Improving query performance for RDS for MySQL with Amazon RDS Optimized Reads - Amazon Relational Database Service
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Improving query performance for RDS for MySQL with Amazon RDS Optimized Reads

You can achieve faster query processing for RDS for MySQL with Amazon RDS Optimized Reads. An RDS for MySQL DB instance or Multi-AZ DB cluster that uses RDS Optimized Reads can achieve up to 2x faster query processing compared to a DB instance or cluster that doesn't use it.

Overview of RDS Optimized Reads

When you use an RDS for MySQL DB instance or Multi-AZ DB cluster that has RDS Optimized Reads turned on, it achieves faster query performance through the use of an instance store. An instance store provides temporary block-level storage for your DB instance or Multi-AZ DB cluster. The storage is located on Non-Volatile Memory Express (NVMe) solid state drives (SSDs) that are physically attached to the host server. This storage is optimized for low latency, high random I/O performance, and high sequential read throughput.

RDS Optimized Reads is turned on by default when a DB instance or Multi-AZ DB cluster uses a DB instance class with an instance store, such as db.m5d or db.m6gd. With RDS Optimized Reads, some temporary objects are stored on the instance store. These temporary objects include internal temporary files, internal on-disk temp tables, memory map files, and binary log (binlog) cache files. For more information about the instance store, see Amazon EC2 instance store in the Amazon Elastic Compute Cloud User Guide for Linux Instances.

The workloads that generate temporary objects in MySQL for query processing can take advantage of the instance store for faster query processing. This type of workload includes queries involving sorts, hash aggregations, high-load joins, Common Table Expressions (CTEs), and queries on unindexed columns. These instance store volumes provide higher IOPS and performance, regardless of the storage configurations used for persistent Amazon EBS storage. Because RDS Optimized Reads offloads operations on temporary objects to the instance store, the input/output operations per second (IOPS) or throughput of the persistent storage (Amazon EBS) can now be used for operations on persistent objects. These operations include regular data file reads and writes, and background engine operations, such as flushing and insert buffer merges.


Both manual and automated RDS snapshots only contain engine files for persistent objects. The temporary objects created in the instance store aren't included in RDS snapshots.

Use cases for RDS Optimized Reads

If you have workloads that rely heavily on temporary objects, such as internal tables or files, for their query execution, then you can benefit from turning on RDS Optimized Reads. The following use cases are candidates for RDS Optimized Reads:

  • Applications that run analytical queries with complex common table expressions (CTEs), derived tables, and grouping operations

  • Read replicas that serve heavy read traffic with unoptimized queries

  • Applications that run on-demand or dynamic reporting queries that involve complex operations, such as queries with GROUP BY and ORDER BY clauses

  • Workloads that use internal temporary tables for query processing

    You can monitor the engine status variable created_tmp_disk_tables to determine the number of disk-based temporary tables created on your DB instance.

  • Applications that create large temporary tables, either directly or in procedures, to store intermediate results

  • Database queries that perform grouping or ordering on non-indexed columns

Best practices for RDS Optimized Reads

Use the following best practices for RDS Optimized Reads:

  • Add retry logic for read-only queries in case they fail because the instance store is full during the execution.

  • Monitor the storage space available on the instance store with the CloudWatch metric FreeLocalStorage. If the instance store is reaching its limit because of workload on the DB instance, modify the DB instance to use a larger DB instance class.

  • When your DB instance or Multi-AZ DB cluster has sufficient memory but is still reaching the storage limit on the instance store, increase the binlog_cache_size value to maintain the session-specific binlog entries in memory. This configuration prevents writing the binlog entries to temporary binlog cache files on disk.

    The binlog_cache_size parameter is session-specific. You can change the value for each new session. The setting for this parameter can increase the memory utilization on the DB instance during peak workload. Therefore, consider increasing the parameter value based on the workload pattern of your application and available memory on the DB instance.

  • Use the default value of MIXED for the binlog_format. Depending on the size of the transactions, setting binlog_format to ROW can result in large binlog cache files on the instance store.

  • Set the internal_tmp_mem_storage_engine parameter to TempTable, and set the temptable_max_mmap parameter to match the size of the available storage on the instance store.

  • Avoid performing bulk changes in a single transaction. These types of transactions can generate large binlog cache files on the instance store and can cause issues when the instance store is full. Consider splitting writes into multiple small transactions to minimize storage use for binlog cache files.

  • Use the default value of ABORT_SERVER for the binlog_error_action parameter. Doing so avoids issues with the binary logging on DB instances with backups enabled.

Using RDS Optimized Reads

When you provision an RDS for MySQL DB instance with one of the following DB instance classes in a Single-AZ DB instance deployment, Multi-AZ DB instance deployment, or Multi-AZ DB cluster deployment, the DB instance automatically uses RDS Optimized Reads.

To turn on RDS Optimized Reads, do one of the following:

RDS Optimized Reads is available in all Amazon Web Services Regions RDS where one or more of the DB instance classes with local NVMe SSD storage are supported. For information about DB instance classes, see DB instance classes.

DB instance class availability differs for Amazon Web Services Regions. To determine whether a DB instance class is supported in a specific Amazon Web Services Region, see Determining DB instance class support in Amazon Web Services Regions.

If you don't want to use RDS Optimized Reads, modify your DB instance or Multi-AZ DB cluster so that it doesn't use a DB instance class that supports the feature.

Monitoring DB instances that use RDS Optimized Reads

You can monitor DB instances that use RDS Optimized Reads with the following CloudWatch metrics:

  • FreeLocalStorage

  • ReadIOPSLocalStorage

  • ReadLatencyLocalStorage

  • ReadThroughputLocalStorage

  • WriteIOPSLocalStorage

  • WriteLatencyLocalStorage

  • WriteThroughputLocalStorage

These metrics provide data about available instance store storage, IOPS, and throughput. For more information about these metrics, see Amazon CloudWatch instance-level metrics for Amazon RDS.

Limitations for RDS Optimized Reads

The following limitations apply to RDS Optimized Reads:

  • RDS Optimized Reads is supported for RDS for MySQL version 8.0.28 and higher. For information about RDS for MySQL versions, see MySQL on Amazon RDS versions.

  • You can't change the location of temporary objects to persistent storage (Amazon EBS) on the DB instance classes that support RDS Optimized Reads.

  • When binary logging is enabled on a DB instance, the maximum transaction size is limited by the size of the instance store. In MySQL, any session that requires more storage than the value of binlog_cache_size writes transaction changes to temporary binlog cache files, which are created on the instance store.

  • Transactions can fail when the instance store is full.