AWS Big Data Blog
Tag: Apache Spark
Monitor Spark streaming applications on Amazon EMR
This post demonstrates how to implement a simple SparkListener, monitor and observe Spark streaming applications, and set up some alerts. The post also shows how to use alerts to set up automatic scaling on Amazon EMR clusters, based on your CloudWatch custom metrics.
Read MoreHow Drop used the Amazon EMR runtime for Apache Spark to halve costs and get results 5.4 times faster
This post details how we designed and implemented our data lake’s batch ETL pipeline to use Amazon EMR, and the numerous ways we iterated on its architecture to reduce Apache Spark runtimes from hours to minutes and save over 50% on operational costs.
Read MoreSimplify data pipelines with AWS Glue automatic code generation and Workflows
In this post, we discuss how to leverage the automatic code generation process in AWS Glue ETL to simplify common data manipulation tasks, such as data type conversion and flattening complex structures. We also explore using AWS Glue Workflows to build and orchestrate data pipelines of varying complexity. Lastly, we look at how you can leverage the power of SQL, with the use of AWS Glue ETL and Glue Data Catalog, to query and transform your data.
Read MoreBest practices to scale Apache Spark jobs and partition data with AWS Glue
The first post of this series discusses two key AWS Glue capabilities to manage the scaling of data processing jobs. The first allows you to horizontally scale out Apache Spark applications for large splittable datasets. The second allows you to vertically scale up memory-intensive Apache Spark applications with the help of new AWS Glue worker types. The post also shows how to use AWS Glue to scale Apache Spark applications with a large number of small files commonly ingested from streaming applications using Amazon Kinesis Data Firehose. Finally, the post shows how AWS Glue jobs can use the partitioning structure for large datasets in Amazon S3 to provide faster execution times for Apache Spark applications.
Read More