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3.5
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        • Optimize cost of a Java microservice on Kubernetes while preserving SLOs in production
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        • Optimizing a sample application running on AWS
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        • Optimizing a Spark application
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        • Optimizing cost of a Kubernetes microservice while preserving SLOs in production
        • Optimizing cost of a Java microservice on Kubernetes while preserving SLOs in production
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        • Elasticsearch 6
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    • Command Line commands
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    • Release Notes
  • Knowledge Base
    • Creating custom optimization packs
    • Setting up a Konakart environment for testing Akamas
    • Modeling a sample Java-based e-commerce application (Konakart)
    • Optimizing a web application
    • Optimizing a sample Java OpenJ9 application
    • Optimizing a sample Linux system
    • Optimizing a MongoDB server instance
    • Optimizing a Kubernetes application
    • Leveraging Ansible to automate AWS instance management
    • Guidelines for optimizing AWS EC2 instances
    • Optimizing an Oracle Database server instance
    • Optimizing an Oracle Database for an e-commerce service
    • Guidelines for optimizing Oracle RDS
    • Optimizing a MySQL server database running Sysbench
    • Optimizing a MySQL server database running OLTPBench
    • Optimizing a live full-stack deployment (K8s + JVM)
    • Setup Instana integration
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  • Operator arguments
  • Parameters applied from Experiments
  • Examples

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  1. Reference
  2. Workflow Operators

SparkLivy Operator

The SparkLivy operator uses Livy to run Spark applications on a Spark instance.

Operator arguments

Name
type
Value restrictions
Is required
Default
Description

file

String

It should be a path to a valid java or python spark application file

Yes

Spark application to submit (jar or python file)

args

List of Strings, Numbers or Booleans

Yes

Additional application arguments

className

String

No. Required for java applications.

The entry point of the java application.

name

String

No

Name of the task. When submitted the id of the study, experiment and trial will be appended.

queue

String

No

The name of the YARN queue to which submit a Spark application

pyFiles

List of Strings

Each item of the list should be a path that matches an existing python file

No

A list of python scripts to be added to the PYTHONPATH

proxyUser

String

No

The user to be used to launch Spark applications

pollingInterval

Number

pollingInterval > 0

No

10

The number of seconds to wait before checking if a launched Spark application has finished

component

String

It should match the name of an existing Component of the System under test

Yes

The name of the component whose properties can be used as arguments of the operator

Parameters applied from Experiments

The operator fetches the following parameters from the current Experiment to apply them to the System under test.

Name
Description
Restrictions

spark_driver_memory

Memory for the driver

spark_executor_memory

Memory per executor

spark_total_executor_cores

Total cores used by the application

Spark standalone and Mesos only

spark_executor_cores

Cores per executor

Spark standalone and YARN only

spark_num_executors

The number of executors

YARN only

Examples

Execute with Livy

- name: Run spark application
  operator: SparkLivy
  arguments:
    component: sparkemr
    file: /spark-examples.jar

Last updated 1 year ago

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