: cannot evaluate scalar expressions containing sequence operations in this context
SQLSTATE: 0A000
Dropping a column referenced by a partial index
CockroachDB prevents a column from being dropped using ALTER TABLE ... DROP COLUMN
if it is referenced by a partial index predicate. To drop such a column, the partial indexes need to be dropped first using DROP INDEX
. #97813.
Schema change DDL statements inside a multi-statement transaction can fail while other statements succeed
Most schema change DDL statements that run inside a multi-statement transaction with non-DDL statements can fail at COMMIT
time, even if other statements in the transaction succeed. This leaves such transactions in a "partially committed, partially aborted" state that may require manual intervention to determine whether the DDL statements succeeded.
Some DDL statements do not have this limitation. CREATE TABLE
and CREATE INDEX
statements have the same atomicity guarantees as other statements within a transaction.
If such a failure occurs, CockroachDB will emit a CockroachDB-specific error code, XXA00
, and the following error message:
transaction committed but schema change aborted with error: <description of error>
HINT: Some of the non-DDL statements may have committed successfully, but some of the DDL statement(s) failed.
Manual inspection may be required to determine the actual state of the database.
If you must execute schema change DDL statements inside a multi-statement transaction, we strongly recommend checking for this error code and handling it appropriately every time you execute such transactions.
This error will occur in various scenarios, including but not limited to:
- Creating a unique index fails because values aren't unique.
- The evaluation of a computed value fails.
- Adding a constraint (or a column with a constraint) fails because the constraint is violated for the default/computed values in the column.
To see an example of this error, start by creating the following table.
CREATE TABLE T(x INT);
INSERT INTO T(x) VALUES (1), (2), (3);
Then, enter the following multi-statement transaction, which will trigger the error.
BEGIN;
ALTER TABLE t ADD CONSTRAINT unique_x UNIQUE(x);
INSERT INTO T(x) VALUES (3);
COMMIT;
pq: transaction committed but schema change aborted with error: (23505): duplicate key value (x)=(3) violates unique constraint "unique_x"
HINT: Some of the non-DDL statements may have committed successfully, but some of the DDL statement(s) failed.
Manual inspection may be required to determine the actual state of the database.
In this example, the INSERT
statement committed, but the ALTER TABLE
statement adding a UNIQUE
constraint failed. We can verify this by looking at the data in table t
and seeing that the additional non-unique value 3
was successfully inserted.
SELECT * FROM t;
x
+---+
1
2
3
3
(4 rows)
Schema changes between executions of prepared statements
When the schema of a table targeted by a prepared statement changes after the prepared statement is created, future executions of the prepared statement could result in an error. For example, adding a column to a table referenced in a prepared statement with a SELECT *
clause will result in an error:
CREATE TABLE users (id INT PRIMARY KEY);
PREPARE prep1 AS SELECT * FROM users;
ALTER TABLE users ADD COLUMN name STRING;
INSERT INTO users VALUES (1, 'Max Roach');
EXECUTE prep1;
ERROR: cached plan must not change result type
SQLSTATE: 0A000
It's therefore recommended to explicitly list result columns instead of using SELECT *
in prepared statements, when possible.
Declarative schema changer does not track rows in system.privileges
The declarative schema changer does not track rows in the system.privileges
table, which prevents the declarative schema changer from successfully running the DROP OWNED BY
statement. #88149
New values generated by DEFAULT
expressions during ALTER TABLE ADD COLUMN
When executing an ALTER TABLE ADD COLUMN
statement with a DEFAULT
expression, new values generated:
- use the default search path regardless of the search path configured in the current session via
SET SEARCH_PATH
. - use the UTC time zone regardless of the time zone configured in the current session via
SET TIME ZONE
. - have no default database regardless of the default database configured in the current session via
SET DATABASE
, so you must specify the database of any tables they reference. - use the transaction timestamp for the
statement_timestamp()
function regardless of the time at which theALTER
statement was issued.
Some column-dropping schema changes do not roll back properly
Some schema changes that drop columns cannot be rolled back properly.
In some cases, the rollback will succeed, but the column data might be partially or totally missing, or stale due to the asynchronous nature of the schema change. #46541
In other cases, the rollback will fail in such a way that will never be cleaned up properly, leaving the table descriptor in a state where no other schema changes can be run successfully. #47712
To reduce the chance that a column drop will roll back incorrectly:
Perform column drops in transactions separate from other schema changes. This ensures that other schema change failures will not cause the column drop to be rolled back.
