Spark Operator
This topic provides an overview of Spark Operator on HPE Ezmeral Runtime Enterprise.
HPE Ezmeral Runtime Enterprise 5.4.0 and
      later supports multiversion Spark Operator. You can submit Spark Applications for different
      versions of Apache Spark using a single Spark Operator. When you submit the Spark
      Applications, Spark Operator creates a Kubernetes spark-submit job. The
        spark-submit job spawns the driver pod. A Spark driver pod launches a set
      of Spark executors that execute the job you want to run.
Starting from HPE Ezmeral Runtime Enterprise 5.6.0, Spark 3.3.x and later versions support enhanced S3 features introduced in Hadoop 3.x.
Starting from HPE Ezmeral Runtime Enterprise 5.5.0, you can choose to use Spark images provided by HPE Ezmeral Runtime Enterprise or your own open-source Spark images.
Spark Operator supports open-source Spark version compatible with the Kubernetes version supported on HPE Ezmeral Runtime Enterprise. With the support for open-source Spark, you can build your Spark with Hadoop 3 profile or any other profile of your choice.
You can integrate open-source Spark with Spark History Server by using PVC.
To use open-source Spark, build Spark and then build Spark images to run in HPE Ezmeral Runtime Enterprise. See Building Spark and Building Images.
- Data Fabric filesystem, Data Fabric Streams, and any other Data Fabric sources and sinks which require Data Fabric client.
- Data Fabric specific security features (Data Fabric SASL).
- If you are a local user, set the spark.mapr.user.secretoption on your Spark applicationyamlfile.
- If you are AD/LDAP user, spark.mapr.user.secretoption is automatically set using the ticketgenerator webhook.
- You must not change the user context. See using pod security context.