Graal Platform Documentation

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Overview

  • What is Graal Platform?
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Quickstart

  • Quickstart

Tutorials

  • Get started with Python
  • Get started with Dask
  • Get started with XGBoost
  • Get started with Apache Spark and Maven
  • Get started with Apache PySpark
  • Get started with Apache Beam and Gradle
  • Use the API
  • Using the command line tool (graalctl)
  • Using secrets
  • Migration from Databricks
  • Get started with Tensorflow
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  • Setting up the Hadoop bridge
  • Get started with Apache Flink and Maven
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  • Get started with Apache Spark Streaming Pulsar
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  • Get started with the SDK

How-to guides

  • Using Graal Platform with Azure Data Factory
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Troubleshoot & debug

  • Troubleshooting
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Get started with XGBoost

Prerequisites

You need the following:

  • Git
  • Python >=3.6
  • pip

Some libraries installed on Graal:

  • adlfs==2022.2.0
  • aiohttp==3.8.1
  • gcsfs==2022.1.0
  • lightgbm==3.3.2
  • prometheus-client==0.14.1
  • protobuf==3.19.4
  • pyarrow==6.0.1
  • python-socketio==5.6.0
  • s3fs==2022.1.0
  • h5py==3.1.0
  • pandas==1.1.5
  • xgboost==1.5.2

Distributed feature

In order to use xgboost distributed it is necessary to adapt your code. For more information here is the official documentation of XGBoost distributed_xgboost_kubernetes Graal takes care of installing and preparing the XGBoost operator, the job configuration and its creation in Kubernetes.

Example

Clone the example project and use pip to build it. The example project named xgboost_examples is composed of 2 modules, one for xgboost and one for lightgbm.

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