오랫동안 하둡 주위에 많은 마약 중독이 있었다. 하둡은 매우 효율적인 큰 데이터 프로세싱 툴을 인식하기 때문에이 과대가 예상. 그러나 시간이 약간의 감기를보고왔다, 하드 사실. 과대 광고가 천천히 죽고 기업이 투자 수익을보고 시작하면 그것은 시간이다,,en,설문 조사,,en,가트너에 의해 실시,,en,많은 회사들이 사용하는 기술이 없기 때문에 하둡에 투자 할 계획이없는 것으로 보여 것 또는 여전히 사용자 비우호적 인 도구로 간주됩니다,,en,다른 이유도있다,,en,하둡의 전망에 대해 낙관적 인 사람의 또 다른 그룹이있다,,en,상황이 혼란을 보이는 경우,,en,하둡 향한 자세가 과대와는 환멸의 위상을 입력이기 때문이고, 그 자연,,en,이 기업은 현실 얻을 시작 시간입니다,,en,이 회사가 객관적으로 평가하고 하둡을 사용하는 시간입니다,,en,하둡 도입에 대한 의견을 대조,,en,위에서 언급 한 바와 같이,,en (ROI). A survey, conducted by Gartner, seems to show that a lot of companies are not planning to invest in Hadoop because they do not have the skills to use it or it is still deemed a user-unfriendly tool. There are other reasons as well. However, there is another group of people who are bullish about the prospects of Hadoop. If the situation seems confusing, it is because the attitude towards Hadoop is entering the phase of disillusionment from that of hype and that is natural. This is the time when businesses start to get realistic. This is the time when companies will objectively evaluate and use Hadoop.
Contrasting opinions on Hadoop adoption
As stated above, 이 하둡 채택에있어 기업은 두 그룹으로 나누어집니다,,en,한 그룹은 꺼려 기업 포함,,en,주저하거나 신중는 하둡 채택에 와서 두 번째 그룹은 하둡 좋은 투자 수익 (ROI)을 제공하는 것입니다 생각 기업을 포함하는 경우,,en,이전 그룹의 태도는 가트너의 조사에 반영됩니다,,en,설문 조사에서 두드러진 연구 결과는 다음과 같습니다 감안할 때,,en,조사 결과 5 월에 발표 된 주,,en,결과는 꽤 업데이트됩니다,,en,설문 조사의 타겟 고객으로 구성 중소 규모 기업과 C 레벨 임원,,en,응답자의 미래에 하둡에 투자 할 계획이없는,,en,다만,,en,응답자의 향후 2 년에 하둡에 투자 할 계획을 가지고,,en,응답자의 배포 또는 하둡 실험,,en: one group comprises enterprises that are reluctant, hesitant or circumspect when it comes to Hadoop adoption and the second group comprises enterprises that believe Hadoop is going to give good ROI. The attitude of the former group is reflected in the Gartner survey. Given below are the salient findings from the survey. Note that the survey findings were released in May, 2015. So, the results are pretty updated. The survey target audience comprised small and medium sized companies and C-level executives.
- 54% of the respondents do not plan to invest in Hadoop in the future.
- Just 18% of the respondents have plans to invest in Hadoop in the next two years.
- 26% of the respondents are deploying or experimenting with Hadoop.
- 하둡 채택에 주저하거나 망설였다 기업은 하둡에 대해 생각하지 않는 이유와 같은 기술 부족 및 사용자의 텃세를 인용,,en,머브 아드리안에 따르면,,en,가트너의 부사장,,en,어떤 계획이나 이미 하둡 여행에 조직의 대형 발생으로,,en,하둡에 대한 미래 수요는 적어도 다음을 통해 상당히 빈혈이 보인다,,en,그 위에,,en,하둡 채택을위한 단기 계획의 부족 제안,,en,빅 데이터 현상에 대한 지속적인 열정에도 불구하고,,en,하둡에 대한 수요는 특히 가속되지 않는다,,en,하둡에 대한 이러한 부정적인 반응에 대한 주요 이유는 아래와 같다,,en,하둡 기술의 부족은 중요한 제약 조건입니다,,en,기업은 직원이 하둡을 사용 할 수없는 주장,,en,원래의 형태로,,en.
According to Merv Adrian (vice president at Gartner), “With such large incidence of organizations with no plans or already on their Hadoop journey, future demand for Hadoop looks fairly anemic over at least the next 24 개월”. Moreover, the lack of near-term plans for Hadoop adoption suggests that, despite continuing enthusiasm for the big data phenomenon, demand for Hadoop specifically is not accelerating”. The main reasons for such a negative response to Hadoop are given below.
- Lack of Hadoop skills is an important constraint. Enterprises claim that their staff is not capable of using Hadoop. Hadoop, in its original form, has been largely confined to an exclusive group who could use it productively. Though a number of third-party tools are coming up to facilitate the use of Hadoop, even they are not easy to use. The main complaint against Hadoop and the third-party tools are they require new skills to be learnt which means additional investment. Existing skills cannot be used. Though training is available for these tools, experts believe that it will take another 2 to 3 years for these programs to gain credence.
- For many enterprises, Hadoop is not a priority. They think that Hadoop is overkill for the business problems it is supposed to solve. It is like deploying a missile to kill a group of flies. Also, the cost of Hadoop adoption is more than the benefit derived by solving the business problems enterprises are facing.
