Amazon Aurora MySQL reference - Amazon Aurora
ParametersInapplicable MySQL parameters and status variablesAurora MySQL eventsAurora MySQL isolation levelsAurora MySQL hintsStored procedures

Amazon Aurora MySQL reference

This reference includes information about Aurora MySQL parameters, status variables, and general SQL extensions or differences from the community MySQL database engine.

Aurora MySQL parameters

You manage your Amazon Aurora MySQL DB cluster in the same way that you manage other Amazon RDS DB instances, by using parameters in a DB parameter group. Amazon Aurora differs from other DB engines in that you have a DB cluster that contains multiple DB instances. As a result, some of the parameters that you use to manage your Aurora MySQL DB cluster apply to the entire cluster. Other parameters apply only to a particular DB instance in the DB cluster.

To manage cluster-level parameters, you use DB cluster parameter groups. To manage instance-level parameters, you use DB parameter groups. Each DB instance in an Aurora MySQL DB cluster is compatible with the MySQL database engine. However, you apply some of the MySQL database engine parameters at the cluster level, and you manage these parameters using DB cluster parameter groups. You can't find cluster-level parameters in the DB parameter group for an instance in an Aurora DB cluster. A list of cluster-level parameters appears later in this topic.

You can manage both cluster-level and instance-level parameters using the AWS Management Console, the AWS CLI, or the Amazon RDS API. You use separate commands for managing cluster-level parameters and instance-level parameters. For example, you can use the modify-db-cluster-parameter-group CLI command to manage cluster-level parameters in a DB cluster parameter group. You can use the modify-db-parameter-group CLI command to manage instance-level parameters in a DB parameter group for a DB instance in a DB cluster.

You can view both cluster-level and instance-level parameters in the console, or by using the CLI or RDS API. For example, you can use the describe-db-cluster-parameters AWS CLI command to view cluster-level parameters in a DB cluster parameter group. You can use the describe-db-parameters CLI command to view instance-level parameters in a DB parameter group for a DB instance in a DB cluster.

For more information on DB parameter groups, see Working with DB parameter groups and DB cluster parameter groups. For rules and restrictions for Aurora Serverless clusters, see Aurora Serverless and parameter groups.

Cluster-level parameters

The following table shows all of the parameters that apply to the entire Aurora MySQL DB cluster.

Parameter name Modifiable Notes

aurora_binlog_read_buffer_size

Yes

Only affects clusters that use binary log (binlog) replication. For information about binlog replication, see Replication between Aurora and MySQL or between Aurora and another Aurora DB cluster (binlog replication).

aurora_binlog_replication_max_yield_seconds

Yes

Only affects clusters that use binary log (binlog) replication. For information about binlog replication, see Replication between Aurora and MySQL or between Aurora and another Aurora DB cluster (binlog replication).

aurora_binlog_use_large_read_buffer

Yes

Only affects clusters that use binary log (binlog) replication. For information about binlog replication, see Replication between Aurora and MySQL or between Aurora and another Aurora DB cluster (binlog replication).

aurora_enable_replica_log_compression

Yes

For more information, see Performance considerations for Amazon Aurora MySQL replication. Doesn't apply to clusters that are part of an Aurora global database.

aurora_enable_repl_bin_log_filtering

Yes

For more information, see Performance considerations for Amazon Aurora MySQL replication. Doesn't apply to clusters that are part of an Aurora global database.

aurora_enable_zdr

Yes

For more information, see High availability considerations for Amazon Aurora MySQL replication.

aurora_load_from_s3_role

Yes

For more information, see Loading data into an Amazon Aurora MySQL DB cluster from text files in an Amazon S3 bucket.

aurora_select_into_s3_role

Yes

For more information, see Saving data from an Amazon Aurora MySQL DB cluster into text files in an Amazon S3 bucket.

auto_increment_increment

Yes

auto_increment_offset

Yes

aws_default_lambda_role

Yes

For more information, see Invoking a Lambda function from an Amazon Aurora MySQL DB cluster.

aws_default_s3_role

Yes

binlog_checksum

Yes

binlog_format

Yes

For more information, see Replication between Aurora and MySQL or between Aurora and another Aurora DB cluster (binlog replication).

binlog_row_image

No

binlog_rows_query_log_events

Yes

character-set-client-handshake

Yes

character_set_client

Yes

character_set_connection

Yes

character_set_database

Yes

character_set_filesystem

Yes

character_set_results

Yes

character_set_server

Yes

collation_connection

Yes

collation_server

Yes

completion_type

Yes

default_storage_engine

No

Aurora MySQL clusters use the InnoDB storage engine for all of your data.

innodb_autoinc_lock_mode

Yes

innodb_checksums

No

innodb_cmp_per_index_enabled

Yes

innodb_commit_concurrency

Yes

innodb_data_home_dir

No

Aurora MySQL uses managed instances where you don't access the filesystem directly.

innodb_file_per_table

Yes

innodb_flush_log_at_trx_commit

Yes

innodb_ft_max_token_size

Yes

innodb_ft_min_token_size

Yes

innodb_ft_num_word_optimize

Yes

innodb_ft_sort_pll_degree

Yes

innodb_online_alter_log_max_size

Yes

innodb_optimize_fulltext_only

Yes

innodb_page_size

No

innodb_purge_batch_size

Yes

innodb_purge_threads

Yes

innodb_rollback_on_timeout

Yes

innodb_rollback_segments

Yes

innodb_spin_wait_delay

Yes

innodb_strict_mode

Yes

innodb_support_xa

Yes

innodb_sync_array_size

Yes

innodb_sync_spin_loops

Yes

innodb_table_locks

Yes

innodb_undo_directory

No

Aurora MySQL uses managed instances where you don't access the filesystem directly.

innodb_undo_logs

Yes

innodb_undo_tablespaces

No

lc_time_names

Yes

lower_case_table_names

Yes

master-info-repository

Yes

master_verify_checksum

Yes

require_secure_transport

Yes

For more information, see Using SSL/TLS with Aurora MySQL DB clusters.

server_audit_events

Yes

server_audit_excl_users

Yes

server_audit_incl_users

Yes

server_audit_logging

Yes

For instructions on uploading the logs to Amazon CloudWatch Logs, see Publishing Amazon Aurora MySQL logs to Amazon CloudWatch Logs.

server_id

No

skip-character-set-client-handshake

Yes

skip_name_resolve

No

sync_frm

Yes

time_zone

Yes

tls_version

Yes

For more information, see TLS versions for Aurora MySQL.

