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[jvm-packages] update local dev build process (#4640)

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This commit is contained in:
Mathew Wicks
2019-07-16 16:23:06 +12:00
committed by Nan Zhu
parent 9975c533c7
commit 6323ef94ad
10 changed files with 205 additions and 44 deletions
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jvm-packages/README.md
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@@ -98,3 +98,23 @@ spark.read.format("libsvm").load("trainingset_libsvm")
```
Spark assumes that the dataset is 1-based indexed. However, when you do prediction with other bindings of XGBoost (e.g. Python API of XGBoost), XGBoost assumes that the dataset is 0-based indexed. It creates a pitfall for the users who train model with Spark but predict with the dataset in the same format in other bindings of XGBoost.
## Development
You can build/package xgboost4j locally with the following steps:
**Linux:**
1. Ensure [Docker for Linux](https://docs.docker.com/install/) is installed.
2. Clone this repo: `git clone --recursive https://github.com/dmlc/xgboost.git`
3. Run the following command:
- With Tests: `./xgboost/jvm-packages/dev/build-linux.sh`
- Skip Tests: `./xgboost/jvm-packages/dev/build-linux.sh --skip-tests`
**Windows:**
1. Ensure [Docker for Windows](https://docs.docker.com/docker-for-windows/install/) is installed.
2. Clone this repo: `git clone --recursive https://github.com/dmlc/xgboost.git`
3. Run the following command:
- With Tests: `.\xgboost\jvm-packages\dev\build-linux.cmd`
- Skip Tests: `.\xgboost\jvm-packages\dev\build-linux.cmd --skip-tests`
*Note: this will create jars for deployment on Linux machines.*