Drop all constraints (including unique indexes) on the column in a separate transaction, before dropping the column.
Drop any default values or computed expressions on a column before attempting to drop the column. This prevents conflicts between constraints and default/computed values during a column drop rollback.
If you think a rollback of a column-dropping schema change has occurred, check the jobs table. Schema changes with an error prefaced by cannot be reverted, manual cleanup may be required
might require manual intervention.
ALTER COLUMN
limitations
You cannot alter the data type of a column if:
- The column is part of an index.
- The column has
CHECK
constraints. - The column owns a sequence.
- The column has a
DEFAULT
expression. This will result in anERROR: ... column ... cannot also have a DEFAULT expression
withSQLSTATE: 42P16
. - The
ALTER COLUMN TYPE
statement is part of a combinedALTER TABLE
statement. - The
ALTER COLUMN TYPE
statement is inside an explicit transaction.
Most ALTER COLUMN TYPE
changes are finalized asynchronously. Schema changes on the table with the altered column may be restricted, and writes to the altered column may be rejected until the schema change is finalized.
CREATE TABLE AS
limitations
The primary key of tables created with CREATE TABLE ... AS
is not automatically derived from the query results. You must specify new primary keys at table creation. For examples, see Specify a primary key.
Remove a UNIQUE
index created as part of CREATE TABLE
UNIQUE
indexes created as part of a CREATE TABLE
statement cannot be removed without using CASCADE
. Unique indexes created with CREATE INDEX
do not have this limitation.
Max size of a single column family
When creating or updating a row, if the combined size of all values in a single column family exceeds the max range size for the table, the operation may fail, or cluster performance may suffer.
As a workaround, you can either manually split a table's columns into multiple column families, or you can create a table-specific zone configuration with an increased max range size.
Dropping a single partition
CockroachDB does not currently support dropping a single partition from a table. In order to remove partitions, you can repartition the table.
Placeholders in PARTITION BY
When defining a table partition, either during table creation or table alteration, it is not possible to use placeholders in the PARTITION BY
clause.
#19464
Unsupported trigram syntax
The following PostgreSQL syntax and features are currently unsupported for trigrams:
word_similarity()
built-in function.strict_word_similarity()
built-in function.%>
and<%
comparisons and acceleration.<<%
and%>>
comparisons and acceleration.<->
,<<->
,<->>
,<<<->
, and<->>>
comparisons.- Acceleration on regex string matching.
%
comparisons,show_trgm
, and trigram index creation on collated strings.
Unsupported full-text search features
The following PostgreSQL syntax and features are currently unsupported for full-text search:
- Aspects of text search configurations other than the specified dictionary.
websearch_to_tsquery()
built-in function.tsquery_phrase()
built-in function.ts_rank_cd()
built-in function.setweight()
built-in function.- Inverted joins on
TSVECTOR
values. tsvector || tsvector
comparisons.tsquery || tsquery
comparisons.tsquery && tsquery
comparisons.tsquery <-> tsquery
comparisons.!! tsquery
comparisons.tsquery @> tsquery
andtsquery <@ tsquery
comparisons.
CockroachDB does not allow inverted indexes with STORING
CockroachDB does not allow inverted indexes with a STORING
column. #88278
Multiple arbiter indexes for INSERT ON CONFLICT DO UPDATE
CockroachDB does not currently support multiple arbiter indexes for INSERT ON CONFLICT DO UPDATE
, and will return an error if there are multiple unique or exclusion constraints matching the ON CONFLICT DO UPDATE
specification. #53170
Expression index limitations
- The expression cannot reference columns outside the index's table.
