Why you should use this Hadoop online test?

The Hadoop Online test helps recruiters and hiring managers identify qualified Hadoop developers and administrators from a pool of resumes. It reduces the administrative overhead of interviewing too many candidates and saves expensive engineering time by filtering out candidates without prior hands-on Hadoop experience. The Hadoop Online Test screens candidates for the typical skills recruiters look for in Big Data Hadoop developers: Understanding of Bid Data challenges and how Hadoop solves Big Data problems Installing and configuring a Hadoop cluster on cloud services like Amazon Web Services (AWS) Translating complex analysis problems into multi-stage MapReduce jobs Integrating HBase with MapReduce for data processing tasks Understanding of Hadoop architecture (Secondary/Checkpoint/Back up nodes, HA configuration and YARN) Understanding other Hadoop-based technologies (Hive, Pig, and Spark) Working with file formats like SequenceFile, AVRO etc Performing CRUD operations from HBase Analyzing relational data (Hive and MySQL) and non-relational data (HBase, Cassandra, and MongoDB) Understanding of how Hadoop clusters are managed (YARN Zookeeper, Zeppelin etc) Publishing data to Hadoop clusters (Kafka, Sqoop, and Flume)

Hadoop Online Test

About the test:

The Hadoop Online Test uses scenario-based MCQ questions to evaluate candidates' ability to install Hadoop clusters on the cloud, run optimized MapReduce jobs on Hadoop clusters and write efficient Pig instructions and Hive queries to perform data analysis on complex datasets. The test screens for core Hadoop framework knowledge that hiring managers look for in Hadoop developers and administrators.

Covered skills:

Installing and configuring Hadoop clusters
Writing efficient Hive and Pig queries
Handling streaming data
Troubleshooting and monitoring

Core Hadoop architecture (HDFS; YARN; MapReduce)
Publishing data to clusters
Working with different file formats

See all covered skills

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9 reasons why

Adaface Hadoop Online Test is the most accurate way to shortlist Hadoop Admins

Reason #1

Tests for on-the-job skills

The Hadoop Online test helps recruiters and hiring managers identify qualified Hadoop developers and administrators from a pool of resumes. It reduces the administrative overhead of interviewing too many candidates and saves expensive engineering time by filtering out candidates without prior hands-on Hadoop experience.

The Hadoop Online Test screens candidates for the typical skills recruiters look for in Big Data Hadoop developers:

Understanding of Bid Data challenges and how Hadoop solves Big Data problems
Installing and configuring a Hadoop cluster on cloud services like Amazon Web Services (AWS)
Translating complex analysis problems into multi-stage MapReduce jobs
Integrating HBase with MapReduce for data processing tasks
Understanding of Hadoop architecture (Secondary/Checkpoint/Back up nodes, HA configuration and YARN)
Understanding other Hadoop-based technologies (Hive, Pig, and Spark)
Working with file formats like SequenceFile, AVRO etc
Performing CRUD operations from HBase
Analyzing relational data (Hive and MySQL) and non-relational data (HBase, Cassandra, and MongoDB)
Understanding of how Hadoop clusters are managed (YARN Zookeeper, Zeppelin etc)
Publishing data to Hadoop clusters (Kafka, Sqoop, and Flume)

Reason #2

No trick questions

Traditional assessment tools use trick questions and puzzles for the screening, which creates a lot of frustration among candidates about having to go through irrelevant screening assessments.

The main reason we started Adaface is that traditional pre-employment assessment platforms are not a fair way for companies to evaluate candidates. At Adaface, our mission is to help companies find great candidates by assessing on-the-job skills required for a role.

Why we started Adaface ->

Reason #3

Non-googleable questions

We have a very high focus on the quality of questions that test for on-the-job skills. Every question is non-googleable and we have a very high bar for the level of subject matter experts we onboard to create these questions. We have crawlers to check if any of the questions are leaked online. If/ when a question gets leaked, we get an alert. We change the question for you & let you know.

These are just a small sample from our library of 10,000+ questions. The actual questions on this Hadoop Online Test will be non-googleable.