Instance-level parameters

The following table shows all of the parameters that apply to a specific DB instance in an Aurora MySQL DB cluster.

Parameter name Modifiable Notes

allow-suspicious-udfs

No

aurora_lab_mode

Yes

For more information, see Amazon Aurora MySQL lab mode.

aurora_oom_response

Yes

For more information, see Amazon Aurora MySQL out of memory issues .

aurora_parallel_query

Yes

Set to ON to enable parallel query in Aurora MySQL versions 1.23 and 2.09 or higher. The old aurora_pq parameter isn't used in these versions. For more information, see Working with parallel query for Amazon Aurora MySQL.

aurora_pq

Yes

Set to OFF to turn off parallel query for specific DB instances in Aurora MySQL versions before 1.23 and 2.09. In 1.23 and 2.09 or higher, turn parallel query on and off with aurora_parallel_query instead. For more information, see Working with parallel query for Amazon Aurora MySQL.

autocommit

Yes

automatic_sp_privileges

Yes

back_log

Yes

basedir

No

Aurora MySQL uses managed instances where you don't access the filesystem directly.

binlog_cache_size

Yes

binlog_max_flush_queue_time

Yes

binlog_order_commits

Yes

binlog_stmt_cache_size

Yes

bulk_insert_buffer_size

Yes

concurrent_insert

Yes

connect_timeout

Yes

core-file

No

Aurora MySQL uses managed instances where you don't access the filesystem directly.

datadir

No

Aurora MySQL uses managed instances where you don't access the filesystem directly.

default_time_zone

No

default_tmp_storage_engine

Yes

default_week_format

Yes

delay_key_write

Yes

delayed_insert_limit

Yes

delayed_insert_timeout

Yes

delayed_queue_size

Yes

div_precision_increment

Yes

end_markers_in_json

Yes

enforce_gtid_consistency

Sometimes

Modifiable in Aurora MySQL version 2.04 and later.

eq_range_index_dive_limit

Yes

event_scheduler

Yes

explicit_defaults_for_timestamp

Yes

flush

No

flush_time

Yes

ft_boolean_syntax

No

ft_max_word_len

Yes

ft_min_word_len

Yes

ft_query_expansion_limit

Yes

ft_stopword_file

Yes

general_log

Yes

For instructions on uploading the logs to CloudWatch Logs, see Publishing Amazon Aurora MySQL logs to Amazon CloudWatch Logs.

general_log_file

No

Aurora MySQL uses managed instances where you don't access the filesystem directly.

group_concat_max_len

Yes

gtid-mode

Sometimes

Modifiable in Aurora MySQL version 2.04 and later.

host_cache_size

Yes

init_connect

Yes

innodb_adaptive_hash_index

Yes

innodb_adaptive_max_sleep_delay

Yes

Modifying this parameter has no effect, because innodb_thread_concurrency is always 0 for Aurora.

innodb_autoextend_increment

Yes

innodb_buffer_pool_dump_at_shutdown

No

innodb_buffer_pool_dump_now

No

innodb_buffer_pool_filename

No

innodb_buffer_pool_load_abort

No

innodb_buffer_pool_load_at_startup

No

innodb_buffer_pool_load_now

No

innodb_buffer_pool_size

Yes

innodb_change_buffer_max_size

No

Aurora MySQL doesn't use the InnoDB change buffer at all.

innodb_compression_failure_threshold_pct

Yes

innodb_compression_level

Yes

innodb_compression_pad_pct_max

Yes

innodb_concurrency_tickets

Yes

Modifying this parameter has no effect, because innodb_thread_concurrency is always 0 for Aurora.

innodb_file_format

Yes

innodb_flush_log_at_timeout

No

innodb_flushing_avg_loops

No

innodb_force_load_corrupted

No

innodb_ft_aux_table

Yes

innodb_ft_cache_size

Yes

innodb_ft_enable_stopword

Yes

innodb_ft_server_stopword_table

Yes

innodb_ft_user_stopword_table

Yes

innodb_large_prefix

Yes

innodb_lock_wait_timeout

Yes

innodb_log_compressed_pages

No

innodb_lru_scan_depth

Yes

innodb_max_purge_lag

Yes

innodb_max_purge_lag_delay

Yes

innodb_monitor_disable

Yes

innodb_monitor_enable

Yes

innodb_monitor_reset

Yes

innodb_monitor_reset_all

Yes

innodb_old_blocks_pct

Yes

innodb_old_blocks_time

Yes

innodb_open_files

Yes

innodb_print_all_deadlocks

Yes

innodb_random_read_ahead

Yes

innodb_read_ahead_threshold

Yes

innodb_read_io_threads

No

innodb_read_only

No

Aurora MySQL manages the read-only and read/write state of DB instances based on the type of cluster. For example, a provisioned cluster has one read/write DB instance (the primary instance) and any other instances in the cluster are read-only (the Aurora Replicas).

