If a SQL statement returns an unexpected result or takes longer than expected to process, this page will help you troubleshoot the issue.
SELECT statement performance issues
The common reasons for a sub-optimal SELECT performance are inefficient scans, full scans, and incorrect use of indexes. To improve the performance of SELECT statements, refer to the following documents:
Query is always slow
To detect whether your cluster has slow queries, check the service latency graph and the CPU graph. If the graphs show latency spikes or CPU usage spikes, it might indicate slow queries in your cluster.
Once you determine that you do have slow queries in your cluster, use the Statements page to identify the high latency SQL statements. To view the Statements page, access the Admin UI and then click Statements on the left.
You can then use the Statements Details page to drill down to individual statements. You can also use EXPLAIN ANALYZE statement, which executes a SQL query and returns a physical query plan with execution statistics. Query plans provide information around SQL execution, which can be used to troubleshoot slow queries by figuring out where time is being spent, how long a processor (i.e., a component that takes streams of input rows and processes them according to a specification) is not doing work, etc.
If you need help interpreting the output of the EXPLAIN ANALYZE statement, contact us.
Query is sometimes slow
If the query performance is irregular:
Run
SHOW TRACEfor the query twice: once when the query is performing as expected and once when the query is slow.Contact us to analyze the outputs of the
SHOW TRACEcommand.
Cancelling running queries
See Cancel query
Low throughput
Throughput is affected by the disk I/O, CPU usage, and network latency. Use the Admin UI to check the following metrics:
Disk I/O: Disk IOPS in progress
CPU usage: CPU percent
Network latency: Service latency SQL 99th percentile
Single hot node
A hot node is one that has much higher resource usage than other nodes. To determine if you have a hot node in your cluster, access the Admin UI, click Metrics on the left, and navigate to the following graphs. Hover over each of the following graphs to see the per-node values of the metrics. If one of the nodes has a higher value, you have a hot node in your cluster.
Replication dashboard > Average queries per store graph.
Overview Dashboard > Service Latency graph
Hardware Dashboard > CPU percent graph
SQL Dashboard > SQL Connections graph
Hardware Dashboard > Disk IOPS in Progress graph
Solution:
If you have a small table that fits into one range, then only one of the nodes will be used. This is expected behavior. However, you can split your range to distribute the table across multiple nodes.
If the SQL Connections graph shows that one node has a higher number of SQL connections and other nodes have zero connections, check if your app is set to talk to only one node.
Check load balancer settings.
Check for transaction contention.
If you have a monotonically increasing index column or Primary Key, then your index or Primary Key should be redesigned. See Unique ID best practices for more information.
INSERT/UPDATE statements are slow
Use the Statements page to identify the slow SQL statements. To view the Statements page, access the Admin UI and then click Statements on the left.
Refer to the following documents to improve INSERT / UPDATE performance:
Per-node queries per second (QPS) is high
If a cluster is not idle, it is useful to monitor the per-node queries per second. Cockroach will automatically distribute load throughout the cluster. If one or more nodes is not performing any queries there is likely something to investigate. See exec_success and exec_errors which track operations at the KV layer and sql_{select,insert,update,delete}_count which track operations at the SQL layer.
Increasing number of nodes does not improve performance
See Why would increasing the number of nodes not result in more operations per second?
bad connection & closed responses
If you receive a response of bad connection or closed, this normally indicates that the node you connected to died. You can check this by connecting to another node in the cluster and running cockroach node status.
Once you find the downed node, you can check its logs (stored in cockroach-data/logs by default).
Because this kind of behavior is entirely unexpected, you should file an issue.
SQL logging
There are several ways to log SQL queries. The type of logging to use depends on your requirements and on the purpose of the logs.
- For system troubleshooting and performance optimization, turn on cluster-wide execution logs.
- For local testing, turn on per-node execution logs.
- For per-table audit logs for security purposes, turn on SQL audit logs.
Cluster-wide execution logs
For production clusters, the best way to log all queries is to turn on the cluster-wide setting sql.trace.log_statement_execute:
> SET CLUSTER SETTING sql.trace.log_statement_execute = true;
With this setting on, each node of the cluster writes all SQL queries it executes to a separate log file cockroach-sql-exec.log. When you no longer need to log queries, you can turn the setting back off:
> SET CLUSTER SETTING sql.trace.log_statement_execute = false;
Per-node execution logs
Alternatively, if you are testing CockroachDB locally and want to log queries executed just by a specific node, you can either pass a CLI flag at node startup, or execute a SQL function on a running node.
Using the CLI to start a new node, pass the --vmodule flag to the cockroach start command. For example, to start a single node locally and log all client-generated SQL queries it executes, you'd run:
$ cockroach start --insecure --listen-addr=localhost --vmodule=exec_log=2 --join=<join addresses>
To log CockroachDB-generated SQL queries as well, use --vmodule=exec_log=3.
From the SQL prompt on a running node, execute the crdb_internal.set_vmodule() function:
> SELECT crdb_internal.set_vmodule('exec_log=2');
This will result in the following output:
crdb_internal.set_vmodule
+---------------------------+
0
(1 row)
Once the logging is enabled, all client-generated SQL queries executed by the node will be written to the CockroachDB log file as follows:
I180402 19:12:28.112957 394661 sql/exec_log.go:173 [n1,client=127.0.0.1:50155,user=root] exec "psql" {} "SELECT version()" {} 0.795 1 ""
SQL audit logs
This is an experimental feature. The interface and output are subject to change.
SQL audit logging is useful if you want to log all queries that are run against specific tables, by specific users.
For a tutorial, see SQL Audit Logging.
For reference documentation, see
ALTER TABLE ... EXPERIMENTAL_AUDIT.
Note that enabling SQL audit logs can negatively impact performance. As a result, we recommend using SQL audit logs for security purposes only.
Something else?
Try searching the rest of our docs for answers or using our other support resources, including:
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