IRJET- A Scrutiny on Research Analysis of Big Data Analytical Method and Cloud Computing with De

International Research Journal of Engineering and Technology (IRJET) Volume: 06 Issue: 04 | Apr 2019

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A SCRUTINY ON RESEARCH ANALYSIS OF BIG DATA ANALYTICAL METHOD AND CLOUD COMPUTING WITH DEVELOPING IMPACT OF TESTING Tanuj G Bhandary1, Dr.Anandhi Giri2 1Student,

YMT College of Management, kharghar Professor, Dept. of Master in Computer Applicaiton(MCA),YMT College of Management, Kharghar, Maharashtra, India.

-------------------------------------------------------------------------***---------------------------------------------------------------------2Associate

ABSTRACT: The fast development in Big Data, just as the extension in data analytics platforms lately, for example, Hadoop and NoSQL, are making new opportunities for cloud computing. Open cloud providers, for example, Amazon Web Services, Google, and Microsoft offer their own brands of the big data system in their cloud, regardless of whether NoSQL or SQL, that is most proficient and effortlessly versatile for companies all things are considered. The majority of this direct us toward the equal connection among cloud and Big Data that is driven by consumer demand for greater, better, and quicker applications. Truth be told, the combination of Big Data and distributed or cloud computing has prompted another services model referred to as Analytics as a Service (AaaS). This model will give association speedier, adaptable approaches to incorporate, analyze, change, and imagine different kinds of structured, semi-structured, and unstructured data in progressively.

information execution to little and medium measured organizations. Cloud can give a framework, platform, and programming assets or software resources as administrations or services to big data. Big Data gives generous incentive to associations who execute cloud in their foundation or infrastructure. Big data and cloud technology join to make big data analytics in the cloud a sensible choice. Big data analytics is growing to include data from a multitude of sources new analytics techniques should be created so the vast amounts of data generated can be managed efficiently. Also, new tools need to be developed to process those data. Big Data as a Service and its goal is to make the whole procedure of Big Data analytics simpler and give companies the opportunity for further business intelligence. In this research paper, we examine testing natural engineering with important key advantages, to perform the execution of experiments and utilized testing strategies to improve the nature of cloud applications.

Big Data is a data analysis methodology technique empowered by ongoing advances in advances and engineering. However, big data involve a huge commitment of hardware and processing resources, making adoption costs of big data technology prohibitive to small and medium-sized businesses. Cloud or Distributed computing offers the guarantee of huge

KEYWORDS: Big data, data analytics, data management, big data-asa-service, analytics-as-a-service, business intelligence lease, storage cloud computing, Hadoop, cost-benefit analysis model. advances in automated sensors and capacity have made a great deal of data, for instance, Internet, sensor, spouting or phone data. Big data speaks to higher and more extravagant data that demonstrates more insights concerning practices, exercises, and occasions that happened all around, so the investigation of these big data would require access to assorted sorts of resources inside less reaction time. There are three kinds of data: organized data; data put away in SQL databases and have standard organizations like date, keywords, numbers, which can be recovered effectively by explicit questions. Semi-organized data; like organized data isn't put away in databases yet have some organized arrangements like XML and CSV records. To recover the semi-organized data, complex rules are required. The third kind is the unstructured data;

1. INTRODUCTION: The Internet has become the answer for all our questions as it is a place where information is shared and the web is being browsed for data. The Internet immersion continually increases, as an ever-expanding number of people pursue the Web, use email also and casual association applications to visit with one another or get to remote interactive media administrations, for instance, flexible TV. As big data showed up on the scene as another pattern in the most recent decade. Many associations like Google, Yahoo, eBay, Facebook, Amazon, Flipkart, and Twitter ended up worried about big data since their appearance on the business scene. The entrance to such an overall data and correspondence structure close by the

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data that don't have a particular configuration and isn't put away in the database, similar to instant messages, video, and sound. Organizations that gather data may utilize it to deliver new income streams. For that, furthermore, organizations must start with a business purpose behind the analytics, and after that, recognize which type of analytics, they have to decide how data will be gathered, arranged, and handled for the chose structure of analytics.

