001 学习 Hadoop 的 11 个主要原因

001 Why Hadoop is Important – 11 Major Reasons To Learn Hadoop Hadoop

In today’s fast-paced world we hear a term – Big Data. Nowadays various companies collect data posted online. This unstructured data found on websites like Facebook, Instagram, emails etc comprise Big Data. Big Data demands a cost-effective, innovative solution to store and analyze it. Hadoop is the answer to all Big Data requirements. So, let’s explore why Hadoop is so important.

在当今这个快节奏的世界里，我们听到了一个术语 -- 大数据. 如今，各种公司都在网上发布数据. Facebook 、 Instagram 、电子邮件等网站上的非结构化数据包括大数据. 大数据需要一个经济高效、创新的解决方案来存储和分析它. Hadoop 是所有大数据需求的答案. 那么，让我们来探讨一下 Hadoop 为何如此重要.

Why Hadoop is Important – 11 Major Reasons To Learn Hadoop

Hadoop Quiz

Why Hadoop is Important

Hadoop 为何重要

Below is the list of 11 features that answer – Why Hadoop?

下面是 11 个功能的列表，这些功能回答了 Hadoop 的原因？

1. Managing Big Data

1. 驾驭大数据

As we are living in the digital era there is a data explosion. The data is getting generated at a very high speed and high volume. So there is an increasing need to manage this Big Data.

我们生活在数字时代、数据爆炸，数据以非常高的速度和体积生成. 因此，管理这些大数据的需求越来越大.

Why Hadoop

As we can see from the above chart that the volume of unstructured data is increasing exponentially. Therefore in order to manage this ever-increasing volume of data, we require Big Data technologies like Hadoop. According to Google from the dawn of civilization till 2003 mankind generated 5 exabytes of data. Now we produce 5 exabytes every two days. There is an increasing need for a solution which could handle this much amount of data. In this scenario, Hadoop comes to rescue.

从上面的图表中我们可以看到，非结构化数据的数量呈指数级增长. 因此，为了管理不断增长的数据量，我们需要 大数据技术 像 Hadoop. 据谷歌 从文明的黎明到 2003年，人类产生了 5 exabytes 的数据.现在我们每两天生产 5 个亿字节.人们越来越需要一个能够处理如此大量数据的解决方案.在这种情况下，Hadoop 来救援.

With its robust architecture and economical feature, it is the best fit for storing huge amounts of data. Though it might seem difficult to learn Hadoop, with the help of DataFlair Big Data Hadoop Course, it becomes easy to learn and start a career in this fastest growing field. So Hadoop must be learnt by all those professionals willing to start a career in big data as it is the base for all big data jobs.

它具有强大的架构和经济的特性，是存储海量数据的最佳选择. 学习和开始职业生涯变得很容易. 因此，所有愿意在大数据领域开始职业生涯的专业人士都必须学习 Hadoop，因为它是所有大数据工作的基础.

2. Exponential Growth of Big Data Market

2. 成倍增长的大数据集市

***“Hadoop Market**** is expected to reach ****$99.31B**** by ****2022**** at a ****CAGR**** of ****42.1%”**** – *Forbes

Slowly companies are realizing the advantage big data can bring to their business. The big data analytics sector in India will grow eightfold. As per NASSCOM, it will reach USD 16 billion by 2025 from USD 2 billion. As India progresses, there is penetration of smart devices in cities and in villages. This will scale up the big data market.

公司慢慢意识到大数据给他们的业务带来的优势. 印度的大数据分析行业将增长 8 倍.根据 NASSCOM，到 2025年，从 160亿美元到 20亿美元.随着印度的进步，智能设备已经渗透到城市和乡村.这将扩大大数据市场.

As we can see from the below image there is a growth in the Hadoop market.

正如我们从下图中看到的，Hadoop 市场正在增长.

Why Hadoop

There is a prediction that the Hadoop market will grow at a CAGR of 58.02% in the time period of 2013 – 2020. It will reach 1.5 billion in 2012.

有预测称，在 58.02%-2013年期间，Hadoop 市场将以 2020 的复合年增长率增长.到 2020年将从 2012年的 502亿美元增至 15亿美元.

