This document discusses a performance issue where a database experienced high CPU usage in the kernel mode. Tracing tools identified that detaching from multiple shared memory segments during connection release was causing the high CPU. The database server had a NUMA architecture, causing the database instance to create multiple shared memory segments across NUMA nodes. Increasing the shared memory size limit did not resolve it, as the instance was optimizing for NUMA.
This document provides an in-depth overview of the LMS (Log Mining Server) process in Oracle databases. It discusses how LMS uses pollsys system calls and sockets to listen for incoming messages. It also examines the workload distribution across LMS processes and how LMS applies undo blocks to construct cache recovery (CR) buffers. Session-level statistics and tools like snapper.sql are demonstrated to analyze LMS workload and performance.
Dbms plan - A swiss army knife for performance engineersRiyaj Shamsudeen
This document discusses dbms_xplan, a tool for performance engineers to analyze execution plans. It provides options for displaying plans from the plan table, shared SQL area in memory, and AWR history. Dbms_xplan provides more detailed information than traditional tools like tkprof, including predicates, notes, bind values, and plan history. It requires privileges to access dictionary views for displaying plans from memory and AWR. The document also demonstrates usage examples and output formats for dbms_xplan.analyze.
The document discusses optimization of Real Application Clusters (RAC) in Oracle 12c. It provides background on the author and outlines common root causes of RAC performance issues such as CPU/memory starvation, network issues, and excessive dynamic remastering. The document then presents golden rules for RAC diagnostics including avoiding focusing only on top wait events, eliminating infrastructure issues, identifying problem instances, examining both send and receive side metrics, and using histograms. Specific techniques are described for analyzing wait events like gc buffer busy.
This document provides an introduction to cost based optimization. It discusses key concepts like selectivity, cardinality, histograms, and correlation issues. The author is Riyaj Shamsudeen, an Oracle expert with 18 years of experience. Sample code and examples are provided to illustrate how to calculate selectivity and cardinality accurately to improve query optimization. Extended statistics are highlighted as a way to address correlation between column predicates in Oracle 11g and above.
This document discusses why SQL optimizers sometimes produce suboptimal query plans. It begins by introducing concepts like selectivity, cardinality, and histograms which are important for query optimization. It then describes issues like correlation between predicates that can cause underestimation of cardinality. The document recommends gathering statistics on columns and indexes, using histograms, and explains how Oracle 11g's extended statistics feature can help address correlation problems.
The document discusses Oracle database logging and redo operations. It describes how Oracle uses physiological logging to generate redo records from change vectors. Change vectors transition database blocks between versions. Redo records group change vectors and transition the overall database state. The document provides an example redo record for an INSERT statement, showing the change vectors for both the table and undo segments involved in the transaction.
This document provides an overview of advanced RAC troubleshooting concepts by Riyaj Shamsudeen. It discusses key concepts related to cache coherency, single and multi-block reads and transfers in RAC, buffer changes when modifying data, and common wait events seen in RAC environments like gc cr block 2-way and gc cr block 3-way. The document is intended for experienced Oracle professionals and provides examples and demonstrations of the various RAC concepts discussed.
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【Maclean liu技术分享】拨开oracle cbo优化器迷雾,探究histogram直方图之秘 0321maclean liu
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Another year goes by, and most likely, another data access framework has been invented. It will claim to be the fastest, smartest way to talk to the database, and just like all those that came before it, it will not be. Because the best database access tool has been there for more than 30 years now, and that is PL/SQL. Although we all sometimes fall prey to the mindset of “Oh look, a shiny new tool, we should start using it," the performance and simplicity of PL/SQL remain unmatched. This session looks at the failings of other data access languages, why even a cursory knowledge of PL/SQL will make you a better developer, and how to get the most out of PL/SQL when it comes to database performance.