IBM data analysts fight that the key size of big data is the "4Vs": volume, speed, variety, and veracity. As broad and little endeavors persistently try to design new things to oversee big data, the open source stages, for instance, Hadoop, allow to load, save and query a significant dimension of data and execute superior big data analytics in parallel over a exceeded on the bundle. Bunch getting ready models, for instance, Map Reduce, engage the data organization, mix and taking care of from different sources. Various big data plans in the market abuse outside information from an extent of sources (e.g., relational associations) for exhibiting and feeling examination, for instance, the IBM Social Media Analytics Software as a Service course of action. Cloud providers have recently begun to develop new server farm for encouraging long range relational correspondence, business, media content or legitimate applications and organizations.

Toward this path, the determination of the records distribution core innovation relies upon a few variables, for example, the volume of information, the velocity with which the data is required or the type of investigation to be performed. Theoretical huge information stockroom sketch is displayed. Another necessary check is the conveyance of big data capabilities through the cloud. The appropriation of big data as-a-benefit (BDaaS) plans of motion empowers the effective stockpiling and administration of big informational collections and information coping with from an outdoor supplier, and also the misuse of a full scope of investigation abilities (i.e., information and prescient examination or enterprise understanding are given as administration primarily based purposes in the cloud). In this specific circumstance, Zheng et al. essentially audit the administration produced big data and big data as-a-benefit the proposition of a framework to supply usefulness to overseeing and breaking down a number of varieties of administration created huge information. A primary data as-a-benefit

2. BACKGROUND: Big data and cloud computing have risen as a giant area of lookup for many researchers, mirroring the volume and effect of innovation in method and model in modern business organizations. The starting and increase of big data used to be as early as 2011. Cloud computing as one of the most well-known developments in the closing decade, appeared at the top of the list of the ten new developments in 2012. Although big data and Cloud computing are nonetheless in their initial levels of development, they are still struggling from so many issues and programming problem issues. Even though, it grew to be so obvious to many researchers that utilizing their skills have produced full business services.

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According to Jiang and Chai (2016), the expression big data was connected to data units that are so massive where software tools generally can't hold, manage, and process them for the duration of a suitable time frame. The enforcement of big data is widely well-known by many industries and companies at present (Wang and Zhao, 2016). Big data has imparted a golden opportunity to the universal market, every part of the industry is attempting to evaluate the higher possibilities to attain and analyses much extra information to take higher decisions. Too a good deal data means a lot more use-cases main to more illustrations of business evaluations that subsequently would lead to higher business decision making, this scenario will lead to greater earnings for many industries (Sosna et al., 2010).

Cloud computing substantiated itself inside the business, training, and IT conditions. Any association in such situations can utilize, share, and design assets that are accessible in the cloud, along these lines, diminishing the cost of these assets For some processing foundations and expert representatives who manage big amounts of analysed data, cloud computing can comprehend such difficulties by lessening the cost, time, and exertion by means of sharing the required assets on the cloud, so organizations can pay to utilize these assets as administrations. An extremely decent overview of portable cloud computing and Internet of things for big data applications was directed. A few Companies who are worried about media communications; volume and speed of more ethical route traffic, got the advantage from the gathered data utilizing the intensity of big data analytics.

For instance, Disney land got the advantage from big data analytics by means of presenting numerous benefits therefore from the gathered data from. Amazon utilized the gathered data as well to foresee what a client wants to purchase and, in this manner, acquainted the items with them as per their preferences. In numerous associations, the changes coming about because of data analytics have produced a vital enthusiasm for business knowledge; which in some cases point to procedures and advances that assistance in creating better understandability of the market and furthermore help in making better choices in exact timespan.

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structure has been likewise utilized to supply big information administrations and data investigation outcomes to clients, upgrade talent and reduce cost.

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control. This gathering the primary problems in Big Data into three classifications in view of the shared attribute of the check.

