The document provides instructions for configuring huge pages on a Linux server for an Oracle database:
1. Set memory locking limits in /etc/security/limits.conf for the oracle and grid users.
2. Run a script called hugepages_settings.sh that will calculate the recommended number of huge pages based on the existing shared memory segments.
3. Take the number output from the script and set it for the vm.nr_hugepages parameter in /etc/sysctl.conf, reboot the server, and restart the Oracle database.
PostgreSQL is one of the most advanced relational databases. It offers superb replication capabilities. The most important features are: Streaming replication, Point-In-Time-Recovery, advanced monitoring, etc.
PostgreSQL is one of the most advanced relational databases. It offers superb replication capabilities. The most important features are: Streaming replication, Point-In-Time-Recovery, advanced monitoring, etc.
Vous avez récemment commencé à travailler sur Spark et vos jobs prennent une éternité pour se terminer ? Cette présentation est faite pour vous.
Himanshu Arora et Nitya Nand YADAV ont rassemblé de nombreuses bonnes pratiques, optimisations et ajustements qu'ils ont appliqué au fil des années en production pour rendre leurs jobs plus rapides et moins consommateurs de ressources.
Dans cette présentation, ils nous apprennent les techniques avancées d'optimisation de Spark, les formats de sérialisation des données, les formats de stockage, les optimisations hardware, contrôle sur la parallélisme, paramétrages de resource manager, meilleur data localité et l'optimisation du GC etc.
Ils nous font découvrir également l'utilisation appropriée de RDD, DataFrame et Dataset afin de bénéficier pleinement des optimisations internes apportées par Spark.
This slide was presented at Mydbops Database Meetup 4 by Bajranj ( Zenefits ). ZFS as a filesystem has good features that can enhance MySQL by compression, Quick Snapshots and others.
These slides show how to reduce latency on websites and reduce bandwidth for improved user experience.
Covering network, compression, caching, etags, application optimisation, sphinxsearch, memcache, db optimisation
MySQL Replication Overview -- PHPTek 2016Dave Stokes
MySQL Replication has been around for a long time but are you up to date on the latest updates such as multi-source or group replication? Can you explain the differences between GTID and non-GTID replication? This is a quick 30 minute overview of MySQL replication as of 5.7
This ppt was used by Devrim at pgDay Asia 2017. He talked about some important facts about WAL - Transaction Logs or xlogs in PostgreSQL. Some of these can really come handy on a bad day
To Hire, or to train, that is the question (Percona Live 2014)Geoffrey Anderson
"We're hiring!"
How many times have you heard this phrase at a conference? Every database-driven company is hiring and that makes for pretty stiff competition when trying to get a new DBA. Instead of searching for the perfect database administrator from a conference or Linkedin, why not look internally at your organization for system administrators or engineers who may be an equally good fit given the right training.
In this talk, I'll explain how the DBAs at Box developed a knowledge-sharing culture around databases and disseminated important learnings to other members of the company. I'll also cover the mentorship process we established to train other members of our Operations team to become rock star DBAs and manage our MySQL and HBase infrastructure at Box.
From common errors seen in running Spark applications, e.g., OutOfMemory, NoClassFound, disk IO bottlenecks, History Server crash, cluster under-utilization to advanced settings used to resolve large-scale Spark SQL workloads such as HDFS blocksize vs Parquet blocksize, how best to run HDFS Balancer to re-distribute file blocks, etc. you will get all the scoop in this information-packed presentation.
Vous avez récemment commencé à travailler sur Spark et vos jobs prennent une éternité pour se terminer ? Cette présentation est faite pour vous.
Himanshu Arora et Nitya Nand YADAV ont rassemblé de nombreuses bonnes pratiques, optimisations et ajustements qu'ils ont appliqué au fil des années en production pour rendre leurs jobs plus rapides et moins consommateurs de ressources.
Dans cette présentation, ils nous apprennent les techniques avancées d'optimisation de Spark, les formats de sérialisation des données, les formats de stockage, les optimisations hardware, contrôle sur la parallélisme, paramétrages de resource manager, meilleur data localité et l'optimisation du GC etc.
Ils nous font découvrir également l'utilisation appropriée de RDD, DataFrame et Dataset afin de bénéficier pleinement des optimisations internes apportées par Spark.
