- Introduction
- Query Plan
- How to read the query plan
- Join algorithms
- Indexes
- Hints
- Statistics
- Partitioning
- Caching
- Temporary, staging tables, and materialized views
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.
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Set a goal and achieve it before Christmas | goal setting | sales | business
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