- Functional expression output must be determined by the input arguments. For example, you can't use the volatile function
now()
to create an index because its output depends on more than just the function arguments. - CockroachDB does not allow expression indexes to reference computed columns. #67900
CockroachDB does not support expressions as
ON CONFLICT
targets. This means that unique expression indexes cannot be selected as arbiters forINSERT .. ON CONFLICT
statements. For example:CREATE TABLE t (a INT, b INT, UNIQUE INDEX ((a + b)));
CREATE TABLE
INSERT INTO t VALUES (1, 2) ON CONFLICT ((a + b)) DO NOTHING;
invalid syntax: statement ignored: at or near "(": syntax error SQLSTATE: 42601 DETAIL: source SQL: INSERT INTO t VALUES (1, 2) ON CONFLICT ((a + b)) DO NOTHING ^ HINT: try \h INSERT
INSERT INTO t VALUES (1, 2) ON CONFLICT ((a + b)) DO UPDATE SET a = 10;
invalid syntax: statement ignored: at or near "(": syntax error SQLSTATE: 42601 DETAIL: source SQL: INSERT INTO t VALUES (1, 2) ON CONFLICT ((a + b)) DO UPDATE SET a = 10 ^ HINT: try \h INSERT
Data types
Spatial support limitations
CockroachDB supports efficiently storing and querying spatial data, with the following limitations:
Not all PostGIS spatial functions are supported. #49203
The
AddGeometryColumn
spatial function only allows constant arguments. #49402The
AddGeometryColumn
spatial function only allows thetrue
value for itsuse_typmod
parameter. #49448CockroachDB does not support the
@
operator. Instead of using@
in spatial expressions, we recommend using the inverse, with~
. For example, instead ofa @ b
, useb ~ a
. #56124CockroachDB does not yet support
INSERT
s into thespatial_ref_sys
table. This limitation also blocks theogr2ogr -f PostgreSQL
file conversion command. #55903CockroachDB does not yet support k-nearest neighbors. #55227
CockroachDB does not support using schema name prefixes to refer to data types with type modifiers (e.g.,
public.geometry(linestring, 4326)
). Instead, use fully-unqualified names to refer to data types with type modifiers (e.g.,geometry(linestring,4326)
). #56492Defining a custom SRID by inserting rows into
spatial_ref_sys
is not currently supported. #55903
OID
limitations
Refer to OID
best practices.
Limitations for composite types
Changefeed types are not fully integrated with user-defined composite types. Running changefeeds with user-defined composite types is in Preview. Certain changefeed types do not support user-defined composite types. Refer to the change data capture Known Limitations for more detail. The following limitations apply:
- A changefeed in Avro format will not be able to serialize user-defined composite (tuple) types. #102903
- A changefeed emitting CSV will include
AS
labels in the message format when the changefeed serializes a user-defined composite type. #102905
Updating subfields of composite types using dot syntax results in a syntax error. #102984
ALTER TYPE
limitations
- When running the
ALTER TYPE
statement, you can only reference a user-defined type from the database that contains the type. - You can only cancel
ALTER TYPE
schema change jobs that drop values. This is because when you drop a value, CockroachDB searches through every row that could contain the type's value, which could take a long time. All otherALTER TYPE
schema change jobs are non-cancellable.
JSONB
limitations
- You cannot use primary key, foreign key, and unique constraints on
JSONB
values.
Security and privileges
GRANT
/REVOKE
limitations
User/role management operations (such as GRANT
and REVOKE
) are schema changes. As such, they inherit the limitations of schema changes.
For example, schema changes wait for concurrent transactions using the same resources as the schema changes to complete. In the case of role memberships being modified inside a transaction, most transactions need access to the set of role memberships. Using the default settings, role modifications require schema leases to expire, which can take up to 5 minutes.
This means that long-running transactions elsewhere in the system can cause user/role management operations inside transactions to take several minutes to complete. This can have a cascading effect. When a user/role management operation inside a transaction takes a long time to complete, it can in turn block all user-initiated transactions being run by your application, since the user/role management operation in the transaction has to commit before any other transactions that access role memberships (i.e., most transactions) can make progress.
If you want user/role management operations to finish more quickly, and do not care whether concurrent transactions will immediately see the side effects of those operations, set the session variable allow_role_memberships_to_change_during_transaction
to true
.
When this session variable is enabled, any user/role management operations issued in the current session will only need to wait for the completion of statements in other sessions where allow_role_memberships_to_change_during_transaction
is not enabled.
To accelerate user/role management operations across your entire application, you have the following options:
- Set the session variable in all sessions by passing it in the client connection string.
Apply the
allow_role_memberships_to_change_during_transaction
setting globally to an entire cluster using theALTER ROLE ALL
statement:ALTER ROLE ALL SET allow_role_memberships_to_change_during_transaction = true;
DROP OWNED BY
limitations
ENUM
types are not dropped.DROP OWNED BY
drops all owned objects as well as any grants on objects not owned by the role.If the role for which you are trying to
DROP OWNED BY
was granted a system-level privilege (i.e., using theGRANT SYSTEM ...
statement), the following error will be signalled:ERROR: cannot perform drop owned by if role has synthetic privileges; foo has entries in system.privileges SQLSTATE: 0A000 HINT: perform REVOKE SYSTEM ... for the relevant privileges foo has in system.privileges
The phrase "synthetic privileges" in the error message refers to system-level privileges.