A. VOLUME OF BIG DATA The data compose that increments most rapidly is vague information. This data write is described by way of "human data, for example, pinnacle notch recordings, films, photographs, logical reenactments, financial exchanges, cellphone records, genomic datasets, seismic pictures, geospatial maps, email, post, Facebook data, callfocus discussions, cellphone calls, website clicks, archives, sensor information, telemetry, therapeutic archives and pictures, climatology and local weather records, log documents, and content.

As indicated by way of cyberspace, data with unstructured can also signify over 70% to 80%of all data in associations. This information, which for the most phase start from online networking, represent 80% of the data international and characterize 90% of Big Data. As of now, 84% of IT chiefs procedure unstructured information, and this charge is relied upon to drop with the aid of 44% soon. To store the expanded measure of information, HDDs must have substantial capacity limits. In this way, the accompanying segment explores the advancement rate of HDDs

Fig. 1: A conceptual big data warehouse architecture Data increments rapidly at a rate of 10x at ordinary intervals. From 1986 to 2007, the international capacities with admire to mechanical records stockpiling, calculation, preparing, and correspondence had been observed through 60 analogs and advanced improvements in 2007.

In computer technology, Big Data is a primary difficulty that requires actual consideration. Up to this point, the primary scenes of Big Data have no longer been introduced together. Moreover, Big Data cannot be organized using current improvements and strategies. Therefore, the age of boundless information by using the fields of science, business, and society is a global issue. As for statistics examination, for example, systems and fashionable apparatuses have not been supposed to seem and dissect good sized datasets. Therefore, associations ride early difficulties in making, overseeing, and controlling massive datasets. Frameworks of data replication have likewise proven some protection shortcomings as for the age of several duplicates, data administration, and strategy.

These techniques represent the data that are put away, broke down, and acquired to. They additionally figure out the value of this information. To method, unstructured data sources in Big Data ventures, worries with respect to the versatility, low idleness, and execution of statistics foundations and their server farms need to be tended to. In the IT enterprise, all in all, the quick ascent of Big Data has produced new problems and difficulties as for data administration and investigation. Five regular problems are volume, assortment, speed, esteem, and multifaceted nature as per in this examination, there are greater problems recognized with information, for example, the quick improvement of volume, assortment, esteem, administration, and security. Each problem speaks to a big difficulty of specialized research that requires discourse.

Future research bearings in this area are resolved in light of possibilities and a few open problems in Big Data

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B. RAPID GROWTH OF DATA As already mention in Volume of Big data there has been a rapid growth of data by international and almost characterize by 90% of Big Data. The data is growing rapidly throughout the world. Starting at now, 84% of IT bosses procedure unstructured data, and this charge is depended upon to drop by means of 44% inside the near future.

C. DEVELOPMENT RATE OF HARD DISK DRIVES (HDDS) The enthusiasm for an electronic limit is exceptionally adaptable. It cannot be definitely met and is controlled just via spending designs and company ability and talk about the recorded surroundings of restrict devices, beginning with attractive tapes and plates and optical, stable state, and electromechanical devices. Going earlier than the computerized revolt, data was generally secured in easy tapes as confirmed by means of the reachable bits.

3. BIG DATA MANAGEMENT The format of Big Data needs to be synchronized with the help institution of the affiliation. To date, most of the data used by means of affiliations are lethargic. Data is logically sourced from a number of fields that are disturbed and tangled, for e.g., data from machines or sensors and sweeping wellsprings of open and personal data.

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Effectively, most associations have been no longer capable of both trap or save these data, and accessible gadgets could not control the data in a smart measure of time. At any rate, the new Big Data development improves execution, energizes headway in the matters and companies of plans of activity, and offers necessary administration guide. Tremendous Data improvement hopes to restrain equipment and taking care of charges and to test the estimation of Big Data until now giving primary affiliation resources. Suitably directed Big Data are open, tried and true, secure, and sensible. Hereafter, Big Data features can be related to a variety of complicated normal controls, along with barometrical science, astronomy, sedate, science, genomics, and biogeochemistry. In the going with the region, we all of sudden seem at information business enterprise mechanical assemblies and recommend each other data existence cycle that uses the progressions and wordings of Big Data.

corporations may want to improve their businesses. For example, companies like Google, Twitter, Amazon, and Facebook introduced their interest in processing big data within the cloud via accumulating big quantities of data using comments posted on social media. The collected information expanded its products and decreased cost.

