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Announcing Google Cloud Dataflow runner for Apache Flink
Monday, March 23, 2015
More and more organizations have learned, through experimentation, how much latent value exists in large scale data and how it can be unearthed via parallelized data processing. Bringing these practices into production requires faster, easier and more reliable data processing pipelines.
Google Cloud Dataflow
is designed to meet these requirements. It’s a fully managed, highly scalable, strongly consistent processing service for both batch and stream processing. It merges batch and stream into a unified programming model which offers programming simplicity, powerful semantics and operational robustness. The first two of these benefits are properties of the Dataflow programming model itself, which Google released in open source via a
SDK
, and is not tied to running on Google Cloud Platform.
Today, we’re announcing another deployment option for your Dataflow processing pipelines. The team behind the fast-growing
Apache Flink
project has released a
Cloud Dataflow runner for Flink
, allowing any Dataflow program to execute on a Flink cluster. Apache Flink is a
new
Apache Top-Level project that offers APIs and a distributed processing engine for batch and stream data processing.
By running on Flink, Dataflow pipelines benefit not only from the power of the Dataflow programming model, but also from the portability, performance and flexibility of the Flink runtime. It provides a robust execution engine with custom memory management and a cost-based optimizer. And best of all, you have the assurance that your Dataflow pipelines are portable beyond Google Cloud Dataflow: via the Flink runner, your pipelines can execute both on-premise (virtualized or bare-metal) or in the cloud (on VMs).
This brings the number of production-ready deployment runtimes for your Dataflow pipelines to three and gives you the flexibility to choose the right platform and the right runtime for your jobs, and keep your options open as the big data landscape continues to evolve. Available Dataflow runners include:
Apache Flink
, on-premises or in the cloud, as announced today
Apache Spark
, on-premises or in the cloud, thanks to the
Dataflow runner for Spark, contributed by Cloudera
Google Cloud Dataflow
, a
fully managed service
(currently in Alpha, apply
here
to join)
For more information, see the
blog post
by
data Artisans
, who created the Google Cloud Dataflow runner for Flink.
We’re thrilled by the growth of deployment options for the portable Dataflow programming model. No matter where you deploy your Dataflow jobs, join us using the
“google-cloud-dataflow” tag on StackOverflow
and let us know if you have any questions.
-Posted by William Vambenepe, Product Manager
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