Exadata is Oracle's database machine that is optimized for performance and cost-effectiveness. It uses a unique architecture with database and storage grids that eliminate performance tradeoffs. This architecture, along with technologies like hybrid columnar compression, the intelligent storage grid, and smart flash cache, make Exadata the best platform for data warehousing, OLTP, and database consolidation.
DDN: Massively-Scalable Platforms and Solutions Engineered for the Big Data a...inside-BigData.com
In this talk from the DDN User Group at ISC’13, James Coomer from DataDirect Networks presents: Massively-Scalable Platforms and Solutions Engineered for the Big Data and Cloud Era.
Watch the presentation here: http://insidehpc.com/2013/06/26/video-james-coomer-keynotes-ddn-user-group-at-isc13/
Getting Started with Apache Spark and Alluxio for Blazingly Fast AnalyticsAlluxio, Inc.
Alluxio Austin Meetup
Aug 15, 2019
Speaker: Bin Fan
Apache Spark and Alluxio are cousin open source projects that originated from UC Berkeley’s AMPLab. Running Spark with Alluxio is a popular stack particularly for hybrid environments. In this session, I will briefly introduce Apache Spark and Alluxio, share the top ten tips for performance tuning for real-world workloads, and demo Alluxio with Spark.
DDN: Massively-Scalable Platforms and Solutions Engineered for the Big Data a...inside-BigData.com
In this talk from the DDN User Group at ISC’13, James Coomer from DataDirect Networks presents: Massively-Scalable Platforms and Solutions Engineered for the Big Data and Cloud Era.
Watch the presentation here: http://insidehpc.com/2013/06/26/video-james-coomer-keynotes-ddn-user-group-at-isc13/
Getting Started with Apache Spark and Alluxio for Blazingly Fast AnalyticsAlluxio, Inc.
Alluxio Austin Meetup
Aug 15, 2019
Speaker: Bin Fan
Apache Spark and Alluxio are cousin open source projects that originated from UC Berkeley’s AMPLab. Running Spark with Alluxio is a popular stack particularly for hybrid environments. In this session, I will briefly introduce Apache Spark and Alluxio, share the top ten tips for performance tuning for real-world workloads, and demo Alluxio with Spark.
Scalable and High available Distributed File System Metadata Service Using gR...Alluxio, Inc.
Alluxio Community Office Hour
Apr 7, 2020
For more Alluxio events: https://www.alluxio.io/events/
Speaker: Bin Fan
Alluxio (alluxio.io) is an open-source data orchestration system that provides a single namespace federating multiple external distributed storage systems. It is critical for Alluxio to be able to store and serve the metadata of all files and directories from all mounted external storage both at scale and at speed.
This talk shares our design, implementation, and optimization of Alluxio metadata service (master node) to address the scalability challenges. Particularly, we will focus on how to apply and combine techniques including tiered metadata storage (based on off-heap KV store RocksDB), fine-grained file system inode tree locking scheme, embedded state-replicate machine (based on RAFT), exploration and performance tuning in the correct RPC frameworks (thrift vs gRPC) and etc. As a result of the combined above techniques, Alluxio 2.0 is able to store at least 1 billion files with a significantly reduced memory requirement, serving 3000 workers and 30000 clients concurrently.
In this Office Hour, we will go over how to:
- Metadata storage challenges
- How to combine different open source technologies as building blocks
- The design, implementation, and optimization of Alluxio metadata service
Achieving Separation of Compute and Storage in a Cloud WorldAlluxio, Inc.
Alluxio Tech Talk
Feb 12, 2019
Speaker:
Dipti Borkar, Alluxio
The rise of compute intensive workloads and the adoption of the cloud has driven organizations to adopt a decoupled architecture for modern workloads – one in which compute scales independently from storage. While this enables scaling elasticity, it introduces new problems – how do you co-locate data with compute, how do you unify data across multiple remote clouds, how do you keep storage and I/O service costs down and many more.
Enter Alluxio, a virtual unified file system, which sits between compute and storage that allows you to realize the benefits of a hybrid cloud architecture with the same performance and lower costs.
In this webinar, we will discuss:
- Why leading enterprises are adopting hybrid cloud architectures with compute and storage disaggregated
- The new challenges that this new paradigm introduces
- An introduction to Alluxio and the unified data solution it provides for hybrid environments
Vidhyalive offers netapp training(Instructor led live online training) with real-world scenarios.Learn how to configure the technologies of the NetApp. Please visit Here for further details: http://www.vidhyalive.com/product/netapp-training/
How to Build a Cloud Native Stack for Analytics with Spark, Hive, and Alluxio...Alluxio, Inc.
