#DO WE NEED TO INSTALL APACHE SPARK HOW TO#
#DO WE NEED TO INSTALL APACHE SPARK DRIVER#
#DO WE NEED TO INSTALL APACHE SPARK CODE#
#DO WE NEED TO INSTALL APACHE SPARK SERIES#
#DO WE NEED TO INSTALL APACHE SPARK DOWNLOAD#

In this example I will use a dedicated Spark master node that sits outside of the 3-node Cassandra cluster вЂ“ with each Cassandra nodes additionally running a Spark slave. Running this on a dedicated Spark master node would be a good place to do this.

#DO WE NEED TO INSTALL APACHE SPARK DRIVER#

It does not require a lot of resources to run therefore contention is not a major concern.ДЄdditionally the location of the Spark driver application should be considered. The Spark master node can be located on any of these slave machines, or on a separate box. To achieve optimal performance the slaves should be overlaid on the Cassandra cluster. Design the deploymentДЇor a standalone cluster we are going to need 1 x Spark-master node and n number of Spark-slaves. To perform a standalone cluster setup, the following needs to be done: 2.1. It is generally a good idea to run the driver application вЂњcloseвЂќ to the processing cluster, but not a strict requirement as long as the network addressability is fulfilled.

#DO WE NEED TO INSTALL APACHE SPARK CODE#

The executors connect to the driver at the start of the process to obtain code and other artefacts as well as the decomposed processing tasks they need to execute. The driver does not have to run on the same machines where we run the Spark Master or Workers, but it must be network addressable and reachable from them. In my previous blog, all the code examples belonged to the driver application.

Driver application: this is what the end-user creates and it contains the coded (Scala, Java, Python, R) logic that is to be executed on the Spark cluster.

These executors are responsible to do the actual data processing.

Spark executor: executors are running on the worker nodes and they are independent processes belonging to each job submitted to the cluster.

The Cluster Manager only supervises job execution, but does not run any data processing

Cluster manager: the entry point of the cluster management framework from where the resources necessary to run the job can be allocated.

The diagram below shows a running Spark job along with the major components involved: The simplest approach is to just use a standalone Spark cluster as itвЂ™s easy to set up and will do the job. Spark is to a certain degree agnostic to what resource management framework we use вЂ“ out of the box it can run on Mesos, YARN or itвЂ™s own standalone cluster manager. To enable us to run a Spark jobs in a distributed fashion, we are going to need some kind of processing cluster overlaid on the Cassandra nodes. Address Load Tokens Owns (effective) Host ID Rack Having configured and started the cluster, using the nodetool we should be able to view our state which should look as follows: ~]$ nodetool status We start with a simple Cassandra deployment, where, in the simple case there is no need for any extra configuration (see вЂњIsolating workloadsвЂќ section for more production-like recommendations).

#DO WE NEED TO INSTALL APACHE SPARK DOWNLOAD#

The latest version is available for download from the Apache Cassandra website here. Deploy and configure a Cassandra clusterДЇirst, we are going to need a running Cassandra cluster. LetвЂ™s take a look at the process step-by-step. In any production deployment you should consider using DNS names instead. In order to keep things simple for this blogpost, I am going to use IP addresses alone to configure everything.

Spark-Cassandra connector 2.0.0 (for Scala 2.11).

At the time of writing, the following versions were used: There is a good вЂњversion compatibilityвЂќ matrix on the GitHub wiki of the Spark-Cassandra connector. To do this, the following components are needed:Д«e careful about the various versions of frameworks and libraries. Going through the process also helps understanding how DSE ultimately works under the hood.

On the other hand, the components to configure such a setup from scratch are all available as open source software.

Installing a mixed Open source Cassandra / Spark cluster If you are already a user of DSE or considering adopting it, this is definitely the way to go.

#DO WE NEED TO INSTALL APACHE SPARK HOW TO#

DataStax has good documentation about how to install and configure their solution: The simplest and most obvious choice is to get DataStax Enterprise which contains Cassandra, Spark with a highly available Spark Master, and many more components bundled up.

#DO WE NEED TO INSTALL APACHE SPARK SERIES#

This blog is the second part of a series вЂњSpark вЂ“ the Pragmatic bitsвЂќ.

Do we need to install apache spark