Query optimization techniques in SQL

This is an advanced course which embodies an aggregation of all the neccessery techniques to write optimized queries.
Free tutorial
Rating: 4.3 out of 5 (52 ratings)
5,587 students
57min of on-demand video
English
English [Auto]

To learn how to read and use the query plan in SQL.
To study different join algorithms and best conditions of it application.
To master the optimal usage of indexing depending on the task
To master superior features and functionality of SQL by using partitioning, hints, caching, e.t.c

Requirements

  • Basic SQL knowledge including the ability to write basic SQL queries, to use aggregate and analytical functions and to write your own functions.

Description

This course is designed for people who want to master SQL at the middle and senior levels. We will discuss the Oracle database as an example, but all the working and research methods can be applied to other relational databases.

In our course, we will talk about such an important aspect as query optimization and will deeper analyze the theoretical questions that may be useful not only for successful work, but also for the interviews. The focus will be on the technical implementation of the acquired knowledge, paying the most attention to the "under the hood" operation.

What you should already be able to do

- write basic SQL queries

⁃ use aggregate functions

⁃ use analytical functions

⁃ write your own functions (in PLSQL or, speaking of Oracle, using the with construction: a new feature introduced by Oracle, and according to the presentation, it should work 4 times faster than PLSQL variant).

In this course we will go through:

- query plan and how to read it

- join algorithms

- hints and statistics

- indexing

- caching

- partitioning

- use of temporary, intermediate tables and materialized views

Mastering the topics mentioned above will drastically improve an overall perfomance of your SQL queries and will allow you to properly time manage your applications with the most efficient use of available resources.

Who this course is for:

  • Developers/analysts who are working with databases and want to do it more efficiently.

Instructors

Data Engineer Innotech
Nikita Vasilev
  • 4.3 Instructor Rating
  • 52 Reviews
  • 5,587 Students
  • 1 Course

Senior Data Engineer, 5+ YOE in insurance & retail banking with expertise in highload scalable applications and data processing.

Teacher, tech writer, hackathon judge/mentor.

technical skills

Languages : Python, SQL, PL/SQL, Scala

Technologies : Spark, Hadoop, Airflow, Oracle Apex, Cron

Databases : Oracle, Teradata, Hive, Impala, Greenplum, Postgres

Tools: Git, Jira, Bitbucket, Confluence, Teamcity, Nexus, Maven

Familiar with: Data Science, Html, Css, JS

Data engineer
Arsen Petrenko
  • 4.3 Instructor Rating
  • 52 Reviews
  • 5,587 Students
  • 1 Course

5 years of experience in condensed matter physics as a beam scientist, over 20 scientific publications. Data Engineer/Analysis with 3 years of experience in building efficient, scalable, and resilient distributed data pipelines for collecting, cleaning, and aggregating large volumes of data.

School teacher, scientific competition judge.

My main technical skills

Languages : Python, С++, Scala, SQL, PL/SQL, VBA

Technologies : Spark, Hadoop,  Airflow,  Linux/Unix/Windows cli, Fast load, Fast export

Databases : Oracle, Hive, MS sql, MySql, Impala

Tools: Git, Jira, Bitbucket, Confluence

Familiar with: Data Science

Data Engineer
Veronika Vasileva
  • 4.3 Instructor Rating
  • 52 Reviews
  • 5,587 Students
  • 1 Course

Data Engineer/Analysis with 5+ years of experience in building efficient, scalable, and resilient distributed data pipelines for collecting, cleaning, and aggregating large volumes of data.

University teacher, technical writer, and hackathon judge, mentor.

My main technical skills

Languages : Python, SQL, PL/SQL, VBA

Technologies : pySpark, Hadoop, Text Mining, Oracle apex, Airflow, Cron, Linux/Unix/Windows cli, Fast load, Fast export, xml, VS Business intelligence

Databases : Oracle, Greenplum, Hive, Teradata, MS sql, MySql, Impala

Tools: Git, Jira, Bitbucket, confluence

Familiar with: Data Science, Html, Css, JS

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