innodb_replication_delay

Yes

innodb_sort_buffer_size

Yes

innodb_stats_auto_recalc

Yes

innodb_stats_method

Yes

innodb_stats_on_metadata

Yes

innodb_stats_persistent

Yes

innodb_stats_persistent_sample_pages

Yes

innodb_stats_transient_sample_pages

Yes

innodb_thread_concurrency

No

innodb_thread_sleep_delay

Yes

Modifying this parameter has no effect, because innodb_thread_concurrency is always 0 for Aurora.

interactive_timeout

Yes

join_buffer_size

Yes

keep_files_on_create

Yes

key_buffer_size

Yes

key_cache_age_threshold

Yes

key_cache_block_size

Yes

key_cache_division_limit

Yes

local_infile

Yes

lock_wait_timeout

Yes

log-bin

No

Setting binlog_format to STATEMENT, MIXED, or ROW automatically sets log-bin to ON. Setting binlog_format to OFF automatically sets log-bin to OFF. For more information, see Replication between Aurora and MySQL or between Aurora and another Aurora DB cluster (binlog replication).

log_bin_trust_function_creators

Yes

log_bin_use_v1_row_events

Yes

log_error

No

log_output

Yes

log_queries_not_using_indexes

Yes

log_slave_updates

No

log_throttle_queries_not_using_indexes

Yes

log_warnings

Yes

long_query_time

Yes

low_priority_updates

Yes

max_allowed_packet

Yes

max_binlog_cache_size

Yes

max_binlog_size

No

max_binlog_stmt_cache_size

Yes

max_connect_errors

Yes

max_connections

Yes

For more information, see Maximum connections to an Aurora MySQL DB instance.

max_delayed_threads

Yes

max_error_count

Yes

max_heap_table_size

Yes

max_insert_delayed_threads

Yes

max_join_size

Yes

max_length_for_sort_data

Yes

max_prepared_stmt_count

Yes

max_seeks_for_key

Yes

max_sort_length

Yes

max_sp_recursion_depth

Yes

max_tmp_tables

Yes

max_user_connections

Yes

max_write_lock_count

Yes

metadata_locks_cache_size

Yes

min_examined_row_limit

Yes

myisam_data_pointer_size

Yes

myisam_max_sort_file_size

Yes

myisam_mmap_size

Yes

myisam_sort_buffer_size

Yes

myisam_stats_method

Yes

myisam_use_mmap

Yes

net_buffer_length

Yes

net_read_timeout

Yes

net_retry_count

Yes

net_write_timeout

Yes

old-style-user-limits

Yes

old_passwords

Yes

optimizer_prune_level

Yes

optimizer_search_depth

Yes

optimizer_switch

Yes

For information about Aurora MySQL features that use this switch, see Best practices with Amazon Aurora MySQL.

optimizer_trace

Yes

optimizer_trace_features

Yes

optimizer_trace_limit

Yes

optimizer_trace_max_mem_size

Yes

optimizer_trace_offset

Yes

performance-schema-consumer-events-waits-current

Yes

performance-schema-instrument

Yes

performance_schema

Yes

performance_schema_accounts_size

Yes

performance_schema_consumer_global_instrumentation

Yes

performance_schema_consumer_thread_instrumentation

Yes

performance_schema_consumer_events_stages_current

Yes

performance_schema_consumer_events_stages_history

Yes

performance_schema_consumer_events_stages_history_long

Yes

performance_schema_consumer_events_statements_current

Yes

performance_schema_consumer_events_statements_history

Yes

performance_schema_consumer_events_statements_history_long

Yes

performance_schema_consumer_events_waits_history

Yes

performance_schema_consumer_events_waits_history_long

Yes

performance_schema_consumer_statements_digest

Yes

performance_schema_digests_size

Yes

performance_schema_events_stages_history_long_size

Yes

performance_schema_events_stages_history_size

Yes

performance_schema_events_statements_history_long_size

Yes

performance_schema_events_statements_history_size

Yes

performance_schema_events_transactions_history_long_size

Yes

Aurora MySQL 2.x only

performance_schema_events_transactions_history_size

Yes

Aurora MySQL 2.x only

performance_schema_events_waits_history_long_size

Yes

performance_schema_events_waits_history_size

Yes

performance_schema_hosts_size

Yes

performance_schema_max_cond_classes

Yes

performance_schema_max_cond_instances

Yes

performance_schema_max_digest_length

Yes

performance_schema_max_file_classes

Yes

performance_schema_max_file_handles

Yes

performance_schema_max_file_instances

Yes

performance_schema_max_index_stat

Yes

Aurora MySQL 2.x only

performance_schema_max_memory_classes

Yes

Aurora MySQL 2.x only

performance_schema_max_metadata_locks

Yes

Aurora MySQL 2.x only

performance_schema_max_mutex_classes

Yes

performance_schema_max_mutex_instances

Yes

performance_schema_max_prepared_statements_instances

Yes

Aurora MySQL 2.x only

performance_schema_max_program_instances

Yes

Aurora MySQL 2.x only

performance_schema_max_rwlock_classes

Yes

performance_schema_max_rwlock_instances

Yes

performance_schema_max_socket_classes

Yes

performance_schema_max_socket_instances

Yes

performance_schema_max_sql_text_length

Yes

Aurora MySQL 2.x only

performance_schema_max_stage_classes

Yes

performance_schema_max_statement_classes

Yes

performance_schema_max_statement_stack

Yes

Aurora MySQL 2.x only

performance_schema_max_table_handles

Yes

performance_schema_max_table_instances

Yes

performance_schema_max_table_lock_stat

Yes

Aurora MySQL 2.x only

performance_schema_max_thread_classes

Yes

performance_schema_max_thread_instances

Yes

performance_schema_session_connect_attrs_size

Yes

performance_schema_setup_actors_size

Yes

performance_schema_setup_objects_size

Yes

performance_schema_users_size

Yes

pid_file

No

plugin_dir

No

Aurora MySQL uses managed instances where you don't access the filesystem directly.