As the market for Big Data grows there will be a rising need for Big Data technologies. Hadoop forms the base of many big data technologies. The new technologies like Apache Spark and Flink work well over Hadoop. As it is an in-demand big data technology, there is a need to master Hadoop. As the requirements for Hadoop professionals are increasing, this makes it a must to learn technology.

随着大数据市场的增长,大数据技术的需求.Hadoop 是众多大数据技术的基础.Apache Spark 和 Flink 等新技术在 Hadoop 上运行良好.大数据技术是一种有需求的大数据技术,掌握 Hadoop.随着对 Hadoop 专业人员的要求越来越高，这使得学习技术成为必须.

3. Lack of Hadoop Professionals

3. Hadoop 缺乏专业人员

As we have seen, the Hadoop market is continuously growing to create more job opportunities every day. Most of these Hadoop job opportunities remain vacant due to unavailability of the required skills. So this is the right time to show your talent in big data by mastering the technology before its too late. Become a Hadoop expert and give a boost to your career. This is where DataFlair plays an important role to make you Hadoop expert.

正如我们所看到的，Hadoop 市场不断增长，每天都在创造更多的就业机会.这些大部分Hadoop 工作机会由于没有所需的技能，仍然空缺.因此，现在是时候通过在为时已晚之前掌握这项技术来展示你在大数据方面的天赋了.成为 Hadoop 专家给你的职业生涯一个提升.这是 DataFlair 在让你成为 Hadoop 专家方面发挥重要作用的地方.

4. Hadoop for all

4. Hadoop 的一切

Professionals from various streams can easily learn Hadoop and become master of it to get high paid jobs. IT professionals can easily learn MapReduce programming in java or python, those who know scripting can work on Hadoop ecosystem component named Pig. Hive or drill is easy for those who know to the script.

来自各种流的专业人员可以轻松学习 Hadoop，并成为 it 的大师，从而获得高薪工作.IT 专业人士可以轻松学习 MapReduce用 java 或 python 编程，知道脚本的人可以在 Hadoop 生态系统组件 Pig 上工作.对于那些知道脚本的人来说，Hive 或 drill 很容易.

You can easily learn it if you are:

如果你是，你可以很容易地学习它:

• IT Professional

• Testing professional

• Mainframe or support engineer

• DB or DBA professional

• Graduate willing to start a career in big data

• Data warehousing professional

• The project manager or lead

• IT 专业

• 测试专业人员

• 主机或支持工程师

• 专业数据库或 DBA

• 愿意在大数据领域开始职业生涯的毕业生

• 数据仓库专业人员

• 项目经理或领导

5. Robust Hadoop Ecosystem

5. 强劲 Hadoop 的生态系统

Hadoop has a very robust and rich ecosystem which serves a wide variety of organizations. Organizations like web start-ups, telecom, financial and so on are needing Hadoop to answer their business needs.

Hadoop 有一个非常强大和丰富的生态系统为各种各样的组织服务.像 web 初创企业、电信、金融等组织都需要 Hadoop 来满足他们的业务需求.

Hadoop ecosystem contains many components like MapReduce, Hive, HBase, Zookeeper, Apache Pig etc. These components are able to serve a broad spectrum of applications. We can use Map-Reduce to perform aggregation and summarization on Big Data. Hive is a data warehouse project on the top HDFS. It provides data query and analysis with SQL like interface. HBase is a NoSQL database. It provides real-time read-write to large datasets. It is natively integrated with Hadoop. Pig is a high-level scripting language used with Hadoop. It describes the data analysis problem as data flows. One can do all the data manipulation in it with Pig. Zookeeper is an open source server that coordinates between various distributed processes. Distributed applications use zookeeper to store and convey updates to important configuration information.

Hadoop 生态系统包含 MapReduce 、 Hive 、 HBase 、 Zookeeper 、 Apache Pig 等多个组件，这些组件能够服务于广泛的应用.我们可以使用地图缩小对大数据进行汇总汇总.Hive 是顶级 HDFS 上的一个数据仓库项目.它提供了类似 SQL 接口的数据查询和分析.一个 NoSQL 数据库.它提供对大型数据集的实时读写.它与 Hadoop 本身集成.Pig 是 Hadoop 中使用的高级脚本语言.它将数据分析问题描述为数据流.你可以用 Pig 做所有的数据操作.Zookeeper 是一个在各种分布式进程之间进行协调的开源服务器.分布式应用程序使用 zookeeper 来存储重要配置信息的更新.

