From fbfbd525d8a0877000ecbcf5fcb1362a2c7a6508 Mon Sep 17 00:00:00 2001
From: Jiaming Yuan <jm.yuan@outlook.com>
Date: Thu, 23 Jul 2020 14:00:19 +0800
Subject: [PATCH] Cache dependencies on Github Action. (#5928)

---
 .github/workflows/main.yml | 14 ++++++++++++++
 R-package/DESCRIPTION      |  6 +++---
 2 files changed, 17 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index 46e91e55d..e32e81de9 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -25,6 +25,13 @@ jobs:
       with:
         java-version: 1.8
 
+    - name: Cache Maven packages
+      uses: actions/cache@v2
+      with:
+        path: ~/.m2
+        key: ${{ runner.os }}-m2-${{ hashFiles('./jvm-packages/pom.xml') }}
+        restore-keys: ${{ runner.os }}-m2
+
     - name: Test JVM packages
       run: |
         cd jvm-packages
@@ -61,6 +68,13 @@ jobs:
       with:
         r-version: ${{ matrix.config.r }}
 
+    - name: Cache R packages
+      uses: actions/cache@v2
+      with:
+        path: ${{ env.R_LIBS_USER }}
+        key: ${{ runner.os }}-r-${{ matrix.config.r }}-1-${{ hashFiles('R-package/DESCRIPTION') }}
+        restore-keys: ${{ runner.os }}-r-${{ matrix.config.r }}-2-
+
     - name: Install dependencies
       shell: Rscript {0}
       run: |
diff --git a/R-package/DESCRIPTION b/R-package/DESCRIPTION
index c9237a3a9..be9c62649 100644
--- a/R-package/DESCRIPTION
+++ b/R-package/DESCRIPTION
@@ -31,9 +31,9 @@ Authors@R: c(
   )
 Description: Extreme Gradient Boosting, which is an efficient implementation
     of the gradient boosting framework from Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>.
-    This package is its R interface. The package includes efficient linear 
-    model solver and tree learning algorithms. The package can automatically 
-    do parallel computation on a single machine which could be more than 10 
+    This package is its R interface. The package includes efficient linear
+    model solver and tree learning algorithms. The package can automatically
+    do parallel computation on a single machine which could be more than 10
     times faster than existing gradient boosting packages. It supports
     various objective functions, including regression, classification and ranking.
     The package is made to be extensible, so that users are also allowed to define