Top Spark Projects to Sharpen Your Skills and Build Your Spark Portfolio

Spark is an important tool in advanced analytics, primarily because it can be used to quickly handle different types of data, regardless of its size and structure. Spark can also be integrated into Hadoop’s Distributed File System to process data with ease. Pairing with Yet Another Resource Negotiator (YARN) can also make data processing easier. 

If you want to work on an Apache big data project using Spark, you will need to spend time practicing. This article outlines 15 beginning, intermediate, and advanced Spark projects that can help you develop and sharpen crucial skills. 

5 Skills That Spark Projects Can Help You Practice

If you want to pursue a career in analytics, you’ll need to develop proficient Spark skills. Listed below are some of the essential skills that you can practice through Spark projects. 

• NoSQL. NoSQL uses nontraditional data models, as opposed to relational database management systems (RDBMS). This creative tool utilizes flexible, visually appealing, and easy-to-understand data models, moving away from conventional platforms.  
• MapReduce. This is a model within the Hadoop framework responsible for filtering, sorting, and summarizing big datasets. It uses a process that separates big data into smaller datasets for easier and faster processing. 
• Data Visualization. In the world of big data, being able to visualize data and tell a story with it is one of the best ways to engage your audience. It is an essential skill for data professionals and is involved in creating high-quality graphs and charts.  
• Big Data. Big data refers to large datasets that are complex, high in volume, and arriving at great speeds, and rarely manageable by typical software. As this is one of Spark’s strengths, Spark projects are especially helpful in allowing you to gain big data skills.
• Machine Learning. Machine learning is essential in developing automated functions. As a form of artificial intelligence, it relies on data input and can perform predictive analysis with minimal human assistance. Data analytics depend on machine learning when handling big data.

Best Spark Project Ideas for Beginners 

Projects are helpful because they give you real-world experience and help build your portfolio.  Below are some common projects for beginners to practice to learn and strengthen their skills in Spark.  

Job and Server Management

• Spark Skills Practiced: Big data

This beginner project involves creating a job and server management system. The system deploys never-ending tasks or jobs including results, jars, contexts, and logs. Every job has an interface and a set of parameters that make the project more complex.

Spark technology can simplify the entire process with an open-source framework and Restful API. The project should allow other programmers to add job submissions from different languages and environments.

Data Pipeline Management

• Spark Skills Practiced: NoSQL

This project involves streamlining data pipeline management for industries with huge datasets. Normally, data pipeline management consists of different activities such as ingestion and extraction of data processes from the source. It also involves transforming the data into an understandable and readable format. The system will then load the data into a data warehouse.

Predicting Flight Delays

• Spark Skills Practiced: Big data

The goal of this project is to create a system that predicts flight delays using an airline dataset. Spark can be used to perform predictive and descriptive analysis on large datasets and handle big data from the airline industry with accuracy. 

Data Hub Creation

• Spark Skills Practiced: MapReduce

This project requires you to create a data hub to consolidate data with ease. The inflow of data has risen exponentially because of the prevalence of online applications. A data hub can help manage this information for easy access and modification. Spark can be used with MapReduce to integrate data from different sources.

Ecommerce Analytics

• Spark Skills Practiced: Machine learning

This project helps handle the complexities of ecommerce analytics. The ecommerce industry produces a lot of data from product reviews and real-time transactions. It can be difficult to manage streaming analytics and data due to the dynamic environment. Spark, along with machine learning algorithms, makes it easier to work with unstructured data.

Best Intermediate Spark Project Ideas 

If you already have Spark skills and experience, working on intermediate projects may be a good option for you. Some of the best intermediate Spark project ideas are listed below. These projects will build on your beginner-level skills and prepare you to take on advanced projects.

Data Consolidation

• Spark Skills Practiced: MapReduce

The goal of this consolidation project is to create a data lake or enterprise data hub. Data lakes are useful in various corporate setups to store data in different functional areas. They often show up as files on HDFS or Hive tables and offer horizontal scalability. You can request group access and use algorithm models like MapReduce to start this data-crunching project.

