performance

Deep dive into building a Data Lakehouse with Delta Lake and Spark

Deep dive into building a Data Lakehouse with Delta Lake and Spark

Leave a Comment / Databricks Meetup, Advanced, Databricks, Delta Lake, Spark /
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Sofia Oropeza
Marketing and Sales Director @Data-Driven. I am a passionate professional who strives to deliver excellent customer service, solve problems using modern technology and deliver practical solutions under resource and time constraints.
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Deep dive into building a Data Lakehouse with Delta Lake and Spark Watch the recorded webinar that deep dives into building a data lakehouse with Delta Lake and Spark. https://youtu.be/mrHfdeH6az0 A big thank you to Jonathan Neo for a great presentation at the October Sydney Databricks meetup. Here’s what was covered: What makes up the Lakehouse architecture …

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Databricks August Meetup - Databricks Performance Tuning with Gin Jia

Things You Wish You Had Known Earlier About Databricks Performance

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Rodney Joyce
Azure-certified Data Architect with a focus on delivering business value and guiding customers through the maze of analytical architectures, design and implementation activities.

Experienced in setting up modern data platforms with advanced predictive analytic workloads. Brings strong people skills and a devops-centric, entrepreneurial approach to Enterprise software delivery.


Rodney Joyce
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A big thank you to Jixin Jia (Gin), Databricks Solution Architect for a brilliant presentation, one that I personally found very interesting and learn a few things I didn’t know. Watch the online video recording to learn more about how to improve Databricks performance! To pick your interest, here are some of topics covered: 1. …

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Delta Lake Performance

Databricks Performance: Fixing the Small File Problem with Delta Lake

Leave a Comment / Data Lake, Advanced, Delta Lake, Spark /
Avatar of Anjana Rupasinghege
Anjana Rupasinghege
Anjana Rupasinghege is the Technical Director and Lead
Architect at Data Driven, specialised in Cloud, Security, Data
and Analytics.

With a background in Azure modern data architecture, he
has over 15 years of experience working in Information
Technology in industries such as Government, Banking,
Telecommunication and Consulting.

Anjana Rupasinghege
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A common Databricks performance problem we see in enterprise data lakes are that of the “Small Files” issue.  One of our customers is a great example – we ingest 0.5TB of JSON and CSV data per day made of 5kb files which equates to millions of files a week in the data lake Raw zone. …

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