6. Research Tool

6..研究工具

Hadoop has come up as a powerful research tool. It allows an organization to find answers to their business questions. Hadoop helps them in research and development work. Companies use it to perform the analysis. They use this analysis to develop a rapport with the customer.

Hadoop 已经成为一个强大的研究工具.它允许一个组织找到他们的业务问题的答案.Hadoop 帮助他们进行研发工作.公司用它来进行分析.他们利用这种分析与顾客建立融洽的关系.

Applying Big Data techniques improve operational effectiveness and efficiencies of generating great revenue in business. It brings a better understanding of the business value and develops business growth. Communication and distribution of information between different companies are feasible via big data analytics and IT techniques. The organizations can collect data from their customers to grow their business.

申请大数据技术提高运营效率和效率，为企业创造巨大的收入.它带来了对业务价值的更好理解和业务增长的发展.不同公司之间的信息沟通和分配是可行的大数据分析和 IT 技术.组织可以从他们的客户那里收集数据来发展他们的业务.

7. Ease of Use

7. 易用性

Creators of Hadoop have written it in Java, which has the biggest developer community. Therefore, it is easy to adapt by programmers. You can have the flexibility of programming in other languages too like C, C++, Python, Perl, Ruby etc. If you are familiar with SQL, it is easy to use HIVE. If you are ok with scripting then PIG is for you.

Hadoop 的创建者用 Java 编写了它拥有最大的开发者社区.因此，程序员很容易适应.你也可以像 C，C + +，Python，Perl，Ruby 等其他语言的编程的灵活性.如果你熟悉 SQL，它很容易使用 HIVE.如果你对脚本没问题，那么 PIG 是给你的.

Hadoop framework handles all the parallel processing of the data at the back-end. We need not worry about the complexities of distributed processing while coding. We just need to write the driver program, mapper and reducer function. Hadoop framework takes care of how the data gets stored and processed in a distributed manner. With the introduction of Spark in Hadoop, ecosystem coding has become even easier. In MapReduce, we need to write thousands of lines of code. But in Spark, it has come down to only a few lines of code to achieve the same functionality.

Hadoop 框架处理后端数据的所有并行处理.在编码时，我们不需要担心分布式处理的复杂性.我们只需要编写驱动程序、映射程序和 reducer 函数就可以了.Hadoop 框架负责如何以分布式方式存储和处理数据.随着Hadoop 中 Spark 的介绍生态系统编码变得更加容易.在 MapReduce 中，我们需要编写数千行代码.但是在 Spark 中，实现相同功能的代码只有几行.

8. Hadoop is Omnipresent

8. Hadoop无处不在

Why Hadoop is important

There is no industry where Big Data has not reached. Big Data has covered almost all domains like healthcare, retail, government, banking, media, transportation, natural resources and so on. We can see this in the figure above. People are increasingly becoming data aware. This means they are realizing the power of data. Hadoop is a framework which can harness this power of data to improve the business.

没有一个行业没有大数据.大数据已经覆盖了医疗、零售、政府、银行、媒体、交通、自然资源等几乎所有领域.我们可以在上图中看到这一点.人们越来越意识到数据.这意味着他们正在意识到数据的力量.Hadoop 是一个可以利用这种数据力量来改进业务的框架.

Companies all over the world are trying to access information from various sources like social media. They are doing so in order to improve their performance and increase their revenue. Many organization face problem in processing heterogeneous data to extract value out of it. It has a capability to guide revolutionary transformation in research, invention and business marketing.

世界各地的公司都试图从社交媒体等各种来源获取信息.他们这样做是为了提高业绩，增加收入.许多组织在处理异构数据以从中提取价值时面临着问题.它有能力指导研究、发明创造和商业营销的革命性变革.