The second group is optimistic and confident about Hadoop adoption. There are companies that have started using Hadoop for their mainstream business and are reaping benefits. The main feature that is being used is real-time data processing. For example, companies can prevent fraud by analyzing data on a real-time basis. Companies are able to provide better products by analyzing on a real-time basis data feedback from their customers. They are receiving data from website-usage, video, Internet banking, social media and various other sources. In a survey conducted by TechValidate, 96% of the respondents are running several use cases on a single Hadoop cluster and among them, 20% are deploying nearly 50 use cases on a single Hadoop cluster. The survey revealed that 73% of the respondents are deploying their products and services and 59% are benefiting from reduced costs. Most of the above companies are MapR customers. According to Bryon Dover, a big data engineer with the Rubicon Project, “MapR gives me the reliability to process 3 trillion transactions a month with 99.999% uptime.”
What to make of the above findings?
The two extreme attitudes towards Hadoop adoption can be generally confusing but in the context of business cycle, this stage represents just another phase: that of enterprises leaving the hype stage and entering the evaluation stage. When there is hype, everything seems rosy but when there is evaluation, the disadvantages also come out. So, businesses are finding out how to best use Hadoop to solve their business problems or whether, Hadoop is at all required.
Hadoop needs to get over its exclusivity for sure because it is considered a difficult tool to use, available only to people who are specialized. There is no good front-end that makes it easy for people to process and analyze data. Also, there is a need to learn Hadoop and that needs additional investment. Third-party tools that claim to make Hadoop easy to use are not exactly living up to their claims. So, the whole offering needs modifications and it is going to take time. Basically, Hadoop needs to prove that it is easy to use.
Enterprises need to realize that one of the best uses of Hadoop is when you are processing data real time. That is where the second group of customers is reaping benefits. Batch processing is not where you should be focusing. Real time processing can enable you prevent frauds and offer customized products and services to your customers. Hadoop is not meant for static data. The image below shows that real-time usage is the biggest consideration for Hadoop.
In this context, it is pertinent to mention Apache Spark which has been doing a stellar job analyzing big data real time. It gives you a unified and comprehensive framework that helps you to manage huge data sets from variety of sources in real-time basis. The biggest advantage with Spark is that you can rapidly write applications in Python, Java or Scala and has more than 80 high-level operators. It also supports SQL queries, machine learning, streaming data and processing of graph data, other than Map and Reduce operations. 극히 간결한, it can prove to be an effective real-time processing application.
하둡의 실시간 사용,,en,새로운 기술의 채택은 시간이 걸립니다,,en,과대 광고 및 채택은 다른 것들,,en,그것은 아주 가능하다의 백분율,,en,하둡은 많은 기업의 주류 생산 단계에 진입하고 그 혜택이 보여주는 시작으로 몇 시간이 지나면 그렇게 할 수 하둡에 투자 할 계획하지 않은 가트너 설문 조사의 응답자의,,en,이 제품의 새로운 기술은 하둡을 더 사용할 수 있도록하기 시작, 특히 이후,,en,하둡의 SQL,,en,더 넓은 지역 사회에 하둡이 더 접근 할 수 있도록 단지 출발점이 될 수 있습니다,,en,하둡을 향한 무관심은 비생산적인 도구가되지 않습니다,,en,그것은 기업이 여전히 방법에 익숙하지 않은 유일한 것입니다,,en,MapR 고객은 확증 겠지만,,en
Image1: 하둡의 실시간 사용,,en,새로운 기술의 채택은 시간이 걸립니다,,en,과대 광고 및 채택은 다른 것들,,en,그것은 아주 가능하다의 백분율,,en,하둡은 많은 기업의 주류 생산 단계에 진입하고 그 혜택이 보여주는 시작으로 몇 시간이 지나면 그렇게 할 수 하둡에 투자 할 계획하지 않은 가트너 설문 조사의 응답자의,,en,이 제품의 새로운 기술은 하둡을 더 사용할 수 있도록하기 시작, 특히 이후,,en,하둡의 SQL,,en,더 넓은 지역 사회에 하둡이 더 접근 할 수 있도록 단지 출발점이 될 수 있습니다,,en,하둡을 향한 무관심은 비생산적인 도구가되지 않습니다,,en,그것은 기업이 여전히 방법에 익숙하지 않은 유일한 것입니다,,en,MapR 고객은 확증 겠지만,,en
Any adoption of a new technology takes time. Hype and adoption are different things. It is quite possible that a percentage of the 57% of the respondents of the Gartner survey who did not plan to invest in Hadoop may do so after some time as Hadoop enters the mainstream production stage of many companies and its benefits start showing. This is especially after new technologies of products start to make Hadoop more usable. The SQL on Hadoop, 예를 들면, may be just the starting point of making Hadoop more accessible to a wider community.
Summary
The indifference towards Hadoop does not make it an unproductive tool. It is only that businesses are still unfamiliar with its ways. As MapR customers will corroborate, you need to identify how to best use Hadoop for solving your business problems. Using it for real-time data processing in the mainstream production appears to be the way to go. 비슷하게, there are other benefits too that still seem undiscovered. Of course, much around Hadoop and its ecosystem needs to change. It needs to be more accessible to anyone who wants to use it. The slow adoption rate of Hadoop could turn out into an acceptable proposition after 2 to 3 years.
