Introduction To Hadoop

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1 Introduction To Hadoop Kenneth Heafield Google Inc January 14, 2008 Example code from Hadoop used under the Apache License Version 2.0 and modified for presentation. Except as otherwise noted, the content of this presentation is licensed under the Creative Commons Attribution 2.5 License. Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

2 Outline 1 Mapper Reducer Main 2 How it Works Serialization Data Flow 3 Lab Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

3 Mapper Mapper < wikipedia.org, The Free > < The, 1 >, < Free, 1 > public void map(writablecomparable key, Writable value, OutputCollector output, Reporter reporter) throws IOException { String line = ((Text)value).toString(); StringTokenizer itr = new StringTokenizer(line); Text word = new Text(); while (itr.hasmoretokens()) { word.set(itr.nexttoken()); output.collect(word, new IntWritable(1)); Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

4 Mapper Mapper < wikipedia.org, The Free > < The, 1 >, < Free, 1 > public void map(writablecomparable key, Writable value, OutputCollector output, Reporter reporter) throws IOException { String line = ((Text)value).toString(); StringTokenizer itr = new StringTokenizer(line); Text word = new Text(); while (itr.hasmoretokens()) { word.set(itr.nexttoken()); output.collect(word, new IntWritable(1)); Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

5 Mapper Mapper < wikipedia.org, The Free > < The, 1 >, < Free, 1 > public void map(writablecomparable key, Writable value, OutputCollector output, Reporter reporter) throws IOException { String line = ((Text)value).toString(); StringTokenizer itr = new StringTokenizer(line); Text word = new Text(); while (itr.hasmoretokens()) { word.set(itr.nexttoken()); output.collect(word, new IntWritable(1)); Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

6 Mapper Mapper < wikipedia.org, The Free > < The, 1 >, < Free, 1 > public void map(writablecomparable key, Writable value, OutputCollector output, Reporter reporter) throws IOException { String line = ((Text)value).toString(); StringTokenizer itr = new StringTokenizer(line); Text word = new Text(); while (itr.hasmoretokens()) { word.set(itr.nexttoken()); output.collect(word, new IntWritable(1)); Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

7 Mapper Mapper < wikipedia.org, The Free > < The, 1 >, < Free, 1 > public void map(writablecomparable key, Writable value, OutputCollector output, Reporter reporter) throws IOException { String line = ((Text)value).toString(); StringTokenizer itr = new StringTokenizer(line); Text word = new Text(); while (itr.hasmoretokens()) { word.set(itr.nexttoken()); output.collect(word, new IntWritable(1)); Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

8 Reducer Reducer < The, 1 >, < The, 1 > < The, 2 > public void reduce(writablecomparable key, Iterator values, OutputCollector output, Reporter reporter) throws IOException { int sum = 0; while (values.hasnext()) { sum += ((IntWritable) values.next()).get(); output.collect(key, new IntWritable(sum)); Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

9 Reducer Reducer < The, 1 >, < The, 1 > < The, 2 > public void reduce(writablecomparable key, Iterator values, OutputCollector output, Reporter reporter) throws IOException { int sum = 0; while (values.hasnext()) { sum += ((IntWritable) values.next()).get(); output.collect(key, new IntWritable(sum)); Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

10 Reducer Reducer < The, 1 >, < The, 1 > < The, 2 > public void reduce(writablecomparable key, Iterator values, OutputCollector output, Reporter reporter) throws IOException { int sum = 0; while (values.hasnext()) { sum += ((IntWritable) values.next()).get(); output.collect(key, new IntWritable(sum)); Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

11 Reducer Reducer < The, 1 >, < The, 1 > < The, 2 > public void reduce(writablecomparable key, Iterator values, OutputCollector output, Reporter reporter) throws IOException { int sum = 0; while (values.hasnext()) { sum += ((IntWritable) values.next()).get(); output.collect(key, new IntWritable(sum)); Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

12 Main Main public static void main(string[] args) throws IOException { JobConf conf = new JobConf(WordCount.class); conf.setjobname("wordcount"); conf.setmapperclass(mapclass.class); conf.setcombinerclass(reduceclass.class); conf.setreducerclass(reduceclass.class); conf.setnummaptasks(new Integer(40)); conf.setnumreducetasks(new Integer(30)); conf.setinputpath(new Path("/shared/wikipedia_small")); conf.setoutputpath(new Path("/user/kheafield/word_count")); conf.setoutputkeyclass(text.class); conf.setoutputvalueclass(intwritable.class); JobClient.runJob(conf); Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