Alluxio Austin Meetup
Aug 15, 2019
Speakers: Tim Kelly & Thai Bui, Bazaarvoice
At Bazaarvoice, a software-as-a-service digital marketing company, the data engineering team is tasked to handle data at massive Internet-scale to serve over 1,900 of the biggest internet retailers and brands.
We built our data pipelines all in the cloud using Apache Spark and Hive on AWS EC2 accessing data in S3. AWS enables us to scale “out” the infrastructure capacity effortlessly to keep up with the Internet-scale data and web traffic, but scaling out also exposes certain limitations like the ability to further scale “up”. While this cloud native stack is scalable and elastic we experience performance limitations, because data access is limited by the network bandwidth, and this is exacerbated for workloads that involve repeated queries.
To address the data access challenges, we leverage Alluxio, an open source data orchestration system for analytics in the cloud. Alluxio serves as a transparent caching layer for hot and warm data, such that Hive and Spark jobs are able to access all data transparently in S3. We have seen 10x performance acceleration of Spark and Hive jobs on S3 with Alluxio.
Basic knowledge of Storage technology and complete understanding on DAS, NAS & SAN with advantages and disadvantages. A quick understanding on storage will help you make the best decision in terms of cost and need.
The Importance of Fast, Scalable Storage for Today’s HPCIntel IT Center
Today, data drives discovery. And discoveries create are key to creating sustained advantages. The better your critical workflows are able to create and access data – the better you’ll be able to discover new, innovative solutions to important problems, or to create entirely new products. More than ever before, data intensive applications need the sustained performance and virtually unlimited scalability that only parallel storage software delivers.
Designed for maximum performance and scale, storage solutions powered by Lustre software deliver the performance at scale to meet today’s storage requirements. As the most widely used parallel storage system for HPC, Lustre-powered storage is the ideal storage foundation.
But scalable performance storage by itself only solves half the problem. Today’s users expect storage solutions that deliver sustained performance, scale upward to near limitless capacities, and are simple to install and manage. Intel(r) Enterprise Edition for Lustre* software combines the straight line speed and scale of Lustre with the bottom line need for lowered management complexity and cost.
As the recognized leaders in the development and support of the Lustre file system, Intel has the expertise to make storage solutions for data intensive applications faster, smarter and easier.
Currently working in Saudi Arabia.
4.5 Years Work Experience in Infrastructure [Roads & Utilities(Pipelines and Water Reservoirs), Bridges and High rise Building Structure].
Scalable and High available Distributed File System Metadata Service Using gR...Alluxio, Inc.
Alluxio Community Office Hour
Apr 7, 2020
For more Alluxio events: https://www.alluxio.io/events/
Speaker: Bin Fan
Alluxio (alluxio.io) is an open-source data orchestration system that provides a single namespace federating multiple external distributed storage systems. It is critical for Alluxio to be able to store and serve the metadata of all files and directories from all mounted external storage both at scale and at speed.
This talk shares our design, implementation, and optimization of Alluxio metadata service (master node) to address the scalability challenges. Particularly, we will focus on how to apply and combine techniques including tiered metadata storage (based on off-heap KV store RocksDB), fine-grained file system inode tree locking scheme, embedded state-replicate machine (based on RAFT), exploration and performance tuning in the correct RPC frameworks (thrift vs gRPC) and etc. As a result of the combined above techniques, Alluxio 2.0 is able to store at least 1 billion files with a significantly reduced memory requirement, serving 3000 workers and 30000 clients concurrently.
In this Office Hour, we will go over how to:
- Metadata storage challenges
- How to combine different open source technologies as building blocks
- The design, implementation, and optimization of Alluxio metadata service
Achieving Separation of Compute and Storage in a Cloud WorldAlluxio, Inc.
Alluxio Tech Talk
Feb 12, 2019
Speaker:
Dipti Borkar, Alluxio
The rise of compute intensive workloads and the adoption of the cloud has driven organizations to adopt a decoupled architecture for modern workloads – one in which compute scales independently from storage. While this enables scaling elasticity, it introduces new problems – how do you co-locate data with compute, how do you unify data across multiple remote clouds, how do you keep storage and I/O service costs down and many more.
Enter Alluxio, a virtual unified file system, which sits between compute and storage that allows you to realize the benefits of a hybrid cloud architecture with the same performance and lower costs.
