Application Performance Optimization and Load Balancing

Application Performance optimisation and Load fitApplication Performance Optimization and Load Balancing utilize tear and Caching TechniquesAkilesh KailashSunil Iyer Kolar Suresh KumarSabarish VenkatramanABSTRACTAs the selective information processing and demand for storage grows, the mathematical exploit of a critical application should invariably be intact with respect to disk I/O. There has been considerable improvements related to disk seek, latency and spindle speeds However, these improvements have not met the challenges and addresses the need for improve performance and shipment balancing. The challenge of any Database administrator is to maximize the Application I/O performance and ensure the high availability with zero downtime. This performance challenge digest be met using I/O monitor lizarding, Load balancing, Cache management and burst (Redundant Array of tinny discs) technologies. The primary goal of this constitution is to exemplify the details of succes sfully solving the I/O problems of a database application in a consistent fashion with the appropriate rupture configurations, caching mechanisms and fill balancing algorithm.Categories and Subject DescriptorsB.3.2 Design Styles Mass storage RAID.D.4.2 Storage Management subaltern storage, Storage hierarchies.D.4.3 File Systems Management File organization.D.4.4 Communications Management Input/Output.D.4.5 Reliability Backup procedures, Fault-tolerance.General TermsAlgorithms, Performance, Design, Theory, Reliability.KeywordsRAID Redundant Array of Inexpensive DisksI/O Input/OutputDBA Database AdministratorsHA High AvailabilityOLTP Online Transaction Processing.IOPS HBA 1. INTRODUCTIONRAID technology addresses the need for higher storage competency in IO system and provides the feature of data redundancy. This helps in efficient and improved disk access and avoids data loss by disk nonstarters. Theoretically, RAID is primarily used to create a logical disk from two or mor e physical disk drives in order to provide high bandwidth. RAID is an imperative part of storage stack and fabric degree and is coordinated by various storage vendors kindred EMC, Hitachi, NetApp. RAID technologies have enumerated different methods in building storage stacks and sub-systems for different kinds of databases.Thus, the two main technical reasons for switching to RAID argon scalability and high availability in the context of I/O and system performance. As the database sizes of today have grown manifold from the gigabytes to petabytes range, the intricacy to scale I/O performance of much(prenominal) gigantic systems is needed very much for critical applications.Load balancing is a critical factor in environments like Operating Systems, Clusters, Networking and Applications. They play a quintessential case in the performance and reliability of any environment avoiding catastrophic failures. In a quotidian scenario, the resource allocation and load balancing atomic number 18 through through hash methods, genetic algorithms and several scheduling algorithms in Operating systems.Many database applications demand high throughput and availability from storage subsystems. For instance, a stock marketplace application running in New York stock exchange will need to have a high throughput and bandwidth with absolutely no downtime. This requires continuous operation i.e., the need to satisfy each I/O request even in the case of disk failures.It is not accep submit to meet the aforementi atomic number 53d requirements at the be of deprived performance mainly in real-time applications such as video and audio. It is highly unacceptable if a video is played at slower speed or the data is lost during transmission and ends abruptly.Since a database application may encounter extreme I/O activity or suffer a sudden spike of I/O activities for a brief period of time, the organization of the database structure onto the disk becomes imperative.2. PROBLEM DEFIN ITION missionary station critical data centers have a compelling need to have highly available applications and services thereby ensuring zero downtime. Current clustering solutions, like MSCS or HP Service Guard enable HA for vital applications. However, such applications be specific and developed only for the OS/application for which they argon designed.The I/O performance and their patterns of a database application has to be analyzed by understanding their relation with the physical storage so that it helps in determine the deployment of application found on any given workload.I/O from an application needs to be categorized based on which appropriate techniques dirty dog be used in order to improve its performance. There atomic number 18 many DBA tuning software which are primarily used for indexing the database and monitor the drive activities. This approach