🧐 Question
Easy Count number of occurrences Mappers Reducers	Solve
Chusk works as Hadoop developer at Pesla Inc. Chusk is tasked with processing input data to count number of occurrences of each unique word. Chusk did the following to achieve this: 1. Tokenize each word and emit lateral value 1 with Mapper 2. Reducer increments counter for each literal 1 it receives Chusk is now tasked with optimizing this by using a combiner. Will Chusk be able to reuse existing reducers as combiners? A: Yes B: No C: Because the sum operation is both associative and commutative and the input and output types to the reduce method match D: Because the sum operation in the Reducer is incompatible with the operation of a combiner E: Because the combiner is incompatible with a Mapper, which doesn't use the same data type for both the key and value F: Insufficient information
Medium Hive ngrams	Solve
Assuming the following Hive statements execute successfully, choose the correct statements that describe the result: from fooddata select context_ngrams(sentences(lines), array("twiggy", "romato", null), 68); A. A bigram of the top 68 sentences that contain the substring "twiggy romato" in the lines column of the input data A1 table. B. An 68-value ngram of sentences that contain the words "twiggy" or "romato" in the lines column of the fooddata table. C. A trigram of the top 68 sentences that contain "twiggy romato" followed by a null space in the lines column of the fooddata table. D. A frequency distribution of the top 68 words that follow the subsequence "twiggy romato" in the lines column of the fooddata table.
Easy P Q relations Pig	Solve
Consider the following two relations, P and Q: What is the output of the following Pig command? Q = GROUP P BY p2; DUMP Q;

	🧐 Question	🔧 Skill
	Easy Count number of occurrences Mappers Reducers	3 mins Hadoop	Solve
Chusk works as Hadoop developer at Pesla Inc. Chusk is tasked with processing input data to count number of occurrences of each unique word. Chusk did the following to achieve this: 1. Tokenize each word and emit lateral value 1 with Mapper 2. Reducer increments counter for each literal 1 it receives Chusk is now tasked with optimizing this by using a combiner. Will Chusk be able to reuse existing reducers as combiners? A: Yes B: No C: Because the sum operation is both associative and commutative and the input and output types to the reduce method match D: Because the sum operation in the Reducer is incompatible with the operation of a combiner E: Because the combiner is incompatible with a Mapper, which doesn't use the same data type for both the key and value F: Insufficient information
	Medium Hive ngrams	2 mins Hadoop	Solve
Assuming the following Hive statements execute successfully, choose the correct statements that describe the result: from fooddata select context_ngrams(sentences(lines), array("twiggy", "romato", null), 68); A. A bigram of the top 68 sentences that contain the substring "twiggy romato" in the lines column of the input data A1 table. B. An 68-value ngram of sentences that contain the words "twiggy" or "romato" in the lines column of the fooddata table. C. A trigram of the top 68 sentences that contain "twiggy romato" followed by a null space in the lines column of the fooddata table. D. A frequency distribution of the top 68 words that follow the subsequence "twiggy romato" in the lines column of the fooddata table.
	Easy P Q relations Pig	2 mins Hadoop	Solve
Consider the following two relations, P and Q: What is the output of the following Pig command? Q = GROUP P BY p2; DUMP Q;

	🧐 Question	🔧 Skill	💪 Difficulty	⌛ Time
	Count number of occurrences Mappers Reducers	Hadoop	Easy	3 mins	Solve
Chusk works as Hadoop developer at Pesla Inc. Chusk is tasked with processing input data to count number of occurrences of each unique word. Chusk did the following to achieve this: 1. Tokenize each word and emit lateral value 1 with Mapper 2. Reducer increments counter for each literal 1 it receives Chusk is now tasked with optimizing this by using a combiner. Will Chusk be able to reuse existing reducers as combiners? A: Yes B: No C: Because the sum operation is both associative and commutative and the input and output types to the reduce method match D: Because the sum operation in the Reducer is incompatible with the operation of a combiner E: Because the combiner is incompatible with a Mapper, which doesn't use the same data type for both the key and value F: Insufficient information
	Hive ngrams	Hadoop	Medium	2 mins	Solve
Assuming the following Hive statements execute successfully, choose the correct statements that describe the result: from fooddata select context_ngrams(sentences(lines), array("twiggy", "romato", null), 68); A. A bigram of the top 68 sentences that contain the substring "twiggy romato" in the lines column of the input data A1 table. B. An 68-value ngram of sentences that contain the words "twiggy" or "romato" in the lines column of the fooddata table. C. A trigram of the top 68 sentences that contain "twiggy romato" followed by a null space in the lines column of the fooddata table. D. A frequency distribution of the top 68 words that follow the subsequence "twiggy romato" in the lines column of the fooddata table.
	P Q relations Pig	Hadoop	Easy	2 mins	Solve
Consider the following two relations, P and Q: What is the output of the following Pig command? Q = GROUP P BY p2; DUMP Q;

Reason #4

1200+ customers in 75 countries

With Adaface, we were able to optimise our initial screening process by upwards of 75%, freeing up precious time for both hiring managers and our talent acquisition team alike!

Brandon Lee, Head of People, Love, Bonito

Reason #5

Designed for elimination, not selection

The most important thing while implementing the pre-employment Hadoop Online Test in your hiring process is that it is an elimination tool, not a selection tool. In other words: you want to use the test to eliminate the candidates who do poorly on the test, not to select the candidates who come out at the top. While they are super valuable, pre-employment tests do not paint the entire picture of a candidate’s abilities, knowledge, and motivations. Multiple easy questions are more predictive of a candidate's ability than fewer hard questions. Harder questions are often "trick" based questions, which do not provide any meaningful signal about the candidate's skillset.

