Structured Streaming

Kevin Feasel

2016-08-02

Spark

Andrew Ray explains streaming solutions using Spark 2.0:

If you are familiar with traditional Spark streaming you may notice that the above example is lacking an explicit batch duration. In structured streaming the equivalent feature is a trigger. By default it will run batches as quickly as possible, starting the next batch as soon as more data is available and the previous batch is complete. You can also set a more traditional fixed batch interval for your trigger. In the future more flexible trigger options will be added.

A related consequence is that windows are no longer forced to be a multiple of the batch duration. Furthermore, windows needn’t be only on processing time anymore, we can rearrange events that may have been delayed or arrived out of order and window by event time. Suppose our input stream had a column event_time that we wanted to do windowed counts on. Then we could do something like the following to get counts of events in a 1 minute window:

Right now, there are some pretty strict limitations on this new streaming, but I imagine they’ll loosen up quite soon.

Related Posts

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

Securely Accessing External Resources From Databricks AWS

Itai Weiss shows how you can securely hit external data sources when using Databricks for AWS: For security purposes, Databricks Apache Spark clusters are deployed in an isolated VPC dedicated to Databricks within the customer’s account. In order to run their data workloads, there is a need to have secure connectivity between the Databricks Spark […]

Read More

Categories

August 2016
MTWTFSS
« Jul Sep »
1234567
891011121314
15161718192021
22232425262728
293031