Impressions on Cloudera Impala

Today I attended a meet up arranged by the Chicago Big Data meet up at 6pm titled "Cloudera Impala". We were fortunate to have Marcel Kornacker, Lead Architect of Cloudera Impala as the presenter.  Marcel must have been pleasantly surprised to experience 70 Degree Fahrenheit weather in Chicago in December. It was one of those beautiful days, courtesy "Global Warming".

Speaker Impressions:-

My first impressions on Marcel were as follows:  he was unlike those speakers who do the pre-talk theatrics such as going around the room shaking hands or speaking loudly.  He was moving quietly (closer to the presentation area) or having silent conversations. So I deduced him to be a geeky dude, who does not seek conversations in the presentation room. So I thought it probably is not a marketing/technical evangelist person who will be shallow on the technical details of the presentation.

The other concern was whether he had an European accent that may be difficult to grasp, if he was too geeky.  Marcel started speaking.  As they say, do not judge a book by its cover, he drove away the accent issue and gave me the feeling that I will at least be able to hear what he is going to say. He speaks well and convincingly well on a topic where he is the subject matter expert.

Jonathan Seidman, organizer of the Chicago Big Data group, introduced Marcel as an ex-googler who has worked on the F1 database project in the past. I did not know what F1 was at Google. It sounded like important.  That was a good introduction to set the stage for Marcel. If he was employed at Google in a core database tech field. he should definitely know things well. As a presenter, Marcel did a good job discussing the objectives, intricacies, target areas and limitations of Impala. Kudos!

Impala Impressions :-

Let me get back to Impala. Marcel said that the code was written in C++. Bummer. As you know, Hadoop ecosystem is primarily Java (even though you have bits and pieces and tools that are non Java such as Hadoop Streaming). I guess Marcel knows C++ well. That is why he chose to write Impala in C++.  He mentioned that the interface of Impala for applications will be via ODBC. Ok, there is the first roadblock. I write Java code. Now if I want to be excited about Impala, I will need to look at some form of JDBC to ODBC bridge or wait for Marcel's team to code up some client utilities.  People tinkering with the Hadoop ecosystem may have the same questions/impressions as me.

While Hive exists for Java programmers to do SQL with Hadoop ecosystem, Marcel is trying to bring in C++ to the equation.  Here is the catch though.  Impala according to Marcel, performs 3 times better than Hive in certain situations. Wow, this can be a big thing.  But alas, we cannot use Impala via Java interfaces. So we are stuck with Hive (just remember Hives is bad allergy and not fun. :).  We are talking about Apache Hive), if we want to use SQL like interfaces into Hadoop.

I am sure there will be takers for Impala. I am not going to be doing any experimentation with it because I do not intend to a) use C++ or ODBC or b) use CDH4. My experiments are with Apache Hadoop community version and there are enough goodies to get excited about there. :)

Unlike Hive, Impala does not use Map Reduce underneath. It has Query Plans that get fragmented and distributed among the nodes in a cluster. There is a component that gathers the results of the plan execution. 

After the talk on my way back, I googled Marcel to learn more about him.  I hit on the following article that gives a very good background into Marcel.
http://www.wired.com/wiredenterprise/2012/10/kornacker-cloudera-google/
Basically Marcel is a details guy, with a PhD from Univ of Cal at Berkeley and is an excellent cook.

Cloudera Impala is in the hands of an excellent Chef.  Good Luck Marcel!

Other people such as http://java.sys-con.com/node/2461455 are getting excited about Impala.  Mention of "near real time" without the use of wind river or RTOS. :)

Market Basket Analysis : Importance

Market Basket Analysis according to Wikipedia is defined as follows:
"The term market basket analysis in the retail business refers to research that provides the retailer with information to understand the purchase behaviour of a buyer. This information will enable the retailer to understand the buyer's needs and rewrite the store's layout accordingly, develop cross-promotional programs, or even capture new buyers (much like the cross-selling concept)." 

It is very importance to understand the importance of Market Basket Analysis in the Big Data Arena. 

Questions such as:

• What products are typically bought together?
• How many quantities of products are bought together?

This probably looks simple to you. 

But if you recall Amazon generating recommendations such as : If you buy Book A (costing $25) and Book B(costing $15) together, you can for $35. Well, as a consumer you got a discount of $5.  But Amazon used MBA to determine which books go together based on customer purchases. Now they just increased their sales while losing $5 (if the books were bought separately).  Amazon would not have increased sales if they had arbitrarily clubbed two books together.  

Think along the following lines:

a) A person buying a pack of cigarettes is also probably going to buy a book of matches or a lighter.

b) A person buying a stapler is also probably going to buy staples.

c) A person buying a school bag is also probably going to buy books/pens/pencils.

Even though a), b) and c) are common sense - MBA can help retailers figure this out through processing Point Of Sale (POS) transactional data. 