Reason #6

1 click candidate invites

Email invites: You can send candidates an email invite to the Hadoop Online Test from your dashboard by entering their email address.

Public link: You can create a public link for each test that you can share with candidates.

API or integrations: You can invite candidates directly from your ATS by using our pre-built integrations with popular ATS systems or building a custom integration with your in-house ATS.

Reason #7

Detailed scorecards & benchmarks

Reason #8

High completion rate

Adaface tests are conversational, low-stress, and take just 25-40 mins to complete.

This is why Adaface has the highest test-completion rate (86%), which is more than 2x better than traditional assessments.

Reason #9

Advanced Proctoring

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How is the test customized for Senior Hadoop Developers/ Administrators?

For intermediate/ senior Hadoop administrators, we customize the questions to include advanced topics and increase the difficulty level of the questions. The senior Hadoop developer test includes adding questions on topics like

Chaining MapReduce jobs together to analyze complex datasets
Understanding of difference phases of MapReduce in detail
Tuning and optimizing slowing running MapReduce jobs, Pig instructions and Hive queries
Understanding how Joins work behind the scenes and writing optimized join statement
Consuming streaming data using Spark Streaming, Flink, and Storm
Commissioning, Decommissioning and Recommissioning machines
Taking cluster backups and enabling capacity schedulers
Understanding of Hadoop security and authentication
Complex topics like file formats, custom writables and input/output formats

What roles can I use the Hadoop Online Test for?

Hadoop Admin
Hadoop Engineer
Hadoop Tester
Hadoop Application Developer
Big Data Developer - Hadoop
Senior Big Data Engineer - Hadoop
Senior Hadoop Administrator

What topics are covered in the Hadoop Online Test?

Hadoop Architecture And Mapreduce

Single-Node and Multi-Node Clusters

Installing Hadoop Clusters

Monitoring Hadoop Clusters

HDFS/ Hadoop Balancer

YARN Framework

Managing Resources and Scheduling

HDFS Federation and High Availability

Running and managing MapReduce jobs

Pig instructions

Hive queries

Spark

Capacity Scheduler

Handling streaming data using Streaming API

Analyzing relational and non-relational data

Publishing data to clusters

Backup, recovery and maintenance

Hadoop Security and Authentication

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The hiring managers felt that through the technical questions that they asked during the panel interviews, they were able to tell which candidates had better scores, and differentiated with those who did not score as well. They are highly satisfied with the quality of candidates shortlisted with the Adaface screening.

85%

reduction in screening time

View Full Case Study

FAQs

Can I evaluate Hadoop and Spark in the same test?

Yes. You can evaluate multiple skills in the same test. If your Hadoop job description requires candidates to have experience with Hadoop and Apache Spark, we include questions on both the skills. You can check our standard Spark Online Test to understand what kind of questions will be used to evaluate Spark knowledge.

Can I evaluate other Big Data technologies like Hive, Pig, SQL in the same test?

Yes. Big Data roles at different companies require candidates to have experience in different technologies. We support customizing the assessments to work for your job description. This includes including questions to evaluate multiple skills in the same test. Popular Hadoop roles require candidates to have experience with related technologies like Hive, Pig, SQL, Spark. If you require, we include questions on these topics in the same test so that you can identify the right candidates for your company. You can check our standard SQL Online Test and Spark Online Test to see how those skills are evaluated.

Can I combine multiple skills into one custom assessment?

Yes, absolutely. Custom assessments are set up based on your job description, and will include questions on all must-have skills you specify.

Do you have any anti-cheating or proctoring features in place?

We have the following anti-cheating features in place:

Non-googleable questions
IP proctoring
Web proctoring
Webcam proctoring
Plagiarism detection
Secure browser

Read more about the proctoring features.

How do I interpret test scores?

The primary thing to keep in mind is that an assessment is an elimination tool, not a selection tool. A skills assessment is optimized to help you eliminate candidates who are not technically qualified for the role, it is not optimized to help you find the best candidate for the role. So the ideal way to use an assessment is to decide a threshold score (typically 55%, we help you benchmark) and invite all candidates who score above the threshold for the next rounds of interview.

What experience level can I use this test for?

Each Adaface assessment is customized to your job description/ ideal candidate persona (our subject matter experts will pick the right questions for your assessment from our library of 10000+ questions). This assessment can be customized for any experience level.

Does every candidate get the same questions?

Yes, it makes it much easier for you to compare candidates. Options for MCQ questions and the order of questions are randomized. We have anti-cheating/ proctoring features in place. In our enterprise plan, we also have the option to create multiple versions of the same assessment with questions of similar difficulty levels.