Kyle Hailey is an Oracle expert who has worked with Oracle since 1990. He has experience with Oracle support, porting versions of Oracle, benchmarking, and real world performance. He has also worked with startups, Quest Software, Oracle OEM, and Embarcadero. The document discusses row locks in Oracle and how to find blocking sessions and SQL using tools like ASH, v$lock, and Logminer. It provides examples of creating row lock waits and how to investigate them using these tools.
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When you execute a business task on a computer system, you create an experience. The duration of this experience is called response time. The richest and easiest information about response time to obtain in the whole Oracle technology stack is available from the Oracle Database tier: Oracle's extended SQL trace data. But in almost 100% of first tries with using trace data, people make a data collection mistake that complicates their analysis. This is the story of that mistake.
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This document provides information on various debugging and profiling tools that can be used for Ruby including:
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- google perftools profiler for CPU profiling
- pprof to analyze profiling data
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Nowadays system administrators have great choices when it comes down to Linux performance profiling and monitoring. The challenge is to pick the appropriate tools and interpret their results correctly.
This talk is a chance to take a tour through various performance profiling and benchmarking tools, focusing on their benefit for every sysadmin.
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At the end the goal is to gather reference points to look at, whenever you are faced with performance problems.
Take the chance to close your knowledge gaps and learn how to get the most out of your system.
This document provides an agenda for a presentation on advanced RAC troubleshooting. It introduces the presenter, Riyaj Shamsudeen, and his background and qualifications. The agenda covers various topics related to optimizing global cache performance, understanding important RAC wait events, tuning RAC background processes, troubleshooting interconnect and network issues, effective use of parallel query, and resolving locking issues. Disclaimers are provided to indicate the content represents the author's opinions and is not an official position.
OSMC 2015 | Linux Performance Profiling and Monitoring by Werner FischerNETWAYS
The document discusses various Linux tools for profiling and monitoring system performance and resources. It provides examples of using mpstat to monitor CPU usage, vmstat to view memory and I/O statistics, and pidstat to analyze resource usage of specific processes. It also covers using iostat to monitor I/O subsystem performance and device utilization. The document aims to help understand how to use these tools to collect statistics and identify potential performance bottlenecks.
OSMC 2015: Linux Performance Profiling and Monitoring by Werner FischerNETWAYS
Nowadays system administrators have great choices when it comes down to Linux performance profiling and monitoring. The challenge is to pick the appropriate tools and interpret their results correctly.
This talk is a chance to take a tour through various performance profiling and benchmarking tools, focusing on their benefit for every sysadmin.
More than 25 different tools are presented. Ranging from well known tools like strace, iostat, tcpdump or vmstat to new features like Linux tracepoints or perf_events. You will also learn which tools can be monitored by Icinga and which monitoring plugins are already available for that.
At the end the goal is to gather reference points to look at, whenever you are faced with performance problems.
Take the chance to close your knowledge gaps and learn how to get the most out of your system.
The document provides an overview of Amazon EC2 instance types and best practices for optimizing performance. It discusses factors to consider when choosing an EC2 instance, how instances deliver performance and flexibility, and tips for making the most of different instance types. The document reviews EC2 instance history, describes virtual CPUs and resource allocation, and provides guidance on topics like NUMA, hugepages, operating systems, and hardware aspects that impact performance.
SRV402 Deep Dive on Amazon EC2 Instances, Featuring Performance Optimization ...Amazon Web Services
Amazon EC2 provides a broad selection of instance types to accommodate a diverse mix of workloads. In this session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and Accelerated Computing (GPU and FPGA) instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
Oracle Architecture document discusses:
1. The cost of an Oracle Enterprise Edition license is $47,500 per processor.
2. It provides an overview of key Oracle components like the instance, database, listener and cost based optimizer.
3. It demonstrates how to start an Oracle instance, check active processes, mount and open a database, and query it locally and remotely after starting the listener.
