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Technologies / Data & Analytics

Apache Spark SQL - structured data processing

An intensive training course dedicated to the effective use of Apache Spark SQL in processing structured data in a distributed environment. The program covers both the theoretical basics of DataFrame processing and the practical aspects of implementing efficient transformations and analysis. Participants work with real data sets, learning how to optimize queries and effectively use the Catalyst engine. The workshop is conducted in the form of practical classes, where each concept is immediately verified through the implementation of specific use cases.

Issues

  • DataFrame and Dataset model

  • Query catalyst

  • Data operations

  • Window functions

  • Performance optimization

  • Memory management

  • Data partitioning

  • Integration of sources

  • Data formats

  • Persistence

  • Data transformations

  • Structural analysis

This training is part of the path:

Benefits

  • Gain an in-depth understanding of the mechanisms of Spark SQL and the DataFrame model
  • Master techniques for efficient transformation and analysis of structured data
  • Assimilate query optimization and memory management methods
  • Advanced analytical features available in Spark SQL
  • Acquire the ability to design efficient data processing pipelines
  • Understand best practices for integrating diverse data sources

Who is this training for?

Big Data developers working with structured data
Data analysts using Apache Spark
Data engineers designing ETL pipelines
Data Scientists in need of efficient processing
Developers migrating from traditional databases
Data integration specialists

Prerequisites

  • Basic knowledge of Apache Spark
  • Experience in working with SQL
  • Knowledge of basic programming
  • Understand data processing concepts

Training program

01

Spark SQL engine architecture

  • DataFrame and Dataset model
02

Query catalyst

  • Data types and schemas
  • Transformations and analysis
  • DataFrame operations
03

Window functions

  • Aggregations and groupings
  • Data manipulation
  • Optimization and efficiency
04

Catalyst Optimizer

  • Memory management
  • Data partitioning
  • Caching strategies
  • Integration and implementation
05

Data sources

  • Data format
06

Serialization

  • Data persistence

Delivery Methods

Online

  • Convenience of participating from anywhere
  • Interactive live sessions with trainer
  • Materials available for 30 days
  • No travel costs

On-site

  • Direct contact with trainer and group
  • Intensive hands-on workshops
  • Networking with other participants
  • Full focus on learning

Frequently asked questions

Who is the Apache Spark SQL - structured data processing training for?

This training is designed for professionals looking to develop skills in apache spark sql - structured data processing. Required level: intermediate.

How long is the Apache Spark SQL - structured data processing training?

The training lasts 1. Available in online or on-site format.

Will I receive a certificate?

Yes — every participant receives a completion certificate confirming acquired competencies. EITT holds ISO 9001 accreditation.

Can this training be conducted for a closed group?

Yes — we offer dedicated closed trainings for companies. We customize the program to your team's needs. Contact us for an individual quote.

Monika Fengler
Monika Fengler Opiekun szkolenia

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Funding Options

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Up to 80%

Development Services Database

Up to 80% funding for SMEs from EU funds

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Up to 100%

National Training Fund

Up to 100% funding for employers

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We train teams at Poland's largest companies

ING Bank - EITT client
mBank - EITT client
PKO Bank Polski - EITT client
PZU - EITT client
Allianz - EITT client
T-Mobile - EITT client
KGHM - EITT client
PGE - EITT client
IKEA - EITT client
InPost - EITT client
Leroy Merlin - EITT client
ZUS - EITT client

Interested in this training?

Contact us - we'll prepare an offer tailored to your organization's needs.

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