port

No

Aurora MySQL manages the connection properties and enforces consistent settings for all DB instances in a cluster.

preload_buffer_size

Yes

profiling_history_size

Yes

query_alloc_block_size

Yes

query_cache_limit

Yes

query_cache_min_res_unit

Yes

query_cache_size

Yes

query_cache_type

Yes

query_cache_wlock_invalidate

Yes

query_prealloc_size

Yes

range_alloc_block_size

Yes

read_buffer_size

Yes

read_only

No

Aurora MySQL manages the read-only and read/write state of DB instances based on the type of cluster. For example, a provisioned cluster has one read/write DB instance (the primary instance) and any other instances in the cluster are read-only (the Aurora Replicas).

read_rnd_buffer_size

Yes

relay-log

No

relay_log_info_repository

Yes

relay_log_recovery

No

safe-user-create

Yes

secure_auth

Yes

secure_file_priv

No

Aurora MySQL uses managed instances where you don't access the filesystem directly.

skip-slave-start

No

skip_external_locking

No

skip_show_database

Yes

slave_checkpoint_group

Yes

slave_checkpoint_period

Yes

slave_parallel_workers

Yes

slave_pending_jobs_size_max

Yes

slave_sql_verify_checksum

Yes

slow_launch_time

Yes

slow_query_log

Yes

For instructions on uploading the logs to CloudWatch Logs, see Publishing Amazon Aurora MySQL logs to Amazon CloudWatch Logs.

slow_query_log_file

No

Aurora MySQL uses managed instances where you don't access the filesystem directly.

socket

No

sort_buffer_size

Yes

sql_mode

Yes

sql_select_limit

Yes

stored_program_cache

Yes

sync_binlog

No

sync_master_info

Yes

sync_relay_log

Yes

sync_relay_log_info

Yes

sysdate-is-now

Yes

table_cache_element_entry_ttl

No

table_definition_cache

Yes

table_open_cache

Yes

table_open_cache_instances

Yes

temp-pool

Yes

thread_handling

No

thread_stack

Yes

timed_mutexes

Yes

tmp_table_size

Yes

tmpdir

No

Aurora MySQL uses managed instances where you don't access the filesystem directly.

transaction_alloc_block_size

Yes

transaction_prealloc_size

Yes

tx_isolation

Yes

updatable_views_with_limit

Yes

validate-password

No

validate_password_dictionary_file

No

validate_password_length

No

validate_password_mixed_case_count

No

validate_password_number_count

No

validate_password_policy

No

validate_password_special_char_count

No

wait_timeout

Yes

Inapplicable MySQL parameters and status variables

Because of architectural differences between Aurora MySQL and MySQL, some MySQL parameters and status variables don't apply to Aurora MySQL.

The following MySQL parameters don't apply to Aurora MySQL:

  • innodb_adaptive_flushing

  • innodb_adaptive_flushing_lwm

  • innodb_change_buffering

  • innodb_checksum_algorithm

  • innodb_doublewrite

  • innodb_flush_method

  • innodb_flush_neighbors

  • innodb_io_capacity

  • innodb_io_capacity_max

  • innodb_log_buffer_size

  • innodb_log_file_size

  • innodb_log_files_in_group

  • innodb_max_dirty_pages_pct

  • innodb_use_native_aio

  • innodb_write_io_threads

  • thread_cache_size

The following MySQL status variables don't apply to Aurora MySQL:

  • innodb_buffer_pool_bytes_dirty

  • innodb_buffer_pool_pages_dirty

  • innodb_buffer_pool_pages_flushed

Note

These lists are not exhaustive.

Aurora MySQL events

The following are some common wait events for Aurora MySQL.

Note

For information about the naming conventions used in MySQL wait events, see Performance Schema instrument naming conventions in the MySQL documentation.

io/aurora_redo_log_flush

In this wait event, a session is writing data to Aurora storage. Typically, this wait event is for a write I/O operation in Aurora MySQL.

io/aurora_respond_to_client

In this wait event, a thread is in the process of returning the result set to the client.

io/file/csv/data

In this wait event, there are threads writing to tables in comma-separated value (CSV) format. Check your CSV table usage. A typical cause of this event is setting log_output on a table.

io/file/innodb/innodb_data_file

In this wait event, there are threads waiting on I/O operations to storage. This event is more prevalent in I/O intensive workloads. SQL statements showing a comparatively large proportion of this wait event might be running disk intensive queries. Or they might be requesting data that can't be satisfied from the InnoDB buffer pool. To find out, check your query plans and cache hit ratios. For more information, see Buffering and caching in the MySQL documentation.

io/file/sql/binlog

In this wait event, there is a thread waiting on a binlog file that is being written to disk.

io/socket/sql/client_connection

In this wait event, a thread is in the process of handling a new connection.

io/table/sql/handler

This is a table I/O wait event. Typically, these types of events can be followed by a nested event such as a file I/O event. For more information about 'atom' and 'molecule' events in the Performance Schema, see Performance Schema atom and molecule events in the MySQL documentation.

lock/table/sql/handler

This wait event is a table lock wait event handler. For more information about 'atom' and 'molecule' events in the Performance Schema, see Performance Schema atom and molecule events in the MySQL documentation.

synch/cond/mysys/my_thread_var::suspend

In this wait event, threads are suspended when they are waiting on a condition. For example, this event occurs when threads are waiting for table level lock. We recommend that you investigate your workload to see what threads might be acquiring table locks on your DB instance. For more information about table locking in MySQL, see Table locking issues in the MySQL documentation.

synch/cond/sql/MDL_context::COND_wait_status

In this wait event, there are threads waiting on a table metadata lock. For more information, see Optimizing locking operations in the MySQL documentation.

