open source

Apache Toree

Apache Toree acts as a middleman between an interactive application, and an Apache Spark™ cluster. It is a project undergoing Incubation at The Apache Software Foundation (ASF)*

When we first started connecting applications to Spark, we discovered the existing interaction mechanisms had serious limitations, such as requiring code to be bundled in a JAR and writing results out to an external datastore.

To overcome these limitations, we wrote the Apache Toree that uses the IPython protocol. Despite the protocol’s name, Apache Toree is not limited to supporting just Python, and indeed our first application was a Notebook for analyzing data with Scala.

Toree supports a number of types of interactions. In one common case, applications send snippets of code which are then executed by Spark, and the results are returned directly to the application. This style of interaction is what users of Notebooks experience when they evaluate code in cells. Instead of sending raw code, an application can send magics, which might be commands to add a JAR to the Spark execution context or a call to execute a shell command such as “ls”. Toree provides a well-defined mechanism to associate functionality with magics, and this is a useful point of extensibility of the system. The Kernel also supports an RPC-like interaction for applications to communicate with Spark. This is supported through the “Comm API” which is useful, for example, when an application needs to repetitively apply the same function to different data values.

Applications wanting to work with Spark can be located remotely from a Spark cluster and use a Apache Toree Client to communicate with a Apache Toree Server running on the cluster, or they can communicate directly with the Apache Toree Server. Multiple clients/applications can communicate with a single Kernel which contains a Spark application context, and this provides a simple form of multi-tenancy.

Github Get Started Read More

*Apache Toree is an effort undergoing Incubation at The Apache Software Foundation (ASF), sponsored by the Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.


You Might Also Enjoy

Gidon Gershinsky
Gidon Gershinsky
2 months ago

How Alluxio is Accelerating Apache Spark Workloads

Alluxio is fast virtual storage for Big Data. Formerly known as Tachyon, it’s an open-source memory-centric virtual distributed storage system (yes, all that!), offering data access at memory speed and persistence to a reliable storage. This technology accelerates analytic workloads in certain scenarios, but doesn’t offer any performance benefits in other scenarios. The purpose of this blog is to... Read More

James Spyker
James Spyker
4 months ago

Streaming Transformations as Alternatives to ETL

The strategy of extracting, transforming and then loading data (ETL) to create a version of your data optimized for analytics has been around since the 1970s and its challenges are well understood. The time it takes to run an ETL job is dependent on the total data volume so that the time and resource costs rise as an enterprise’s data volume grows. The requirement for analytics databases to be mo... Read More