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.

Related Posts

Anomaly Detection With Kafka Streams

Ajmal Karuthakantakath shows us an application which performs fairly simple anomaly detection using Kafka Streams: The problem is in the banking loan payment domain, where customers have taken a loan and they need to make monthly payments to repay the loan amount. Assume there are millions of customers in the system and all these customers need […]

Read More

Master Data In Azure

Matt How explains why Master Data Services isn’t a great cloud-based master data management solution and offers up an alternative: Excel is easy to use, but not user friendly Excel is on nearly every desktop in any Windows based organisation and with the Master Data Services Add-in, it puts the data well within the reach […]

Read More

Categories

June 2017
MTWTFSS
« May Jul »
 1234
567891011
12131415161718
19202122232425
2627282930