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Advanced Autovacuum Tuning and pganalyze VACUUM advisor

Understand the most important VACUUM metrics, concepts like xmin horizon, how to prevent transaction ID wraparound, estimating bloat, and more.

Here is what you will learn in this webinar:

  • How to identify ineffective VACUUMs that run but don’t actually produce any results
  • Tracking freezing stats to prevent TXID wraparound, and how to find problem tables
  • The VACUUM xmin horizon, and how it causes “Dead Tuples Not Yet Removable”, and how pganalyze alerts you of this situation
  • Why BUFFERS is important, and how to interpret the hits counter
  • How pganalyze calculates the age of transaction IDs using calendar time (not just counting TXIDs)
  • How pganalyze estimates bloat, and when the estimates are more vs less accurate
  • The new logic for scale factor and threshold tuning recommendations, and how it works behind the scenes
  • How VACUUMs that have multiple index phases can use a lot of resources, and how pganalyze recommends changing autovacuum_work_mem to avoid the problem
  • The pganalyze VACUUM Advisor

How to use the Postgres query planner to debug bad plans and speed up queries

Understand how the Postgres query planner chooses different plans for the same query, and how to debug bad plans.

Here is what you will learn in this webinar:

  • How to go from a slow query to a query plan that shows which exact part was slow
  • Understanding "Scans" and how Postgres decides which index to use
  • Why BUFFERS is important, and how to interpret the hits counter
  • How to rewrite queries based on plans to speed up performance
  • The different planner settings and how they influence plan choices
  • How to identify when plans "fall over" to a bad query plan and why this can happen
  • Choosing particular query plans using planner hints with pg_hint_plan
  • How managed cloud providers offer ways to control query plans (such as Aurora Query Plan Management), and how it compares to pg_hint_plan
  • Using the Postgres queryid to link pg_stat_statements, pg_stat_activity and auto_explain
  • Generic query plans, and how to get them from pg_stat_statements output
  • Looking at query plans over time with pganalyze - and how it works behind the scenes
  • and much more

How to tune Postgres autovacuum to improve performance and reduce bloat

Tune your autovacuum settings to ensure that VACUUM runs at the right time and is effective for your workload.

Here is what you will learn in this webinar:

  • The physicality of tables
  • The Transaction ID clock
  • All-visible pages and slow queries
  • Understanding autovacuum scheduling
  • Cost delay 101
  • Aggressive and Failsafe VACUUMs
  • Dead tuples not yet removable
  • VACUUMing in the cloud - RDS, Aurora, Cloud SQL & AlloyDB
  • Estimating and fixing table bloat

How To Reason About Indexing Your Postgres Database

See how Postgres chooses which index to use, and learn a methodology for analyzing queries and optimizing indexes.

Here is what you will learn in this webinar:

  • How Postgres chooses which index to use
  • Background about indexing
  • What is a “good enough” index?
  • A structured approach for finding the right indexes
  • A look behind the scenes: The pganalyze Indexing Engine

Optimizing Postgres I/O Performance and Costs

We dive into I/O optimization in Postgres and how tuning I/O helps reduce overall database costs.

Here is what you will learn in this webinar:

  • Common causes for I/O spikes in Postgres and how they affect infrastructure costs
  • How to map high read and/or write IOPS to database activity
  • Using EXPLAIN plans to find heavy hitting I/O intensive queries
  • Caching in Postgres, and how the buffer cache hit ratio can be improved to reduce I/O
  • Finding the root cause of high I/O costs of cloud databases such as Amazon Aurora
  • and much more


Hundreds Of Companies Monitor Their Production PostgreSQL Databases With pganalyze

Atlassian
DoorDash
Moody's
fuboTv
Salsify
CounterPath
Ipsy

Robin Fernandes
pganalyze is essential to making our Postgres databases run faster, and makes sure end-users have the best experience possible.
- Robin Fernandes, Software Development Manager, Atlassian