This slide was presented at Mydbops Database Meetup 4 by Bajranj ( Zenefits ). ZFS as a filesystem has good features that can enhance MySQL by compression, Quick Snapshots and others.
These slides show how to reduce latency on websites and reduce bandwidth for improved user experience.
Covering network, compression, caching, etags, application optimisation, sphinxsearch, memcache, db optimisation
MySQL Replication Overview -- PHPTek 2016Dave Stokes
MySQL Replication has been around for a long time but are you up to date on the latest updates such as multi-source or group replication? Can you explain the differences between GTID and non-GTID replication? This is a quick 30 minute overview of MySQL replication as of 5.7
This ppt was used by Devrim at pgDay Asia 2017. He talked about some important facts about WAL - Transaction Logs or xlogs in PostgreSQL. Some of these can really come handy on a bad day
To Hire, or to train, that is the question (Percona Live 2014)Geoffrey Anderson
"We're hiring!"
How many times have you heard this phrase at a conference? Every database-driven company is hiring and that makes for pretty stiff competition when trying to get a new DBA. Instead of searching for the perfect database administrator from a conference or Linkedin, why not look internally at your organization for system administrators or engineers who may be an equally good fit given the right training.
In this talk, I'll explain how the DBAs at Box developed a knowledge-sharing culture around databases and disseminated important learnings to other members of the company. I'll also cover the mentorship process we established to train other members of our Operations team to become rock star DBAs and manage our MySQL and HBase infrastructure at Box.
From common errors seen in running Spark applications, e.g., OutOfMemory, NoClassFound, disk IO bottlenecks, History Server crash, cluster under-utilization to advanced settings used to resolve large-scale Spark SQL workloads such as HDFS blocksize vs Parquet blocksize, how best to run HDFS Balancer to re-distribute file blocks, etc. you will get all the scoop in this information-packed presentation.
Get higher transaction throughput and better price/performance with an Amazon...Principled Technologies
In addition, the EBS gp3-backed EC2 r5b.16xlarge instance delivered a lower average transaction latency to offer more consistent transactional database performance than two Microsoft Azure E64ds_v4 VM configurations
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Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
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Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
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1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
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• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
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The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
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In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
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Mission to Decommission: Importance of Decommissioning Products to Increase E...
Huge pages
1. :HugePages
به شرح زيرetc/security/limits.conf/ در فايلmemlock 1. انجام تنظيمات
oracle
soft memlock
oracle
hard memlock
grid
soft memlock
grid
hard memlock
60397977
60397977
60397977
60397977
.مقداري كه براي اين پارامتر بايد در نظر گرفته شود بايد اندكي از حافظه فيزيكي موجود بر روي ديتابيس سرور كمتر باشد
. كه به صورت كيلوبايت برابر مقدار بال مي شود، مناسب استG 58 حافظه حدودG 64 به عنوان مثال براي
.2
HugePages 3. به دست آوردن عدد مناسب براي پارامتر
پيش نياز ها
.a
Oracle Instance بال بودن
.b
Automatic Memory Management غير فعال بودن
.c
و كپي اسكريپت زير در آنhugepages_settings.sh ايجاد يك فايل شل بر روي سرور ديتابيس با نام
.d
#!/bin/bash
#
# hugepages_settings.sh
#
# Linux bash script to compute values for the
# recommended HugePages/HugeTLB configuration
#
# Note: This script does calculation for all shared memory
# segments available when the script is run, no matter it
# is an Oracle RDBMS shared memory segment or not.
#
# This script is provided by Doc ID 401749.1 from My Oracle Support
# http://support.oracle.com
2. # Welcome text
echo "
This script is provided by Doc ID 401749.1 from My Oracle Support
(http://support.oracle.com) where it is intended to compute values for
the recommended HugePages/HugeTLB configuration for the current shared
memory segments. Before proceeding with the execution please note following:
* For ASM instance, it needs to configure ASMM instead of AMM.
* The 'pga_aggregate_target' is outside the SGA and
you should accommodate this while calculating SGA size.
* In case you changes the DB SGA size,
as the new SGA will not fit in the previous HugePages configuration,
it had better disable the whole HugePages,
start the DB with new SGA size and run the script again.