How is this relevant to Big Data?

Well, POS transactional data is not small in quantity for a typical retailer. There are hundreds and thousands of transactions that they have to analyze.

Apache Hadoop Security

Apache Hadoop is synonymous with Big Data. Majority of Big Data processing happens via the Hadoop ecosystem. If you have a Big Data project, chances of you using elements of the Hadoop ecosystem is very huge.

One of the biggest challenges with the Hadoop ecosystem is security. The Map/Reduce processing framework in Hadoop does not really have major security support. HDFS uses the Unix file system model security. The HDFS security model may work perfectly for storing data in a distributed file system.

Kerberos based authentication is used as the primary security mechanism in the Hadoop Map/Reduce framework. But there is no real data confidentiality/privacy mechanisms in supported.

Data can be in motion (passing through programs) or network elements. Data can be at rest in data stores. The HDFS security controls seem to be adequate for data at rest.  But for data that is being processed via the Map/Reduce mechanism, it is up to the developers/programmers to utilize encryption mechanisms.

If you need guidance, please do email me at anil  AT  apache  DOT org.  I will be happy to suggest approaches to achieve Big Data Security.

Hadoop By White, Tom (Google Affiliate Ad)Hadoop in Action By Lam, Chuck (Google Affiliate Ad)

R: Introduction to statistics and R-Studio

This post will describe some of the common operations of the R statistical package.

Assuming you have installed R on your linux machine.

Step 1: Create a work directory.

 $ mkdir R_Work

$ cd R_Work/

Step 2: Let us invoke "R".

$ R

R version 2.15.1 (2012-06-22) -- "Roasted Marshmallows"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: x86_64-redhat-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

  Natural language support but running in an English locale

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> q()


Basically to quit R, you need to type in q()

Step 3:  Install R-Studio for your Operating System

http://www.rstudio.org/

$>rstudio

Step 4:  Install rJava

It is very important that you get the following command right.

Run as Root

 # sudo R CMD javareconf JAVA=/usr/lib/jvm/java-1.6.0-openjdk-1.6.0.0.x86_64/jre/bin/java JAVA_HOME=/usr/java/latest JAVAC=/usr/java/latest/bin/javac JAR=/usr/java/latest/bin/jar JAVAH=/usr/java/latest/bin/javah

In this case, we are trying to tell R where the OpenJDK java executable is.  You also want to point to locations where your javac, javah and jar executables are available.

Now we are ready to install rJava

# R

> install.packages("rJava")
Installing package(s) into ‘/usr/lib64/R/library’
(as ‘lib’ is unspecified)
--- Please select a CRAN mirror for use in this session ---
Loading Tcl/Tk interface ... done
.....

* DONE (rJava)
Making packages.html  ... done

The downloaded source packages are in
    ‘/tmp/RtmpwsCz85/downloaded_packages’
Updating HTML index of packages in '.Library'
Making packages.html  ... done
>

This was very painful for me. Took me about 20mins to get it right.

By the way, there is a thread that may be useful to you: 

http://r.789695.n4.nabble.com/rjava-JDK-not-found-td889163.html

Error I was getting was:

Make sure R is configured with full Java support (including JDK). Run
R CMD javareconf
as root to add Java support to R. 

Reference

http://cran.r-project.org/doc/manuals/R-intro.html

http://svn.r-project.org/R/trunk/src/scripts/javareconf

Installing R statistical package on Fedora

If you are operating on Fedora (or any other flavors of Linux), chances are that there is availability of pre-built package of R.

On Fedora 16, I did
$> sudo yum info R
Installed Packages
Name        : R
Arch        : x86_64
Version     : 2.15.1
Release     : 1.fc16
Size        : 0.0 
Repo        : installed
From repo   : updates
Summary     : A language for data analysis and graphics
URL         : http://www.r-project.org
License     : GPLv2+
Description : This is a metapackage that provides both core R userspace and
            : all R development components.
            :
            : R is a language and environment for statistical computing and
            : graphics. R is similar to the award-winning S system, which was
            : developed at Bell Laboratories by John Chambers et al. It provides
            : a wide variety of statistical and graphical techniques (linear and
            : nonlinear modelling, statistical tests, time series analysis,
            : classification, clustering, ...).
            :
            : R is designed as a true computer language with control-flow
            : constructions for iteration and alternation, and it allows users
            : to add additional functionality by defining new functions. For
            : computationally intensive tasks, C, C++ and Fortran code can be
            : linked and called at run time.

To install R on fedora,
$> sudo yum install R

Now that you have installed R,  go read up on it at http://cran.r-project.org/doc/manuals/R-intro.html

Embedding Pig Scripts in Java Applications

You are familiar with running pig scripts via the command line. Now what if you intend to run Apache Pig as part of your Java applications?

