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Program overview
Online
On-site
Hybrid
Apache Spark with Scala
Build a strong foundation in big data processing using Apache Spark and Scala by understanding Spark architecture and core APIs. Learn how to process large datasets, apply advanced analytics and streaming, optimize performance, and integrate Spark with diverse data sources for scalable data driven solutions.
Duration:
5 Days
Level:
Advanced
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1500+ users onboarded
Who will Benefit from this Training?
Training Objectives
Build a high-performing, job-ready tech team.
Personalise your team’s upskilling roadmap and design a befitting, hands-on training program with Uptut
Key training modules
Comprehensive, hands-on modules designed to take you from basics to advanced concepts
Download Curriculum
- Spark and Scala Foundations
- Position Spark for large-scale data processing
- Use essential Scala syntax for Spark jobs
- Set up and navigate a Spark development workflow
- Contrast Spark with single-node data tools
- Spark Architecture and RDDs
- Explain driver, executors, and cluster roles
- Work with RDDs as the core distributed abstraction
- Understand lineage, partitions, and fault tolerance
- Choose when RDDs vs higher-level APIs fit
- Transformations and Actions
- Apply common transformations for ETL-style processing
- Trigger actions and understand lazy evaluation
- Persist intermediate results intentionally
- Hands-on: Build a multi-step RDD/DataFrame job
- Spark SQL, DataFrames, and Datasets
- Query structured data with Spark SQL
- Use DataFrames/Datasets for typed analytics
- Read and write common file formats
- Optimize tabular workflows with Catalyst basics
- Spark Streaming and Real-Time Analytics
- Ingest streaming sources for near-real-time pipelines
- Apply windowed aggregations and stateful patterns
- Design for late data and exactly-once concerns
- Build a simple streaming analytics flow
- MLlib and ML Pipelines
- Use MLlib for scalable machine learning
- Assemble featurization and model stages as pipelines
- Evaluate models in distributed settings
- Export pipeline stages for reuse
- GraphX and Advanced Analytics
- Model graph structures for relationship analytics
- Run graph algorithms for influence and connectivity
- Combine graph and tabular analysis patterns
- Identify practical GraphX use cases and limits
- Data Integration and the Big Data Ecosystem
- Integrate Spark with common storage and messaging systems
- Position Spark alongside Hadoop/cloud lake tooling
- Design batch and streaming ingestion boundaries
- Standardize schemas across pipeline stages
- Performance Optimization
- Diagnose shuffles, skew, and partition problems
- Tune memory, caching, and join strategies
- Use Spark UI to find bottlenecks
- Apply a performance checklist before production
- Deployment, Monitoring, Testing, and Debugging
- Deploy Spark jobs to cluster environments
- Monitor job health and resource usage
- Test and debug distributed applications systematically
- Establish operational runbooks for failures
- Distributed Machine Learning
- Scale ML workflows across a Spark cluster
- Compare distributed training patterns and trade-offs
- Productionize feature and model pipelines
- Review end-to-end Spark ML architecture choices
Hands-on Experience with Tools
Training Delivery Format
Flexible, comprehensive training designed to fit your schedule and learning preferences
Opt-in Certifications
AWS, Scrum.org, DASA & more
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100% Live
on-site/online training
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Hands-on
Labs and capstone projects
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Lifetime Access
to training material and sessions
Skill-Gap Assessment
Analysing skill gap and assessing business requirements to craft a unique program
1
Personalisation
Customising curriculum and projects to prepare your team for challenges within your industry
2
Implementation
Supplementing training with consulting support to ensure implementation in real projects
3
Why this course
- High Performance: By leveraging Scala's concise syntax and functional programming features, your business can achieve superior performance and speed in processing and analysing large datasets.
- Scalability: Spark's ability to distribute data and computations across multiple nodes allows your business to scale seamlessly as data volumes grow.
- Advanced Analytics: Apache Spark with Scala provides a rich set of libraries and APIs for advanced analytics. These capabilities empower your business to gain valuable insights, make data-driven decisions, and uncover hidden patterns and trends in your data.
Training objectives
- Gain a comprehensive understanding of the Apache Spark framework, its architecture, and its components.
- Acquire proficiency in the Scala programming language, including its syntax, features, and functional programming concepts.
- Learn how to process and manipulate large datasets using Spark's core APIs and RDDs.
- Explore Spark's advanced analytics capabilities, including machine learning, graph processing, and stream processing.
- Understand techniques and best practices for optimising Spark performance.
- Discover how to integrate Spark with various data sources, including Hadoop Distributed File System (HDFS), Apache Hive, and other popular data storage systems.
- Explore Spark's capabilities for real-time data processing and stream processing.
- Gain familiarity with the broader Spark ecosystem and related technologies.
Who will benefit
- Data Engineers
- Data Scientists
- Data Analysts
- Software Engineers
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Frequently Asked Questions
2. Will my team get any practical experience with this training?
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With our focus on experiential learning, we have made the training as hands-on as possible with assignments, quizzes and capstone projects, and a lab where trainees will learn by doing tasks live.
3. What is your mode of delivery - online or on-site?
We conduct both online and on-site training sessions. You can choose any according to the convenience of your team.
4. Will trainees get certified?
Yes, all trainees will get certificates issued by Uptut under the guidance of industry experts.
5. What do we do if we need further support after the training?
We have an incredible team of mentors that are available for consultations in case your team needs further assistance. Our experienced team of mentors is ready to guide your team and resolve their queries to utilize the training in the best possible way. Just book a consultation to get support.