Overview of Amazon Aurora MySQL - Amazon Aurora
Amazon Aurora MySQL performance enhancementsAurora MySQL and spatial data

Overview of Amazon Aurora MySQL

The following sections provide an overview of Amazon Aurora MySQL.

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Amazon Aurora MySQL performance enhancements

Amazon Aurora includes performance enhancements to support the diverse needs of high-end commercial databases.

Fast insert

Fast insert accelerates parallel inserts sorted by primary key and applies specifically to LOAD DATA and INSERT INTO ... SELECT ... statements. Fast insert caches the position of a cursor in an index traversal while executing the statement. This avoids unnecessarily traversing the index again.

You can monitor the following metrics to determine the effectiveness of fast insert for your DB cluster:

  • aurora_fast_insert_cache_hits: A counter that is incremented when the cached cursor is successfully retrieved and verified.

  • aurora_fast_insert_cache_misses: A counter that is incremented when the cached cursor is no longer valid and Aurora performs a normal index traversal.

You can retrieve the current value of the fast insert metrics using the following command: 


mysql> show global status like 'Aurora_fast_insert%';

You will get output similar to the following:


+---------------------------------+-----------+
| Variable_name                   | Value     |
+---------------------------------+-----------+
| Aurora_fast_insert_cache_hits   | 3598300   |
| Aurora_fast_insert_cache_misses | 436401336 |
+---------------------------------+-----------+

Amazon Aurora MySQL and spatial data

The following list summarizes the main Aurora MySQL spatial features and explains how they correspond to spatial features in MySQL:

  • Aurora MySQL 1.x supports the same spatial data types and spatial relation functions as MySQL 5.6. For more information about these data types and functions, see Spatial Data Types and Spatial Relation Functions in the MySQL 5.6 documentation.

  • Aurora MySQL 2.x supports the same spatial data types and spatial relation functions as MySQL 5.7. For more information about these data types and functions, see Spatial Data Types and Spatial Relation Functions in the MySQL 5.7 documentation.

  • Aurora MySQL 3.x supports the same spatial data types and spatial relation functions as MySQL 8.0. For more information about these data types and functions, see Spatial Data Types and Spatial Relation Functions in the MySQL 8.0 documentation.

  • Aurora MySQL supports spatial indexing on InnoDB tables. Spatial indexing improves query performance on large datasets for queries on spatial data. In MySQL, spatial indexing for InnoDB tables isn't available in MySQL 5.6, but is available in MySQL 5.7 and 8.0. Aurora MySQL uses a different spatial indexing strategy than MySQL for high performance with spatial queries. The Aurora spatial index implementation uses a space-filling curve on a B-tree, which is intended to provide higher performance for spatial range scans than an R-tree.

The following data definition language (DDL) statements are supported for creating indexes on columns that use spatial data types.

CREATE TABLE

You can use the SPATIAL INDEX keywords in a CREATE TABLE statement to add a spatial index to a column in a new table. Following is an example. 

CREATE TABLE test (shape POLYGON NOT NULL, SPATIAL INDEX(shape));

ALTER TABLE

You can use the SPATIAL INDEX keywords in an ALTER TABLE statement to add a spatial index to a column in an existing table. Following is an example. 

ALTER TABLE test ADD SPATIAL INDEX(shape);

CREATE INDEX

You can use the SPATIAL keyword in a CREATE INDEX statement to add a spatial index to a column in an existing table. Following is an example. 

CREATE SPATIAL INDEX shape_index ON test (shape);