And make sure that:
* Oracle Database instance(s) are up and running
* Oracle Database 11g Automatic Memory Management (AMM) is not setup
(See Doc ID 749851.1)
* The shared memory segments can be listed by command:
# ipcs -m
Press Enter to proceed..."
read
# Check for the kernel version
KERN=`uname -r | awk -F. '{ printf("%d.%dn",$1,$2); }'`
# Find out the HugePage size
HPG_SZ=`grep Hugepagesize /proc/meminfo | awk '{print $2}'`
if [ -z "$HPG_SZ" ];then
echo "The hugepages may not be supported in the system where the script is being executed."
exit 1
fi
# Initialize the counter
NUM_PG=0
# Cumulative number of pages required to handle the running shared memory segments
3. for SEG_BYTES in `ipcs -m | cut -c44-300 | awk '{print $1}' | grep "[0-9][0-9]*"`
do
MIN_PG=`echo "$SEG_BYTES/($HPG_SZ*1024)" | bc -q`
if [ $MIN_PG -gt 0 ]; then
NUM_PG=`echo "$NUM_PG+$MIN_PG+1" | bc -q`
fi
done
RES_BYTES=`echo "$NUM_PG * $HPG_SZ * 1024" | bc -q`
# An SGA less than 100MB does not make sense
# Bail out if that is the case
if [ $RES_BYTES -lt 100000000 ]; then
echo "***********"
echo "** ERROR **"
echo "***********"
echo "Sorry! There are not enough total of shared memory segments allocated for
HugePages configuration. HugePages can only be used for shared memory segments
that you can list by command:
# ipcs -m
of a size that can match an Oracle Database SGA. Please make sure that:
* Oracle Database instance is up and running
* Oracle Database 11g Automatic Memory Management (AMM) is not configured"
exit 1
fi
# Finish with results
case $KERN in
'2.4') HUGETLB_POOL=`echo "$NUM_PG*$HPG_SZ/1024" | bc -q`;
echo "Recommended setting: vm.hugetlb_pool = $HUGETLB_POOL" ;;
'2.6') echo "Recommended setting: vm.nr_hugepages = $NUM_PG" ;;
*) echo "Unrecognized kernel version $KERN. Exiting." ;;
esac
# End
chmod +x hugepages_settings.sh تغيير سطح دسترسي فايل به
.e
hugepages_settings.sh/. اجراي فايل
.f
4. .g
با اجراي فايل hugepages_settings.shيك عدد به عنوان خروجي داده مي شود كه اين عدد بايد براي تنظيم
پارامتر hugepageدر سطح سيستم عامل استفاده شود.
4. عدد به دست آمده را در فايل / etc/sysctl.confبه صورت زير تنظيم كنيد:
6941 = vm.nr_hugepages
5. فرمان id –g oracleرا براي به دست آوردن گروه پيش فرض اوراكل اجرا كرده و خروجي را براي پارامتر زير تنظيم
مي كنيم:
`vm.hugetlb_shm_group=`id –g oracle
6. Shutdown Oracle DB & ASM
7. Server Reboot
![# Welcome text
echo "
This script is provided by Doc ID 401749.1 from My Oracle Support
(http://support.oracle.com) where it is intended to compute values for
the recommended HugePages/HugeTLB configuration for the current shared
memory segments. Before proceeding with the execution please note following:
* For ASM instance, it needs to configure ASMM instead of AMM.
* The 'pga_aggregate_target' is outside the SGA and
you should accommodate this while calculating SGA size.
* In case you changes the DB SGA size,
as the new SGA will not fit in the previous HugePages configuration,
it had better disable the whole HugePages,
start the DB with new SGA size and run the script again.
And make sure that:
* Oracle Database instance(s) are up and running
* Oracle Database 11g Automatic Memory Management (AMM) is not setup
(See Doc ID 749851.1)
* The shared memory segments can be listed by command:
# ipcs -m
Press Enter to proceed..."
read
# Check for the kernel version
KERN=`uname -r | awk -F. '{ printf("%d.%dn",$1,$2); }'`
# Find out the HugePage size
HPG_SZ=`grep Hugepagesize /proc/meminfo | awk '{print $2}'`
if [ -z "$HPG_SZ" ];then
echo "The hugepages may not be supported in the system where the script is being executed."
exit 1
fi
# Initialize the counter
NUM_PG=0
# Cumulative number of pages required to handle the running shared memory segments](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)