The workaround is to use
SHOW SYSTEM GRANTS FOR {role}
and then useREVOKE SYSTEM ...
for each privilege in the result. #88149
Privileges for DELETE
and UPDATE
Every DELETE
or UPDATE
statement constructs a SELECT
statement, even when no WHERE
clause is involved. As a result, the user executing DELETE
or UPDATE
requires both the DELETE
and SELECT
or UPDATE
and SELECT
privileges on the table.
Deployment and operations
Admission control
Admission control works on the level of each node, not at the cluster level. The admission control system queues requests until the operations are processed or the request exceeds the timeout value (for example by using SET statement_timeout
). If you specify aggressive timeout values, the system may operate correctly but have low throughput as the operations exceed the timeout value while only completing part of the work. There is no mechanism for preemptively rejecting requests when the work queues are long.
Organizing operations by priority can mean that higher priority operations consume all the available resources while lower priority operations remain in the queue until the operation times out.
Data domiciling
- When columns are indexed, a subset of data from the indexed columns may appear in meta ranges or other system tables. CockroachDB synchronizes these system ranges and system tables across nodes. This synchronization does not respect any multi-region settings applied via either the multi-region SQL statements, or the low-level zone configs mechanism.
- Zone configs can be used for data placement but these features were historically built for performance, not for domiciling. The replication system's top priority is to prevent the loss of data and it may override the zone configurations if necessary to ensure data durability. For more information, see Replication Controls.
- If your log files are kept in the region where they were generated, there is some cross-region leakage (like the system tables described previously), but the majority of user data that makes it into the logs is going to be homed in that region. If that's not strong enough, you can use the log redaction functionality to strip all raw data from the logs. You can also limit your log retention entirely.
- If you start a node with a
--locality
flag that says the node is in region A, but the node is actually running in some region B, data domiciling based on the inferred node placement will not work. A CockroachDB node only knows its locality based on the text supplied to the--locality
flag; it can not ensure that it is actually running in that physical location.
CockroachDB does not test for all connection failure scenarios
CockroachDB servers rely on the network to report when a TCP connection fails. In most scenarios when a connection fails, the network immediately reports a connection failure, resulting in a Connection refused
error.
However, if there is no host at the target IP address, or if a firewall rule blocks traffic to the target address and port, a TCP handshake can linger while the client network stack waits for a TCP packet in response to network requests. To work around this kind of scenario, we recommend the following:
- When migrating a node to a new machine, keep the server listening at the previous IP address until the cluster has completed the migration.
- Configure any active network firewalls to allow node-to-node traffic.
- Verify that orchestration tools (e.g., Kubernetes) are configured to use the correct network connection information.
No guaranteed state switch from DECOMMISSIONING
to DECOMMISSIONED
if node decommission
is interrupted
There is no guaranteed state switch from DECOMMISSIONING
to DECOMMISSIONED
if node decommission
is interrupted in one of the following ways:
- The
cockroach node decommission --wait-all
command was run and then interrupted - The
cockroach node decommission --wait=none
command was run
This is because the state flip is effected by the CLI program at the end. Only the CLI (or its underlying API call) is able to finalize the "decommissioned" state. If the command is interrupted, or --wait=none
is used, the state will only flip to "decommissioned" when the CLI program is run again after decommissioning has done all its work. #94430
Simultaneous client connections and running queries on a single node
When a node has both a high number of client connections and running queries, the node may crash due to memory exhaustion. This is due to CockroachDB not accurately limiting the number of clients and queries based on the amount of available RAM on the node.
To prevent memory exhaustion, monitor each node's memory usage and ensure there is some margin between maximum CockroachDB memory usage and available system RAM. For more details about memory usage in CockroachDB, see this blog post.
To control the maximum number of non-superuser (root
user or other admin
role) connections a gateway node can have open at one time, use the server.max_connections_per_gateway
cluster setting. If a new non-superuser connection would exceed this limit, the error message "sorry, too many clients already"
is returned, along with error code 53300
.
This may be useful in addition to your memory monitoring.
Load-based lease rebalancing in uneven latency deployments
When nodes are started with the --locality
flag, CockroachDB attempts to place the replica lease holder (the replica that client requests are forwarded to) on the node closest to the source of the request. This means as client requests move geographically, so too does the replica lease holder.
However, you might see increased latency caused by a consistently high rate of lease transfers between datacenters in the following case:
- Your cluster runs in datacenters which are very different distances away from each other.
