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SQL Tuning You Can Run Yourself: Preparing for the SQLP Practical Exam

I’ll learn SQLP practical tuning by reproducing the execution plans from the course on my own PC using Oracle 26ai Free. I’ll evaluate 30 hands-on practice problems I created myself using measured figures (blocks read and execution counts), then write out the answers as well.

1 learners are taking this course

Level Intermediate

Course period Unlimited

SQL
SQL
Oracle
Oracle
database-tuning
database-tuning
database
database
SQL
SQL
Oracle
Oracle
database-tuning
database-tuning
database
database

What you will gain after the course

  • Read Starts, A-Rows, and Buffers in the DISPLAY_CURSOR execution plan to pinpoint the steps where inefficiencies occur.

  • We compare index column order, covering indexes, and function-based indexes using actual measurements, then explain the design rationale in our answer.

  • Choose nested-loop, hash, or sort-merge joins and the driving order based on data distribution, then fix them with hints.

  • Using measurements from 23ai, this explains why query transformations, statistics, and bind variables change execution plans.

  • Improve Top-N, pagination, DML, batch, partitioning, and locking issues, with bidirectional MINUS validation to ensure identical results.

  • Solve practical tuning and troubleshooting mock questions within the time limit, and structure your answers to match the grading criteria.

Recommended for
these people

Who is this course right for?

  • Developers and DBAs preparing for the SQLP practical exam who don’t have an environment to run execution plans themselves.

  • An examinee confused because the execution plans in the textbook for 10g/11g differ from the results in the latest version of Oracle.

  • A backend developer looking to learn SQL tuning as a basis for real-world decision-making, not just for exams.

Need to know before starting?

  • Basic SQL knowledge sufficient to read and write SELECT, JOIN, and GROUP BY queries.

  • Enough experience to copy and run commands in a terminal.

  • A personal computer capable of running Docker (8 GB of RAM or more recommended). macOS was tested during the course; general instructions are provided for Windows.

Hello
This is dorian05202988

Career Verified

A data craftsman with over 20 years of experience in databases and IT. As a DBA and manager of a DB Platform team, I work with database platforms and specialize in MySQL, PostgreSQL, Oracle, MongoDB, SQL tuning, AWS, Terraform, and Python. Drawing on experience in the gaming, finance, and IT services industries, I explain database and cloud architecture. I have published 『Oracle Practical Tuning: Learning SQL Patterns』 and 『Oracle Pro*C Practical Project Guide』, and have presented on serverless architectures, database selection, and multi-database strategies at AWS Summit 2018 and 2019 and DataYa Nolja 2020. Recently, I have been working on slow-query analysis and tuning recommendations using Bedrock LLM, automated DB specification sizing, and query workflows through a DB metadata MCP server and Slack bot. I explain database automation for developers and AI applications for non-developers through hands-on exercises tailored to the audience and objectives of each course. Rather than applying AI suggestions as-is, I teach a decision-making framework that verifies result equivalence, execution plans, and observability conditions, and defers action when the supporting evidence is insufficient. Company operational data and credentials are not included in the course materials.

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Curriculum

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65 lectures ∙ (2hr 54min)

Course Materials:

Lecture resources
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