Learning Spark Structured Streaming

Jules Damji has a nice compendium of links and additional resources for people wanting to learn more about Apache Spark’s Structured Streaming:

Structured Streaming In Apache Spark: A new high-level API for streaming

Databricks’ engineers and Apache Spark committers Matei Zaharia, Tathagata Das, Michael Armbrust and Reynold Xin expound on why streaming applications are difficult to write, and how Structured Streaming addresses all the underlying complexities.

There’s quite a bit of reading material on the other side.

Related Posts

Handling Errors in Kafka Connect

Robin Moffatt shows us some techniques for handling errors in your Kafka topics: We’ve seen how setting errors.tolerance = all will enable Kafka Connect to just ignore bad messages. When it does, by default it won’t log the fact that messages are being dropped. If you do set errors.tolerance = all, make sure you’ve carefully thought through […]

Read More

Batch Consumption from Kafka with Spark

Swapnil Chougule shares a few tips on performing batch processing of a Kafka topic using Apache Spark: Spark as a compute engine is very widely accepted by most industries. Most of the old data platforms based on MapReduce jobs have been migrated to Spark-based jobs, and some are in the phase of migration. In short, […]

Read More

Categories

August 2017
MTWTFSS
« Jul Sep »
 123456
78910111213
14151617181920
21222324252627
28293031