In this webinar, we will discuss:
- Why leading enterprises are adopting hybrid cloud architectures with compute and storage disaggregated
- The new challenges that this new paradigm introduces
- An introduction to Alluxio and the unified data solution it provides for hybrid environments
Vidhyalive offers netapp training(Instructor led live online training) with real-world scenarios.Learn how to configure the technologies of the NetApp. Please visit Here for further details: http://www.vidhyalive.com/product/netapp-training/
How to Build a Cloud Native Stack for Analytics with Spark, Hive, and Alluxio...Alluxio, Inc.
Alluxio Austin Meetup
Aug 15, 2019
Speakers: Tim Kelly & Thai Bui, Bazaarvoice
At Bazaarvoice, a software-as-a-service digital marketing company, the data engineering team is tasked to handle data at massive Internet-scale to serve over 1,900 of the biggest internet retailers and brands.
We built our data pipelines all in the cloud using Apache Spark and Hive on AWS EC2 accessing data in S3. AWS enables us to scale “out” the infrastructure capacity effortlessly to keep up with the Internet-scale data and web traffic, but scaling out also exposes certain limitations like the ability to further scale “up”. While this cloud native stack is scalable and elastic we experience performance limitations, because data access is limited by the network bandwidth, and this is exacerbated for workloads that involve repeated queries.
To address the data access challenges, we leverage Alluxio, an open source data orchestration system for analytics in the cloud. Alluxio serves as a transparent caching layer for hot and warm data, such that Hive and Spark jobs are able to access all data transparently in S3. We have seen 10x performance acceleration of Spark and Hive jobs on S3 with Alluxio.
Basic knowledge of Storage technology and complete understanding on DAS, NAS & SAN with advantages and disadvantages. A quick understanding on storage will help you make the best decision in terms of cost and need.
The Importance of Fast, Scalable Storage for Today’s HPCIntel IT Center
Today, data drives discovery. And discoveries create are key to creating sustained advantages. The better your critical workflows are able to create and access data – the better you’ll be able to discover new, innovative solutions to important problems, or to create entirely new products. More than ever before, data intensive applications need the sustained performance and virtually unlimited scalability that only parallel storage software delivers.
Designed for maximum performance and scale, storage solutions powered by Lustre software deliver the performance at scale to meet today’s storage requirements. As the most widely used parallel storage system for HPC, Lustre-powered storage is the ideal storage foundation.
But scalable performance storage by itself only solves half the problem. Today’s users expect storage solutions that deliver sustained performance, scale upward to near limitless capacities, and are simple to install and manage. Intel(r) Enterprise Edition for Lustre* software combines the straight line speed and scale of Lustre with the bottom line need for lowered management complexity and cost.
As the recognized leaders in the development and support of the Lustre file system, Intel has the expertise to make storage solutions for data intensive applications faster, smarter and easier.
Currently working in Saudi Arabia.
4.5 Years Work Experience in Infrastructure [Roads & Utilities(Pipelines and Water Reservoirs), Bridges and High rise Building Structure].
DarioTM is a state-of-the-art in diabetes management platform that connects the user, caregiver and healthcare professional anywhere in the world. Dario‘s cloud-based software provides you with an easy seamless way to record, save, track, analyze, manage & share all your diabetes related information in one lifestyle management platform.
The DarioTM management app supports full diabetes lifecycle and allows you to record your blood glucose, food intake, insulin administered, physical activities and other different activities and situations along with personal trends graphs, personal challenges, sharing and alerting.
The DarioTM Smart Mobile Device Application is a tool for managing your personal diabetes care. To ensure accurate data management, it is recommended that the application be used individually and not be shared on a single device.
Oracle Systems Overview
Engineered systems strategy and overview about exadata, exalitics, superCluster, Exalogic, Oracle virtual appliance, ZFS appliance
Oracle Database Appliance Portfolio overview. #ODA @OralceODA.
This deck will show the benefits of the ODA as your Engineered System best optimised to run the Oracle Database.
