Release version: 0.1
19 files changed
tree: 1638dd6b85131b2ca83992c9c5ce16e1939810f1
  1. .editorconfig
  2. .github/
  3. .gitignore
  4. .travis.yml
  9. bin/
  10. checkstyle.license
  11. checkstyle.xml
  12. client/
  13. common/
  14. compiler/
  15. conf/
  16. deploy/
  17. examples/
  18. formatter.xml
  20. pom.xml
  21. runtime/
  22. webui/


Build Status

A Data Processing System for Flexible Employment With Different Deployment Characteristics.

Online Documentation

Details about Nemo and its development can be found in:

Please refer to the Contribution guideline to contribute to our project.

Nemo prerequisites and setup


  • Java 8
  • Maven
  • YARN settings
  • Protobuf 2.5.0
    • On Ubuntu 14.04 LTS and its point releases:

      sudo apt-get install protobuf-compiler
    • On Ubuntu 16.04 LTS and its point releases:

      sudo add-apt-repository ppa:snuspl/protobuf-250
      sudo apt update
      sudo apt install protobuf-compiler=2.5.0-9xenial1
    • On macOS:

      brew tap homebrew/versions
      brew install protobuf@2.5
    • Or build from source:

    • To check for a successful installation of version 2.5.0, run protoc --version

Installing Nemo

  • Run all tests and install: mvn clean install -T 2C
  • Run only unit tests and install: mvn clean install -DskipITs -T 2C

Running Beam applications

Configurable options

  • -job_id: ID of the Beam job
  • -user_main: Canonical name of the Beam application
  • -user_args: Arguments that the Beam application accepts
  • -optimization_policy: Canonical name of the optimization policy to apply to a job DAG in Nemo Compiler
  • -deploy_mode: yarn is supported(default value is local)


## MapReduce example
./bin/ \
	-job_id mr_default \
	-executor_json `pwd`/examples/resources/beam_test_executor_resources.json \
	-optimization_policy org.apache.nemo.compiler.optimizer.policy.DefaultPolicy \
	-user_main org.apache.nemo.examples.beam.WordCount \
	-user_args "`pwd`/examples/resources/test_input_wordcount `pwd`/examples/resources/test_output_wordcount"

## YARN cluster example
./bin/ \
	-deploy_mode yarn \
 	-job_id mr_transient \
	-executor_json `pwd`/examples/resources/beam_test_executor_resources.json \
 	-user_main org.apache.nemo.examples.beam.WordCount \
 	-optimization_policy org.apache.nemo.compiler.optimizer.policy.TransientResourcePolicy \
	-user_args "hdfs://v-m:9000/test_input_wordcount hdfs://v-m:9000/test_output_wordcount"

Resource Configuration

-executor_json command line option can be used to provide a path to the JSON file that describes resource configuration for executors. Its default value is config/default.json, which initializes one of each Transient, Reserved, and Compute executor, each of which has one core and 1024MB memory.

Configurable options

  • num (optional): Number of containers. Default value is 1
  • type: Three container types are supported:
    • Transient : Containers that store eviction-prone resources. When batch jobs use idle resources in Transient containers, they can be arbitrarily evicted when latency-critical jobs attempt to use the resources.
    • Reserved : Containers that store eviction-free resources. Reserved containers are used to reliably store intermediate data which have high eviction cost.
    • Compute : Containers that are mainly used for computation.
  • memory_mb: Memory size in MB
  • capacity: Number of Tasks that can be run in an executor. Set this value to be the same as the number of CPU cores of the container.


    "num": 12,
    "type": "Transient",
    "memory_mb": 1024,
    "capacity": 4
    "type": "Reserved",
    "memory_mb": 1024,
    "capacity": 2

This example configuration specifies

  • 12 transient containers with 4 cores and 1024MB memory each
  • 1 reserved container with 2 cores and 1024MB memory

Monitoring your job using web UI

Nemo Compiler and Engine can store JSON representation of intermediate DAGs.

  • -dag_dir command line option is used to specify the directory where the JSON files are stored. The default directory is ./dag. Using our online visualizer, you can easily visualize a DAG. Just drop the JSON file of the DAG as an input to it.


./bin/ \
	-job_id als \
	-executor_json `pwd`/examples/resources/beam_test_executor_resources.json \
  	-user_main org.apache.nemo.examples.beam.AlternatingLeastSquare \
  	-optimization_policy org.apache.nemo.compiler.optimizer.policy.TransientResourcePolicy \
  	-dag_dir "./dag/als" \
  	-user_args "`pwd`/examples/resources/test_input_als 10 3"

Speeding up builds

  • To exclude Spark related packages: mvn clean install -T 2C -DskipTests -pl \!compiler/frontend/spark,\!examples/spark
  • To exclude Beam related packages: mvn clean install -T 2C -DskipTests -pl \!compiler/frontend/beam,\!examples/beam