EdX

Hacking PostgreSQL: Data Access Methods (edX)

Hacking PostgreSQL: Data Access Methods (edX)

Learn the science, engineering practices and hacking techniques of data access – core aspects of information processing in a database. This course is about data storage and data processing technologies with examples from PostgreSQL. It is geared toward database core developers, operation systems developers, system architects, and all those who want to understand databases in more detail.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

PostgreSQL is considered the most advanced free open-source database engine. It is developed by a community of hackers around the world - some of them are students just like you!
In this course, you will learn how to use PostgreSQL indices, how to change them according to your demands, and how to implement your ideas and give back to the community.

What you'll learn

  • General ideas of data access
  • PostgreSQL source code organization and development lifecycle
  • PostgreSQL data access technologies
  • Data access development trends

Syllabus

Section 1. General purpose algorithms.
Topic 1: Introduction to PostgreSQL. Core concepts and source code structure.
Topic 2: Developer tools. Querying and coding.
Topic 3: B-tree. Idea, implementation, query analysis.

Section 2. Special algorithms to tackle specific problems, including PostgreSQL’s approach.
Topic 4: Paged memory organization.
Topic 5: Write-ahead log. Point-in-time recovery.
Topic 6: Generalized index search tree (GiST).

Section 3. Specific algorithms implemented only in PostgreSQL.
Topic 7: PostgreSQL extensions. cube and smlar.
Topic 8: Full text search. Generalized inverted index (GIN).
Topic 9: PostgreSQL development lifecycle. Mailing lists and commitfests.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Advanced Linear Algebra: Foundations to Frontiers (edX) EdX
University of Texas at Austin,UTAustinX

Advanced Linear Algebra: Foundations to Frontiers (edX)

Learn advanced linear algebra for computing. Linear algebra is one of the fundamental tools for computational and data scientists. In Advanced Linear Algebra: Foundations to Frontiers (ALAFF), you will build your knowledge, understanding, and skills in linear algebra, practical algorithms for matrix computations, and the analysis of the effects of floating-point arithmetic as performed by computers.

Self Paced
Self-Paced
AP Computer Science A: Java Programming Polymorphism and Advanced Data Structures (edX) EdX
Purdue University,PurdueX

AP Computer Science A: Java Programming Polymorphism and Advanced Data Structures (edX)

AP Computer Science A from Purdue University. This computer science course covers advanced OOP strategies, including polymorphism, abstract classes, super keyword, exceptions, generics, sorting and searching algorithms. This course is for anyone interested in taking a first-level computer-programming course, particularly those who attend a school that does not provide a similar class.

This course is archived
5-12 Weeks
Distributed Machine Learning with Apache Spark (edX) EdX
University of California, Berkeley,BerkeleyX

Distributed Machine Learning with Apache Spark (edX)

Learn the underlying principles required to develop scalable machine learning pipelines and gain hands-on experience using Apache Spark. Machine learning aims to extract knowledge from data, relying on fundamental concepts in computer science, statistics, probability and optimization.

No sessions available
4 Weeks
Introduction to Java Programming: Fundamental Data Structures and Algorithms (edX) EdX
Universidad Carlos III de Madrid - UC3M,UC3Mx

Introduction to Java Programming: Fundamental Data Structures and Algorithms (edX)

Learn to enhance your code by using fundamental data structures and powerful algorithms in Java. In this introductory course, you will learn programming with Java in an easy and interactive way. You will learn about fundamental data structures, such as lists, stacks, queues and trees, and presents algorithms for inserting, deleting, searching and sorting information on these data structures in an efficient way.

Self Paced
Self-Paced
Autonomous Mobile Robots (edX) EdX
ETH Zurich,ETHx

Autonomous Mobile Robots (edX)

Basic concepts and algorithms for locomotion, perception, and intelligent navigation. Robots are rapidly evolving from factory workhorses, which are physically bound to their work-cells, to increasingly complex machines capable of performing challenging tasks in our daily environment. The objective of this course is to provide the basic concepts and algorithms required to develop mobile robots that act autonomously in complex environments.

Self Paced
Self-Paced
Data Structures and Algorithm Design Part I | 数据结构与算法设计(上) (edX) EdX
Tsinghua University,TsinghuaX

Data Structures and Algorithm Design Part I | 数据结构与算法设计(上) (edX)

Learn the basics of data structures and methods to design algorithms and analyze their performance. 本课程旨在围绕各类数据结构的设计与实现,揭示其中的规律原理与方法技巧;同时针对算法设计及其性能分析,使学生了解并掌握主要的套路与手段。

Self Paced
Self-Paced
Introduction to Java Programming: Starting to code in Java (edX) EdX
Universidad Carlos III de Madrid - UC3M,UC3Mx

Introduction to Java Programming: Starting to code in Java (edX)

Learn to program with Java in an easy and interactive way! In this introductory Java programming course, you will be introduced to powerful concepts such as functional abstraction, the object oriented programming (OOP) paradigm and Application Programming Interfaces (APIs). Examples and case studies will be provided so that you can implement simple programs on your own or collaborate with peers.

Self Paced
Self-Paced
Data Structures & Algorithms I: ArrayLists, LinkedLists, Stacks and Queues (edX) EdX
Georgia Institute of Technology,GTx

Data Structures & Algorithms I: ArrayLists, LinkedLists, Stacks and Queues (edX)

Work with the principles of data storage in Arrays, ArrayLists & LinkedList nodes. Understand their operations and performance with visualizations. Implement low-level linear, linked data structures with recursive methods, and explore their edge cases. Extend these structures to the Abstract Data Types, Stacks, Queues and Deques.

Self Paced
Self-Paced