Performance tweaks and tools for Linux (Joe Damato)Ontico
The document discusses various Linux performance analysis tools including lsof to list open files, strace to trace system calls, tcpdump to dump network traffic, perftools from Google for profiling CPU usage, and a Ruby library called perftools.rb for profiling Ruby code. Examples are provided for using these tools to analyze memory usage, slow queries, Ruby interpreter signals, thread scheduling overhead, and identifying hot spots in Ruby web applications.
SRV402 Deep Dive on Amazon EC2 Instances, Featuring Performance Optimization ...Amazon Web Services
Amazon EC2 provides a broad selection of instance types to accommodate a diverse mix of workloads. In this session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and Accelerated Computing (GPU and FPGA) instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
This document provides instructions for implementing an Oracle 11g R2 Real Application Cluster on a Red Hat Enterprise Linux 5.0 system using a two-node configuration. It describes pre-installation steps including hardware and network configuration, installing prerequisite packages and libraries, and configuring the Oracle ASM library driver. Detailed steps are provided for installing Oracle Grid Infrastructure and database software, and configuring the single client access name and storage area network.
SRV402 Deep Dive on Amazon EC2 Instances, Featuring Performance Optimization ...Amazon Web Services
Amazon EC2 provides a broad selection of instance types to accommodate a diverse mix of workloads. In this session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and Accelerated Computing (GPU and FPGA) instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
Solve the colocation conundrum: Performance and density at scale with KubernetesNiklas Quarfot Nielsen
As we move from monolithic applications to microservices, the ability to colocate workloads offers a tremendous opportunity to realize greater development velocity, robustness, and resource utilization. But workload colocation can also introduce performance variability and affect service levels. Google describes the problem as the “tail at scale”—the amplification of negative results observed at the tail of the latency curve when many systems are involved.
With its latest tooling capabilities, Intel has an experiments framework to calculate the trade-offs between low latency and higher density. Niklas Nielsen discusses the challenges and complexities of workload colocation, why solving these challenges matters to your business no matter the size, and how Intel intends to help smarter resource allocations with its latest tooling capabilities and Kubernetes.
Amazon EC2 provides a broad selection of instance types to accommodate a diverse mix of workloads. In this session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and GPU instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
When your query execution is slow, a couple of questions arise. Where to look for resources utilization? What tools do you have to analyze CPU, hard drive and RAM bottlenecks? Could you do something to reduce query execution time? MariaDB's Patrick LeBlanc and Roman Nozdrin touch on both Columnstore's query execution introspection tools as well as operating system capabilities that everyone should know about. They go on to discuss a number of real life use cases too. Some called for configuration changes whilst others forced them to make serious changes in the code.
The document summarizes Maycon Vitali's presentation on hacking embedded devices. It includes an agenda covering extracting firmware from devices using tools like BusPirate and flashrom, decompressing firmware to view file systems and binaries, emulating binaries using QEMU, reverse engineering code to find vulnerabilities, and details four vulnerabilities discovered in Ubiquiti networking devices designated as CVEs. The presentation aims to demonstrate common weaknesses in embedded device security and how tools can be used to analyze and hack these ubiquitous connected systems.
Amazon EC2 provides a broad selection of instance types to accommodate a diverse mix of workloads. In this session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and GPU instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
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If you’ve ever had to analyze a map or GPS data, chances are you’ve encountered and even worked with coordinate systems. As historical data continually updates through GPS, understanding coordinate systems is increasingly crucial. However, not everyone knows why they exist or how to effectively use them for data-driven insights.
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22. 22
pset_bind and _lgrpsys
Calls _lgrpsys and pset_bind are new and googling these
function calls showed that there may be related to Non
Uniforn Memory Access (NUMA) architecture.
