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Training Apache Spark - Master Distributed Big Data

Ref: NGN128
10 people max.
5250 € HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$170/day onsite · +$500 with certification exam
5 journées
distanciel

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Learning objectives

  • Configure a scalable Spark cluster
  • Manipulate advanced DataFrames and Datasets
  • Optimize Spark job performance
  • Implement real-time Spark Streaming
  • Develop ML pipelines with MLlib
  • Deploy and monitor Spark applications
  • Integrate Spark with Kafka and Hadoop

The Learni story

Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.

Don't let this gap widen

Why this program matters

  • Without mastering intermediate Spark, your Big Data jobs take x10 longer, multiplying cloud costs by 5 (up to 100k€/year wasted).

  • 70% of projects fail due to poor optimization, losing critical market opportunities.

  • Untrained data engineers struggle against competition, with stagnant salaries of 10-20%.

  • Avoid streaming downtimes costing 50k€/hour in e-commerce, and imprecise ML models leading to wrong decisions (million € losses).

  • Invest 35h to multiply your productivity from tomorrow.

Fouzi Benzidane
Fouzi Benzidane

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1Spark Installation: Cluster and Environment (PySpark, Scala)

Install and configure a local and cloud Spark cluster, test with real datasets on Databricks, run your first advanced RDD jobs, analyze logs for debugging, produce an initial performance report that boosts your immediate confidence.

Module 2Spark SQL and DataFrames: Optimized Queries (Catalyst Optimizer)

Transform massive data into DataFrames, write complex SQL queries with joins and aggregations, optimize via caching and partitioning, apply to real e-commerce cases, generate temporary views and export to Parquet for x5 speed gains.

Module 3Performance Optimization: Tuning and Monitoring (Spark UI)

Profile your jobs with Spark UI, apply broadcast joins and predicate pushdown, tune executor memory and shuffle, test on terabyte datasets, reduce execution times by 70%, deliver a custom dashboard for production monitoring.

Module 4Spark Streaming: Real-Time Processing (Structured Streaming, Kafka)

Integrate Kafka to ingest live streams, code micro-batches with watermarks, handle late data and fault-tolerance, simulate a real-time IoT dashboard, produce automated alerts, master checkpoints for 99.9% resilience.

Module 5MLlib and Spark Projects: End-to-End Pipelines (GraphX, Deployment)

Build distributed ML models with MLlib, integrate GraphX for graph analytics, deploy via Spark Submit on Kubernetes, complete a capstone project on real data, evaluate metrics and deploy an automated enterprise-ready pipeline.

Evaluation method

  • Daily interactive quizzes
  • Certified final project
  • Pair-programming feedback
  • Qualiopi Certificate

Learning method

  • 70% hands-on on real clusters
  • 30% applied theory
  • Free Databricks exercises
  • Real business cases

Methods, materials and delivery

The Training Apache Spark - Master Distributed Big Data program is delivered onsite or remote (blended-learning, e-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.

The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.

Equipment required

For the smooth delivery of the Training Apache Spark - Master Distributed Big Data program, the following equipment is required:

  • Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
  • Training environments installed on workstations or accessible online
  • Course materials, hands-on exercises and complementary resources
  • Post-training access to materials and educational resources

For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.

* contact us for remote delivery feasibility** ratio varies depending on the program

Skills assessment methods

Assessment of skills acquired during the Training Apache Spark - Master Distributed Big Data program is performed through:

  • During training: case studies, hands-on labs and professional scenarios
  • End of training: self-assessment questionnaire and skills evaluation by the trainer
  • After training: completion certificate detailing acquired skills

Program accessibility

Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.

Enrollment terms and lead times

Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.

Verified reviews

What our learners

4.9 · +100 verified reviews
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« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
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« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
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« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
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« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
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« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
Read all reviews
Our method

Training quality, guaranteed at every step

Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.

Step 1

Rigorous trainer selection

Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.

  • Triple validation: technical, pedagogical, sectoral.
  • Minimum rating 4.8/5 over the last 12 sessions.
Step 2

You meet the trainer beforehand

30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.

  • Live briefing on goals and team context.
  • Veto right — we swap the trainer for free if needed.
Step 3

Content tailored to your context

No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.

  • Hands-on cases drawn from your stack and projects.
  • Program co-written then validated by your team.
Step 4

Continuous quality follow-up

Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.

  • NPS, knowledge quizzes and skills self-assessment.
  • Satisfaction guarantee: fully satisfied or free rework.

A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.

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