The Banica and Hagiu (2015) form a big data infrastructure by use of a new NoSQL DB for storing Big Data in their project and then applied the assignment on Hadoop for gathering each structured data and unstructured data. The first architecture layer was once designed to acquire any kind of data whether or not structured or unstructured whilst the second layer was once used for processing the preceding gathered data the use of Hadoop. The final layer was once used for analyzing the Big Data by use of analytical enterprise and modeling equipment.

A. MANAGEMENT TOOLS

This perspective is related when the measure of data is unnecessarily for a singular machine. HDFS is a greater character boggling than different document pattern given the complexities and vulnerabilities of frameworks. The bundle consists of two kinds of centers. The important center factor is a name-center that goes about as a specialist center. The 2nd middle factor compose is a data center factor that goes about as slave middle point. This kind of middle factor comes in items. Alongside these two kinds of middle points, HDFS can in a similar fashion have helper name-center point. HDFS save archives in prevents, the default rectangular size of which is 64MB. All HDFS information is duplicated in gadgets to operate the parallel getting prepared for an excellent deal of data.

C. HDFS(HADOOP DISTRIBUTED FILE SYSTEM)

With the development of figuring advancement, large volumes can be administered besides requiring supercomputers and excessive cost. Many gadgets and techniques are accessible for data organization, consisting of Simple database, NoSQL, Google Big Table, MemcacheDB, Voldemort, and Data Stream Management System (DSMS). Regardless, associations need to make exceptional gadgets and developments that can store, get to, and study a big measure of data in close constant in light of the way that Big Data shifts from the ordinary data and cannot be secured in a single machine. Also, Big Data does no longer have the structure of regular data. For Big Data, without a doubt the most generally used gadgets and strategies are Hadoop, Map Reduce, and Big Table.

4. CLOUD COMPUTING Circulated registering has changed into some other dealing with a perspective where the cloud may want to provide each virtualized tools and programming sources that stimulated remotely and provide a utilization on-ask for gain illustrate. Conveyed processing provided a capacity to get to share sources and common structure, which give advantages to ask for finished the framework to operate workouts that meet altering business needs. It gives places of work to clients to execute, skip on and control their functions 'on the cloud' which consists of virtualization of benefits that jam and accomplishes itself. Cloud testing makes use of cloud ordinary designing for programming testing. Affiliations searching for after regular testing that passing on a couple of challenges like restricted check spending design, assembly due dates. To serve an excellent thing, testing is the final responses for any sort of difficulty we would seem to be in the future from the client site.

Cloud testing is a kind of programming testing whereby

B. HADOOP IN BIG DATA ANALYTICS Big data analytics need an environment that is supported with cluster servers which can control the required tools needed to analyze and method the large data. According to Kalra (2016), a cloud computing surrounding is already designed with excessive storage and networking capabilities needed to assist big data tools.

Hadoop is “an open source software program platform that enables the processing of massive data sets in a distributed computing environment.” Banica and Hagiu (2015) discussed big data standards and the regulations for building, organizing, and analyzing big datasets in a business environment. The authors provided three architecture layers and indicated some graphical equipment that may want to be used to explore and signify unstructured data. They further specified how well-known

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testing is executed via the usage of sources over cloud functions below the cloud establishment. This is the area cloud testing has created as some other method to manipulate testing where circulated processing prerequisites are used to reproduce certifiable with application's execution, consistency, speed, security, and helpfulness.

The author Chaudhary et al. in 2015 mention that, big data methods enhance the operational effectiveness and efficiencies of producing higher revenues in business. The effectiveness and efficiency of such methods have been analyzed in the literature using the thinking that big data brings a larger appreciation of organizations values and helps in growing enterprise growth.