13 Main Main public static void main(string[] args) throws IOException { JobConf conf = new JobConf(WordCount.class); conf.setjobname("wordcount"); conf.setmapperclass(mapclass.class); conf.setcombinerclass(reduceclass.class); conf.setreducerclass(reduceclass.class); conf.setnummaptasks(new Integer(40)); conf.setnumreducetasks(new Integer(30)); conf.setinputpath(new Path("/shared/wikipedia_small")); conf.setoutputpath(new Path("/user/kheafield/word_count")); conf.setoutputkeyclass(text.class); conf.setoutputvalueclass(intwritable.class); JobClient.runJob(conf); Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

14 Main Main public static void main(string[] args) throws IOException { JobConf conf = new JobConf(WordCount.class); conf.setjobname("wordcount"); conf.setmapperclass(mapclass.class); conf.setcombinerclass(reduceclass.class); conf.setreducerclass(reduceclass.class); conf.setnummaptasks(new Integer(40)); conf.setnumreducetasks(new Integer(30)); conf.setinputpath(new Path("/shared/wikipedia_small")); conf.setoutputpath(new Path("/user/kheafield/word_count")); conf.setoutputkeyclass(text.class); conf.setoutputvalueclass(intwritable.class); JobClient.runJob(conf); Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

15 Main Main public static void main(string[] args) throws IOException { JobConf conf = new JobConf(WordCount.class); conf.setjobname("wordcount"); conf.setmapperclass(mapclass.class); conf.setcombinerclass(reduceclass.class); conf.setreducerclass(reduceclass.class); conf.setnummaptasks(new Integer(40)); conf.setnumreducetasks(new Integer(30)); conf.setinputpath(new Path("/shared/wikipedia_small")); conf.setoutputpath(new Path("/user/kheafield/word_count")); conf.setoutputkeyclass(text.class); conf.setoutputvalueclass(intwritable.class); JobClient.runJob(conf); Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

16 How it Works Serialization Types Purpose Simple serialization for keys, values, and other data Interface Writable Read and write binary format Convert to String for text formats WritableComparable adds sorting order for keys Example Implementations ArrayWritable is only Writable BooleanWritable IntWritable sorts in increasing order Text holds a String Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

17 public class IntPairWritable implements Writable { public int first; public int second; public void write(dataoutput out) throws IOException { out.writeint(first); out.writeint(second); public void readfields(datainput in) throws IOException { first = in.readint(); second = in.readint(); public int hashcode() { return first + second; public String tostring() { return Integer.toString(first) + "," + Integer.toString(second); Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12 A Writable How it Works Serialization

18 How it Works WritableComparable Method Serialization public int compareto(object other) { IntPairWritable o = (IntPairWritable)other; if (first < o.first) return -1; if (first > o.first) return 1; if (second < o.second) return -1; if (second > o.second) return 1; return 0; Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

19 How it Works Data Flow Data Flow Default Flow 1 Mappers read from HDFS 2 Map output is partitioned by key and sent to Reducers 3 Reducers sort input by key 4 Reduce output is written to HDFS 1 HDFS 2 Mapper 3 Reducer 4 HDFS Input Map Sort Reduce Output Input Map Sort Reduce Output Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

20 How it Works Data Flow Combiners Concept Add counts at Mapper before sending to Reducer. Word count is 6 minutes with combiners and 14 without. Implementation Mapper caches output and periodically calls Combiner Input to Combine may be from Map or Combine Combiner uses interface as Reducer Mapper Combine Sort Reduce Output Input Map Cache Sort Reduce Output Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

21 Lab Exercises Recommended: Word Count Get word count running. Bigrams Count bigrams and unigrams efficiently. Capitalization With what probability is a word capitalized? Indexer In what documents does each word appear? Where in the documents? Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

22 Instructions Lab 1 Login to the cluster successfully (and set your password). 2 Get Eclipse installed, so you can build Java code. 3 Install the Hadoop plugin for Eclipse so you can deploy jobs to the cluster. 4 Set up your Eclipse workspace from a template that we provide. 5 Run the word counter example over the Wikipedia data set. Kenneth Heafield (Google Inc) Introduction To Hadoop January 14, / 12

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