- Each node was started with a single tier of
--locality
, e.g.,--locality=datacenter=a
. - Most client requests get sent to a single datacenter because that's where all your application traffic is.
To detect if this is happening, open the DB Console, select the Queues dashboard, hover over the Replication Queue graph, and check the Leases Transferred / second data point. If the value is consistently larger than 0, you should consider stopping and restarting each node with additional tiers of locality to improve request latency.
For example, let's say that latency is 10ms from nodes in datacenter A to nodes in datacenter B but is 100ms from nodes in datacenter A to nodes in datacenter C. To ensure A's and B's relative proximity is factored into lease holder rebalancing, you could restart the nodes in datacenter A and B with a common region, --locality=region=foo,datacenter=a
and --locality=region=foo,datacenter=b
, while restarting nodes in datacenter C with a different region, --locality=region=bar,datacenter=c
.
Size limits on statement input from SQL clients
CockroachDB imposes a hard limit of 16MiB on the data input for a single statement passed to CockroachDB from a client (including the SQL shell). We do not recommend attempting to execute statements from clients with large input.
Using \|
to perform a large input in the SQL shell
In the built-in SQL shell, using the \|
operator to perform a large number of inputs from a file can cause the server to close the connection. This is because \|
sends the entire file as a single query to the server, which can exceed the upper bound on the size of a packet the server can accept from any client (16MB).
As a workaround, execute the file from the command line with cat data.sql | cockroach sql
instead of from within the interactive shell.
Spatial features disabled for ARM Macs
Spatial features are disabled due to an issue with macOS code signing for the GEOS libraries. Users needing spatial features on an ARM Mac may instead use Rosetta to run the Intel binary or use the Docker image distribution. GitHub tracking issue
Logging system limitations
Log files can only be accessed in the DB Console if they are stored in the same directory as the file sink for the DEV
channel.
Per-replica circuit breaker limitations
Per-replica circuit breakers have the following limitations:
- They cannot prevent requests from hanging when the node's liveness range is unavailable. For more information about troubleshooting a cluster that's having node liveness issues, see Node liveness issues.
- They are not tripped if all replicas of a range become unavailable, because the circuit breaker mechanism operates per-replica. This means at least one replica needs to be available to receive the request in order for the breaker to trip.
Kubernetes limitations
Refer to Kubernetes best practices.
Observability
Datadog
The CockroachDB Self-Hosted integration with Datadog only supports displaying cluster-wide averages of reported metrics. Filtering by a specific node is unsupported.
DB Console may become inaccessible for secure clusters
Accessing the DB Console for a secure cluster now requires login information (i.e., username and password). This login information is stored in a system table that is replicated like other data in the cluster. If a majority of the nodes with the replicas of the system table data go down, users will be locked out of the DB Console.
Available capacity metric in the DB Console
If you are testing your deployment locally with multiple CockroachDB nodes running on a single machine (this is not recommended in production), you must explicitly set the store size per node in order to display the correct capacity. Otherwise, the machine's actual disk capacity will be counted as a separate store for each node, thus inflating the computed capacity.
Disaster recovery
Physical cluster replication
- Read queries are not supported on the standby cluster before cutover.
- The primary and standby cluster cannot have different region topology. For example, replicating a multi-region primary cluster to a single-region standby cluster is not supported. Mismatching regions between a multi-region primary and standby cluster is also not supported. #119934
- Before cutover to the standby, the standby cluster does not support running backups or changefeeds.
Large data imports, such as those produced by
RESTORE
orIMPORT
, may dramatically increase replication lag.After the cutover process for physical cluster replication, scheduled changefeeds will continue on the promoted cluster. You will need to manage pausing or canceling the schedule on the promoted standby cluster to avoid two clusters running the same changefeed to one sink. #123776
After a cutover, there is no mechanism to stop applications from connecting to the original primary cluster. It is necessary to redirect application traffic manually, such as by using a network load balancer or adjusting DNS records. #117984
RESTORE
limitations
RESTORE
will not restore a table that references a UDF, unless you skip restoring the function with theskip_missing_udfs
option. Alternatively, take a database-level backup to include everything needed to restore the table. #118195Restoring
GLOBAL
andREGIONAL BY TABLE
tables into a non-multi-region database is not supported. #71502REGIONAL BY TABLE
andREGIONAL BY ROW
tables can be restored only if the regions of the backed-up table match those of the target database. All of the following must be true forRESTORE
to be successful:- The regions of the source database and the regions of the destination database have the same set of regions.