Pig Modes

There are two modes as shown in http://pig.apache.org/docs/r0.7.0/setup.html#Run+Modes

PigServer

This is the main class for embedding Apache Pig as part of your java applications.


import org.apache.pig.PigServer;

=================
 PigServer pigServer = null;
String mode = "local";
 String pigScriptName = null;

Map<String,String> params = null;

List<String> paramFiles = null;

        try {
            pigServer = new PigServer(mode);
            pigServer.setBatchOn();
            pigServer.debugOn();
            InputStream is = getClass().getClassLoader().getResourceAsStream(pigScriptName);
            if(params != null){
                pigServer.registerScript(is, params);
            } else if(paramFiles != null){
                pigServer.registerScript(is, paramFiles);
            } else {
                pigServer.registerScript(is);
            }
            pigServer.executeBatch();
        } catch (Exception e) {
            throw new RuntimeException(e);
        } finally {
            if(pigServer != null){
                pigServer.shutdown();
            }
        }
==========================
Note: the variable mode can be "local" or "mapreduce".

PigServer can take two additional parameters while registering your pig script.

• Params: this is a key/value map passed that can be referenced in your pigscript as $key.
• ParamFiles: takes in filenames that contain the parameters.

You can register the script with the PigServer without providing any params.

Do not forget to bookmark this blog. :)

All the best!

Reference: http://everythingbigdata.blogspot.com/2012/07/apache-pig-tips.html

Hadoop with Drools, Infinispan, PicketLink etc

Here are the slides that I used at JUDCON 2012 in Boston.
http://www.jboss.org/dms/judcon/2012boston/presentations/judcon2012boston_day1track3session2.pdf

In your Map/Reduce programs, you should be able to use any Java library of your choice.  In this regard, you should be able to use:

• Infinispan Data Grids to send cache events from your Map Reduce programs.
• Drools rules engine to apply rules in your M/R programs.
• PicketLink can be used for bringing in security aspects to your M/R programs.

Apache Pig Tips

1) If you want to remove the directory where you are going to perform a STORE operation, then it is better to remove it first.

rmf output/somedir
STORE xyz INTO output/somedir USING PIGSTORAGE()

2) How do I use Pig via Java?
Look at the PigServer usage.

Apache Hadoop Map Reduce - Advanced Example

Map Reduce Example

Latest updated proper work is at http://blog.hampisoftware.com/?p=20

Solve the same problem using Apache Spark: http://blog.hampisoftware.com/?p=41


Use ^^^^

DATED MATERIAL

Continuing with my experiments, now I tried to attempt the Patent Citation Example mentioned in the book "Hadoop In Action" by Chuck Lam.

Data Set

Visit http://nber.org/patents/
Choose acite75_99.zip  and it yielded cite75_99.txt

This file lists the patent number that cites another patent.  In this map reduce example, we are going to attempt to find the reverse.

For a given patent, how many citations exist.

What do you need?

Download Hadoop v1.0.3 from http://hadoop.apache.org
I downloaded hadoop-1.0.3.tar.gz (60MB)

Map Reduce Program

Note: I give out a program that was busted.  Look for commentary following this program as to why it is busted etc. Finally, I give out a working program.

==================
package mapreduce;

import java.io.File;
import java.io.FileNotFoundException;
import java.io.IOException;
import java.util.Iterator;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.KeyValueTextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

public class PatentCitation extends Configured implements Tool{

    public static class PatentCitationMapper extends Mapper<Text,Text,Text,Text> {
        protected void map(Text key, Text value, Context context)
                throws IOException, InterruptedException {
            context.write(value, key);
        }
    }
   
    public static class PatentCitationReducer extends Reducer<Text,Text,Text,Text>{
        protected void reduce(Text key, Iterable<Text> values, Context context)
                throws IOException, InterruptedException {
            String csv = "";
            Iterator<Text> iterator = values.iterator();
            while(iterator.hasNext()){
                if(csv.length() > 0 ) csv += ",";
                csv += iterator.next().toString();
            }
            context.write(key, new Text(csv));
        }
    }
   
    private  void deleteFilesInDirectory(File f) throws IOException {
        if (f.isDirectory()) {
            for (File c : f.listFiles())
                deleteFilesInDirectory(c);
        }
        if (!f.delete())
            throw new FileNotFoundException("Failed to delete file: " + f);
    }
   
    @Override
    public int run(String[] args) throws Exception {
        if(args.length == 0)
            throw new IllegalArgumentException("Please provide input and output paths");
       
        Path inputPath = new Path(args[0]);
        File outputDir = new File(args[1]);
        deleteFilesInDirectory(outputDir);
        Path outputPath = new Path(args[1]);

        Job job = new Job(getConf(), "Hadoop Patent Citation Example");
        job.setJarByClass(PatentCitation.class);

