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Mohammad Islam

4 BLOG ARTICLES 0 RESEARCH PAPERS
Mohammad Islam is a Senior Staff Engineer at Uber. He co-leads the Data cost-efficiency effort and also leads Data security and compliance efforts. He is an Apache Oozie and Tez PMC member.

Engineering Blog Articles

One Stone, Three Birds: Finer-Grained Encryption @ Apache Parquet™

Overview 

Data access restrictions, retention, and encryption at rest are fundamental security controls. This blog explains how we have built and utilized open-sourced Apache Parquet™’s finer-grained encryption feature to support all 3 controls in a unified way. In

Cost Efficiency @ Scale in Big Data File Format

 

Background

Our Apache Hadoop® based data platform ingests hundreds of petabytes of analytical data with minimum latency and stores it in a data lake built on top of the Hadoop Distributed File System (HDFS). We use Apache Hudi

Efficiently Managing the Supply and Demand on Uber’s Big Data Platform

With Uber’s business growth and the fast adoption of big data and AI, Big Data scaled to become our most costly infrastructure platform. To reduce operational expenses, we developed a holistic framework with 3 pillars: platform efficiency, supply, and demand

Cost-Efficient Open Source Big Data Platform at Uber

As Uber’s business has expanded, the underlying pool of data that powers it has grown exponentially, and thus ever more expensive to process. When Big Data rose to become one of our largest operational expenses, we began an initiative to

Challenges and Opportunities to Dramatically Reduce the Cost of Uber’s Big Data

Introduction

Big data is at the core of Uber’s business. We continue to innovate and provide better experiences for our earners, riders, and eaters by leveraging big data, machine learning, and artificial intelligence technology. As a result, over the last