is effective but requires lot of time and in reality it is quite tedious in nature.3. ABSTRACT SOLUTIONThe possible solutions areDetermining the RAID Level and stripe sizeRAID levels are determined on factors such as type of I/O, disk cost, strike/write I/O and so on. The data transfer rate and IOPS performance is very much influenced based on the segment size elect and the striping size used.For example In a RAID 5 configuration, there are 4 disks and 1 simile disk. Let the segment size of each disk be 64KB. Thus, when an I/O of 64KB has to be addressed, it is written to the first drive. The next I/O of 64KB is written to next and so on and finally the parity of the 4 I/Os is calculated and written to the last disk. In case of RAID 1 (Mirroring), there are 2 disk groups and 2 mirror groups. A 64KB I/O would be written to each of the disk drives and mirrored drives.Caching techniquesSplitting the lay awayThe save acts as an interface between the host application and RAID controllers. The cache can be divided into two parts viz. front-end and back-end. Database applications can believe on the front-end cache.Pre flummoxingOLTP applications may have I/O operations which are not sequential the pre-fetch algorithm confirms the addresses which will fetched in future and loads it in memory. The amount of data to be pre-fetched depends on the application requirement, memory and performance desired by application.Database organization on a storage systemOrganizing the database objects such as tables, logs, views on storage layout comes in a wide range. Based on the structure of the database layout, an appropriate storage is chosen.Load BalancingI/O load balancing across cluster nodes are performed using regression analysis. If a port of an HBA or fabric node is loaded intemperately, then the I/O is balanced across the ports which are not utilized to its full potential.4. LITERATURE SURVEYI/O performance and disk I/O contention plays a vital role for critical applications. Our proposal and work on application performance monitor and I/O tuning and load balancing is motivated ba sed on the Oracle I/O Performance and Array tuning Best Practices paper. The proposed solution and enhancements are based on similar lines of these papers. We start off the survey by explaining the technical feasibilities, the pros and cons of these approaches discussed in the papers and explain in brief about the issue we are addressing based on the survey findings.5. PERFORMANCE BOTTLENECKSApplication performance and write access is in the main obtained by using storage Arrays having different RAID configurations. For instance, the striping of data across multiple disks using RAID 1 in order to achieve redundancy is the most common way of obtaining high availability.Disk failure vulnerabilities in enterprise storageThe main motivation of going for striping technologies is because of the vulnerability in disk failures in enterprise storage Arrays which can aftermath in catastrophic loss of data. This high availability of application and I/O is obtained at the cost of write perform ance.Keeping synch of write operationsDuring a write operation, all the writes have to be updated simultaneously to all the disks in order to keep the disks in synch. This will have a catastrophic termination in operations which will have heavy writes and its performance. In addition to it, maintaining the synchronization of data between all disks and achieving concurrency is a difficult task and can lead to system crashes.In order to overcome the aforementioned problems a number of different striping mechanisms have been proposed each of them have their specific trade-off based on cost, high performance, scalability and robustness. The majority of RAID configurations are based on the interleaving of the data and the pattern is which the redundant information is distributed across the disks.Load Balancing of I/O and resource utilizationLoad balancing is essentially implemented in SQL server clustering and is very common practice. There are many third party tools that provide solut ions to load balancing and resource utilization however the limitations of such tools is that the factors to decide on load balancing are very system specific and are dependent heavily on the characteristic of each application.As the database size grows in a short period, we generally observe that the query speed has a performance hit as the number of rows increases. This is mainly observed on applications where the performance data is being collected in frequent intervals and simultaneously the data is read from the DB for other purposes. The general and quick solutions to optimize query speed it to partition the views, indexing and table partitioning. But even then, things are observed to be quite slow. The main problem with such solutions is that the database tables and