        FileInputFormat.setInputPaths(job, inputPath);
        FileOutputFormat.setOutputPath(job, outputPath);

        job.setInputFormatClass(KeyValueTextInputFormat.class);
        job.setOutputFormatClass(TextOutputFormat.class);
       
        job.setMapperClass(PatentCitationMapper.class);
        job.setReducerClass(PatentCitationReducer.class);
       
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(Text.class);

        return job.waitForCompletion(false) ? 0 : -1;
    }

    public static void main(String[] args) throws Exception {
        System.exit(ToolRunner.run(new Configuration(), new PatentCitation(), args));
    }
}


I created a directory called "input" where the cite75_99.txt was placed.  I also created an empty directory called "output".  These directories form the input and output directories for the M/R program

Execution

First Attempt:

I executed the program as is. It choked because my /tmp directory and root filesystem exhausted the disk space.

Second Attempt:

Now I exclusively configure the hadoop tmp directory so I can place the tmp files wherever I want.
-Dhadoop.tmp.dir=/home/anil/judcon12/tmp

Ok, now the program did not choke.  It just ran and ran for 2+ hours. I killed it. It seems the data set is too large to get it finished in a short duration.
The culprit was the reduce phase. It just did not finish.

Third Attempt:

Now I tried to configure the reducers to zero so I can view the output of the map phase.

I tried the property -Dmapred.reduce.tasks=0.  It made no difference.

I then added the following deprecated usage of the Job class. That worked.

        job.setNumReduceTasks(0);

Ok, now the program just undertook the map phase.