synch/cond/sql/MYSQL_BIN_LOG::COND_done

In this wait event, there is a thread waiting on a binlog file that is being written to disk. Binary logging contention can occur on databases with a very high change rate.

synch/mutex/innodb/aurora_lock_thread_slot_futex

In this wait event, there is a thread that is waiting on an InnoDB record lock. If you see this event, check your database for conflicting workloads. For more information, see InnoDB locking in the MySQL documentation.

synch/mutex/innodb/buf_pool_mutex

In this wait event, a thread has acquired a lock on the InnoDB buffer pool.

synch/mutex/sql/LOCK_open

In this wait event, LOCK_open is being used to protect various objects in the data dictionary. This wait event indicates that there are threads waiting to acquire these locks. Typically, this event is caused by data dictionary contention.

synch/mutex/sql/LOCK_table_cache

In this wait event, there are threads waiting to acquire a lock on a table cache instance. For more information, see How MySQL opens and closes tables in the MySQL documentation.

synch/mutex/sql/LOG

In this wait event, there are threads waiting on a log lock. For example, a thread might wait for a lock to write to the slow query log file.

synch/mutex/sql/MYSQL_BIN_LOG::LOCK_commit

In this wait event, there is a thread that is waiting to acquire a lock with the intention of committing to the binary log. Binary logging contention can occur on databases with a very high change rate. Depending on your version of MySQL, there are certain locks being used to protect the consistency and durability of the binary log. In RDS MySQL, binary logs are used for replication and the automated backup process. In Aurora MySQL, binary logs are not needed for native replication or backups. They are disabled by default but can be enabled and used for external replication or change data capture. For more information, see The binary log in the MySQL documentation.

synch/mutex/sql/MYSQL_BIN_LOG::LOCK_log

In this wait event, threads are actively locking the binary log file. Binary logging contention can occur on databases with a very high change rate. Depending on your version of MySQL, there are certain locks being used to protect the consistency and durability of the binary log.

synch/rwlock/innodb/dict

In this wait event, there are threads waiting on an rwlock held on the InnoDB data dictionary.

synch/rwlock/innodb/dict sys RW lock

In this event, there are threads that are waiting on an rwlock held on the InnoDB data dictionary.

synch/rwlock/innodb/dict_operation_lock

In this wait event, there are threads holding locks on InnoDB data dictionary operations.

Aurora MySQL isolation levels

Following, you can learn how DB instances in an Aurora MySQL cluster implement the database property of isolation. Doing so helps you understand how the Aurora MySQL default behavior balances between strict consistency and high performance. You can also decide when to change the default settings based on the characteristics of your workload.

Available isolation levels for writer instances

You can use the isolation levels REPEATABLE READ, READ COMMITTED, READ UNCOMMITTED, and SERIALIZABLE on the primary instance of an Aurora MySQL single-master cluster, or any DB instance in an Aurora MySQL multi-master cluster. These isolation levels work the same in Aurora MySQL as in RDS MySQL.

REPEATABLE READ isolation level for reader instances

By default, Aurora MySQL DB instances configured as read-only Aurora Replicas always use the REPEATABLE READ isolation level. These DB instances ignore any SET TRANSACTION ISOLATION LEVEL statements and continue using the REPEATABLE READ isolation level.

READ COMMITTED isolation level for reader instances

If your application includes a write-intensive workload on the primary instance and long-running queries on the Aurora Replicas, you might experience substantial purge lag. Purge lag happens when internal garbage collection is blocked by long-running queries. The symptom that you see is a high value for history list length in output from the SHOW ENGINE INNODB STATUS command. You can monitor this value using the RollbackSegmentHistoryListLength metric in CloudWatch. This condition can reduce the effectiveness of secondary indexes and lead to reduced overall query performance and wasted storage space.

If you experience such issues, you can use an Aurora MySQL session-level configuration setting, aurora_read_replica_read_committed, to use the READ COMMITTED isolation level on Aurora Replicas. Using this setting can help reduce slowdowns and wasted space that can result from performing long-running queries at the same time as transactions that modify your tables.

We recommend making sure that you understand the specific Aurora MySQL behavior of the READ COMMITTED isolation before using this setting. The Aurora Replica READ COMMITTED behavior complies with the ANSI SQL standard. However, the isolation is less strict than typical MySQL READ COMMITTED behavior that you might be familiar with. Thus, you might see different query results under READ COMMITTED on an Aurora MySQL read replica than for the same query under READ COMMITTED on the Aurora MySQL primary instance or on Amazon RDS MySQL. You might use the aurora_read_replica_read_committed setting for such use cases as a comprehensive report that scans a very large database. You might avoid it for short queries with small result sets, where precision and repeatability are important.

The READ COMMITTED isolation level isn't available for sessions within a secondary cluster in an Aurora global database that use the write forwarding feature. For information about write forwarding, see Write forwarding for secondary AWS Regions with an Aurora global database.

Enabling READ COMMITTED for readers

To enable the READ COMMITTED isolation level for Aurora Replicas, enable the aurora_read_replica_read_committed configuration setting. Enable this setting at the session level while connected a specific Aurora Replica. To do so, run the following SQL commands. 


set session aurora_read_replica_read_committed = ON;
set session transaction isolation level read committed;

You might enable this configuration setting temporarily to perform interactive ad hoc (one-time) queries. You might also want to run a reporting or data analysis application that benefits from the READ COMMITTED isolation level, while leaving the default unchanged for other applications.

