Beware of intensive slow query logging when using – log_queries_not_using_indexes

MySQL slow query log is great for identifying slow queries that are good candidates for optimisation. Slow query logging is disabled by default, but it is activated by DBA's or developers on most environments.

You can use slow query log to record all the traffic but be careful with this action as logging all traffic could be very I/O intensive and could have negative impact on general performance. It is recommended to record all traffic (more...)

Oracle and the Autonomous Database (a personal perspective from afar)

Yeah, if you hadn’t seen that one coming, hmmm, what can I say… Lot’s of…

nVision Performance Tuning: Table of Contents

This post is an index for a series of blog posts that discuss how to get good performance from nVision as used in General Ledger reporting.  As the posts become available links will be updated in this post.
  • Introduction
  • nVision Performance Options
  • Indexing of Ledger, Budget and Summary Ledger Tables
  • Partitioning of Ledger, Budget and Summary Ledger Tables
  • Additional Oracle Instrumentation for nVision
  • Logging Selector Usage
  • Analysis of Tree Usage  with the Selector Log
  • Interval (more...)

Overloaded Indexes (for ODC Appreciation Day)

ODC Appreciation Day is an idea that Tim Hall (aka Oracle-Base) came up with, to show out appreciation for the Oracle Technology Program (OTN)/Oracle Developer Community.

Fig 1 This is an efficient range scan

I want to show my support but rather than mention an Oracle “feature” I particularly like I’d like to mention a “trick” that I (and many others) often employ to help performance. That trick is Overloaded Indexes.

We can all (more...)

ODC Appreciation Day : Oracle Exadata Database Machine

Those that know me well, will know about my “appreciation” of the “Oracle Exadata Database Machine“, more commonly known as “Exadata🙂

So this will be my contribution to ODC Appreciation Day formally known as OTN Appreciation Day, a great initiative by Tim Hall aka Oracle-Base.com.

You can see a summary of last year’s blog post here:
OTN Appreciation Day : Summary

The very first Exadata, was the (more...)

Autonomous Online Index Rebuild for Oracle Multitenant

First things first: Do not rebuild Oracle indexes! … Unless you have to.

If you are even considering rebuilding indexes on an autonomous manner, please stop now, and first spend some time reading some of the many things Richard Foote has to say on his well-recommended blog.

A little side story: Many, many years ago, as I was supporting EBS at Oracle, one day I got a call from a guy with an aussie accent (more...)

Performance Analysis of a CPU-Intensive Workload in Apache Spark

Topic: This post is about techniques and tools for measuring and understanding CPU-bound and memory-bound workloads in Apache Spark. You will find examples applied to studying a simple workload consisting of reading Apache Parquet files into a Spark DataFrame.
 

Why are the topics discussed here relevant

Many workloads for data processing on modern distributed computing architectures are often CPU-bound. Typical servers underlying current data platforms have a large and increasing amount of RAM and (more...)

Free Webinar – How Oracle Works!

Next Tuesday (19th September) I am doing a free webinar for ProHuddle. It lasts under an hour and is an introduction to how some of the core parts of the Oracle RDBMS work, I call it “The Heart of Oracle: How the Core RDBMS Works”. Yes, I try and explain all of the core Oracle RDBMS in under an hour! I’m told I just about manage it. You can see details of the event and (more...)

The full table scan direct path read decision for version 12.2

This post is about the decision the Oracle database engine makes when it is using a full segment scan approach. The choices the engine has is to store the blocks that are physically read in the buffercache, or read the blocks into the process’ PGA. The first choice is what I refer to as a ‘buffered read’, which places the block in the database buffercache so the process itself and other processes can bypass the (more...)

ADF Client Side Validation with JavaScript

In my previous post I explained how to use JS client side formatter for ADF Faces input components - ADF Goes Client Side - UI Performance Boost with JavaScript. The same principle can be applied for client side validation. Most likely you are not going to implement complex validation rules on the client side, but for simple checks - it will be perfect. There will be no roundtrip to the server and this will allow (more...)

