reviews
Hadoop, or Apache Hadoop as it is also known, was first released in 2006. This open-source collection of software utilities had gained a great reputation in the industry. Its data processing capabilities can handle massive amounts of data and large-scale computation. Since a Hadoop cluster involves commodity hardware at a low-cost, data scientists find it a very cost-effective framework.
Start-ups like Cloudera made successful use of Hadoop. This led to the framework becoming very important for big data. Whether it’s data mining or using big data Hadoop in various other ways, the framework demonstrated its flexibility.
That said, some observers question the long-term prospects of Hadoop due to the growing reach of cloud computing. Many modern big data solutions have positioned themselves as an intense competition to Hadoop.
However, its processing power and scalability mean that Hadoop remains highly relevant today. Hadoop supports a great deal of concurrency, thanks to its distributed computing model. It automatically creates a back-up of data sets, which reduces the risks from hardware failures.
Whether you need insights from massive eCommerce data flow or you are working on an Artificial Intelligence (AI) / Machine Learning (ML) project, Hadoop can deliver great value. In another example, businesses are already planning to use Hadoop in conjunction with blockchain to improve the trustworthiness of their data.
Can you hire Hadoop developers easily? Not exactly. Amidst the talk of Hadoop facing stiff competition, a big data engineer with a comprehensive Hadoop skill set earns an impressive paycheck in the United States.
You need to choose the right hiring platform. Websites providing part-time freelancers can help, and some of them focus exclusively on software development. If you want full-time developers, then software development companies are a much better option.
Look for the following skills when interviewing:
Primary Apache Hadoop development skills
The primary skills that a Hadoop developer needs are as follows:
Get a complimentary discovery call and a free ballpark estimate for your project
Trusted by 100x of startups and companies like
- Deep knowledge of the Apache Hadoop framework;
- In-depth knowledge of the MapReduce programming model;
- Comprehensive knowledge of Apache HBase, the popular open-source non-relational database;
- In-depth knowledge of HDFS (Hadoop Distributed File System), which handles the data storage part of Hadoop;
- Deep knowledge of Apache Kafka, the distributed streaming system that helps to integrate real-time data from several stream-producing sources;
- In-depth knowledge of Sqoop, the popular command-line interface (CLI) that helps to transfer data from relational databases to Hadoop and vice-versa;
- Excellent knowledge of SQL;
- Comprehensive knowledge of ETL tools and best practices;
- Deep knowledge of Apache Pig, a well-known platform to create programs that run on Hadoop;
- The experience of creating, managing, monitoring, and troubleshooting of Hadoop infrastructure;
- Sufficient knowledge of Apache Hive, the popular data warehouse solution that utilizes Hadoop and provides query/analysis capabilities;
- Deep knowledge of Linux, which includes the skills to manage its operations, networking, and security aspects.
Other skills that a Hadoop developer needs
You will need a few more skills when you hire Hadoop developers, and these are as follows:
A. Java skills
The creators of Hadoop built it using Java. Developers that work on Hadoop need very good Java skills. This will help them to use the capabilities of Hadoop effectively. They also need good Linux skills since Hadoop was built on Linux.
B. The knowledge of Apache Spark
Effective Hadoop developers should know Apache Spark sufficiently. This cluster computing technology uses Hadoop MapReduce, however, it extends it to achieve greater efficiency. Programmers can write applications quickly using this analytics engine, and they can use it interactively from your Java, Python, R, and Scala shells.
C. An understanding of the limitations of Hadoop
While Hadoop is powerful, you need developers that understand its limitations. Programmers that understand this can help you to implement effective solutions based on Hadoop. They will use the strengths of Hadoop and avoid using it where it isn’t suitable.
For example, developers should understand the limitations of Hadoop in developing web apps. You can develop a web app using JavaScript or Node.js, however, Hadoop can’t be used as the backend of the web app. Hadoop isn’t a database. It offers HDFS, which is a file system that won’t allow random read and write. Experienced developers will know that they should use HBase, which runs on top of Hadoop.
D. The knowledge of security in the context of Hadoop implementation
Another area where Hadoop has limitations is security. Developers need to implement security measures explicitly to secure the data set they will work with. This takes knowledge and experience, and this is a key reason why you should look for Hadoop developers with years of experience.
E. The knowledge of using cloud platforms for Hadoop integration
Depending on your business needs, you might choose to run Hadoop in the cloud. This is especially relevant if you don’t have the necessary on-premise computing resources to run a massive Hadoop cluster.
Reputed managed cloud services providers like Amazon, Google, or Microsoft can help in such cases. AWS, Google Cloud Platform, and Microsoft Azure are powerful cloud platforms with plenty of capabilities and they can help you run Hadoop on the cloud. You need Hadoop developers that are familiar with these cloud platforms.
F. The knowledge of achieving success in a software development project
Finally, you would need a few generic skills and competencies. These are as follows:
- Knowing how to develop RESTful APIs and secure them;
- The ability to write code that others can understand easily, which makes maintenance easier;
- The knowledge of computer science fundamentals;
- The experience of working in large distributed systems;
- Knowing how to manage a large volume of data effectively;
- The experience of reviewing code;
- The ability to collaborate with testers, DevOps engineers, etc.
How to find competent Hadoop developers?
Now that you know the skills and competencies to look for, you need to take the following steps:
1. Choose a hiring platform to hire Hadoop developers
Your choice of hiring platform impacts the future course of your project. If you hire competent people, then your project has a better chance of success.
