Database Optimization and Performance Tuning

Database Optimization and Performance Tuning Paper
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Database Optimization and Performance Tuning Paper
As part of the database management system (DBMS), a query optimizer analyzes queries in the Structured Query Language (SQL) to determine efficient implementation mechanisms (Gulutzan et al., 2003). Optimization is critical in generating the right access plans for queries. For example, when using cursors, optimization commences once the cursor is opened. Furthermore, SQL Anywhere is specifically important because it optimizes every statement before its execution (Gulutzan et al., 2003).
There are several phases that a statement goes through during optimization. The first phase is an annotation (Gulutzan et al., 2003). The annotation phase involves the transformation of the statement into a parse tree. Once the annotation phase is complete, the query rewrite phase begins. In this phase, rewrite optimizations are applied as part of the required iterative semantic transformations. The third phase is the optimization phase. In this phase, a query optimization structure is completed and possible access plans enumerated. The fourth phase is the plan building phase. Here, the best access plan is adopted and used to build a representation of the execution plan. In the execution phase, the result is computed using the execution plan (Gulutzan et al., 2003).
A SQL query designed to collect information from a database can degrade a server’s performance. In this case, it is important to find such queries and improve them. This can be done by rethinking and selecting a more efficient execution of an SQL statement (Niemiec, 2017). However, the process involves gathering statistics to determine the best way of executing the given SQL query. Finding and fixing the errors manually takes time. However, with current technology and software advancements, one can automatically optimize selected SQL queries or create tasks that can improve them. Both processes require optimizer tools. One of the tools used is the SolarWinds Database Performance Analyzer. This optimization tool spots inefficiencies in data access. Another tool is the SentryOne SQL Sentry. This tool utilizes a Top SQL facility to analyze SQL queries for optimization (Niemiec, 2017). 
Typically, database performance is measured using queries per second (QPS) (Mittra, 2002). QPS helps in identifying the number of queries that a database can execute in a given time. However, queries are usually dissimilar. There are UPDATEs, INSERTs, and SELECTs. There are simple queries, and t...