When the aurora_read_replica_read_committed setting is enabled, use the SET TRANSACTION ISOLATION LEVEL command to specify the isolation level for the appropriate transactions. 


set transaction isolation level read committed;

Differences in READ COMMITTED behavior on Aurora replicas

The aurora_read_replica_read_committed setting makes the READ COMMITTED isolation level available for an Aurora Replica, with consistency behavior that is optimized for long-running transactions. The READ COMMITTED isolation level on Aurora Replicas has less strict isolation than on Aurora primary instances or multi-master instances. For that reason, enable this setting only on Aurora Replicas where you know that your queries can accept the possibility of certain types of inconsistent results.

Your queries can experience certain kinds of read anomalies when the aurora_read_replica_read_committed setting is turned on. Two kinds of anomalies are especially important to understand and handle in your application code. A non-repeatable read occurs when another transaction commits while your query is running. A long-running query can see different data at the start of the query than it sees at the end. A phantom read occurs when other transactions cause existing rows to be reorganized while your query is running, and one or more rows are read twice by your query.

Your queries might experience inconsistent row counts as a result of phantom reads. Your queries might also return incomplete or inconsistent results due to non-repeatable reads. For example, suppose that a join operation refers to tables that are concurrently modified by SQL statements such as INSERT or DELETE. In this case, the join query might read a row from one table but not the corresponding row from another table.

The ANSI SQL standard allows both of these behaviors for the READ COMMITTED isolation level. However, those behaviors are different than the typical MySQL implementation of READ COMMITTED. Thus, before enabling the aurora_read_replica_read_committed setting, check any existing SQL code to verify if it operates as expected under the looser consistency model.

Row counts and other results might not be strongly consistent under the READ COMMITTED isolation level while this setting is enabled. Thus, you typically enable the setting only while running analytic queries that aggregate large amounts of data and don't require absolute precision. If you don't have these kinds of long-running queries alongside a write-intensive workload, you probably don't need the aurora_read_replica_read_committed setting. Without the combination of long-running queries and a write-intensive workload, you're unlikely to encounter issues with the length of the history list.

Example Queries showing isolation behavior for READ COMMITTED on Aurora replicas

The following example shows how READ COMMITTED queries on an Aurora Replica might return non-repeatable results if transactions modify the associated tables at the same time. The table BIG_TABLE contains 1 million rows before any queries start. Other data manipulation language (DML) statements add, remove, or change rows while the are running.

The queries on the Aurora primary instance under the READ COMMITTED isolation level produce predictable results. However, the overhead of keeping the consistent read view for the lifetime of every long-running query can lead to expensive garbage collection later.

The queries on the Aurora Replica under the READ COMMITTED isolation level are optimized to minimize this garbage collection overhead. The tradeoff is that the results might vary depending on whether the queries retrieve rows that are added, removed, or reorganized by transactions that commit while the query is running. The queries are allowed to consider these rows but aren't required to. For demonstration purposes, the queries check only the number of rows in the table by using the COUNT(*) function.

Time DML statement on Aurora primary instance Query on Aurora primary instance with READ COMMITTED Query on Aurora replica with READ COMMITTED
T1 INSERT INTO big_table SELECT * FROM other_table LIMIT 1000000; COMMIT;
T2 Q1: SELECT COUNT(*) FROM big_table; Q2: SELECT COUNT(*) FROM big_table;
T3 INSERT INTO big_table (c1, c2) VALUES (1, 'one more row'); COMMIT;
T4 If Q1 finishes now, result is 1,000,000. If Q2 finishes now, result is 1,000,000 or 1,000,001.
T5 DELETE FROM big_table LIMIT 2; COMMIT;
T6 If Q1 finishes now, result is 1,000,000. If Q2 finishes now, result is 1,000,000 or 1,000,001 or 999,999 or 999,998.
T7 UPDATE big_table SET c2 = CONCAT(c2,c2,c2); COMMIT;
T8 If Q1 finishes now, result is 1,000,000. If Q2 finishes now, result is 1,000,000 or 1,000,001 or 999,999, or possibly some higher number.
T9 Q3: SELECT COUNT(*) FROM big_table; Q4: SELECT COUNT(*) FROM big_table;
T10 If Q3 finishes now, result is 999,999. If Q4 finishes now, result is 999,999.
T11 Q5: SELECT COUNT(*) FROM parent_table p JOIN child_table c ON (p.id = c.id) WHERE p.id = 1000; Q6: SELECT COUNT(*) FROM parent_table p JOIN child_table c ON (p.id = c.id) WHERE p.id = 1000;
T12 INSERT INTO parent_table (id, s) VALUES (1000, 'hello'); INSERT INTO child_table (id, s) VALUES (1000, 'world'); COMMIT;
T13 If Q5 finishes now, result is 0. If Q6 finishes now, result is 0 or 1.

If the queries finish quickly, before any other transactions perform DML statements and commit, the results are predictable and the same between the primary instance and the Aurora Replica.

The results for Q1 are highly predictable, because READ COMMITTED on the primary instance uses a strong consistency model similar to the REPEATABLE READ isolation level.

The results for Q2 might vary depending on what transactions commit while that query is running. For example, suppose that other transactions perform DML statements and commit while the queries are running. In this case, the query on the Aurora Replica with the READ COMMITTED isolation level might or might not take the changes into account. The row counts are not predictable in the same way as under the REPEATABLE READ isolation level. They also aren't as predictable as queries running under the READ COMMITTED isolation level on the primary instance, or on an RDS MySQL instance.

The UPDATE statement at T7 doesn't actually change the number of rows in the table. However, by changing the length of a variable-length column, this statement can cause rows to be reorganized internally. A long-running READ COMMITTED transaction might see the old version of a row, and later within the same query see the new version of the same row. The query can also skip both the old and new versions of the row. Thus, the row count might be different than expected.

