Spark Online Test

Q: What are the main Big Data tests?

Popular Big Data tests include: Apache Cassandra Online Test Apache NiFi Online Test Hadoop Online Test Kafka Online Test Pig Online 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
Developing and running Spark jobs (Java; Scala; Python)
Spark Resilient Distributed Datasets (RDD)
Data processing with Spark SQL
Dataframes and Datasets
Spark Streaming to process real-time data
Running Spark on a cluster
Implementing iterative and multi-stage algorithms
Tuning and troubleshooting Spark jobs in a cluster
Graph/ Network analysis with GraphX library
Migrating data from data sources/ databases

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About the Spark Test

The Spark Online Test helps recruiters and hiring managers identify qualified candidates from a pool of resumes, and helps in taking objective hiring decisions. It reduces the administrative overhead of interviewing too many candidates and saves time by filtering out unqualified candidates at the first step of the hiring process.

The test screens for the following skills that hiring managers look for in candidates:

Understanding the fundamentals and architecture of Spark Core
Developing and running Spark jobs using Java, Scala, and Python
Working with Resilient Distributed Datasets (RDD) in Spark
Performing data processing with Spark SQL
Manipulating data using Dataframes and Datasets in Spark
Implementing Spark Streaming to process real-time data
Deploying and running Spark on a cluster
Applying iterative and multi-stage algorithms in Spark
Tuning and troubleshooting Spark jobs in a cluster
Conducting graph and network analysis using the GraphX library
Managing data migration from various sources and databases

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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.

How we design questions

These are just a small sample from our library of 15,000+ questions. The actual questions on this Spark Test will be non-googleable.

🧐 Question
Easy Character count Apache Spark Command Line Interface (Cli) Java	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 Spark Programming Data Processing	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
	Easy Character count Apache Spark Command Line Interface (Cli) Java	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 Spark Programming Data Processing	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 Apache Spark Command Line Interface (Cli) Java	Spark	Easy	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 Programming Data Processing	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:

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Why you should use Pre-employment Spark Online Test?

The Spark Test makes use of scenario-based questions to test for on-the-job skills as opposed to theoretical knowledge, ensuring that candidates who do well on this screening test have the relavant skills. The questions are designed to covered following on-the-job aspects:

Fundamentals of Spark Core
Developing and running Spark jobs in Java, Scala, and Python
Understanding Spark Resilient Distributed Datasets (RDD)
Data processing with Spark SQL
Working with Dataframes and Datasets in Spark
Utilizing Spark Streaming for real-time data processing
Running Spark on a cluster
Implementing iterative and multi-stage algorithms in Spark
Tuning and troubleshooting Spark jobs in a cluster
Performing Graph/Network analysis with GraphX library in Spark

Once the test is sent to a candidate, the candidate receives a link in email to take the test. For each candidate, you will receive a detailed report with skills breakdown and benchmarks to shortlist the top candidates from your pool.

What topics are covered in the Spark Online Test?

Fundamentals of Spark Core: Understanding Spark Core involves knowledge of the basic building blocks and execution model of Apache Spark, such as RDDs, transformations, and actions. This skill is necessary to develop efficient and scalable Spark applications.

Developing and running Spark jobs (Java; Scala; Python): Developing and running Spark jobs requires proficiency in programming languages like Java, Scala, or Python. This skill is crucial to write Spark applications using Spark APIs, perform data processing tasks, and leverage the power of Spark's distributed computing capabilities.

Spark Resilient Distributed Datasets (RDD): Spark RDDs are fundamental data structures in Spark that allow for distributed data processing and fault tolerance. Understanding RDDs is essential for efficient data manipulation, transformation, and parallel computing in Spark.

Data processing with Spark SQL: Spark SQL is a module in Spark that provides a programming interface for querying structured and semi-structured data using SQL-like syntax. This skill is important to analyze and process structured data using SQL operations and leverage the optimizations provided by Spark SQL's query engine.

Dataframes and Datasets: Dataframes and Datasets are higher-level abstractions built on top of RDDs in Spark. They provide a more expressive and efficient way to work with structured and unstructured data. Understanding Dataframes and Datasets is crucial for performing data manipulations, transformations, and aggregations efficiently in Spark.

Spark Streaming to process real-time data: Spark Streaming is a scalable and fault-tolerant stream processing library in Spark that allows for real-time data processing. This skill is important to handle continuous streams of data and perform real-time analytics, enabling applications to react to data changes in near real-time.

Running Spark on a cluster: Running Spark on a cluster involves configuring and deploying Spark applications across a distributed cluster infrastructure. This skill is necessary to take advantage of Spark's distributed computing capabilities and ensure optimal performance and scalability.

Implementing iterative and multi-stage algorithms: Implementing iterative and multi-stage algorithms in Spark involves designing and optimizing algorithms that require multiple iterations or stages to achieve the desired output. This skill is important for tasks like machine learning and graph processing that often involve complex iterative and multi-stage computations.

Tuning and troubleshooting Spark jobs in a cluster: Tuning and troubleshooting Spark jobs in a cluster requires expertise in identifying and resolving performance issues, optimizing resource utilization, and ensuring fault tolerance. This skill is crucial to maximize the efficiency and reliability of Spark applications running on a distributed cluster.

