The Run-In Period for Flink and Hive

Jason addresses the bugs and compatibility issues with Flink-Hive by operating on a Hive database using Flink SQL to demonstrate some of the features provided.

Hive Finally Has Flink!

Jason introduces the architecture of Hive integration in Flink, discusses problems, and how to solve them.

Setting up Spark on MaxCompute

This post provides a walkthrough on how to set up Spark on MaxCompute on Alibaba Cloud.

Using Data Preorganization for Faster Queries in Spark on EMR

This article looks into how you can accelerate query speeds by using the Spark Relational Cache of Alibaba Cloud E-MapReduce.

Use Apache Arrow to Assist PySpark in Data Processing

This article looks at Apache Arrow and its usage in Spark and how you can use Apache Arrow to assist PySpark in data processing operations.

Use Relational Cache to Accelerate EMR Spark in Data Analysis

This article looks into what cache and relational cache is and how you can use it to accelerate EMR spark in data analysis operations.

Use EMR Spark Relational Cache to Synchronize Data Across Clusters

This article looks at EMR Spark Relational Cache, how it can be useful in a number of scenarios, and how use it to synchronize Data Across two clusters.

Rewriting the Execution Plan in the EMR Spark Relational Cache

This article goes through the process of rewriting execution plans in the Spark Relational Cache on EMR.

Setting Up PySpark on Alibaba Cloud CentOS Instance

This tutorial provides a step-by-step tutorial on how to setup PySpark in Alibaba Cloud ECS instance which is running CentOS 7.x operating system.

How to Use Spark Operator with Kubernetes

This article describes how use Spark Operator to run Spark tasks on Kubernetes and its various advantages compared with the traditional spark-submit.

Big Data Storage and Spark on Kubernetes

This article discusses big data storage and how Alibaba Cloud container services and Spark on Kubernetes can be used to meet several different storage scenarios.

Data Processing with SMACK: Spark, Mesos, Akka, Cassandra, and Kafka

This article introduces the SMACK (Spark, Mesos, Akka, Cassandra, and Kafka) stack and illustrates how you can use it to build scalable data processin.