Advanced SQL for Query Tuning and Performance Optimization
Focused View
Dan Sullivan
2:09:16
16 View
01 - Reduce query response time with query tuning.mp4
00:49
02 - What you should know.mp4
00:56
01 - From declarative SQL to a procedural execution plan.mp4
03:03
02 - Scanning tables and indexes.mp4
03:06
03 - Joining tables.mp4
02:23
04 - Partitioning data.mp4
02:23
05 - Challenge Choosing how to partition a table.mp4
00:30
06 - Solution Choosing how to partition a table.mp4
00:40
01 - Using PostgreSQL in Codespaces.mp4
02:33
02 - Explain and analyze.mp4
03:25
03 - Example plan Selecting with a WHERE clause.mp4
02:26
04 - Indexes.mp4
02:43
05 - Challenge Generating a query execution plan.mp4
00:31
06 - Solution Generating a query execution plan.mp4
00:21
01 - Indexing.mp4
03:16
02 - B-tree indexes.mp4
02:21
03 - B-tree index example plan.mp4
04:44
04 - Bitmap indexes.mp4
01:40
05 - Bitmap index example plan.mp4
03:06
06 - Hash indexes.mp4
01:19
07 - Hash index example plan.mp4
02:53
08 - Bloom filter indexes.mp4
06:32
09 - PostgreSQL-specific indexes.mp4
01:54
10 - Challenge Choosing an index.mp4
00:31
11 - Solution Choosing an index.mp4
00:37
01 - Types of joins.mp4
02:36
02 - Nested loops.mp4
03:19
03 - Nested loop example plan.mp4
03:59
04 - Hash joins.mp4
01:29
05 - Hash join example plan.mp4
01:54
06 - Merge joins.mp4
02:23
07 - Merge join example.mp4
03:02
08 - Subqueries vs. joins.mp4
01:13
09 - Challenge Designing a join.mp4
00:24
10 - Solution Designing a join.mp4
00:22
01 - Horizontal vs. vertical partitioning.mp4
02:47
02 - Partition by range.mp4
01:40
03 - Partition by range example.mp4
05:36
04 - Partition by list.mp4
01:27
05 - Partition by list example.mp4
05:37
06 - Partition by hash.mp4
01:55
07 - Partition by hash example.mp4
04:35
08 - Challenge Partitioning a table.mp4
00:36
09 - Solution Partitioning a table.mp4
00:28
01 - Materialized views.mp4
01:41
02 - Creating materialized views.mp4
01:58
03 - Refreshing materialized views.mp4
02:00
04 - Challenge Creating a materialized view.mp4
00:43
05 - Solution Creating a materialized view.mp4
00:29
01 - Collect statistics about data in tables.mp4
03:21
02 - Analyzing execution statistics with pg stat statements.mp4
01:54
03 - Reviewing execution plans with the auto explain module.mp4
02:34
04 - Additional analysis with other pg stats data.mp4
01:26
05 - Challenge Analyze schema statistics.mp4
00:23
06 - Solution Analyze schema statistics.mp4
00:16
01 - Using common table expressions to avoid repetitive computation.mp4
02:11
02 - Hints to the Query Optimizer.mp4
01:43
03 - Parallel query execution.mp4
02:06
04 - Improving cache utilization.mp4
02:20
05 - Miscellaneous tips.mp4
02:21
06 - Challenge Design a common table expression.mp4
00:24
07 - Solution Design a common table expression.mp4
00:18
01 - Next steps.mp4
01:04
Description
SQL queries can be fast and highly efficient, but they can also be slow and demand excessive CPU and memory resources. For many SQL programmers, occasional bouts with long-running queries and poor performance are simply par for the course. But by gaining a better understanding of how databases translate SQL queries into execution plans, you can take steps to avoid these issues. In this course, Dan Sullivan shows you how to analyze query execution plans and use data modeling strategies to boost query performance. Dan describes how SQL queries are executed, highlights different types of indexes and how they factor in query tuning, covers several methods for performing joins, and discusses how to use partitioning and materialized views to improve performance. Plus, Dan shows you how to run PostgreSQL in GitHub Codespaces so you can get started learning faster.
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Dan Sullivan
Instructor's CoursesCloud and data architect with extensive experience in data architecture, data science, machine learning, stream processing, and cloud architecture. Capable of starting with vague initiatives and formulating precise objectives, strategies, and implementation plans. Regularly works with C-level and VP executives while also mentoring and coaching software engineers. Adapts well to unforeseen challenges. He is the author of the official Google Cloud study guides for the Professional Architect, Professional Data Engineer, and Associate Cloud Engineer.
Linkedin Learning
View courses Linkedin LearningLinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications.
It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.
- language english
- Training sessions 63
- duration 2:09:16
- English subtitles has
- Release Date 2023/12/13