On the other hand, developers that aren’t capable of handling complex projects can adversely impact your schedule, budget, and quality objectives. Turning around a troubled project is hard work, you need to avoid this at all costs.
You can find Hadoop developers on freelancer platforms. General-purpose freelancer platforms can connect you to freelancers, and you might be able to get a low hourly rate. However, working with freelancers involves several risks.
Freelancers work part-time in your project, and managing part-time workers remotely can be challenging. Freelancer platforms deduct a considerable part of their pay, which can demotivate freelancers.
Hire expert developers for your next project
1,200 top developers
us since 2016
Reputed software development-focused freelance platforms claim to rely on a stringent screening process. This can help you to get a competent freelancer. However, you still need to mitigate the risks of working with freelancers. Freelance platforms don’t offer any project management support.
Software development companies such as DevTeam.Sapce offer access to full-time Hadoop developers. Our transparent contracting process saves you time and effort. We cover you at every turn, including providing a replacement if the original developer gets sick, etc.
If you are not 100% happy with the quality of your code then you don’t pay until you are.
Finally, we secure your sensitive data using comprehensive measures, which is another advantage. For example, our developers sign a “Non-Disclosure Agreement” (NDA). Review your business needs carefully before choosing a hiring platform.
2. Interview the candidates
You have selected the hiring platform, and now it’s time to interview candidates. If you know Hadoop, then you can interview them. Otherwise, you need to take help from a knowledgeable associate or find interview questions on the Internet.
Cover all the skill areas that we have mentioned. Review the portfolio of the candidates and focus on the complex projects that they have worked on. Ask them how they dealt with specific complexities that relate to your project specification.
Describe the business requirements of your project and ask them how they would approach it. You should expect specific recommendations from them.
3. Provide relevant details about your Hadoop development project
The Hadoop developer you hire needs sufficient information to succeed in your project. Provide relevant documentation like business requirements, technical solutions, test plans, etc. Explain the roles and responsibilities of the developer to them.
Introduce the developer to your larger team. Provide the required access to the technical environment of your project. Show your code repository and ensure that developers get access to it.
Describe your project plan and iterations. Explain your milestone review process and payment terms and conditions. Establish a communication process.
Interview tips to hire big data Hadoop developers
The following interview tips can help you when you hire a big data Hadoop developer:
A. Look for qualified Hadoop developers that can utilize its flexibility
An important advantage of Hadoop is its flexibility. It can process large data sets irrespective of data structures. Hadoop can process structured data, and it can process semi-structured data. You can also use it for unstructured data.
Skilled developers should know how to utilize this flexibility. Look for software developers that have used Hadoop for both unstructured and structured data. Companies like DevTeam.Space provides extensive Hadoop development services including these kinds of software engineers.
B. Hire enough senior software engineers
Big data development projects involving Hadoop can be complex. You need a development team with enough technical skills and experience. Look for developers with extensive knowledge of the Hadoop ecosystem. Apart from skills in programming languages like Java, look for skills in HDFS, Spark, Pig, Hive, MapReduce, HBase, and other relevant tools.
Hire expert developers for your next project
C. Look for top Hadoop developers with experience in cloud computing
The larger shift to cloud computing is unmistakable. Most skilled developers in the Hadoop space might have good knowledge of the framework and the relevant tools. Additionally, the best Hadoop developers have considerable experience in cloud-based projects. Look for experience in using Hadoop on the cloud.
D. Hire developers with experience in using Hadoop for numerous small files
Hadoop works very well for large files. It has a few limitations when accessing small files many times. Top software developers with Hadoop skills should know how to work around such limitations. Look for this experience.
E. Look for experience in working around the processing overheads of Hadoop
Most qualified Hadoop developers know how to maximize the strengths of Hadoop. They also know how to work around its processing overhead. Look for suitably experienced developers. DevTeam.Space can provide you with such top Hadoop developers.
Examples of questions to ask when hiring Hadoop developers
Ask questions that help you assess their practical knowledge. A few samples are as follows:
A. What does a Hadoop “DataNode” do?
Answer: A “DataNode” is a type of Hadoop node, i.e., a computer on the Hadoop distributed network. Such nodes store data residing on a Hadoop cluster. Hadoop replicates data on many DataNodes, which makes Hadoop reliable.
B. What is “rack awareness” in HDFS?
Answer: A “rack” in HDFS refers to all data nodes that form a storage area. It’s the physical location of the data stores. A NameNode in Hadoop has the rack information. This information is the rack ID of each data node. “Rack awareness” is the process to select data nodes that are nearer. This selection utilizes the rack information.
C. What does a combiner do in the Hadoop MapReduce framework?
Answer: A combiner is an optional class in the MapReduce framework. This class accepts the inputs from the “Map” class. It then passes the output key-value pairs to the “Reducer” class. This class summarizes the “map” output records with the same key. The “reduce” task receives that as input. The combiner class reduces the volume of data transferred between “Map” and “Reduce”.
Refer to our Hadoop interview questions for more examples.
Submit a Project With Zero Risk
We recommend that you fill out this DevTeam.Space product specification form so we can help you find the best developer for your project. Once you have, a dedicated account manager from DevTeam.Space will contact you. They will answer any questions that you have and explain the value that our expert Hadoop developers can offer you.