=======================
May 25, 2012 4:40:42 PM org.apache.hadoop.util.NativeCodeLoader <clinit>
WARNING: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
May 25, 2012 4:40:42 PM org.apache.hadoop.mapred.JobClient copyAndConfigureFiles
WARNING: No job jar file set.  User classes may not be found. See JobConf(Class) or JobConf#setJar(String).
May 25, 2012 4:40:42 PM org.apache.hadoop.mapreduce.lib.input.FileInputFormat listStatus
INFO: Total input paths to process : 1
May 25, 2012 4:40:42 PM org.apache.hadoop.io.compress.snappy.LoadSnappy <clinit>
WARNING: Snappy native library not loaded
May 25, 2012 4:40:42 PM org.apache.hadoop.util.ProcessTree isSetsidSupported
INFO: setsid exited with exit code 0
May 25, 2012 4:40:42 PM org.apache.hadoop.mapred.Task initialize
INFO:  Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@420f9c40
May 25, 2012 4:40:44 PM org.apache.hadoop.mapred.Task done
INFO: Task:attempt_local_0001_m_000000_0 is done. And is in the process of commiting
May 25, 2012 4:40:44 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 4:40:44 PM org.apache.hadoop.mapred.Task commit
INFO: Task attempt_local_0001_m_000000_0 is allowed to commit now
May 25, 2012 4:40:44 PM org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
INFO: Saved output of task 'attempt_local_0001_m_000000_0' to /home/anil/judcon12/output
May 25, 2012 4:40:45 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 4:40:45 PM org.apache.hadoop.mapred.Task sendDone
INFO: Task 'attempt_local_0001_m_000000_0' done.
May 25, 2012 4:40:45 PM org.apache.hadoop.mapred.Task initialize
INFO:  Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@527736bd
May 25, 2012 4:40:46 PM org.apache.hadoop.mapred.Task done
INFO: Task:attempt_local_0001_m_000001_0 is done. And is in the process of commiting
May 25, 2012 4:40:46 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 4:40:46 PM org.apache.hadoop.mapred.Task commit
INFO: Task attempt_local_0001_m_000001_0 is allowed to commit now
May 25, 2012 4:40:46 PM org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
INFO: Saved output of task 'attempt_local_0001_m_000001_0' to /home/anil/judcon12/output
May 25, 2012 4:40:48 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 4:40:48 PM org.apache.hadoop.mapred.Task sendDone
INFO: Task 'attempt_local_0001_m_000001_0' done.
May 25, 2012 4:40:48 PM org.apache.hadoop.mapred.Task initialize
INFO:  Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@5749b290
May 25, 2012 4:40:49 PM org.apache.hadoop.mapred.Task done
INFO: Task:attempt_local_0001_m_000002_0 is done. And is in the process of commiting
May 25, 2012 4:40:49 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 4:40:49 PM org.apache.hadoop.mapred.Task commit
INFO: Task attempt_local_0001_m_000002_0 is allowed to commit now
May 25, 2012 4:40:49 PM org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
INFO: Saved output of task 'attempt_local_0001_m_000002_0' to /home/anil/judcon12/output
May 25, 2012 4:40:51 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 4:40:51 PM org.apache.hadoop.mapred.Task sendDone
INFO: Task 'attempt_local_0001_m_000002_0' done.
May 25, 2012 4:40:51 PM org.apache.hadoop.mapred.Task initialize
INFO:  Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@2a8ceeea
May 25, 2012 4:40:52 PM org.apache.hadoop.mapred.Task done
INFO: Task:attempt_local_0001_m_000003_0 is done. And is in the process of commiting
May 25, 2012 4:40:52 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 4:40:52 PM org.apache.hadoop.mapred.Task commit
INFO: Task attempt_local_0001_m_000003_0 is allowed to commit now
May 25, 2012 4:40:52 PM org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
INFO: Saved output of task 'attempt_local_0001_m_000003_0' to /home/anil/judcon12/output
May 25, 2012 4:40:54 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 4:40:54 PM org.apache.hadoop.mapred.Task sendDone
INFO: Task 'attempt_local_0001_m_000003_0' done.
May 25, 2012 4:40:54 PM org.apache.hadoop.mapred.Task initialize
INFO:  Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@46238a47
May 25, 2012 4:40:55 PM org.apache.hadoop.mapred.Task done
INFO: Task:attempt_local_0001_m_000004_0 is done. And is in the process of commiting
May 25, 2012 4:40:55 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 4:40:55 PM org.apache.hadoop.mapred.Task commit
INFO: Task attempt_local_0001_m_000004_0 is allowed to commit now
May 25, 2012 4:40:55 PM org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
INFO: Saved output of task 'attempt_local_0001_m_000004_0' to /home/anil/judcon12/output
May 25, 2012 4:40:57 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 4:40:57 PM org.apache.hadoop.mapred.Task sendDone
INFO: Task 'attempt_local_0001_m_000004_0' done.
May 25, 2012 4:40:57 PM org.apache.hadoop.mapred.Task initialize
INFO:  Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@559113f8
May 25, 2012 4:40:58 PM org.apache.hadoop.mapred.Task done
INFO: Task:attempt_local_0001_m_000005_0 is done. And is in the process of commiting
May 25, 2012 4:40:58 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 4:40:58 PM org.apache.hadoop.mapred.Task commit
INFO: Task attempt_local_0001_m_000005_0 is allowed to commit now
May 25, 2012 4:40:58 PM org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
INFO: Saved output of task 'attempt_local_0001_m_000005_0' to /home/anil/judcon12/output
May 25, 2012 4:41:00 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 4:41:00 PM org.apache.hadoop.mapred.Task sendDone
INFO: Task 'attempt_local_0001_m_000005_0' done.
May 25, 2012 4:41:00 PM org.apache.hadoop.mapred.Task initialize
INFO:  Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@76a9b9c
May 25, 2012 4:41:01 PM org.apache.hadoop.mapred.Task done
INFO: Task:attempt_local_0001_m_000006_0 is done. And is in the process of commiting
May 25, 2012 4:41:01 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 4:41:01 PM org.apache.hadoop.mapred.Task commit
INFO: Task attempt_local_0001_m_000006_0 is allowed to commit now
May 25, 2012 4:41:01 PM org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
INFO: Saved output of task 'attempt_local_0001_m_000006_0' to /home/anil/judcon12/output
May 25, 2012 4:41:03 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 4:41:03 PM org.apache.hadoop.mapred.Task sendDone
INFO: Task 'attempt_local_0001_m_000006_0' done.
May 25, 2012 4:41:03 PM org.apache.hadoop.mapred.Task initialize
INFO:  Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@560c3014
May 25, 2012 4:41:04 PM org.apache.hadoop.mapred.Task done
INFO: Task:attempt_local_0001_m_000007_0 is done. And is in the process of commiting
May 25, 2012 4:41:04 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 4:41:04 PM org.apache.hadoop.mapred.Task commit
INFO: Task attempt_local_0001_m_000007_0 is allowed to commit now
May 25, 2012 4:41:04 PM org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
INFO: Saved output of task 'attempt_local_0001_m_000007_0' to /home/anil/judcon12/output
May 25, 2012 4:41:06 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 4:41:06 PM org.apache.hadoop.mapred.Task sendDone
INFO: Task 'attempt_local_0001_m_000007_0' done.
=======================

So the Map phase is taking between 1-2mins.  It is the reduce phase that does not end for me.  I will evaluate as to why that is the case. :)

Let us see what the output of the map phase looks like:

=============================
anil@sadbhav:~/judcon12/output$ ls
part-m-00000  part-m-00002  part-m-00004  part-m-00006  _SUCCESS
part-m-00001  part-m-00003  part-m-00005  part-m-00007
==============================

You can see the end result of the map phase in these files.

Now onto figuring out the number of reduce phases.

Let me look at the file size

===================
 anil@sadbhav:~/judcon12/input$ wc -l cite75_99.txt
16522439 cite75_99.txt
===================

OMG!  that is something like 16 million 522 thousand entries.  Too much for a laptop to handle.