- The regions were added to each of the databases in the same order.
- The databases have the same primary region.
The following example would be considered as having mismatched regions because the database regions were not added in the same order and the primary regions do not match.
Running on the source database:
ALTER DATABASE source_database SET PRIMARY REGION "us-east1";
ALTER DATABASE source_database ADD region "us-west1";
Running on the destination database:
ALTER DATABASE destination_database SET PRIMARY REGION "us-west1";
ALTER DATABASE destination_database ADD region "us-east1";
In addition, the following scenario has mismatched regions between the databases since the regions were not added to the database in the same order.
Running on the source database:
ALTER DATABASE source_database SET PRIMARY REGION "us-east1";
ALTER DATABASE source_database ADD region "us-west1";
Running on the destination database:
ALTER DATABASE destination_database SET PRIMARY REGION "us-west1";
ALTER DATABASE destination_database ADD region "us-east1";
ALTER DATABASE destination_database SET PRIMARY REGION "us-east1";
Enterprise BACKUP
does not capture database/table/column comments
The COMMENT ON
statement associates comments to databases, tables, or columns. However, the internal table (system.comments
) in which these comments are stored is not captured by a BACKUP
of a table or database.
As a workaround, take a cluster backup instead, as the system.comments
table is included in cluster backups. #44396
Change data capture
Change data capture (CDC) provides efficient, distributed, row-level changefeeds into Apache Kafka for downstream processing such as reporting, caching, or full-text indexing. It has the following known limitations:
- Changefeed target options are limited to tables and column families. #73435
- VPC Peering and AWS PrivateLink in CockroachDB Dedicated clusters do not support connecting to a Kafka sink's internal IP addresses for changefeeds. To connect to a Kafka sink from CockroachDB Dedicated, it is necessary to expose the Kafka cluster's external IP address and open ports with firewall rules to allow access from a CockroachDB Dedicated cluster.
- Webhook sinks only support HTTPS. Use the
insecure_tls_skip_verify
parameter when testing to disable certificate verification; however, this still requires HTTPS and certificates. #73431 - Formats for changefeed messages are not supported by all changefeed sinks. Refer to the Changefeed Sinks page for details on compatible formats with each sink and the
format
option to specify a changefeed message format. #73432 - Using the
split_column_families
andresolved
options on the same changefeed will cause an error when using the following sinks: Kafka and Google Cloud Pub/Sub. Instead, use the individualFAMILY
keyword to specify column families when creating a changefeed. #79452 - Changefeed metrics labels are not supported as tags in Datadog. #104616
- Changefeed types are not fully integrated with user-defined composite types. Running changefeeds with user-defined composite types is in Preview. Certain changefeed types do not support user-defined composite types. Refer to the change data capture Known Limitations for more detail. The following limitations apply:
- A changefeed in Avro format will not be able to serialize user-defined composite (tuple) types. #102903
- A changefeed emitting CSV will include
AS
labels in the message format when the changefeed serializes a user-defined composite type. #102905
- After the cutover process for physical cluster replication, scheduled changefeeds will continue on the promoted cluster. You will need to manage pausing or canceling the schedule on the promoted standby cluster to avoid two clusters running the same changefeed to one sink. #123776
- You can only apply CDC queries on a single table in each statement.
- Some stable functions, notably functions that return MVCC timestamps, are overridden to return the MVCC timestamp of the event, e.g.,
transaction_timestamp
orstatement_timestamp
. Additionally, some time-based functions, such asnow()
are not supported. We recommend using thetransaction_timestamp()
function or thecrdb_internal_mvcc_timestamp
column instead. - You cannot alter a changefeed that uses CDC queries. #83033
- The following are not permitted in CDC queries:
- Volatile functions.
- Sub-select queries.
- Aggregate and window functions (i.e., functions operating over many rows). #98237
delete
changefeed events will only contain the primary key. All other columns will emit asNULL
. See Capture delete messages for detail on running a CDC query that emits the deleted values. #83835
ALTER CHANGEFEED
limitations
- It is necessary to
PAUSE
the changefeed before performing anyALTER CHANGEFEED
statement. #77171 - You cannot alter a changefeed that uses CDC queries. #83033
CockroachDB does not keep track of the
initial_scan
option applied to tables when it is set toyes
oronly
. For example:ALTER CHANGEFEED {job_ID} ADD table WITH initial_scan = 'yes';
This will trigger an initial scan of the table and the changefeed will track
table
. The changefeed will not trackinitial_scan
specified as an option, so it will not display in the output or after aSHOW CHANGEFEED JOB
statement.