Big names like Walmart, New York Times, Facebook etc are all using Hadoop framework for their companies and thus demand a very good number of Hadoop experts. So become Hadoop expert now before its too late to get a job in your dream company.

像沃尔玛、纽约时报、 Facebook 等大公司都在使用 Hadoop 框架因此，他们的公司需要大量的 Hadoop 专家.所以现在就成为 Hadoop 专家吧，在你梦想中的公司找到工作还为时过晚.

9. Higher Salaries

9. 高薪

In the current scenario, there is a gap between demand and supply of Big Data professional. This gap is increasing every day. According to IBM, demand for* US data professionals will reach to 364000 by 2020*. In the wake of the scarcity of Hadoop professionals, organizations are ready to offer big packages for Hadoop skills. As per indeed, the average salary for Hadoop skill is $112,000 per annum. It is 95% higher than the average salaries for all other job postings. There is always a compelling requirement of skilled people who can think from a business point of view. They are the people who understand data and can produce insights with that data. For this reason, technical persons with analytics skills find them in great demand.

在目前的场景下，大数据专业人才的需求和供给存在缺口.这个差距每天都在增加.根据IBM,需求到 2020年，美国数据专业人员将达到 364000 人.在 Hadoop 专业人员稀缺的情况下，组织准备为 Hadoop 技能提供大包.事实上，Hadoop 技能的平均年薪是 112,000 美元.这比所有其他职位的平均工资高出 95%.对于能够从商业角度思考的技术人员来说，总是有令人信服的要求.他们是理解数据的人，可以用这些数据产生洞察力.因此，具有分析技能的技术人员对他们的需求很大.

10. A Maturing Technology

10. 成熟的技术

Hadoop is evolving with time. The new version of Hadoop i.e. Hadoop 3.0 is coming into the market. It has already collaborated with HortonWorks, Tableau, MapR, and even BI experts to name a few. New actors like Spark, Flink etc. are coming on the Big Data stage. These technologies promise the lightening speed of processing. These technologies also provide a single platform for various kinds of workloads. It is compatible with these new players. It provides robust data storage over which we can deploy technologies like Spark and Flink.

Hadoop 是随着时间的推移而发展的.Hadoop 的新版本，即 Hadoop 3.0 即将上市.它已经与 HortonWorks 、 Tableau 、 MapR 甚至 BI 专家合作，仅举几例.像 Spark 、 Flink 等新演员即将登上大数据舞台.这些技术保证了处理的速度.这些技术还为各种工作负载提供了一个单一的平台.它与这些新玩家兼容.它提供了强大的数据存储，我们可以通过它部署 Spark 和 Flink 等技术.

The advent of Spark has enhanced the Hadoop ecosystem. The coming of Spark in the market has enriched the processing capability of Hadoop. Spark creators have designed it to work with Hadoop’s distributed storage system HDFS. It can also work over HBase and Amazon’s S3. Even if you work on Hadoop 1.x you can take advantage of Spark’s capabilities.

Spark 的出现增强了 Hadoop 生态系统.Spark 在市场上的出现，丰富了 Hadoop 的处理能力.Spark creators 将其设计为使用 Hadoop 的分布式存储系统HDFS.它还可以通过 HBase 和 Amazon 的 s3 工作.即使你在 Hadoop 1.X 上工作，你也可以利用 Spark 的功能.

The latest technology Flink also provides compatibility with Hadoop. You can use all the Map-Reduce APIs in Flink without changing a line of code. Flink also supports native Hadoop datatypes like Writable and WritableComparable. We can use Hadoop functions within Flink program. We can mix Hadoop functions with all the other Flink functions.

的Flink 最新技术还提供了与 Hadoop 的兼容性.您可以在不更改一行代码的情况下使用 Flink 中的所有 Map-Reduce api.Flink 还支持本地 Hadoop 数据类型，如可写和可写.我们可以在 Flink 程序中使用 Hadoop 功能.我们可以将 Hadoop 函数与所有其他 Flink 函数混合使用.

