S3Guard

Mingliang Liu and Rajesh Balamohan explain why you shouldn’t use S3 as your primary Hadoop data store, as well as a tool which helps mitigate those problems:

Some of the real world use cases which can be impacted due to the S3 eventual consistency model are:

1. Listing Files. Newly created files might not be visible for data processing. In Hive, Spark and MapReduce, this can lead to erroneous results from incomplete source data or failure to commit all intermediate results.

2. ETL Workflow. Systems like Oozie rely on marker files to trigger the subsequent workflows. Any delay in the visibility of these files can lead to delays in the subsequent workflows.

3. Existence-guarded path operations. Any action which fails if the destination path is present may see a deleted file in a listing, and so fail — even though the file has already been deleted.

Read on to see how S3Guard works and how to enable it in HDP 2.6.