To learn more contact: daryll.whyte@oracle.com
(ODA Account Manager- UK Market)
Exadata has been around since 2008 and the software features are being enhanced each release. This Presentation talks about the 12.1.x.x series of Software updates and some of the things you can now do with Exadata
Oracle has set the bar extremely high for Exadata. We are designing a single hardware platform that is best for any class of Database Workloads. The hardware is identical for all workload types since high compute capacity, high network bandwidth, low latency, high IO throughput, and Flash help any workload. The software features vary by workload. For example Oracle has many Warehouse specific software features such as Bitmap indexing, integrated OLAP and Data Mining, etc. The Unique capabilities of Exadata are highlighted in the presentation by being underlined in Red
Oracle believes that the Scaleable Grid architecture is the architecture of the future. It eliminates the long-standing tradeoff between high-end hardware platforms that are scaleable (up to a point) and available, but also very high cost due to low volume. Sometimes people think that because there is so much compute and storage in a database machine it must consume huge amounts of power. In fact the power consumption is not large. Maximum Power usage of a Full Rack Database Machine is 14KW, typical is 9.8 KW. A single high end SMP platform without storage or switches can consume well over 20 KW.
Exadata allows easy expansion within and between racks. A quarter rack can be upgraded to a half rack. A half rack can be upgraded to a full rack. Two half racks can also be connected together to form the equivalent of a full rack. This is sometimes useful in data centers with weight or heat density restrictions. Once a full rack is deployed it can be increased in half rack size increments. For example a full rack grows to 1.5 racks, then to 2 racks, then to 2.5 racks. Equipment can be mixed across hardware generations. For example a half rack can be grown to a full rack using the next generation of servers to fill out the rack.
This is all about scale out. Scale outwards ! Exadata has much more compute, storage, and interconnect capacity than other systems on the market. An 8 rack Exadata system is equivalent to at least 30 racks of leading conventional products, and costs much less. To purchase equivalent compute and storage capacity using conventional equipment would cost over $100M (The price of a single IBM P595 taken from the TPC web site is about $4MM). The user data capacity is much larger after compression. Scales beyond 8 racks by using external InfiniBand switches
Eliminates the complexity of deploying a high performance database system. Database machines are tested in the factory and delivered ready to run. Because all database machines are the same, their characteristics and operations are well known and understood by Oracle field engineers and support. Each customer will not need to diagnose and resolve unique issues that only occur on their configuration. Performance tuning, and stress testing performed at Oracle is done on the exact same configuration that the customer has ensuring better performance and higher quality. Applications do not need to be certified against Exadata. Applications that are certified with Oracle Database 11.2 RAC will run against Exadata. Very few applications need to certify the storage subsystem underneath a database, and Exadata fundamentally is the Oracle Database with a very fast storage subsystem.
Exadata storage servers scan the data in parallel removing all central bottlenecks. Traditional storage has bottlenecks at the back-end disk loops, caches, controllers, front-end channels, and SAN links. In traditional storage, receiving Terabytes of data into the DB server and filtering it consumes large amount of CPU in the database hosts.
The Exadata Smart Flash cache avoids cache wipe-outs caused by large scans. A simple example is that Exadata knows when a read operation is caused by a backup, and avoids caching the blocks. Note that Enterprise Storage Arrays now support flash disks but there are no reported IOPs numbers from any vendor for their storage array using flash. The I/O performance numbers shown here are measured at the database level, not pure storage statistics that cannot be achieved in practice. Some vendors quote component level performance numbers that cannot be achieved in a complete systems due to bottlenecks at other parts of the system. Also, remember that Exadata is a full system including servers, storage, and networking, not a pure storage device when comparing to other products. NetApp and EMC have released flash cache products. EMC uses conventional flash disks for cache which makes them much slower than Exadata’s Flash PCI cards. NetApp uses Flash PCI cards for their cache, but the largest NetApp systems (6080) have at most 8 flash cards. Neither vendor is willing to quote specific IO’s per second or data throughput numbers for their flash solutions. Neither vendor can combine flash with 10x compression, InfiniBand, and storage offload. Only Oracle allows individual tables and partitions to be placed in flash with a simple command.
Exadata has fully redundant hardware. Redundant servers, redundant storage servers, redundant network. So any component can fail and the system as a whole will keep running. Our measurements to date show that the hardware failure rate is dominated by disk failures. The Oracle database software tolerates failures by continuing to run when various hardware components fail. For example Oracle RAC continues to run after server failures. ASM mirrors data across storage servers so that the failure of a storage server does not cause an outage of the system as a whole. Oracle has unique capabilities for rolling back erroneous changes called flashback. Oracle has unique capabilities for making changes to databases online called online redefinition. All truly highly available systems should have a remote replica. Oracle has the industry’s leading technologies for creating and maintaining remote replica databases. Golden gate provides a powerful symmetric replication capability. Active Data Guard provides an extremely high performance and simple way to create a readable remote replica database.