From 0b607fb8848dab46d1346004641e5e9700afeee6 Mon Sep 17 00:00:00 2001
From: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
Date: Sun, 12 Aug 2018 07:27:28 -0700
Subject: [PATCH] Add link to XGBoost4J-Spark tutorial on AWS Yarn tutorial
 (#3582)

---
 doc/tutorials/aws_yarn.rst | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/doc/tutorials/aws_yarn.rst b/doc/tutorials/aws_yarn.rst
index 9988c0248..62c30967f 100644
--- a/doc/tutorials/aws_yarn.rst
+++ b/doc/tutorials/aws_yarn.rst
@@ -5,9 +5,9 @@ This is a step-by-step tutorial on how to setup and run distributed `XGBoost <ht
 on an AWS EC2 cluster. Distributed XGBoost runs on various platforms such as MPI, SGE and Hadoop YARN.
 In this tutorial, we use YARN as an example since this is a widely used solution for distributed computing.
 
-.. note:: XGBoost on Spark
+.. note:: XGBoost with Spark
 
-  If you are preprocessing training data with Spark, you may want to look at `XGBoost4J-Spark <https://xgboost.ai/2016/10/26/a-full-integration-of-xgboost-and-spark.html>`_, which supports distributed training on Resilient Distributed Dataset (RDD).
+  If you are preprocessing training data with Spark, consider using :doc:`XGBoost4J-Spark </jvm/xgboost4j_spark_tutorial>`.
 
 ************
 Prerequisite