views are located on different servers. Hence a server cluster is used which add in reliability if there is any performance issues seen on one of the cluster nodes.6. RAID LEVEL excerption CRITERIAThe choice of RAID level to be chosen is based on different factors. When a mirrored configuration is chosen such as RAID 1 or RAID 1+0, each write request is duplicated to disk by the raid controller. This results in performance issues if the application does not swear heavily on data duplication and its availability.When higher levels/parity based RAID configuration is used, things get more intricate. Let us consider that, when RAID 5 or RAID 6 is used and if the size of the write I/O is less than the stripe size which is frequently observed in database applications where the data write is around 4kb pages contrasting to the drive size of around 128KB as a result of this, the raid controller has to perform magnitude of I/O operations for just a single request.The main drawback of the above technique is that for a small write request, the raid controller has to first fetch the data from the back end disk to the main memory. Then it has to insert the fresh data at the appropriate position and ca lculate the new parity stripe to perform another write operation back to the disk. Hence, one I/O operation results in roughly 3 to 4 propagation the IOPS. This overhead adds in if the calculation of parity is for two sets as in RAID 6.The other factors of choosing the RAID configuration are the disk/drive cost and I/O pattern. The cost is zero for RAID 0 as there is no redundancy while it is highest for RAID 1 or its crew such as RAID 10. This cost is high because of drive mirroring.The cost of RAID 5 is comparatively lower than RAID 1 but it has one disk which is dedicated for parity. A cleared distinction is required to classify small I/O and large I/O. The bursty nature and large I/O is seen if the request for the I/O is more than the one third of the cache size. All the small/short I/Os are addressed in cache thereby avoiding the RAID access.All in all, RAID 5 and 6 are generally preferred for large I/O and sequential I/O operations while RAID 1 and RAID 10 is preferred for s hort I/O operations.7. mountain chain FOR IMPROVEMENTThis paper goes on the aforementioned aspects and concentrates on monitoring the I/O pattern, analyzing the load on each of the I/O and performing a load balance if required In addition to the above criteria, taking the I/O pattern into consideration, an appropriate RAID configuration along with write-back cache method is used if necessary.8. PROPOSED SOLUTIONCharacterize the I/O patternThe first step is to monitor the I/O and characterize it. This is done using tools such as Perfmon or IO Meter. We plan to use these tools and analyze the I/O pattern of a given application. This monitoring of pattern is required as we will characterize the request as read intensive, write intensive, how the load is being varied.Perform load balancing upon I/O sceptreThe morsel step is to perform load balancing. This is done by analyzing the load and identifying the threshold of the I/O from a server HBA Port through the fabric layer to the stor age Array. Threshold is a boundary which serves as a benchmark for comparison or guidance, and any deviation or breach of the said threshold may result in a change in state of an overall system.Our proposed infrastructure identifies the threshold by analyzing the I/O graph and monitoring the following parametersLinear RegressionSlope of the curveUsing Linear Regression, the value of the slope is calculated. Based on these two parameters, if we observe that if one of the HBA ports is heavily loaded, we tend to balance it out by redistributing the excess load to different cluster nodes.Once the I/O is balanced, an appropriate RAID configuration is calculated.9. closure AND FUTURE WORKAfter studying the I/O access patterns of various workloads, we can clearly the map the database application to the physical storage thereby achieving high performance, fast access and retrieval. This would be helpful for DBAs to deploy management applications and would be easy to track the application p erformance.This analysis can be implemented at the enterprise level configuration as well resulting in efficient usage of physical storage, making it cost effective and trim the work for DBAs or lab administrators.10. REFERENCESThe RAID Book Sixth Edition. RAID Advisory Board.LACIE RAID Technology White Paper.RAID High-Performance, Reliable Secondary Storage ACM Computing Surveys Peter M. Chen, Edward K. Lee.Array tuning best practices A Dell technical white paper DOI=http//www.dell.com/downloads/global/products/pvaul/en/powervault-md3200i-performance-tuning-white-paper.pdf.Exploring Disk Size and Oracle Disk I/O performance DOI= http//www.openmpe.com/cslproceed/HPW02CD/paper/11026.pdf