Jar file for MapReduce new API Job.getInstance(Configuration, String)

job job job getinstance conf
logical flow of mapreduce
hadoop job addcachefile
job setjar
gradle hadoop core
job setjarbyclass filter class

Have setup Hadoop 2.2 .Trying to remove the deprecated API

    Job job = new Job(conf, "word count");

from example Wordcount (which comes with Hadoop ) here

Replaced the deprecated API with


    Job job = Job.getInstance(conf, "word count");

compile error is

Job.getInstance cannot be resolved to a type.

The Job class which is already imported(old API or MR1) seems doesn't have this method.

Which jar contains this new Job class with Job.getInstance(Configuratio,String) method

How to resolve this? Are there any additional changes to the example to migrate to MapReduce v2?

How I solved this issue was by adding hadoop-core as dependency. I had specified only hadoop-common.


Job (Apache Hadoop Main 2.4.1 API), to submit a job: // Create a new Job Job job = new Job(new Configuration()); job. Fields inherited from class org.apache.hadoop.mapreduce.task. Add a file to be localized Set the Jar by finding where a given class came from. public static Job getInstance(Configuration conf, String jobName) throws IOException. Add a file to job config for shared cache processing. If shared cache is enabled, it will return true, otherwise, return false. We don't check with SCM here given application might not be able to provide the job id; ClientSCMProtocol.use requires the application id. Job Submitter will read the files from job config and take care of things.

Change it with this

        Configuration conf = new Configuration();
        Job job = new Job(conf);  


        Job job = new Job(new Configuration());

Job (Apache Hadoop Main 3.0.0 API), Deprecated. Use getInstance(Configuration, String) Add an file path to the current set of classpath entries It adds the file to cache as well. Creates a new Job with no particular Cluster and a given Configuration . static Job Set the job jar. Job getInstance(Configuration conf, String jobName) This method is used to generate a new Job without any cluster and provided configuration and job name. String getJobFile() This method is used to get the path of the submitted job configuration. String getJobName() This method is used to get the user-specified job name. JobPriority getPriority()

Job.getInstance cannot be resolved to a type.

You get the error message because, required libraries are not present on your application class-path. You need hadoop-core*.jar file present on your class-path to resolve this issue.

By the way which jar contains this new Job class with Job.getInstance(Configuratio,String) method

The org.apache.hadoop.mapreduce.Job class contained within hadoop-core-*.jar file. The jar file name will be appended by the hadoop version and vendor name (cdh - Cloudera, hdf - hortenworks etc.)


Job.getInstance() is a static API, and you need not create an instance of the Job class to access it. Interestingly, getInstance() is used to create a new instance of the Job class, and if you already have one created using new keyword, you are not required to call getInstance again.

Replace Job job = new Job.getInstance(conf, "word count"); with Job job = Job.getInstance(conf, "word count");

Java Code Examples org.apache.hadoop.mapreduce.Job.getInstance, Job.getInstance. The examples are extracted from open source Java projects. public static void main(String[] args) throws Exception { Configuration conf Project: mapreduce-samples File: UnitSum.java Source Code and License fourth = makeJar(new Path(TEST_ROOT_DIR, "distributed.fourth.jar"), 4); Job job = Job. public static Job getInstance(Configuration conf) throws IOException Creates a new Job with no particular Cluster and a given Configuration . The Job makes a copy of the Configuration so that any necessary internal modifications do not reflect on the incoming parameter.

If you are using the old MapReduce API, continue using new Job() to create the instance. If you have migrated to the new API, use Job job = Job.getInstance(conf, "word count");

org.apache.hadoop.mapreduce.Job.addCacheFile java code , getInstance(); Configuration conf;new Job(conf); Smart code suggestions by Hadoop DistributedCache is deprecated - what is the preferred API? Job public int run(String[] args) throws Exception { Configuration conf = getConf(); Job job = Job. the name after the # sign as your // file name in your Mapper/Reducer job. The following are Jave code examples for showing how to use addCacheFile() of the org.apache.hadoop.mapreduce.Job class. You can vote up the examples you like. Your votes will be used in our system to get more good examples.

Try that Job job = Job.getInstance(conf, "word count"); change to Job job = new Job(conf);

Apache Hadoop 3.4.0-SNAPSHOT – MapReduce Tutorial, Typically both the input and the output of the job are stored in a file-system. The Hadoop job client then submits the job (jar/executable etc.) Hadoop Pipes is a SWIG-compatible C++ API to implement MapReduce public static void main(​String[] args) throws Exception { Configuration conf = new getInstance(conf). Creates a new Job A Job will be created with a generic Configuration. static Job: getInstance(Configuration conf) Creates a new Job with a given Configuration. static Job: getInstance(Configuration conf, String jobName) Creates a new Job with a given Configuration and a given jobName. String: getJar() Get the pathname of the job's jar

Run Word Count Java Mapreduce Program in Hadoop, How to create Jar file for Wordcount using eclipse IDE for Java. Text value, Context context) throws IOException, InterruptedException { StringTokenizer itr = new StringTokenizer(value. Configuration conf = new Configuration(); conf job = new conf(); //Job job = Job.getInstance(conf, "word count"); job. Once user configures that profiling is needed, she/he can use the configuration property mapreduce.task.profile.{maps|reduces} to set the ranges of MapReduce tasks to profile. The value can be set using the api Configuration.set(MRJobConfig.NUM_{MAP|REDUCE}_PROFILES, String). By default, the specified range is 0-2.

Running MapReduce application on hadoop using eclipse IDE , Also its better to make an executable JAR file and run it without an IDE, for preliminary Does it need additional configuration in Eclipse? Lets the example of WordCount2 on new MR api of Apache Hadoop. getInstance(conf, "​word count"); job.setOutputValueClass(IntWritable.class);. List<String> otherArgs = new  Map Reduce client jars for 2.4.1 hadoop in eclipse. Hadoop avro correct jar files issue. 4. Jar file for MapReduce new API Job.getInstance(Configuration, String) 10.

Hadoop 2.x MapReduce (MR V1) WordCounting Example , 1 MapReduce WordCounting Example; 2 Mapper Program; 3 Reducer Program So we are gong to concentrate on MapReduce New API to develop this getInstance(new Configuration()); job. Create our WordCount application JAR file using Eclipse IDE. StringTokenizer tokenizer = new StringTokenizer(line); Please use org.apache.hadoop.mapreduce.lib.* (it is new API) instead of org.apache.hadoop.mapred.TextInputFormat (it is old). The Mapper and Reducer are nothing new, please see main function, it includes relatively overall configurations, feel free to change them according to your specific requirements.