Let us try another experiment.  Let us choose 20000 patent citations from this file and save it to 20000cite.txt

When I run the program now,  I see that the M/R execution took all of 10 secs to finish.

Let us view the results of the M/R execution.

=============================
anil@sadbhav:~/judcon12/output$ ls
part-r-00000  _SUCCESS
============================

When I look inside the part-r-00000 ,  I see one long line of csv patent citations.  Yeah, you are right.  My reducer is busted.  It is not working.  I need to fix it.....
That is next step....  This exercise was a failure. But there was a lesson here.  If you mess up, you will wait. :)




Ok,  here is the updated map reduce program that works:
======================
package mapreduce;

import java.io.File;
import java.io.FileNotFoundException;
import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.KeyValueTextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

public class PatentCitation extends Configured implements Tool{

    public static class PatentCitationMapper extends Mapper<Text,Text,Text,Text> {
        protected void map(Text key, Text value, Context context)
                throws IOException, InterruptedException {

            String[] citation = key.toString().split(",");
            context.write(new Text(citation[1]), new Text(citation[0]));
        }
    }

    public static class PatentCitationReducer extends Reducer<Text,Text,Text,Text>{
        protected void reduce(Text key, Iterable<Text> values, Context context)
                throws IOException, InterruptedException {
            String csv = "";
            for(Text val:values){
                if(csv.length() > 0 ) csv += ",";
                csv += val.toString();
            }
            context.write(key, new Text(csv));
        }
    }

    private  void deleteFilesInDirectory(File f) throws IOException {
        if (f.isDirectory()) {
            for (File c : f.listFiles())
                deleteFilesInDirectory(c);
        }
        if (!f.delete())
            throw new FileNotFoundException("Failed to delete file: " + f);
    }

    @Override
    public int run(String[] args) throws Exception {
        if(args.length == 0)
            throw new IllegalArgumentException("Please provide input and output paths");

        Path inputPath = new Path(args[0]);
        File outputDir = new File(args[1]);
        deleteFilesInDirectory(outputDir);
        Path outputPath = new Path(args[1]);

        Job job = new Job(getConf(), "Hadoop Patent Citation Example");
        job.setJarByClass(PatentCitation.class);

        FileInputFormat.setInputPaths(job, inputPath);
        FileOutputFormat.setOutputPath(job, outputPath);

        job.setInputFormatClass(KeyValueTextInputFormat.class);
        job.setOutputFormatClass(TextOutputFormat.class);

        job.setMapperClass(PatentCitationMapper.class);
        job.setReducerClass(PatentCitationReducer.class);

        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(Text.class);

        //job.setNumReduceTasks(10000);

        return job.waitForCompletion(false) ? 0 : -1;
    }

    public static void main(String[] args) throws Exception {
        System.exit(ToolRunner.run(new Configuration(), new PatentCitation(), args));
    }
}
=======================================

Running updated program

================================
May 25, 2012 6:14:26 PM org.apache.hadoop.util.NativeCodeLoader <clinit>
WARNING: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
May 25, 2012 6:14:26 PM org.apache.hadoop.mapred.JobClient copyAndConfigureFiles
WARNING: No job jar file set.  User classes may not be found. See JobConf(Class) or JobConf#setJar(String).
May 25, 2012 6:14:26 PM org.apache.hadoop.mapreduce.lib.input.FileInputFormat listStatus
INFO: Total input paths to process : 1
May 25, 2012 6:14:26 PM org.apache.hadoop.io.compress.snappy.LoadSnappy <clinit>
WARNING: Snappy native library not loaded
May 25, 2012 6:14:27 PM org.apache.hadoop.util.ProcessTree isSetsidSupported
INFO: setsid exited with exit code 0
May 25, 2012 6:14:27 PM org.apache.hadoop.mapred.Task initialize
INFO:  Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@420f9c40
May 25, 2012 6:14:27 PM org.apache.hadoop.mapred.MapTask$MapOutputBuffer <init>
INFO: io.sort.mb = 100
May 25, 2012 6:14:27 PM org.apache.hadoop.mapred.MapTask$MapOutputBuffer <init>
INFO: data buffer = 79691776/99614720
May 25, 2012 6:14:27 PM org.apache.hadoop.mapred.MapTask$MapOutputBuffer <init>
INFO: record buffer = 262144/327680
May 25, 2012 6:14:27 PM org.apache.hadoop.mapred.MapTask$MapOutputBuffer flush
INFO: Starting flush of map output
May 25, 2012 6:14:27 PM org.apache.hadoop.mapred.MapTask$MapOutputBuffer sortAndSpill
INFO: Finished spill 0
May 25, 2012 6:14:27 PM org.apache.hadoop.mapred.Task done
INFO: Task:attempt_local_0001_m_000000_0 is done. And is in the process of commiting
May 25, 2012 6:14:30 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 6:14:30 PM org.apache.hadoop.mapred.Task sendDone
INFO: Task 'attempt_local_0001_m_000000_0' done.
May 25, 2012 6:14:30 PM org.apache.hadoop.mapred.Task initialize
INFO:  Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@3a56860b
May 25, 2012 6:14:30 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 6:14:30 PM org.apache.hadoop.mapred.Merger$MergeQueue merge
INFO: Merging 1 sorted segments
May 25, 2012 6:14:30 PM org.apache.hadoop.mapred.Merger$MergeQueue merge
INFO: Down to the last merge-pass, with 1 segments left of total size: 359270 bytes
May 25, 2012 6:14:30 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 6:14:30 PM org.apache.hadoop.mapred.Task done
INFO: Task:attempt_local_0001_r_000000_0 is done. And is in the process of commiting
May 25, 2012 6:14:30 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO:
May 25, 2012 6:14:30 PM org.apache.hadoop.mapred.Task commit
INFO: Task attempt_local_0001_r_000000_0 is allowed to commit now
May 25, 2012 6:14:30 PM org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter commitTask
INFO: Saved output of task 'attempt_local_0001_r_000000_0' to /home/anil/judcon12/output
May 25, 2012 6:14:33 PM org.apache.hadoop.mapred.LocalJobRunner$Job statusUpdate
INFO: reduce > reduce
May 25, 2012 6:14:33 PM org.apache.hadoop.mapred.Task sendDone
INFO: Task 'attempt_local_0001_r_000000_0' done.
=================================


