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Alibaba EMR

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EMR is an all-in-one enterprise-ready big data platform that provides cluster, job, and data management services based on open-source ecosystems, such as Hadoop, Spark, Kafka, Flink, and Storm.

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Alibaba Big Data Practices on Cloud-Native – EMR Spark on ACK

This article discusses the practices and challenges of EMR Spark on Alibaba Cloud Kubernetes.

Application of Delta Lake in Soul

This article explains the background of Delta Lake along with practices, problems, and solutions.

Alibaba Cloud JindoFS Handles Stress Testing Easily with More Than One Billion Files

This article reviews JindoFS stress testing, featuring multiple scenarios and graphs.

Construction, Analysis, and Development Governance of a Cloud-Native Data Lake

This article introduces the best practices and cases for building, analyzing, developing, and governing cloud-native data lakes.

StarLake: Exploration and Practice of Mobvista in Cloud-Native Data Lake

This article introduces the exploration and practice of Mobvista in the field of cloud-native data lakes, as well as the architecture of StarLake.

An Overview of Alibaba Cloud's Comprehensive Cloud-Native Data Lake System

This article introduces the establishment of a cloud-native data lake system based on Alibaba Cloud OSS, Data Lake Formation (DLF), and various computing engines present in Alibaba Cloud.

How Delta Lake and DLF Service Facilitate Real-time CDC Synchronization in a Data Lake

This article explains how to perform real-time CDC synchronization in a data lake using Alibaba Cloud's Data Lake Formation (DLF) service.

How to Use JindoDistCp for Offline Data Migration to a Data Lake

This article discusses the data lake offline data migration process using JindoDistCp and explains how it improves the migration performance in different scenarios.

JindoTable for Data Optimization and Query Acceleration in a Data Lake

The article briefly discusses Alibaba Cloud's JindoTable and explains how it solves the data management problems in a data lake.

Cloud-Native Compute Engine: Challenges and Solutions

This article explains some of the challenges in cloud-native compute engines, and discusses some solutions and future directions.

Data Lake: How to Explore the Value of Data Using Multi-engine Integration

This article briefly discusses the metadata service and multi-engine support capabilities of the Alibaba Cloud Data Lake Formation (DLF) service.

EMR Remote Shuffle Service: A Powerful Elastic Tool of Serverless Spark

This article discusses Alibaba Cloud's EMR Remote Shuffle Service and explains how it solves the shuffle stability problems in compute-storage separation architectures.

Implementation and Challenges of Data Lake Metadata Services

This article explains the benefits, architecture, and implementation challenges of data lake metadata services.

EB-level Data Lake Based on OSS

This article briefly discusses data lake systems, their features, and describes the process of building a data lake storage based on Alibaba Cloud OSS.

Efficient Data Lake Formation Based on JindoFS and OSS

This article explains the process of data lake formation based on Alibaba Cloud OSS and JindoFS big data cache acceleration service.

All-in-one Lake Migration of Multiple Data Sources

This article briefly discusses Alibaba Cloud Data Lake Formation (DLF) service and explains how it solves the data migration challenges during lake migration of data from heterogeneous data sources.

JindoFS Cache-based Acceleration for Machine Learning Training in a Data Lake

The article explains how JindoFS cache-based acceleration service improves machine learning training speed in a data lake.

DataWorks: A Platform for Developing and Governing a Data Lake

This article briefly discusses Alibaba Cloud's big data platform, DataWorks, and explains how it solves the common challenges of a data lake.

JindoFS: Computing and Storage Separation for Cloud-native Big Data

In this blog, we'll introduce the origins of JindoFS and discuss the problems its

In-depth Review of Apache Spark: Spark + AI Summit 2020

Matei Zaharia, founder of the Spark project, gave an in-depth review of Spark at the Spark + AI Summit 2020 in conjunction with its 10-year anniversary.

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5260485642767126 Commented on Using Data Preorganization for Faster Queries in Spark on EMR

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