Physical cluster replication
After the cutover process for physical cluster replication, scheduled changefeeds will continue on the promoted cluster. You will need to manage pausing or canceling the schedule on the promoted standby cluster to avoid two clusters running the same changefeed to one sink. #123776
Performance optimization
Optimizer and locking behavior
The SQL optimizer has limitations under certain isolation levels:
- The new implementation of
SELECT FOR UPDATE
is not yet the default setting underSERIALIZABLE
isolation. It can be used underSERIALIZABLE
isolation by setting theoptimizer_use_lock_op_for_serializable
session setting totrue
. #114737 SELECT FOR UPDATE
does not lock completely-NULL
column families in multi-column-family tables. #116836
Automatic statistics refresher may not refresh after upgrade
The automatic statistics refresher automatically checks whether it needs to refresh statistics for every table in the database upon startup of each node in the cluster. If statistics for a table have not been refreshed in a while, this will trigger collection of statistics for that table. If statistics have been refreshed recently, it will not force a refresh. As a result, the automatic statistics refresher does not necessarily perform a refresh of statistics after an upgrade. This could cause a problem, for example, if the upgrade moves from a version without histograms to a version with histograms. To refresh statistics manually, use CREATE STATISTICS
. #54816
Incorrect query plans for partitions with NULL
values
In cases where the partition definition includes a comparison with NULL
and a query constraint, incorrect query plans are returned. However, this case uses non-standard partitioning which defines partitions which could never hold values, so it is not likely to occur in production environments. #82774
Vectorized engine limitations
- The vectorized engine does not support queries containing a join filtered with an
ON
expression. #38018 - The vectorized engine does not support working with spatial data. Queries with geospatial functions or spatial data will revert to the row-oriented execution engine.
transaction_rows_read_err
and transaction_rows_written_err
do not halt query execution
The transaction_rows_read_err
and transaction_rows_written_err
session settings limit the number of rows read or written by a single transaction. These session settings will fail the transaction with an error, but not until the current query finishes executing and the results have been returned to the client. #70473
sql.guardrails.max_row_size_err
misses indexed virtual computed columns
The sql.guardrails.max_row_size_err
cluster setting misses large rows caused by indexed virtual computed columns. This is because the guardrail only checks the size of primary key rows, not secondary index rows. #69540
Using LIKE...ESCAPE
in WHERE
and HAVING
constraints
CockroachDB tries to optimize most comparisons operators in WHERE
and HAVING
clauses into constraints on SQL indexes by only accessing selected rows. This is done for LIKE
clauses when a common prefix for all selected rows can be determined in the search pattern (e.g., ... LIKE 'Joe%'
). However, this optimization is not yet available if the ESCAPE
keyword is also used. #30192
Import with a high amount of disk contention
IMPORT
can sometimes fail with a "context canceled" error, or can restart itself many times without ever finishing. If this is happening, it is likely due to a high amount of disk contention. This can be mitigated by setting the kv.bulk_io_write.max_rate
cluster setting to a value below your max disk write speed. For example, to set it to 10MB/s, execute:
> SET CLUSTER SETTING kv.bulk_io_write.max_rate = '10MB';
CockroachDB does not properly optimize some left and anti joins with GIN indexes
Left joins and anti joins involving JSONB
, ARRAY
, or spatial-typed columns with a multi-column or partitioned GIN index will not take advantage of the index if the prefix columns of the index are unconstrained, or if they are constrained to multiple, constant values.
To work around this limitation, make sure that the prefix columns of the index are either constrained to single constant values, or are part of an equality condition with an input column (e.g., col1 = col2
, where col1
is a prefix column and col2
is an input column).