An accurate survey used to be carried out via Plageras et al. (2017) for new technologies such as big data, IoT, and cloud computing and monitoring. The authors have tried to discover the frequent operations between these technologies and they tried to get the advantage through combining the functionality to these 4 technologies, to discover out their common operations, and mix their functionality.

Communications and distributions of information between different companies are in modern times convenient the usage of IT techniques and big data analytics. These companies can collect data from their clients to beautify their businesses. For e.g, IBM has developed a collaborating and reacting methodology to assist retired people. IBM has implemented this methodology for the retired person in Italy who needed offerings like healthcare and different emergency services. The developed technology relies upon normally on sensors that are allotted inside the home to measure different elements like heat, O2 level, clamminess, water, and electricity. Any odd readings in these elements will alert the accountable provider departments like fireplace department, paramedics, or police in accordance with the situation. This collaborative responsive method has helped in reducing assistance price of retired person up to 30% and additionally has helped in handing over required offerings in a shorter time with less disbursement.

By merging two algorithms, a new algorithm for IoT networks used to be proposed by means of Memos et al.

(2017). The important concept of the lookup was worried about creating a clever town framework use of the new proposed merged algorithm. According to some authors, their experimental outcomes confirmed the efficiency of the proposed strategy in phrases of privacy and security.

7. EMPLOYING CLOUD COMPUTING IN BIG DATA ANALYTICS Organizations that want cloud computing for big data analytics can use private, public, or combination of both public cloud and private cloud i.e hybrid cloud computing networks. In a private cloud, a company can share sources inside the equal enterprise to analyze data, so staff can store efforts and time when he/she makes use of the accessible sources in the cloud and share it with different employees, information can then be processed and managed quickly. Using a public cloud, a company can share exterior sources to manage its enterprise at a decrease cost. A hybrid cloud; on the different hand, is a merging of both public cloud and private cloud types that can be used inside enterprises to reduce time, cost, effort, and consequently manage big data analytics correctly and effectively.

6. BENEFITS OF BIG DATA ANALYTICS ON BUSINESS Technologies for keeping and analyzing data are widely available at decrease costs, however corporations are taking data in order to use it at new levels, the use of data science to assist for correct and secure enterprise experimentation to direct choice makers and assist them to take a look at outputs, business models, and regeneration of client experience. Sometimes, new developments assist companies to make choices in actual time. These developments have the opportunity to assist an innovative transformation in research, invention, and business marketing. Some companies, like Amazon, eBay, Flipkart and Google have been considered as early commandants, analyzing elements that manipulate overall performance to outline what raises income revenue and consumer interactivity.

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In their research, Zhang et al. (2017) have described the improvement route of smart systems by way of introducing the primary ideas of artificial intelligence, computing device learning, data mining, statistical analysis, structure recognition, synthetic neural networks, and fuzzy appropriate judgment technologies. The authors analyzed, in extra details, the regular pattern of data mining technologies and mentioned the instructions of data mining in artificial intelligence, e-commerce functions, and cellular communication computing.

5. EMPLOYMENT OF BIG DATA ANALYTICS

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The used platform is referred to as one of the cloud computing service models i.e. PaaS for big data analytics in cloud computing. This platform offers an organization's staffs with all the libraries, tools, and wanted functions to operate their jobs. The implementation of Hadoop in cloud computing environments is a suitable example. Moreover, there can be either structured data or non-structured data

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which is distributed among different software in the cloud through billions of users.

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through regular dashboards for a whole investigation of how their applications and the internet will operate throughout top volumes.

Cloud computing could be considered via specific perspectives, like hardware, user, data, or software perspectives. As a hardware perspective, the situation is then will be towards the configuration of the network as soon as it faces a bottleneck. When viewing as a data perspective for cloud computing, we deal with how large the quantity of data that may want to be managed or processed over the cloud. Finally, the software point of view is concerned about how to manipulate exclusive software functions in the cloud and be capable to serve several ranges of users.

