Performance Tuning Recipes

This page provides recipes for fixing performance issues in your applications.

Problems

This section describes how to use CockroachDB commands and dashboards to identify performance problems in your applications.

Observation Diagnosis Solution
  • Your application takes a long time to return results.
  • Excess network latency.
  • Your application is experiencing degraded performance with the following transaction retry errors:
    • SQLSTATE: 40001
    • RETRY_WRITE_TOO_OLD
    • RETRY_SERIALIZABLE
  • The SQL Statement Contention dashboard in the DB Console is showing spikes over time.
  • The SQL Statement Errors graph in the DB Console is showing spikes in retries over time.
  • Your application is experiencing transaction contention.
  • The statement plan produced by EXPLAIN or EXPLAIN ANALYZE indicates that the statement uses a full table scan.
  • Querying the crdb_internal.node_statement_statistics table indicates that you have full table scans in some statement's plans.
  • Viewing the statement plan on the Statement details page of the DB Console indicates that the plan contains full table scans.
  • Running the SHOW FULL TABLE SCANS statement returns results.
  • The Full Table/Index Scans graph in the DB Console is showing spikes over time.
  • Poor quality statement plans retrieve more rows than are required, leading to longer execution times.
  • The Hardware metrics dashboard in the DB Console shows high resource usage per node.
  • The Problem Ranges report on the Advanced Debug page of the DB Console indicates a high number of queries per second on a subset of ranges or nodes.
  • You have resource contention.
  • The Overview dashboard in the DB Console shows high service latency and QPS for INSERT and UPDATE statements.
  • Your tables have long write times.

Solutions

This section provides solutions for common performance issues in your applications.

Transaction contention

Transaction contention occurs when transactions issued from multiple clients at the same time operate on the same data. This can cause transactions to wait on each other (like when many people try to check out with the same cashier at a store) and decrease performance.

Indicators that your application is experiencing transaction contention

Fix transaction contention problems

Find the transactions and statements within the transactions that are experiencing contention. CockroachDB has several tools to help you track down such transactions and statements:

  • In DB Console, visit the Transactions and Statements pages and sort transactions and statements by contention.
  • Query the crdb_internal.cluster_contended_indexes and crdb_internal.cluster_contended_tables tables for your database to find the indexes and tables that are experiencing contention.

    icon/buttons/copy
    > SELECT * FROM movr.crdb_internal.cluster_contended_indexes;
    
    icon/buttons/copy
    > SELECT * FROM movr.crdb_internal.cluster_contended_tables;
    

After you identify the transactions or statements that are causing contention, follow the steps in the next section to avoid contention.

Statements with full table scans

Full table scans often result in poor statement performance.

Indicators that your application has statements with full table scans

  • The following query returns statements with full table scans in their statement plan:

    icon/buttons/copy
    SHOW FULL TABLE SCANS;
    
  • The following query against the CRDB_INTERNAL.node_statement_statistics table returns results:

    icon/buttons/copy
    SELECT count(*) as total_full_scans
    FROM crdb_internal.node_statement_statistics
    WHERE full_scan = true;
    
  • Viewing the statement plan on the Statement details page of the DB Console indicates that the plan contains full table scans.

  • The statement plans returned by the EXPLAIN and EXPLAIN ANALYZE commands indicate that there are full table scans.

  • The Full Table/Index Scans graph in the DB Console is showing spikes over time.

Fix full table scans in statements

Not every full table scan is an indicator of poor performance. The cost-based optimizer may decide on a full table scan when other index or join scans would result in longer execution time.

Examine the statements that result in full table scans and consider adding secondary indexes.

Also see Table scans best practices.

Suboptimal primary keys

Indicators that your tables are using suboptimal primary keys

  • The Hardware metrics dashboard in the DB Console shows high resource usage per node.
  • The Problem Ranges report on the Advanced Debug page of the DB Console indicates a high number of queries per second on a subset of ranges or nodes.

Fix suboptimal primary keys

Evaluate the schema of your table to see if you can redistribute data more evenly across multiple ranges. Specifically, make sure you have followed best practices when selecting your primary key.

If your application with a small dataset (for example, a dataset that contains few index key values) is experiencing resource contention, consider splitting your tables and indexes to distribute ranges across multiple nodes to reduce resource contention.

Slow writes

Indicators that your tables are experiencing slow writes

If the Overview dashboard in the DB Console shows high service latency when the QPS of INSERT and UPDATE statements is high, your tables are experiencing slow writes.

Fix slow writes

Secondary indexes can improve application read performance. However, there is overhead in maintaining secondary indexes that can affect your write performance. You should profile your tables periodically to determine whether an index is worth the overhead. To identify infrequently accessed indexes that could be candidates to drop, query the crdb_internal.index_usage_statistics table:

SELECT
 ti.descriptor_name as table_name,
 ti.index_name,
 total_reads,
 last_read
FROM crdb_internal.index_usage_statistics AS us
JOIN crdb_internal.table_indexes ti
ON us.index_id = ti.index_id
 AND us.table_id = ti.descriptor_id
ORDER BY total_reads ASC;

Use the values in the total_reads and last_read columns to identify indexes that have low usage or are stale and could be dropped.

See also

If you aren't sure whether SQL query performance needs to be improved, see Identify slow queries.

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