For example, suppose you have the following multi-region database and tables:
CREATE DATABASE multi_region_test_db PRIMARY REGION "europe-west1" REGIONS "us-west1", "us-east1" SURVIVE REGION FAILURE;
USE multi_region_test_db;
CREATE TABLE t1 (
k INT PRIMARY KEY,
geom GEOMETRY
);
CREATE TABLE t2 (
k INT PRIMARY KEY,
geom GEOMETRY,
INVERTED INDEX geom_idx (geom)
) LOCALITY REGIONAL BY ROW;
And you insert some data into the tables:
INSERT INTO t1 SELECT generate_series(1, 1000), 'POINT(1.0 1.0)';
INSERT INTO t2 (crdb_region, k, geom) SELECT 'us-east1', generate_series(1, 1000), 'POINT(1.0 1.0)';
INSERT INTO t2 (crdb_region, k, geom) SELECT 'us-west1', generate_series(1001, 2000), 'POINT(2.0 2.0)';
INSERT INTO t2 (crdb_region, k, geom) SELECT 'europe-west1', generate_series(2001, 3000), 'POINT(3.0 3.0)';
If you attempt a left join between t1
and t2
on only the geometry columns, CockroachDB will not be able to plan an inverted join:
> EXPLAIN SELECT * FROM t1 LEFT JOIN t2 ON st_contains(t1.geom, t2.geom);
info
------------------------------------
distribution: full
vectorized: true
• cross join (right outer)
│ pred: st_contains(geom, geom)
│
├── • scan
│ estimated row count: 3,000
│ table: t2@primary
│ spans: FULL SCAN
│
└── • scan
estimated row count: 1,000
table: t1@primary
spans: FULL SCAN
(15 rows)
However, if you constrain the crdb_region
column to a single value, CockroachDB can plan an inverted join:
> EXPLAIN SELECT * FROM t1 LEFT JOIN t2 ON st_contains(t1.geom, t2.geom) AND t2.crdb_region = 'us-east1';
info
--------------------------------------------------
distribution: full
vectorized: true
• lookup join (left outer)
│ table: t2@primary
│ equality: (crdb_region, k) = (crdb_region,k)
│ equality cols are key
│ pred: st_contains(geom, geom)
│
└── • inverted join (left outer)
│ table: t2@geom_idx
│
└── • render
│
└── • scan
estimated row count: 1,000
table: t1@primary
spans: FULL SCAN
(18 rows)
If you do not know which region to use, you can combine queries with UNION ALL
:
> EXPLAIN SELECT * FROM t1 LEFT JOIN t2 ON st_contains(t1.geom, t2.geom) AND t2.crdb_region = 'us-east1'
UNION ALL SELECT * FROM t1 LEFT JOIN t2 ON st_contains(t1.geom, t2.geom) AND t2.crdb_region = 'us-west1'
UNION ALL SELECT * FROM t1 LEFT JOIN t2 ON st_contains(t1.geom, t2.geom) AND t2.crdb_region = 'europe-west1';
info
----------------------------------------------------------
distribution: full
vectorized: true
• union all
│
├── • union all
│ │
│ ├── • lookup join (left outer)
│ │ │ table: t2@primary
│ │ │ equality: (crdb_region, k) = (crdb_region,k)
│ │ │ equality cols are key
│ │ │ pred: st_contains(geom, geom)
│ │ │
│ │ └── • inverted join (left outer)
│ │ │ table: t2@geom_idx
│ │ │
│ │ └── • render
│ │ │
│ │ └── • scan
│ │ estimated row count: 1,000
│ │ table: t1@primary
│ │ spans: FULL SCAN
│ │
│ └── • lookup join (left outer)
│ │ table: t2@primary
│ │ equality: (crdb_region, k) = (crdb_region,k)
│ │ equality cols are key
│ │ pred: st_contains(geom, geom)
│ │
│ └── • inverted join (left outer)
│ │ table: t2@geom_idx
│ │
│ └── • render
│ │
│ └── • scan
│ estimated row count: 1,000
│ table: t1@primary
│ spans: FULL SCAN
│
└── • lookup join (left outer)
│ table: t2@primary
│ equality: (crdb_region, k) = (crdb_region,k)
│ equality cols are key
│ pred: st_contains(geom, geom)
│
└── • inverted join (left outer)
│ table: t2@geom_idx
│
└── • render
│
└── • scan
estimated row count: 1,000
table: t1@primary
spans: FULL SCAN
(54 rows)
Locality optimized search limitations
Locality optimized search does not work for queries that use partitioned unique indexes on virtual computed columns. A workaround for computed columns is to make the virtual computed column a stored computed column. Locality optimized search does not work for queries that use partitioned unique expression indexes. #68129
Locality optimized search works only for queries selecting a limited number of records (up to 100,000 unique keys).
Query plans for materialized views
- The optimizer may not select the most optimal query plan when querying materialized views because CockroachDB does not collect statistics on materialized views. #78181.
Inverted join for tsvector
and tsquery
types is not supported
CockroachDB cannot index-accelerate queries with @@
predicates when both sides of the operator are variables. #102731