11. Hadoop has a Better Career Scope

11.Hadoop 有更好的职业范围

Hadoop excels in processing a wide variety of data. We have various components of Hadoop ecosystem providing batch processing, stream processing, machine learning and so on. Learning it will open gates to a variety of job roles like:

Hadoop 擅长处理各种各样的数据.我们有 Hadoop 生态系统的各种组件，提供批处理、流处理、机器学习等.学习它将为各种工作角色打开大门，比如:

• Big Data Architect

• Hadoop Developer

• Data Scientist

• Hadoop Administrator

• Data Analyst

• 大数据架构师

• Hadoop 开发者

• 数据科学家

• Hadoop 管理员

• 数据分析师

By learning Hadoop you can get into the hottest field in IT nowadays. Even a fresher can get into this field with proper training and hard work. People already in the IT industry working as ETL, architect, mainframe professional and so on have an edge over freshers. But with a determination, you can build your career as a Hadoop professional. Companies use it almost in all domains like education, health care, insurance and so on. This enhances the chances of getting placed as a Hadoop professional.

通过学习 Hadoop，你可以进入当今最热门的领域.即使是一个新人也可以通过适当的培训和努力工作进入这个领域.已经在 IT 行业从事 ETL 、架构师、大型机专业人员等工作的人比新人更有优势.但是有了决心，你可以打造你的 Hadoop 职业生涯.公司几乎在教育、医疗保健、保险等所有领域都使用它.这增加了成为 Hadoop 专业人员的机会.

Increased Adoption of Hadoop by Big Data Companies

大数据公司更多地采用 Hadoop

Why Hadoop

Fortune 1000 companies are adopting Big Data for their growing business needs. Here is the status of big data adoption across various organizations –

《财富》 1000 强企业采用大数据满足他们日益增长的业务需求.以下是各种组织采用大数据的情况 --

• 12% of big data initiatives are under consideration

• 17% of big data initiatives are underway

• 67% of big data in production

• 12%大数据计划正在考虑之中

• 17%大数据计划正在进行中

• 67%生产中的大数据

From the above statistics, it is clear that the adoption of Hadoop is accelerating. This is creating a* huge demand for Hadoop professionals* with high salary bracket.

从以上的统计数据可以清楚的看出，Hadoop 的采用正在加速.这是创造一个Hadoop 专业人员的巨大需求工资待遇很高.

As said by Christy Wilson Hadoop is the way of the future. This is because companies aren’t going to be able to remain competitive without the power of big data. And there no viable, affordable options aside from Hadoop.

正如 Christy Wilson Hadoop 所说，这是未来的道路.这是因为如果没有大数据的力量，公司将无法保持竞争力.除了 Hadoop 之外，没有可行的、负担得起的选项.

Hope you got the answer to why Hadoop.

希望你对 Hadoop 的原因有了答案.

Summary

Hence, in this why Hadoop article, we saw that this is the age of emerging technologies and tough competitions. The best way to shine is to have a solid understanding of the skill in which you want to build your career. Online training which is instructor-led is useful for learning Big Data technology. Also, the training with hands-on projects would give a good grip on the technology. Hadoop started off with just two components i.e. HDFS and MapReduce. As time passed more than 15 components got added to the Hadoop ecosystem and it is still growing. Learning these old components helps in understanding the newly added components.

因此，在 Hadoop 的这篇文章中，我们看到，这是一个新兴技术和激烈竞争的时代.闪耀的最佳方式是对你想要建立职业生涯的技能有一个坚实的理解.讲师指导的在线培训对于学习大数据技术非常有用.此外，通过动手项目进行的培训将会很好地掌握这项技术.Hadoop 最初只有两个组件，即 HDFS 和 MapReduce.随着时间的推移，Hadoop 生态系统中增加了超过 15 个组件，并且仍在增长.学习这些旧组件有助于理解新添加的组件.

The article is sufficient enough to decide why you should learn Hadoop. So start learning it today and DataFlair promises to help you in your Hadoop learning path. You can tell us your thoughts on why Hadoop article through comments.

这篇文章足以决定为什么你应该学习 Hadoop.所以从今天开始学习它，DataFlair 承诺帮助你在 Hadoop 学习道路上.你可以通过评论告诉我们你对 Hadoop 文章的想法.

https://data-flair.training/blogs/why-hadoop