17252: 4.5957 munmap (0xFFFFFD7FFDAE0000, 32768) = 0
17252: 4.5958 lgrp_version (1, ) = 1
17252: 4.5958 _lgrpsys (1, 0, ) = 42
17252: 4.5958 _lgrpsys (3, 0x00000000, 0x00000000) = 19108
17252: 4.5959 _lgrpsys (3, 0x00004AA4, 0x06399D60) = 19108
17252: 4.5959 _lgrpsys (1, 0, ) = 42
17252: 4.5960 pset_bind (PS_QUERY, P_LWPID, 4294967295, 0xFFFFFD7FFFDFB11C) = 0
17252: 4.5960 pset_info (PS_MYID, 0x00000000, 0xFFFFFD7FFFDFB0D4, 0x00000000) = 0
17252: 4.5961 pset_info (PS_MYID, 0x00000000, 0xFFFFFD7FFFDFB0D4, 0x061AA2B0) = 0
23. 23
NUMA architecture (overview)
Memory #1
Memory #2 Memory #3 Memory #4
CPU 0 CPU 1 CPU 2 CPU 3 CPU 4 CPU 5 CPU 6 CPU 7
For cpu0 and cpu1, memory board 1 is local. Other
memory areas are remote for cpu0 and cpu1.
Access to local memory is faster compared to
remote memory access.
24. 24
NUMA architecture (Overview )
Shm 1 Shm 2 Shm 3 Shm 4
Memory #1
Memory #2 Memory #3 Memory #4
CPU 0 CPU 1 CPU 2 CPU 3 CPU 4 CPU 5 CPU 6 CPU 7
dbwr 0 Dbwr 1 Dbwr 2 Dbwr 3
To make use of NUMA technology, Oracle spreads
SGA across NUMA nodes.
25. 25
NUMA optimization
Binds DBWR to a CPU set. That DBWR handles all writes from
that shared memory segment.
User processes also tries to use free buffers from the working set
of buffers from that NUMA node process is running from.
(Update: This turned out to be a Oracle database bug 5173642).
LGWR also seems to have some code optimization to better use
NUMA technology, but my test cases are not conclusive enough.
26. 26
Locality groups
In Solaris, NUMA technology is implemented as locality groups.
_lgrpsys and pset_bind calls are to get current locality group
information and bind processes to a processor set.
Now, we can understand why SGA was split into multiple
segments.
But, Do we really have that many locality groups in this server?
27. 27
Locality groups
Lgrpinfo tool can provide NUMA node details
:~#/usr/local/bin/lgrpinfo
lgroup 0 (root):
Children: 10 12 14 15 17 19 21 23
CPUs: 0-15
Memory: installed 65024 Mb, allocated 2548 Mb, free 62476 Mb
Lgroup resources: 1-8 (CPU); 1-8 (memory)
Latency: 146
lgroup 1 (leaf):
Children: none, Parent: 9
CPUs: 0 1
Memory: installed 7680 Mb, allocated 1964 Mb, free 5716 Mb
Lgroup resources: 1 (CPU); 1 (memory)
Load: 0.105
Latency: 51
...
There were many locality groups
defined and seven of them were
leaf node locality groups in this server.
29. 29
Is NUMA bad?
Indeed 10 shared memory segments were created, one for a
locality groups.
We disabled NUMA to resolve this problem temporarily.
NUMA is a great technology. Sequent Dynix/ptx has
implemented NUMA technology successfully a decade ago.
It’s just that we are encountering an unfortunate side effect of
NUMA.
30. 30
Solution
We can disable NUMA or reduce number of NUMA nodes.
*._enable_NUMA_optimization=FALSE
*._db_block_numa = 1
Use patch for bug 819953 disable NUMA instead of underscore
parameters (only if needed to disable NUMA)
Note 399261.1 and 759565.1 describes these issues.
It looks like, there is one shared memory segment per locality
group and one segment encompassing all locality groups. One
small bootstrap segment is also created.
31. 31
Solution – contd.
Another option is to control logout rate.
Jonathan Lewis mentioned these parameters to control logout
storm rate later.
Parameter Meaning Value
_logout_storm_retrycnt maximum retry count for logouts 600
timeout in centi-seconds for wait 5
between retries
_logout_storm_timeout
number of processes that can logout in a 0
second
_logout_storm_rate