Note:
Cockroach Labs supports the current stable release and two releases prior. Therefore, this version will no longer be supported after the Spring 2019 release.

This page describes newly identified limitations in the CockroachDB v1.1 release as well as unresolved limitations identified in earlier releases.

New Limitations

Enterprise restores after creating, dropping, or truncating tables

Note:
As of v1.1.1, it is no longer possible to create an incremental backup if a table has been created, dropped, or truncated after the full backup. This prevents attempts to restore from a broken backup. See #19286.

It is not possible to perform an enterprise RESTORE from a full BACKUP with incremental backups if you created, dropped, or truncated any tables after the full backup. Attempting to restore in this case will fail with an error.

As a workaround, any time you create, drop, or truncate a table, perform another full BACKUP of your cluster.

Maximum cluster size

Note:
Resolved as of v1.2-alpha.20171026. See #17016.

The locations of all ranges in a cluster are stored in a two-level index at the beginning of the key-space, known as meta ranges, where the first level (meta1) addresses the second, and the second level (meta2) addresses data in the cluster. A limitation in v1.1 prevents meta2 from being split; thus, the max size of a single range, 64MiB by default, limits the overall size of a cluster to 64TB. Clusters beyond this size will experience problems.

Available capacity metric in the Admin UI

If you are running multiple nodes on a single machine (not recommended in production) and didn't specify the maximum allocated storage capacity for each node using the --store flag, the capacity metrics in the Admin UI are incorrect. This is because when multiple nodes are running on a single machine, the machine's hard disk is treated as an available store for each node, while in reality, only one hard disk is available for all nodes. The total available capacity is then calculated as the hard disk size multiplied by the number of nodes on the machine.

Downgrading to v1.1.0 from a later v1.1.x patch release

If you have started or upgraded a cluster using v1.1.1 or a later release, then you will not be able to downgrade the cluster to the v1.1.0 binary. This is due to an issue with the version setting in the v1.1.0 release that was fixed in v1.1.1. Changing between different x.y.z versions of the same x.y release is typically safe.

Unresolved Limitations

Schema changes within transactions

Within a single transaction:

  • DDL statements cannot follow DML statements. As a workaround, arrange DML statements before DDL statements, or split the statements into separate transactions.
  • A CREATE TABLE statement containing FOREIGN KEY or INTERLEAVE clauses cannot be followed by statements that reference the new table. This also applies to running TRUNCATE on such a table because TRUNCATE implicitly drops and recreates the table.
  • A table cannot be dropped and then recreated with the same name. This is not possible within a single transaction because DROP TABLE does not immediately drop the name of the table. As a workaround, split the DROP TABLE and CREATE TABLE statements into separate transactions.

Schema changes between executions of prepared statements

When the schema of a table targeted by a prepared statement changes before the prepared statement is executed, CockroachDB allows the prepared statement to return results based on the changed table schema, for example:

> 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;
+----+-----------+
| id |   name    |
+----+-----------+
|  1 | Max Roach |
+----+-----------+
(1 row)

It's therefore recommended to not use SELECT * in queries that will be repeated, via prepared statements or otherwise.

Also, a prepared INSERT, UPSERT, or DELETE statement acts inconsistently when the schema of the table being written to is changed before the prepared statement is executed:

  • If the number of columns has increased, the prepared statement returns an error but nonetheless writes the data.
  • If the number of columns remains the same but the types have changed, the prepared statement writes the data and does not return an error.

Join flags when restarting a cluster with different addresses

In all our deployment tutorials, we provide the addresses of the first few nodes in the cluster to the --join flag when starting each node. In a new cluster, this ensures that all nodes are able to learn the location of the first key-vlaue range, which is part of a meta-index identifying where all range replicas are stored, and which nodes require to initialize themselves and start accepting incoming connections. Each node also persists the addresses of all other nodes in the cluster on disk such that it can reconnect to them if the nodes in the --join flag ever happen to be unavailable when restarting. This ensures that a restarting node will always be able to connect to a node with a copy of the first range even if they're no longer located on the nodes in the --join flag.

However, if the nodes in a cluster are restarted with different addresses for some reason, then it's not guaranteed that a copy of the first range will be on the nodes in the join flags. In such cases, the --join flags must form a fully-connected directed graph. The easiest way to do this is to put all of the new nodes' addresses into each node's --join flag, which ensures all nodes can join a node with a copy of the first key-value range.

INSERT ON CONFLICT vs. UPSERT

When inserting/updating all columns of a table, and the table has no secondary indexes, we recommend using an UPSERT statement instead of the equivalent INSERT ON CONFLICT statement. Whereas INSERT ON CONFLICT always performs a read to determine the necessary writes, the UPSERT statement writes without reading, making it faster.

This issue is particularly relevant when using a simple SQL table of two columns to simulate direct KV access. In this case, be sure to use the UPSERT statement.

Repeated or combined commands in the SQL shell history

Note:
Resolved as of v2.0.

Our built-in SQL shell stores previously executed commands in the shell's history. In some cases, these commands are unexpectedly duplicated.

Also, in some terminals, such as st or xterm without tmux, previously executed commands are combined into a single command in the SQL shell history.

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.

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 the ALTER statement was issued.

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 Admin UI, 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.

Overload resolution for collated strings

Many string operations are not properly overloaded for collated strings, for example:

> SELECT 'string1' || 'string2';
+------------------------+
| 'string1' || 'string2' |
+------------------------+
| string1string2         |
+------------------------+
(1 row)
> SELECT ('string1' collate en) || ('string2' collate en);
pq: unsupported binary operator: <collatedstring{en}> || <collatedstring{en}>

Write and update limits for a single transaction

A single transaction can contain at most 100,000 write operations (e.g., deletions or changes to individual columns) and at most 64MiB of combined updates. When a transaction exceeds these limits, it gets aborted. INSERT INTO .... SELECT FROM ... and DELETE FROM ... WHERE <non-selective filter> queries commonly encounter these limits.

If you need to increase these limits, you can update the cluster-wide settings kv.transaction.max_intents and kv.raft.command.max_size. For INSERT INTO .. SELECT FROM queries in particular, another workaround is to manually page through the data you want to insert using separate transactions.

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 (64MiB by default) 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.

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.

SQL subexpressions and memory usage

Many SQL subexpressions (e.g., ORDER BY, UNION/INTERSECT/EXCEPT, GROUP BY, subqueries) accumulate intermediate results in RAM on the node processing the query. If the operator attempts to process more rows than can fit into RAM, the node will either crash or report a memory capacity error. For more details about memory usage in CockroachDB, see this blog post.

Query planning for OR expressions

Given a query like SELECT * FROM foo WHERE a > 1 OR b > 2, even if there are appropriate indexes to satisfy both a > 1 and b > 2, the query planner performs a full table or index scan because it cannot use both conditions at once.

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.

cockroach dump does not support cyclic foreign key references

The cockroach dump command will successfully create a dump file for a table with a foreign key reference to itself, or a set of tables with a cyclic foreign key dependency (e.g., a depends on b depends on a). That dump file, however, can only be executed after manually editing the output to remove the foreign key definitions from the CREATE TABLE statements and adding them as ALTER TABLE ... ADD CONSTRAINT statements after the INSERT statements.



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