The results of Q5 and Q6 might be identical or slightly different. Query Q6 on the Aurora Replica under READ COMMITTED is able to see, but is not required to see, the new rows that are committed while the query is running. It might also see the row from one table but not from the other table. If the join query doesn't find a matching row in both tables, it returns a count of zero. If the query does find both the new rows in PARENT_TABLE and CHILD_TABLE, the query returns a count of one. In a long-running query, the lookups from the joined tables might happen at widely separated times.

Note

These differences in behavior depend on the timing of when transactions are committed and when the queries process the underlying table rows. Thus, you're most likely to see such differences in report queries that take minutes or hours and that run on Aurora clusters processing OLTP transactions at the same time. These are the kinds of mixed workloads that benefit the most from the READ COMMITTED isolation level on Aurora Replicas.

Aurora MySQL hints

You can use SQL hints with Aurora MySQL queries to fine-tune performance. You can also use hints to prevent execution plans for important queries to change based on unpredictable conditions.

Tip

To verify the effect that a hint has on a query, examine the query plan produced by the EXPLAIN statement. Compare the query plans with and without the hint.

The following hints apply to queries that use the hash join feature. These hints are available in Aurora MySQL 2.08 and higher.

HASH_JOIN, NO_HASH_JOIN

Turns on or off the ability of the optimizer to choose whether to use the hash join optimization method for a query. HASH_JOIN enables the optimizer to use hash join if that mechanism is more efficient. NO_HASH_JOIN prevents the optimizer from using hash join for the query. This hint is available in Aurora MySQL 2.08 and higher.

The following examples show how to use this hint. 


EXPLAIN SELECT/*+ HASH_JOIN(t2) */ f1, f2
  FROM t1, t2 WHERE t1.f1 = t2.f1;

EXPLAIN SELECT /*+ NO_HASH_JOIN(t2) */ f1, f2
  FROM t1, t2 WHERE t1.f1 = t2.f1;
HASH_JOIN_PROBING, NO_HASH_JOIN_PROBING

In a hash join query, specifies whether or not to use the specified table for the probe side of the join. The query tests whether column values from the build table exist in the probe table, instead of reading the entire contents of the probe table. You can use HASH_JOIN_PROBING and HASH_JOIN_BUILDING to specify how hash join queries are processed without reordering the tables within the query text. This hint is available in Aurora MySQL 2.08 and higher.

The following examples show how to use this hint. Specifying the HASH_JOIN_PROBING hint for the table T2 has the same effect as specifying NO_HASH_JOIN_PROBING for the table T1. 


EXPLAIN SELECT /*+ HASH_JOIN(t2) HASH_JOIN_PROBING(t2) */ f1, f2
  FROM t1, t2 WHERE t1.f1 = t2.f1;

EXPLAIN SELECT /*+ HASH_JOIN(t2) NO_HASH_JOIN_PROBING(t1) */ f1, f2
  FROM t1, t2 WHERE t1.f1 = t2.f1;
HASH_JOIN_BUILDING, NO_HASH_JOIN_BUILDING

In a hash join query, specifies whether or not to use the specified table for the build side of the join. The query processes all the rows from this table to build the list of column values to cross-reference with the other table. You can use HASH_JOIN_PROBING and HASH_JOIN_BUILDING to specify how hash join queries are processed without reordering the tables within the query text. This hint is available in Aurora MySQL 2.08 and higher.

The following examples show how to use this hint. Specifying the HASH_JOIN_BUILDING hint for the table T2 has the same effect as specifying NO_HASH_JOIN_BUILDING for the table T1. 


EXPLAIN SELECT /*+ HASH_JOIN(t2) HASH_JOIN_BUILDING(t2) */ f1, f2
  FROM t1, t2 WHERE t1.f1 = t2.f1;

EXPLAIN SELECT /*+ HASH_JOIN(t2) NO_HASH_JOIN_BUILDING(t1) */ f1, f2
  FROM t1, t2 WHERE t1.f1 = t2.f1;
JOIN_FIXED_ORDER

Specifies that tables in the query are joined based on the order they are listed in the query. It is especially useful with queries involving three or more tables. It is intended as a replacement for the MySQL STRAIGHT_JOIN hint. Equivalent to the MySQL JOIN_FIXED_ORDER hint. This hint is available in Aurora MySQL 2.08 and higher.

The following examples show how to use this hint. 


EXPLAIN SELECT /*+ JOIN_FIXED_ORDER */ f1, f2
  FROM t1 JOIN t2 USING (id) JOIN t3 USING (id) JOIN t4 USING (id);
JOIN_ORDER

Specifies the join order for the tables in the query. It is especially useful with queries involving three or more tables. Equivalent to the MySQL JOIN_ORDER hint. This hint is available in Aurora MySQL 2.08 and higher.

The following examples show how to use this hint. 


EXPLAIN SELECT /*+ JOIN_ORDER (t4, t2, t1, t3) */ f1, f2
  FROM t1 JOIN t2 USING (id) JOIN t3 USING (id) JOIN t4 USING (id);
JOIN_PREFIX

Specifies the tables to put first in the join order. It is especially useful with queries involving three or more tables. Equivalent to the MySQL JOIN_PREFIX hint. This hint is available in Aurora MySQL 2.08 and higher.

The following examples show how to use this hint. 


EXPLAIN SELECT /*+ JOIN_ORDER (t4, t2) */ f1, f2
  FROM t1 JOIN t2 USING (id) JOIN t3 USING (id) JOIN t4 USING (id);
JOIN_SUFFIX

Specifies the tables to put last in the join order. It is especially useful with queries involving three or more tables. Equivalent to the MySQL JOIN_SUFFIX hint. This hint is available in Aurora MySQL 2.08 and higher.

The following examples show how to use this hint. 


EXPLAIN SELECT /*+ JOIN_ORDER (t1, t3) */ f1, f2
  FROM t1 JOIN t2 USING (id) JOIN t3 USING (id) JOIN t4 USING (id);

For information about using hash join queries, see Working with hash joins in Aurora MySQL.

