Enhancing Query Performance: Leveraging In-Memory Optimized Dates in Oracle 23ai

In-Memory Column Store

Unlike traditional row-based storage, The In-Memory Column Store (IM column store) stores tables and partitions in memory using a columnar format optimized for rapid scans. This columnar format is optimized for analytical workloads, allowing for efficient scanning of specific columns without needing to read entire rows. 

In-Memory Optimized Dates

To enhance the performance of DATE-based queries DATE components (i.e. DAY, MONTH, YEAR) can be extracted and populated in the IM column store leveraging the In-Memory Expressions framework. This approach enables faster query processing on DATE columns, significantly improving the performance of date-based analytic queries.

Enhancing Efficiency in Oracle 23ai: Using the Automatic SQL Transpiler

 

What is Context Switching between PL/SQL and SQL?

The PL/SQL engine is a virtual machine that resides in memory and processes the PL/SQL m-code instructions. When the PL/SQL engine encounters an SQL statement, a context switch is made to pass the SQL statement to the Oracle server processes. The PL/SQL engine waits for the SQL statement to complete and for the results to be returned before it continues to process subsequent statements in the PL/SQL block. 

In other words, context switching in Oracle databases refers to the overhead incurred when control shifts between the SQL engine and the PL/SQL engine during the execution of mixed SQL and PL/SQL code. The two engines operate in different runtime environments, so when you run SQL statements within PL/SQL code, the database has to 'switch' between these environments. This switching can cause performance degradation.

Automatic PL/SQL to SQL Transpiler

PL/SQL functions within SQL statements are automatically converted (transpiled) into SQL expressions whenever possible.

Exploring Bigfile Tablespaces with Default Settings in oracle 23ai

BIGFILE Tablespace

A bigfile tablespace is a tablespace with a single, but large datafile. Traditional small file tablespaces, in contrast, typically contain multiple datafiles, but the files cannot be as large. Making SYSUAX, SYSTEM and USER tablespaces bigfile by default will benefit large databases by reducing the number of datafiles, thereby simplifying datafile, tablespace and overall global database management for users.