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Apache Spark Declarative Pipelines: The Evolution from Imperative to Declarative Data Engineering - Part 1
Everything You Need to Know About Apache Spark 4.1's Game-Changing Declarative Pipeline Feature
Jul 10
•
Daniel Aronovich
2
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Big Data Performance Weekly
Apache Spark Declarative Pipelines: The Evolution from Imperative to Declarative Data Engineering - Part 1
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June 2025
Databricks & Snowflake Summits 2025 aftermath - Part 1: Catalog Wars
The Data Catalog Wars Heat Up: What We Learned from Conference Season
Jun 19
•
Meni Shmueli
and
Daniel Aronovich
3
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Big Data Performance Weekly
Databricks & Snowflake Summits 2025 aftermath - Part 1: Catalog Wars
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May 2025
Apache Spark 4.0: What the Performance Improvements Actually Mean for Your Daily Work
Why Spark 4.0 means less time tuning and more time building
May 29
•
Daniel Aronovich
6
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Big Data Performance Weekly
Apache Spark 4.0: What the Performance Improvements Actually Mean for Your Daily Work
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Apache Spark on Kubernetes: From Manual Submissions to Operators - Part 1
A practitioner's guide to the Spark-on-Kubernetes toolbox and when to use each approach
May 22
•
Daniel Aronovich
and
Meni Shmueli
5
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Apache Spark on Kubernetes: From Manual Submissions to Operators - Part 1
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AI Assistants vs. Big Data: The Missing Infrastructure Context - Part 2
Why Performance Optimization Requires More Than AI-Generated Spark Code in Production Data Pipelines
May 15
•
Daniel Aronovich
1
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AI Assistants vs. Big Data: The Missing Infrastructure Context - Part 2
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Why Big Data Engineers Are Missing Out on the AI Code Revolution - Part 1
The Ultimate Paradox of 2025: Big Data Engineers Top the Charts Yet Fall Behind
May 8
•
Daniel Aronovich
1
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Big Data Performance Weekly
Why Big Data Engineers Are Missing Out on the AI Code Revolution - Part 1
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April 2025
Unpacking Trino's Query Execution: From SQL to Splits
Understanding How Your SQL Query Flows Through Trino's Distributed Architecture
Apr 24
•
Daniel Aronovich
2
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Big Data Performance Weekly
Unpacking Trino's Query Execution: From SQL to Splits
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Understanding Apache Spark's Execution Hierarchy: From Applications to Tasks
Learn how the Apache Spark execution model works from Applications to Jobs, Stages, and Tasks. To optimize performance and debug your big data…
Apr 17
•
Daniel Aronovich
6
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Big Data Performance Weekly
Understanding Apache Spark's Execution Hierarchy: From Applications to Tasks
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2
Mastering Apache Spark Partitioning: Coalesce vs. Repartition
Optimizing Performance Through Strategic Data Distribution
Apr 10
•
Daniel Aronovich
1
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Big Data Performance Weekly
Mastering Apache Spark Partitioning: Coalesce vs. Repartition
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Understanding Wide vs. Narrow Transformations in Apache Spark: Why It Matters for Performance
Optimize Your Spark Jobs by Understanding Data Dependencies and Shuffle Operations
Apr 3
•
Daniel Aronovich
3
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Big Data Performance Weekly
Understanding Wide vs. Narrow Transformations in Apache Spark: Why It Matters for Performance
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March 2025
Transformations vs. Actions in Apache Spark: The Key to Efficient Data Processing
Understanding the Core Mechanics Behind Spark's Lazy Evaluation Model
Mar 27
•
Daniel Aronovich
3
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Big Data Performance Weekly
Transformations vs. Actions in Apache Spark: The Key to Efficient Data Processing
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Spark Connect Part 2: Debugging and Performance Breakthroughs
Ever spent an entire day trying to debug a Spark job that failed hours into execution? What if you could identify issues in seconds instead?
Mar 20
•
Daniel Aronovich
4
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Big Data Performance Weekly
Spark Connect Part 2: Debugging and Performance Breakthroughs
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