Hadoop：开发机运行spark程序，抛出异常：ERROR Shell: Failed to locate the winutils binary in the hadoop binary path

问题：

windows开发机运行spark程序，抛出异常：ERROR Shell: Failed to locate the winutils binary in the hadoop binary path，但是可以正常执行，并不影响结果。

// :: WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
// :: ERROR Shell: Failed to locate the winutils binary in the hadoop binary path
java.io.IOException: Could not locate executable null\bin\winutils.exe in the Hadoop binaries.
    at org.apache.hadoop.util.Shell.getQualifiedBinPath(Shell.java:)
    at org.apache.hadoop.util.Shell.getWinUtilsPath(Shell.java:)
    at org.apache.hadoop.util.Shell.<clinit>(Shell.java:)
    at org.apache.hadoop.util.StringUtils.<clinit>(StringUtils.java:)
    at org.apache.hadoop.security.Groups.parseStaticMapping(Groups.java:)
    at org.apache.hadoop.security.Groups.<init>(Groups.java:)
    at org.apache.hadoop.security.Groups.<init>(Groups.java:)
    at org.apache.hadoop.security.Groups.getUserToGroupsMappingService(Groups.java:)
    at org.apache.hadoop.security.UserGroupInformation.initialize(UserGroupInformation.java:)
    at org.apache.hadoop.security.UserGroupInformation.ensureInitialized(UserGroupInformation.java:)
    at org.apache.hadoop.security.UserGroupInformation.loginUserFromSubject(UserGroupInformation.java:)
    at org.apache.hadoop.security.UserGroupInformation.getLoginUser(UserGroupInformation.java:)
    at org.apache.hadoop.security.UserGroupInformation.getCurrentUser(UserGroupInformation.java:)
    at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$.apply(Utils.scala:)
    at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$.apply(Utils.scala:)
    at scala.Option.getOrElse(Option.scala:)
    at org.apache.spark.util.Utils$.getCurrentUserName(Utils.scala:)
    at org.apache.spark.SparkContext.<init>(SparkContext.scala:)
    at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:)
    at com.lm.sparkLearning.utils.SparkUtils.getJavaSparkContext(SparkUtils.java:)
    at com.lm.sparkLearning.rdd.RddLearning.main(RddLearning.java:)
// :: WARN RddLearning: singleOperateRdd mapRdd->[, , , ]
// :: WARN RddLearning: singleOperateRdd flatMapRdd->[, , , , , , , ]
// :: WARN RddLearning: singleOperateRdd filterRdd->[, ]
// :: WARN RddLearning: singleOperateRdd distinctRdd->[, , ]
// :: WARN RddLearning: singleOperateRdd sampleRdd->[, ]
// :: WARN RddLearning: the program end

这里所执行的程序是：

package com.lm.sparkLearning.rdd;

import java.util.Arrays;
import java.util.Iterator;
import java.util.List;

import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.FlatMapFunction;
import org.apache.spark.api.java.function.Function;
import org.apache.spark.api.java.function.Function2;
import org.apache.spark.api.java.function.VoidFunction;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import com.lm.sparkLearning.utils.SparkUtils;

public class RddLearning {
    private static Logger logger = LoggerFactory.getLogger(RddLearning.class);

    public static void main(String[] args) {

        JavaSparkContext jsc = SparkUtils.getJavaSparkContext("RDDLearning", "local[2]", "WARN");

        SparkUtils.createRddExternal(jsc, "D:/README.txt");
        singleOperateRdd(jsc);

        jsc.stop();

        logger.warn("the program end");
    }

    public static void singleOperateRdd(JavaSparkContext jsc) {
        List<Integer> nums = Arrays.asList(new Integer[] { 1, 2, 3, 3 });
        JavaRDD<Integer> numsRdd = SparkUtils.createRddCollect(jsc, nums);

        // map
        JavaRDD<Integer> mapRdd = numsRdd.map(new Function<Integer, Integer>() {
            private static final long serialVersionUID = 1L;

            @Override
            public Integer call(Integer v1) throws Exception {
                return (v1 + 1);
            }
        });

        logger.warn("singleOperateRdd mapRdd->" + mapRdd.collect().toString());

        JavaRDD<Integer> flatMapRdd = numsRdd.flatMap(new FlatMapFunction<Integer, Integer>() {
            private static final long serialVersionUID = 1L;

            @Override
            public Iterable<Integer> call(Integer t) throws Exception {
                return Arrays.asList(new Integer[] { 2, 3 });
            }
        });

        logger.warn("singleOperateRdd flatMapRdd->" + flatMapRdd.collect().toString());

        JavaRDD<Integer> filterRdd = numsRdd.filter(new Function<Integer, Boolean>() {
            private static final long serialVersionUID = 1L;

            @Override
            public Boolean call(Integer v1) throws Exception {
                return v1 > 2;
            }
        });

        logger.warn("singleOperateRdd filterRdd->" + filterRdd.collect().toString());

        JavaRDD<Integer> distinctRdd = numsRdd.distinct();

        logger.warn("singleOperateRdd distinctRdd->" + distinctRdd.collect().toString());

        JavaRDD<Integer> sampleRdd = numsRdd.sample(false, 0.5);

        logger.warn("singleOperateRdd sampleRdd->" + sampleRdd.collect().toString());
    }
}

解决方案：

1.下载winutils的windows版本
GitHub上，有人提供了winutils的windows的版本，项目地址是：https://github.com/srccodes/hadoop-common-2.2.0-bin,直接下载此项目的zip包，下载后是文件名是hadoop-common-2.2.0-bin-master.zip,随便解压到一个目录。
2.配置环境变量
增加用户变量HADOOP_HOME，值是下载的zip包解压的目录，然后在系统变量path里增加$HADOOP_HOME\bin 即可。

添加“%HADOOP%\bin”到path

再次运行程序，正常执行。