8. EXAMPLES ON CLOUD COMPUTING AND BIG DATA ANALYTICS (BDA) BENEFITS Cloud computing is used in many environments and big data is deployed in the inner side of it in many areas, the following are examples of BDA and cloud computing:

Fig. 2: Infrastructure capacity /cost 10. FORMS OF CLOUD-BASED SOFTWARE TESTING

1. Healthcare: Modern-day technologies in healthcare surroundings have produced rapid, huge, and heterogeneous quantities of information that wanted to be processed and used in a beneficial way. Cloud computing and big data analytics got here to help specific hospitals in managing such big clinical data that got here out from affected person reports, medical examinations, and other sources, by means of gathering and processing accumulated data in a manageable way to assist in improving services offered by way of healthcare centers through the possibilities provided by Cloud computing.

There are 4 different kinds of forms of cloud-based software testing or application. Each has been focused on different objectives: A. TESTING A SaaS IN A CLOUD It reassures the satisfactory of a Software as a Service or also said as SaaS in a cloud primarily based on its functional and non-functional service requirements.

B. TESTING OF A CLOUD

2. Education and learning: The transformation from standard techniques of studying into online studying has led to big amounts of data to turn out to be accessible online. Such data wants to be processed and modified into understanding and then educational sources can then be used on the cloud to reduce the cost troubles.

It approves the nature of a cloud from an external view in bright of the gave cloud decided skills and administration highlights.

C. TESTING INSIDE A CLOUD

9. ARCHITECTURE SUPPORT FOR CLOUD COST & TESTING

It tests the nature of a cloud from an interior view in light of the interior foundations of a cloud and decided cloud proficiencies. Just cloud dealers can execute this type of test because they have gets to internal foundations and associations between its internal SaaS and programmed proficiencies, security, administration, and screen.

Cloud computing engineering, lots of the identical as some different software or programming, is regarded into two principles segments: Front End and Back End. The front end is a client or any software which is making use of cloud administrations. Back end is the system of client machines with servers having PC application and data stockpiling framework. Cloud has introduced together server enterprise to administrate the frameworks customer, requests and so on. When client conditions are produced and the test is outlined and executed. Once the test completed the cloud expert corporation deliver comes about and examination returned to corporate IT specialists

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applications, sinking the price of registering, while expands testing viability.

For appear into researchers, we would possibly prefer to lean towards mechanization testing utilization and presentation of computerization testing devices for cloud software as future work to be executed as a specialist action. In this research, I have been gone through BDA method and Cloud Computing with developing impact of testing where we can testing on the basis of the already stored data in database but we can develop from using already stored data to live data which is performed presently with cloud computing and BDA using Business Intelligence where the data will be automated detect and simultaneously test the data.

Fig. 3: Cloud-based testing 11. CONCLUSION: Taking Advantage of Big Data Analytics (BDA) inside a cloud computing environment can promote quickness and industrialization performance. The transformation towards BDA helps the performance predictors to permit selection makers to appoint similarly data in making many movements when striving enterprise goals. When companies appoint BDA, they can basically predict already unpredictable things, and thus, improve the overall performance of processes. Organizations can get the advantages by price reduction, satisfactory operations plan, decrease stock levels, high-quality organizational labor force, and remove a wasteful source of the usage of big data in a cloud computing environment. These developments will have an impact on the enhancements in operations efficiency. We would possibly no longer say that each and every successful enterprise will utilize big data in cloud computing environments to alternate the decision-making process. Big data will train us to be in the race and despite the challenges in BDA, many sectors can develop themselves in being quickness of utilizing big data in cloud computing environments. Since systems administration is pervasive and excellent measures of data are presently accessible, big data is imagined to be the gadget for efficiency development, improvement and client excess. Immense open entrance recognized with reducing part of big data examination and enterprise perception is at the front line of research, concentrating on the examination of creative business-driven philosophies that can alternate specific segments.

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Cloud testing must be feasible making use of specific foundations of cloud administrations and testing devices.

As the development of cloud innovation and testing as administrations, more scientists work have completed tackling the open problems and difficulties in cloud computing. In this paper, testing ideas used to develop the area of cloud testing. Presently days, Diversion of programming enterprise in the direction of cloud computing due to the fact of specific reasons, for example, price decrease. Testing in the cloud, use the cloud

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