Parallel Reality


"Expect everything, I always say, and the unexpected never happens."
-- Norton Juster, The Phantom Tollbooth

The following question was recently posted in an Oracle forum:


hi Friends,
I see  this wait event latch: parallel query alloc buffer, when a job meant for doing some cleanup ran this query.
Why does this wait event come happen? , i searched google,MOS no exact hit for explanation of the exact same event.
Looking at query does  (more...)

Friday Philosophy – Sometime The Solution Has To Not Only Match The Problem But Also…

…The People!

When you design a system for end users, a good designer/developer considers the “UX” – User eXperience. The system has to be acceptable to the end user. This is often expressed as “easy to use” or “fun” or “Quick”. But in reality, the system can fail in all sort of ways but still be a success if the end user gets something out of using it. I’ve said it before and I’ll say (more...)

The Slow Tires

Once there was a man with a car. On this car he had 4 tires.
As the car is a modern one it has a nice board computer which collects many measurements. One is the rotation per minute of the tires.
One day it took more time for the man to get home than usually. So he decided to check his car's computer for any values which could lead to that delay.
After some minutes (more...)

Validate Performance Improvement Using Query Folding Feature in Power BI

I’ve been using Power BI for a couple months now, not as a developer, but as a system architecture. I may not deal with dashboard and report development on a daily basis, however, I, as an end user, use Power BI extensively to monitor Azure and Power BI usage including audit and billing. I would like to learn more about this tool to its nuts and bolts. The intention of this blog series is to (more...)

Diving into Spark and Parquet Workloads, by Example

Topic: In this post you can find a few simple examples illustrating important features of Spark when reading partitioned tables stored in Parquet, in particular with a focus on performance investigations. The main topics covered are:
  • Partition pruning
  • Column projection
  • Predicate/filter push-down
  • Tools for investigating Parquet metadata
  • Tools for measuring Spark metrics

Motivations: The combination of Spark and Parquet currently is a very popular foundation for building scalable analytics platforms. At least this is what (more...)

OGh Tech Experience 2017 – recap

On June 15th and 16th 2017 the very first OGh Tech Experience was held. This 2-day conference was a new combination of the DBA Days and Fusion Middleware Tech Experience that were held in previous years. To summarize: OGh hit bullseye. It was two days packed with excellent in-depth technical sessions, good customer experiences and great networking opportunities.

The venue was well chosen. De Rijtuigenloods in Amersfoort is a former maintenance building of the Dutch (more...)

#Javaland 2017 wrap up

Yes – I did it again and attend Javaland conference in Phantasialand BrĂĽhl.

It was not easy this year to concentrate on the sessions because of the hottest march of the last 100 years. But the quality of the sessions beats the weather. Maybe again my invest in reading the abstracts and filter the sessions before the conference has payed off.

Day 1 Conference

Jens Schauder: documentation & slides with AsciiDoc, Git, Gradle and Reveal.js

(more...)

On Measuring Apache Spark Workload Metrics for Performance Troubleshooting

Topic: This post is about measuring Apache Spark workload metrics for performance investigations. In particular you can find the description of some practical techniques and a simple tool that can help you with Spark workload metrics collection and performance analysis. The post is released with accompanying code on GitHub: sparkMeasure

Introduction to Spark performance instrumentation

  
From recent experience I find that scalability and performance are some of the key motivating factors that drive people (more...)

Business rules, common sense and query performance

Very often, significant performance benefits can be obtained by using some very basic knowledge of the application, its data and business rules. Sometimes even less than that: even if you are not familiar with the application logic at all, you can still use common sense to make some reasonable guesses that would get you a long way in improving query’s performance. Here is an example (based on an actual query that I had to tune (more...)

LNS and LOG_BUFFER

In a oracle data guard environment Log Network Server (LNS) process transports the redo from the primary to the standby site. The behavior of LNS process is different from SYNC and ASYNC mode replication. In ASYNC mode transport, LNS read the redo from log buffer and hand over it to the RFS process in the target site. It is not necessary the redo is always available in the buffer cache. If there is not enough (more...)