Graph/ Network analysis with GraphX library: GraphX is a graph computation library in Spark that provides an API for graph processing and analysis. Understanding GraphX is important for tasks like social network analysis, recommendation systems, and fraud detection that involve analyzing relationships and patterns in graph data.

Migrating data from data sources/ databases: Migrating data from data sources or databases to Spark involves understanding various data ingestion techniques, such as batch processing, streaming, and data connectors. This skill is necessary to efficiently transfer and process data from external sources in Spark for further analysis and computation.

Full list of covered topics

The actual topics of the questions in the final test will depend on your job description and requirements. However, here's a list of topics you can expect the questions for Spark Test to be based on.

Spark RDD

Spark DataFrame

Spark Dataset

Spark SQL

Spark Streaming

Spark GraphX

Spark Cluster

Spark Graph and Network Analysis

Spark Iterative Algorithms

Spark Multi-stage Algorithms

Spark Job Tuning

Spark Job Troubleshooting

Spark Data Migration

Spark Core Fundamentals

Java Spark Development

Scala Spark Development

Python Spark Development

Data Processing in Spark

Real-time Data Processing in Spark

Spark Architecture

Handling Exceptions and Errors in Spark

Spark Data Manipulation

Spark Data Aggregation

Spark Data Filtering

Spark Data Transformation

Spark Data Visualization

Spark Data Joins

Spark Data Partitioning

Spark Data Caching

Spark Data Serialization

Spark Data Compression

Spark Data Sources

Spark Data Loading

Spark Data Saving

Spark Data Exploration

Spark Data Preprocessing

Spark Data Analytics

Spark Data Mining

Spark Data Quality

Spark Data Integration

Spark Data Streaming

Spark Data Pipelines

Spark Data Storage

Spark Data Security

Spark Data Access Control

Spark Data Backup

Spark Data Recovery

Spark Data Replication

Spark Data Compression

Spark Data Encryption

Spark Data Schema

Spark Data Serialization

Spark Data Indexing

Spark Data Visualization

Spark Data Benchmarking

Spark Machine Learning

Spark Deep Learning

Spark Neural Networks

Spark Graph Algorithms

Spark Social Network Analysis

Spark Community Detection

Spark Clustering

Spark Classification

Spark Regression

Spark Anomaly Detection

Spark Recommendation Systems

Spark Sentiment Analysis

Spark Natural Language Processing

Spark Geospatial Analysis

Spark Time Series Analysis

Spark Collaborative Filtering

Spark Dimensionality Reduction

Spark Model Evaluation

Spark Feature Engineering

Spark Feature Selection

Spark Hyperparameter Tuning

Spark Model Deployment

Spark Model Monitoring

Spark Model Interpretability

What roles can I use the Spark Online Test for?

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

How is the Spark Online Test customized for senior candidates?

For intermediate/ experienced candidates, we customize the assessment questions to include advanced topics and increase the difficulty level of the questions. This might include adding questions on topics like

Migrating data from various data sources/databases
Working with Spark MLlib for machine learning tasks
Optimizing Spark performance using caching and persistence
Using Spark for natural language processing (NLP) tasks
Implementing Spark for real-time analytics
Understanding and managing Spark Executors and Workers
Utilizing Spark for large-scale data processing
Implementing Spark for real-time data visualization
Integrating Spark with other Big Data technologies like Hadoop and Cassandra
Implementing Spark on cloud platforms for scalability and flexibility

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Have questions about the Spark Hiring Test?

What is Spark Test?

The Spark Test is designed to evaluate a candidate's knowledge and skills in Apache Spark. This test is used by recruiters to identify candidates who are proficient in various Spark-related tasks such as developing and running Spark jobs, processing data with Spark SQL, and more. It is helpful in hiring roles where Spark expertise is required.

Can I combine the Spark Test with the PySpark Test questions?

Yes, recruiters can request a single custom test with multiple skills, including PySpark. For more details on the PySpark Test, please refer to our test library.

What topics are evaluated in the Spark Test?

The Spark Test covers a wide range of skills including Fundamentals of Spark Core, Spark SQL, Dataframes and Datasets, Spark Streaming, running Spark on a cluster, iterative algorithms, GraphX library, job tuning, and migrating data from various sources.

How to use the Spark Test in my hiring process?

Use our assessment software at the early stages of your recruitment process. Add a link to the assessment in your job post or invite candidates via email. Adaface helps you identify the most skilled candidates quickly.

Can I test Spark and SQL together in a test?

Yes, you can combine both Spark and SQL skills in a single test. This is particularly useful for roles requiring expertise in data processing and analysis. For more details, refer to the SQL Online Test.

What are the main Big Data tests?

Popular Big Data tests include:

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. Here's a quick guide on how you can request a custom test.

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
Screen proctoring
Web proctoring
Webcam proctoring
Plagiarism detection
Secure browser
Copy paste protection

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.

I'm a candidate. Can I try a practice test?

No. Unfortunately, we do not support practice tests at the moment. However, you can use our sample questions for practice.

What is the cost of using this test?

You can check out our pricing plans.

Can I get a free trial?

Yes, you can sign up for free and preview this test.

I just moved to a paid plan. How can I request a custom assessment?

Here is a quick guide on how to request a custom assessment on Adaface.

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Along with scorecards that report the performance of the candidate in detail, you also receive a comparative analysis against the company average and industry standards.

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