Apache Spark for Data Engineers Masterclass
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Apache Spark for Data Engineers Masterclass
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placeVeenendaal 17 aug. 2026 tot 18 aug. 2026Toon rooster event 17 augustus 2026, 09:00-16:00, Veenendaal event 18 augustus 2026, 09:00-16:00, Veenendaal |
Beschrijving
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Get a deeper understanding of Apache Spark in order to optimize your data workflow.
In this course, you will explore techniques and best practices for optimizing Apache Spark applications. As you study the architectural elements of Spark, you will learn to work with the Spark UI. You will identify and address common performance issues caused by shuffles and skew. Advanced optimization strategies for join, union, and merge operations, data formats, caching mechanisms, garbage collector settings, data partitioning, bucketing, and Delta Lake optimizations are also covered. Additionally, you will explore regular maintenance tasks for Spark applications and learn how to customize Spark session co…
Veelgestelde vragen
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Meer weten over de onderwerpen die aan bod komen en de vereiste voorkennis? Neem vrijblijvend contact met ons op.
Get a deeper understanding of Apache Spark in order to optimize your data workflow.
In this course, you will explore techniques and best practices
for optimizing Apache Spark applications. As you study the
architectural elements of Spark, you will learn to work with the
Spark UI. You will identify and address common performance issues
caused by shuffles and skew. Advanced optimization strategies for
join, union, and merge operations, data formats, caching
mechanisms, garbage collector settings, data partitioning,
bucketing, and Delta Lake optimizations are also covered.
Additionally, you will explore regular maintenance tasks for Spark
applications and learn how to customize Spark session
configurations for optimal performance.
- Describe the architecture of a spark application. [Remember]
- Explain the structure and functionality of the Spark UI.
[Understand]
- Predict common performance issues casued by shuffling and data
skew. [Apply]
- Optimize join, union, and merge operations in Spark.
[Analyze]
- Change the data format for optimal performance. [Apply]
- Implement caching mechanisms and garbage collector settings for
enhanced performance. [Apply]
- Use data partitioning and bucketing in Spark workloads.
[Apply]
- Apply Delta Lake optim…
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Deel je ervaring
Heb je ervaring met deze cursus? Deel je ervaring en help anderen kiezen. Als dank voor de moeite doneert Springest € 1,- aan Stichting Edukans.Er zijn nog geen veelgestelde vragen over dit product. Als je een vraag hebt, neem dan contact op met onze klantenservice.