Alluxio

• Spark Skills Practiced: MapReduce

This project is meant to be an orchestration layer between storage systems like Amazon, HDFS, Ceph and S3, and Spark. The role of the system is to move data from the central warehouse for processing in the computation framework. It offers dedicated data sharing capabilities and is written in MapReduce, Apache Spark, and Flink. It is also known as a memory-centric storage system. 

Zeppelin

• Spark Skills Practiced: Python

This project utilizes Jupyter style notebooks for Apache Spark. It has an IPython interpreter that offers you a better way to collaborate and share ideas on designs. To build this project, you can use a web-based notebook that offers interactive data analytics. 

The software should be able to publish code execution results directly to your blog or website as an embedded frame. It should create data-driven documents and allow you to organize data and collaborate with others.

Streaming Analytics Fraud Detection 

• Spark Skills Practiced: Machine learning

This is a cool project that aims to develop an anomaly detection tool and intrusion tool that uses HBase as its general data store. This project is important because the security and finance industries use lots of streaming analytics applications. It allows you to analyze transactional data to find any anomaly before the process ends.

Real-Time Dashboard 

• Spark Skills Practiced: Big data

This project involves creating a time-series-based dashboard for analyzing business performance. The time-series data is used to inspect web traffic, IT operations, demographic data, user clicks, and pricing fluctuations. 

All the parameters mentioned above depend on time and their values are gathered and stored within short intervals. This makes the size of the database increase rapidly and requires specialized analysis to draw insightful conclusions to accelerate business growth.

Best Advanced Spark Project Ideas

If you have created beginner and intermediate-level projects with Spark, you’ll be prepared for more advanced projects. Listed below are some of the best advanced Spark projects to improve your skills and build your professional portfolio.

Cassandra Connector

• Spark Skills Practiced: NoSQL

This project involves creating a scalable data management system with NoSQL. You can use Spark to create this project. You’ll learn to write Spark RDDs, data frames for Cassandra tables, and execute Cassandra Query Language (CQL) queries. 

Mesos

• Spark Skills Practiced: Big data

This project will allow you to administer big data infrastructures. You have an option to duplicate the open-source project so you can understand the architecture fully. It comprises an agent, Mesos master, and other components along with a framework. This project will be able to handle workloads with isolation and dynamic load sharing. It will also help promote large-scale deployments. 

Complex Event Processing

• Spark Skills Practiced: Big data

This project allows you to explore apps with very low latency that involve picoseconds, sub-seconds, and nanoseconds. Some notable examples include high-end trading apps, real-time call record rating systems, and systems that process Internet of Things events. 

The project can be a real-time vehicle-monitoring app and Spark can be used alongside Flume to simulate sensor data. You can also use the Redis data structure to act as a sub/pub middleware.

Sentiment Analysis 

• Spark Skills Practiced: Big data

This specialized analysis project could be based on product reviews or movie reviews. It is meant to predict if the review will be negative or positive. This model takes into account the opinion expressed by the users from their words and ignores the ratings given to the product or movie.

This binary classification problem may be a bit challenging. You can also work on a multi-class sentiment analysis project which involves recommending movies based on ones you have liked or disliked.

Language Identification

• Spark Skills Practiced: Machine learning 

This project will help you master machine learning techniques used in language identification. The project can be modeled after simple methods such as guessing the language using known articles. While building your project, you need to consider the features of each language to make them easily identifiable.

Next Steps: Start Organizing Your Spark Portfolio

After developing the necessary technical skills, you should consider effective ways to showcase those skills. The best way to do this is by creating a portfolio that demonstrates your capabilities to employers. Below are some tips you can use to help you organize your portfolio.

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Check Job Listings

Before building your portfolio, you need to do some research. First, check job listings of roles you would like to pursue. A good place to search for job listings is LinkedIn. Try to organize your portfolio with related projects first so that employers can quickly and easily see that your skills are relevant to the job description.

Showcase Your Capabilities

A professional portfolio is often your first impression on employers. It allows you to show them that you’re fully prepared and qualified for the related position. For this reason, your portfolio should adequately showcase your capabilities. You can do this by including a variety of projects with short descriptions that outline the techniques, languages, and skills involved.

Make a Good Impression

The point of your portfolio is to make a good impression on your potential employer. Be clear and concise in your portfolio. You need to document your projects properly. Try to provide a description of each project, your process, and how you completed the project. 

Spark Projects FAQ