Kubernetes与大数据之四：基于Kubernetes的Spark运行Terasort(50GB data)

 

一、前言

Terasort可以测试Kubernetes平台对于Spark计算过程的如下需求的支持：

从HDFS读取能力

向HDFS写入能力

shuffle中网络读写能力

本文使用如下terasort的实现，包括TeraGen、TeraSort和TeraValidate：

https://github.com/ehiggs/spark-terasort

转载自https://blog.csdn.net/cloudvtech

二、准备工作

2.1 获取代码

git clone https://github.com/ehiggs/spark-terasort.git

2.2 修改编译配置

指定合适的spark和scala版本

  UTF-8
  2.11.8
  2.11
  2.1.1

2.3 编译

mvn install

ls target/
archive-tmp                  generated-sources  maven-status                    spark-terasort-1.1-SNAPSHOT-jar-with-dependencies.jar
classes                      jars              site                            spark-terasort-1.1-SNAPSHOT-javadoc.jar
classes.440875732.timestamp  maven-archiver    spark-terasort-1.1-SNAPSHOT.jar  surefire

转载自https://blog.csdn.net/cloudvtech

三、运行

3.1 在hdfs建立数据目录

hadoop fs -mkdir /terasort

3.2 建立spark运行的namespace和权限

admin-role.conf

kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1beta1
metadata:
  name: spark-admin
  annotations:
    rbac.authorization.kubernetes.io/autoupdate: "true"
roleRef:
  kind: ClusterRole
  name: cluster-admin
  apiGroup: rbac.authorization.k8s.io
subjects:
- kind: ServiceAccount
  name: spark-admin
  namespace: spark
---
apiVersion: v1
kind: ServiceAccount
metadata:
  name: spark-admin
  namespace: spark
  labels:
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile

建立spark namespace并绑定cluster-admin role

kubectl create namespace spark
kubectl apply -f admin-role.conf 

3.3 运行TeraGen

run_spark_teragen.sh 

/root/spark/bin/spark-submit     \

  --master k8s://https://192.168.0.3:6443  \  #master地址

  --deploy-mode cluster   \

  --name spark-terasort   \

  --class com.github.ehiggs.spark.terasort.TeraGen   \ #class地址

  --conf spark.kubernetes.namespace=spark \ #namespace

  --conf spark.kubernetes.authenticate.driver.serviceAccountName=spark-admin \ #service account

  --conf spark.kubernetes.container.image=192.168.0.3:5000/spark:terasort     \ #镜像地址

  --conf spark.eventLog.dir=hdfs://192.168.2.11:9000/eventLog \ #log地址

  --conf spark.eventLog.enabled=true \ #打开log

  --conf spark.executor.instances=50 \ #executor数目

  --conf spark.driver.cores=2 \ #driver CPU数目

  --conf spark.driver.memory=8g \ #driver内存

  --conf spark.executor.memory=6g \ #executor内存

  --conf spark.executor.cores=1 \ #executor CPU数目

  --proxy-user hadoop \ #运行用户

                       local:///opt/spark/examples/jars/spark-terasort-1.1-SNAPSHOT-jar-with-dependencies.jar \

                       50g \ #数据大小

                       hdfs://172.2.2.11:9000/terasort/50g_generated #数据生成目录

3.4 运行TeraSort

run_spark_terasort.sh 

/root/spark/bin/spark-submit     \
  --master k8s://https://172.3.0.3:6443  \
  --deploy-mode cluster   \
  --name spark-terasort   \
  --class com.github.ehiggs.spark.terasort.TeraSort   \
  --conf spark.kubernetes.namespace=spark \
  --conf spark.kubernetes.authenticate.driver.serviceAccountName=spark-admin \
  --conf spark.kubernetes.container.image=172.3.0.3:5000/spark:terasort     \
  --conf spark.eventLog.dir=hdfs://172.2.2.11:9000/eventLog \
  --conf spark.eventLog.enabled=true \
  --conf spark.executor.instances=50 \
  --conf spark.driver.cores=2 \
  --conf spark.driver.memory=8g \
  --conf spark.executor.memory=6g \
  --conf spark.executor.cores=1 \
  --proxy-user hadoop \
    local:///opt/spark/examples/jars/spark-terasort-1.1-SNAPSHOT-jar-with-dependencies.jar \
    hdfs://172.2.2.11:9000/terasort/50g_generated \
    hdfs://172.2.2.11:9000/terasort/50g_sorted

Stages： 

Executors：

Tasks： 

3.5 运行TeraValidate

run_spark_teravarify.sh 

/root/spark/bin/spark-submit     \
  --master k8s://https://172.3.0.3:6443  \
  --deploy-mode cluster   \
  --name spark-terasort   \
  --class com.github.ehiggs.spark.terasort.TeraValidate   \
  --conf spark.kubernetes.namespace=spark \
  --conf spark.kubernetes.authenticate.driver.serviceAccountName=spark-admin \
  --conf spark.kubernetes.container.image=172.3.0.3:5000/spark:terasort     \
  --conf spark.eventLog.dir=hdfs://172.2.2.11:9000/eventLog \
  --conf spark.eventLog.enabled=true \
  --conf spark.executor.instances=50 \
  --conf spark.driver.cores=2 \
  --conf spark.driver.memory=8g \
  --conf spark.executor.memory=6g \
  --conf spark.executor.cores=1 \
  --proxy-user hadoop \
    local:///opt/spark/examples/jars/spark-terasort-1.1-SNAPSHOT-jar-with-dependencies.jar \
    hdfs://172.2.2.11:9000/terasort/50g_sorted \
    hdfs://172.2.2.11:9000/terasort/50g_varified

3.6 运行概览

3.7 运行状态图示

系统资源使用情况

转载自https://blog.csdn.net/cloudvtech