Let us look at the output:
===============
anil@sadbhav:~/judcon12/output$ ls
part-r-00000  _SUCCESS
================

If you look inside the part-xxx file, you will the results:

======================
 "CITED" "CITING"
1000715 3861270
1001069 3858600
1001170 3861317
1001597 3861811
1004288 3861154
1006393 3861066
1006952 3860293
.......
1429311 3861187
1429835 3860154
1429968 3860060
1430491 3859976
1431444 3861601
1431718 3859022
1432243 3861774
1432467 3862478
1433649 3861223,3861222
1433923 3861232
1434088 3862293
1435134 3861526
1435144 3858398
....
======================


Woot!

Additional Information

If you see the following error, it means you have disk space issues.

org.apache.hadoop.util.DiskChecker$DiskErrorException: Could not find any valid local directory for output/spill0.out


How do I set my own tmp directory for Hadoop?
-Dhadoop.tmp.dir=
or
-Dmapred.local.dir=    (for map/reduce)

References

http://blog.hampisoftware.com

Pig: Deriving meaningful data from SSO logs

If you use CAS sso solution, then you can generate logs.  I have a text file called "CASLoginLog.txt"  This file is basically a snippet of login trail for 3 days in March. I have changed usernames and many things. So your file may look a bit different. :)

Step: Generate a CAS SSO Login Trail

===================================
Date    Action  Username        Service         Ticket
28.3.2012 2:28:01       SERVICE_TICKET_CREATED  user1   https://myurl   ST-13133--org-sso
28.3.2012 2:27:30       SERVICE_TICKET_CREATED  user2   https://myurl/url ST-13046--j-sso
28.3.2012 2:27:17       TICKET_GRANTING_TICKET_DESTROYED                        TGT-3380--j-sso
28.3.2012 2:27:17       SERVICE_TICKET_CREATED  user3   https://c/thread/197282?tstart=0        ST-13045-j-sso
28.3.2012 2:27:16       TICKET_GRANTING_TICKET_CREATED  firstlion               TGT-3567--j-sso
28.3.2012 2:26:30       SERVICE_TICKET_CREATED  user4   https://issues.j.org/secure/D.jspa      ST-13044--j-sso
27.3.2012 23:12:37      SERVICE_TICKET_CREATED  user2   https://c/thread/151832?start=15&tstart=0       ST-13048--j-sso
27.3.2012 22:51:51      SERVICE_TICKET_CREATED  user5   https://c/login.jspa    ST-13038--j-sso
27.3.2012 22:51:50      TICKET_GRANTING_TICKET_CREATED  user5           TGT-3527--j-sso
27.3.2012 22:51:49      TICKET_GRANTING_TICKET_CREATED  user5           TGT-3526--j-sso
26.3.2012 14:17:27      SERVICE_TICKET_CREATED  user1   https://c/message/725882?tstart=0       ST-11709--j-sso
26.3.2012 13:02:51      TICKET_GRANTING_TICKET_CREATED  user1           TGT-3223--j-sso
=======================================

So let us try to figure out, how many times in these 3 days, each user was provided a "SERVICE_TICKET_CREATED" action.

I am going to use Apache Pig to generate the output.

