Why you should use this Spark online test?

Spark online test screens candidates for the following common skills hiring managers look for: Fundamentals of Spark Core and Spark architecture Developing Spark scripts/ jobs using Python API, Java API or Scala API Working with RDDs in Spark, different types of actions and transformations to process and analyze large datasets Working with data sources, sinks and aggregating data with Pair RDDs Creating and Working with Spark Context, DataFrames, and DataSets Working with structured data using Spark SQL (Spark SQL Clauses: Distribute by, order by, clustered by, sort by; Window functions: rank, row_number, dense_rank) Processing continuous streams of data in real-time using Spark Streaming Loading data from HDFS for use in Spark applications & writing the results back into HDFS using Spark Performing standard extract, transform, load (ETL) processes on data using the Spark API Reading and writing files in a variety of file formats Analyzing networks and graphs with GraphX Along with these the test also has code-tracing MCQ questions and coding questions to evaluate hands-on Scala/ Java/ Python programming skills.

Spark Online Test

About the test:

The Apache Spark Online Test evaluates the candidate's ability to transform structured data with RDD API and SparkSQL (Datasets and DataFrames), convert big-data challenges into iterative/ multi-stage Spark scripts, optimize existing Spark jobs using partitioning/ caching and analyze graph structures using GraphX.

Covered skills:

Fundamentals of Spark Core
Spark Resilient Distributed Datasets (RDD)
Dataframes and Datasets
Running Spark on a cluster
Tuning and troubleshooting Spark jobs in a cluster
Migrating data from data sources/ databases

Developing and running Spark jobs (Java; Scala; Python)
Data processing with Spark SQL
Spark Streaming to process real-time data
Implementing iterative and multi-stage algorithms
Graph/ Network analysis with GraphX library

See all covered skills

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9 reasons why

Adaface Spark Online Test is the most accurate way to shortlist Spark Developers

Reason #1

Tests for on-the-job skills

Spark online test screens candidates for the following common skills hiring managers look for:

Fundamentals of Spark Core and Spark architecture
Developing Spark scripts/ jobs using Python API, Java API or Scala API
Working with RDDs in Spark, different types of actions and transformations to process and analyze large datasets
Working with data sources, sinks and aggregating data with Pair RDDs
Creating and Working with Spark Context, DataFrames, and DataSets
Working with structured data using Spark SQL (Spark SQL Clauses: Distribute by, order by, clustered by, sort by; Window functions: rank, row_number, dense_rank)
Processing continuous streams of data in real-time using Spark Streaming
Loading data from HDFS for use in Spark applications & writing the results back into HDFS using Spark
Performing standard extract, transform, load (ETL) processes on data using the Spark API
Reading and writing files in a variety of file formats
Analyzing networks and graphs with GraphX

Along with these the test also has code-tracing MCQ questions and coding questions to evaluate hands-on Scala/ Java/ Python programming skills.

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 Spark Test will be non-googleable.

🧐 Question
Medium Character count	Solve
Penny created a jar file for her character count example written in Java. The jar name is attempt.jar and the main class is com.penny.CharCount.java, which requires an input file name and output directory as input parameters. Which of the following is the correct command to submit a job in Spark with the given constraints?
Medium File system director Spark Scala API Spark Streaming	Solve
Review the following Spark job description: 1. Monitor file system director for new files. 2. For new files created in the “/rambo” dictionary, perform word count. Which of the following snippets would achieve this?
Medium Grade-Division-Points Spark Scala API DataFrame	Solve
Consider the following Spark DataFrame: Which of the given code fragments produce the following result:

	🧐 Question	🔧 Skill
	Medium Character count	2 mins Spark	Solve
Penny created a jar file for her character count example written in Java. The jar name is attempt.jar and the main class is com.penny.CharCount.java, which requires an input file name and output directory as input parameters. Which of the following is the correct command to submit a job in Spark with the given constraints?
	Medium File system director Spark Scala API Spark Streaming	3 mins Spark	Solve
Review the following Spark job description: 1. Monitor file system director for new files. 2. For new files created in the “/rambo” dictionary, perform word count. Which of the following snippets would achieve this?
	Medium Grade-Division-Points Spark Scala API DataFrame	4 mins Spark	Solve
Consider the following Spark DataFrame: Which of the given code fragments produce the following result:

	🧐 Question	🔧 Skill	💪 Difficulty	⌛ Time
	Character count	Spark	Medium	2 mins	Solve
Penny created a jar file for her character count example written in Java. The jar name is attempt.jar and the main class is com.penny.CharCount.java, which requires an input file name and output directory as input parameters. Which of the following is the correct command to submit a job in Spark with the given constraints?
	File system director Spark Scala API Spark Streaming	Spark	Medium	3 mins	Solve
Review the following Spark job description: 1. Monitor file system director for new files. 2. For new files created in the “/rambo” dictionary, perform word count. Which of the following snippets would achieve this?
	Grade-Division-Points Spark Scala API DataFrame	Spark	Medium	4 mins	Solve
Consider the following Spark DataFrame: Which of the given code fragments produce the following result:

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 Spark 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 Spark 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 & comparative results

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 Apache Spark Developers?

The questions for Senior Spark Developers will be of a higher difficulty level and are based on advanced topics like:

Deploying Spark in a cluster and sharing information between nodes using broadcast variables and accumulators
Deep understanding of Spark internal architecture - batch and streaming data, DAG scheduler, query optimizer, and execution engine
Improving Spark's performance with persistence and partitioning
Using Spark's MLlib to create Machine Learning Models
Simulating fault tolerance situations and recovery
Using Spark with Random Forests for Classification
Using Spark's Gradient Boosted Trees
Implementing iterative algorithms such as breadth-first-search
Integration of Spark with Hive Warehouse (Hive Optimization Concepts like Partition, Bucketing, Joins)
Limitations of MapReduce and the role of Spark in overcoming these limitations
Deploying Spark on Hadoop, Apache Mesos, Kubernetes, standalone

Additionally, the MCQs and coding questions to evaluate Scala/ Java/ Python skills will be of higher difficulty levels.

What roles can I use the Spark Test for?

Spark Developer
Software Developer - Spark
Big Data Engineer
Senior Spark Developer
Scala Big Data Developer
Senior Big Data Engineer
Spark Engineer

What topics are covered in the Spark Online Test?

Spark Core

Spark SQL

Spark Streaming

Spark MLlib

GraphX

Resilient Distributed Datasets (RDD)

Datasets

Dataframes

Yarn

Hadoop clusters

Lazy evaluation

Caching

Partitioning

Structured streaming

Dstreams

Spark Scala API

Spark Java API

Spark Python API

Job Scheduling

Security

Migration

Configuration and monitoring

Clusters

Nodes

Broadcast variables and accumulators

Data sources and sinks

Integrating with Hive and Hadoop

Data persistence and cache

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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

How is the test customized based on programming languages?

Spark supports different programming languages like Java, Scala, Python and R. We customize Spark tests according to programming language in the following ways:

The code snippets in scenario-based Spark MCQ questions will be of the programming language you pick
MCQ questions designed to evaluate the particular programming language will be added to the assessment
Coding questions to be programmed in the chosen programming language will be added to the assessment

You can check our standard Java, Scala, and Python tests to get a sense of question quality.

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.