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3.1.2
3.1.2
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  1. Using Akamas
  2. Guidelines for defining optimization studies

Optimizing Spark

Last updated 2 years ago

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When optimizing applications running on the Apache Spark framework, the goal is to find the configurations that best optimize the allocated resources or the execution time.

Please refer to the for the list of component types, parameters, metrics, and constraints.

Workflows

Applying parameters

Akamas offers several operators that you can use to apply the parameters for the tuned Spark application. In particular, we suggest using the , which connects to a target instance to submit the application using the configuration parameters to test.

Other solutions include:

  • the , which allows submitting the application along with the configuration parameters using the

  • the standard , which allows running a custom command or script once the updated the default Spark configuration file or a custom one using a template.

A typical workflow

You can organize a typical workflow to optimize a Spark application in three parts:

  1. Setup the test environment

    1. prepare any required input data

    2. apply the Spark configuration parameters, if you are going for a file-based solution

  2. Execute the Spark application

  3. Perform cleanup

Here’s an example of a typical workflow where Akamas executes the Spark application using the :

name: Spark workflow
tasks:
   - name: cwspark
     arguments:
        master: yarn
        deployMode: cluster
        file: /home/hadoop/scripts/pi.py
        args: [ 100 ]L

Telemetry Providers

Here’s a configuration example for a telemetry provider instance:

provider: SparkHistoryServer
config:
  address: sparkmaster.akamas.io
  port: 18080

Examples

Akamas can access statistics using the . This provider maps the metrics in this optimization pack to the statistics provided by the History Server endpoint.

See this for an example of a study leveraging the Spark pack.

Spark optimization pack
Spark SSH Submit operator
Spark Livy Operator
Livy Rest interface
Executor operator
FileConfigurator operator
Spark SSH Submit operator
Spark History Server
Spark History Server Provider
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