Aurora MySQL stored procedures

You can call the following stored procedures while connected to the primary instance in an Aurora MySQL cluster. These procedures control how transactions are replicated from an external database into Aurora MySQL, or from Aurora MySQL to an external database. To learn how to use replication based on global transaction identifiers (GTIDs) with Aurora MySQL, see Using GTID-based replication for Aurora MySQL.

mysql.rds_set_master_auto_position

Sets the replication mode to be based on either binary log file positions or on global transaction identifiers (GTIDs).

Syntax


CALL mysql.rds_set_master_auto_position (auto_position_mode);

Parameters

auto_position_mode

A value that indicates whether to use log file position replication or GTID-based replication:

  • 0 – Use the replication method based on binary log file position. The default is 0.

  • 1 – Use the GTID-based replication method.

Usage notes

For an Aurora MySQL DB cluster, you call this stored procedure while connected to the primary instance.

The master user must run the mysql.rds_set_master_auto_position procedure.

For Aurora, this procedure is supported for Aurora MySQL version 2.04 and later MySQL 5.7–compatible versions. GTID-based replication isn't supported for Aurora MySQL 1.1 or 1.0.

mysql.rds_set_external_master_with_auto_position

Configures an Aurora MySQL primary instance to accept incoming replication from an external MySQL instance. This procedure also configures replication based on global transaction identifiers (GTIDs).

This procedure is available for both Amazon RDS MySQL and Aurora MySQL. It works differently depending on the context. When used with Aurora MySQL, this procedure doesn't configure delayed replication. This limitation is because Amazon RDS MySQL supports delayed replication but Aurora MySQL doesn't.

Syntax


CALL mysql.rds_set_external_master_with_auto_position (
  host_name
  , host_port
  , replication_user_name
  , replication_user_password
  , ssl_encryption
);

Parameters

host_name

The host name or IP address of the MySQL instance running external to Aurora to become the replication master.

host_port

The port used by the MySQL instance running external to Aurora to be configured as the replication master. If your network configuration includes Secure Shell (SSH) port replication that converts the port number, specify the port number that is exposed by SSH.

replication_user_name

The ID of a user with REPLICATION CLIENT and REPLICATION SLAVE permissions on the MySQL instance running external to Aurora. We recommend that you provide an account that is used solely for replication with the external instance.

replication_user_password

The password of the user ID specified in replication_user_name.

ssl_encryption

This option is not currently implemented. The default is 0.

Usage notes

For an Aurora MySQL DB cluster, you call this stored procedure while connected to the primary instance.

The master user must run the mysql.rds_set_external_master_with_auto_position procedure. The master user runs this procedure on the primary instance of an Aurora MySQL DB cluster that acts as a replication target. This can be the replication target of an external MySQL DB instance or an Aurora MySQL DB cluster.

For Aurora, this procedure is supported for Aurora MySQL version 2.04 and later MySQL 5.7-compatible versions. GTID-based replication isn't supported for Aurora MySQL 1.1 or 1.0.

Before you run mysql.rds_set_external_master_with_auto_position, configure the external MySQL DB instance to be a replication master. To connect to the external MySQL instance, specify values for replication_user_name and replication_user_password. These values must indicate a replication user that has REPLICATION CLIENT and REPLICATION SLAVE permissions on the external MySQL instance.

To configure an external MySQL instance as a replication master

  1. Using the MySQL client of your choice, connect to the external MySQL instance and create a user account to be used for replication. The following is an example. 

    
CREATE USER 'repl_user'@'mydomain.com' IDENTIFIED BY 'SomePassW0rd'

  2. On the external MySQL instance, grant REPLICATION CLIENT and REPLICATION SLAVE privileges to your replication user. The following example grants REPLICATION CLIENT and REPLICATION SLAVE privileges on all databases for the 'repl_user' user for your domain. 

    
GRANT REPLICATION CLIENT, REPLICATION SLAVE ON *.* TO 'repl_user'@'mydomain.com'
IDENTIFIED BY 'SomePassW0rd'

When you call mysql.rds_set_external_master_with_auto_position, Amazon RDS records certain information. This information is the time, the user, and an action of "set master" in the mysql.rds_history and mysql.rds_replication_status tables.

To skip a specific GTID-based transaction that is known to cause a problem, you can use the mysql.rds_skip_transaction_with_gtid stored procedure. For more information about working with GTID-based replication, see Using GTID-based replication for Aurora MySQL.

Examples

When run on an Aurora primary instance, the following example configures the Aurora cluster to act as a read replica of an instance of MySQL running external to Aurora. 


call mysql.rds_set_external_master_with_auto_position(
  'Externaldb.some.com',
  3306,
  'repl_user'@'mydomain.com',
  'SomePassW0rd');

mysql.rds_skip_transaction_with_gtid

Skips replication of a transaction with the specified global transaction identifier (GTID) on an Aurora primary instance.

You can use this procedure for disaster recovery when a specific GTID transaction is known to cause a problem. Use this stored procedure to skip the problematic transaction. Examples of problematic transactions include transactions that disable replication, delete important data, or cause the DB instance to become unavailable.

Syntax


CALL mysql.rds_skip_transaction_with_gtid (gtid_to_skip);

Parameters

gtid_to_skip

The GTID of the replication transaction to skip.

Usage notes

For an Aurora MySQL DB cluster, you call this stored procedure while connected to the primary instance.

The master user must run the mysql.rds_skip_transaction_with_gtid procedure.

For Aurora, this procedure is supported for Aurora MySQL version 2.04 and later MySQL 5.7-compatible versions. GTID-based replication isn't supported for Aurora MySQL 1.1 or 1.0.