how to write mapreduce program in hadoop

Hadoop Reading Notes series article:http://blog.csdn.net/caicongyang/article/category/2166855 (series of articles will be gradually trimmed to complete, add data file format expected related comments)1. Description:From the given file, find the maximum of 100 values, given the data file format as follows:5331656517800292911374982668522067918224212228227533691229525338221001067312284316342740518015 ...2. Use the TreeMap class in the code below, so

1. To write MapReduce on eclipse, you need to install the Hadoop plug-in on eclipse by installing the contrib/eclipse-plugin/in the Hadoop installation directory The Hadoop-0.20.2-eclipse-plugin.jar is copied to the plugins directory in the Eclipse installation directory. 2.

to facilitate the MapReduce direct access to the relational database (mysql,oracle). Hadoop offers two classes of Dbinputformat and Dboutputformat. Through the Dbinputformat class, the database table data is read into HDFs, and the result set generated by MapReduce is imported into the database table according to the Dboutputformat class.error when executing

(Firstpartitioner.class);//partition functionJob.setsortcomparatorclass (Keycomparator.class);//This course does not have custom sortcomparator, but instead uses Intpair's own sortJob.setgroupingcomparatorclass (Groupingcomparator.class);//Group functionJob.setmapoutputkeyclass (Intpair.class);Job.setmapoutputvalueclass (Intwritable.class);Job.setoutputkeyclass (Text.class);Job.setoutputvalueclass (Intwritable.class);Job.setinputformatclass (Textinputformat.class);Job.setoutputformatclass (Text

In the development of the Mr Program of Hadoop, it is often necessary to statistic some Map/reduce's running state information, which can be implemented by custom counter, which is done by the Code runtime check instead of the configuration information.1. Create a Counter enumeration class of your own.enum Process_counter { bad_records, bad_groups;}2, in need of statistics, such as map or reduce phase

Reference: http://blog.csdn.net/zklth/article/details/11829563Hadoop processing GBK text, found that the output is garbled, the original Hadoop is involved in encoding is written dead UTF-8, if the file encoding format is other types (such as GBK), it will appear garbled.When you simply read the text in the Mapper or reducer program, use TransformTextToUTF8 (text, "GBK"), and transcode to ensure that it is

file size does not exceed 1.1 times times the Shard size, it will be divided into a shard, avoid opening two map, one of the running data is too small, wasting resources.Summary, the Shard process is about, first traverse the target file, filter some non-conforming files, and then add to the list, and then follow the file name to slice the Shard (the size of the previous calculation of the size of the formula, the end of a file may be merged, in fact, often

operations, and the default ones are not used. Define KeyPair The custom output type is run by putting the map's output into reduce, so you need to implement the Writablecomparable interface of Hadoop, and the template variable for that interface is KeyPair, It's like longwritable a meaning (see longwritable's definition to know) To implement the Writablecomparable interface, you must override the Write/re

= serverSocket. accept (); // Construct a data input stream to receive data DataInputStream in = new DataInputStream (soc. getInputStream ()); // Construct a data output stream to send data DataOutputStream out = new DataOutputStream (soc. getOutputStream ()); // Disconnect Soc. close () Client Process // Create a client Socket Socket soc = new Socket (serverHost, port ); // Construct a data input stream to receive data DataInputStream in = new DataInputStream (soc. ge

Using python to write MapReduce functions -- Taking WordCount as an ExampleAlthough the Hadoop framework is written in java, the Hadoop program is not limited to java, but can be used in python, C ++, ruby, and so on. In this example, wr