Step: Code a Pig Script

My pig script is called CASLog.pig

=====================================
file = LOAD 'CASLoginLog.txt' USING PigStorage(' ') AS (ticketDate: chararray,ticketTime: chararray,action: chararray,username: chararray,service: chararray,ticket: chararray);

trimmedfile = FOREACH file GENERATE TRIM(ticketDate) as ticketDate, TRIM(action) AS action, TRIM(username) AS username ,TRIM(ticket) AS ticket ;

selectedrows = FILTER trimmedfile BY action == 'SERVICE_TICKET_CREATED';

usersgroup = GROUP selectedrows BY username;

counts = FOREACH usersgroup GENERATE group AS username, COUNT(selectedrows) AS num_digits;

STORE counts INTO 'result' USING PigStorage('=');
==========================================

Step:  Execute Apache Pig

Now let me run Pig on this.

===========================================
$ sh ../pig-0.9.2/bin/pig -x local CASLog.pig

....
Input(s):
Successfully read records from: "file:///hadoop/pig/anilpig/CASLoginLog.txt"

Output(s):
Successfully stored records in: "file:///hadoop/pig/anilpig/result"

Job DAG:
job_local_0001


2012-03-30 16:56:09,762 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Success!
============================================

Pig does the Map Reduce magic under the covers and stores the end result in a directory called "result" based on the last statement in the pig file.

Step :  View the results.

========================
$ vi result/part-r-00000

user1=2
user2=2
user3=1
user4=1
user5=1
========================


It took me like a couple of hours to get the script correct and working, after a lot of trial and error.  But I had to write 0 lines of Apache Hadoop Map Reduce java code.

Trying out Apache Pig

I was going through Alex P's blog posts and one post that attracted my attention was related to Apache Pig.  I have been thinking of playing with Pig Latin Scripts to simulate Map Reduce functionality.

I tried to use pig to run Alex's pig script.  He just gives the input values and the output from Pig along with the Pig script.  There is no information on how to use Pig. That is fine. He just wants reader to go through the Pig manual. :)

Here is what I tried out:

1)  Downloaded Apache Pig 0.9.2  (that was the latest version).
2) The script from Alex uses PiggyBank which is in Pig Contrib directory. Looks like I will have to build Pig.

=====================
pig_directory $>  ant

...

[javacc] Java Compiler Compiler Version 4.2 (Parser Generator)
   [javacc] (type "javacc" with no arguments for help)
...
   [javacc] File "SimpleCharStream.java" is being rebuilt.
   [javacc] Parser generated successfully.

prepare:
    [mkdir] Created dir: xxx/pig-0.9.2/src-gen/org/apache/pig/parser

genLexer:

genParser:

genTreeParser:

gen:

compile:
     [echo] *** Building Main Sources ***
     [echo] *** To compile with all warnings enabled, supply -Dall.warnings=1 on command line ***
     [echo] *** If all.warnings property is supplied, compile-sources-all-warnings target will be executed ***
     [echo] *** Else, compile-sources (which only warns about deprecations) target will be executed ***
  [taskdef] Could not load definitions from resource net/sf/antcontrib/antcontrib.properties. It could not be found.

compile-sources:
    [javac] xxx/pig-0.9.2/build.xml:429: warning: 'includeantruntime' was not set, defaulting to build.sysclasspath=last; set to false for repeatable builds
    [javac] Compiling 667 source files to /home/anil/hadoop/pig/pig-0.9.2/build/classes
    [javac] Note: Some input files use or override a deprecated API.
    [javac] Note: Recompile with -Xlint:deprecation for details.
    [javac] Note: Some input files use unchecked or unsafe operations.
    [javac] Note: Recompile with -Xlint:unchecked for details.
     [copy] Copying 1 file to xxx/pig-0.9.2/build/classes/org/apache/pig/tools/grunt
     [copy] Copying 1 file to xxx/pig-0.9.2/build/classes/org/apache/pig/tools/grunt
  [taskdef] Could not load definitions from resource net/sf/antcontrib/antcontrib.properties. It could not be found.

compile-sources-all-warnings:

jar:
  [taskdef] Could not load definitions from resource net/sf/antcontrib/antcontrib.properties. It could not be found.

jarWithSvn:
  [taskdef] Could not load definitions from resource net/sf/antcontrib/antcontrib.properties. It could not be found.

ivy-download:
      [get] Getting: http://repo2.maven.org/maven2/org/apache/ivy/ivy/2.2.0/ivy-2.2.0.jar
      [get] To: /home/anil/pig/pig-0.9.2/ivy/ivy-2.2.0.jar
      [get] Not modified - so not downloaded

ivy-init-dirs:

ivy-probe-antlib:

ivy-init-antlib:

ivy-init:

ivy-buildJar:
[ivy:resolve] :: resolving dependencies :: org.apache.pig#Pig;0.9.3-SNAPSHOT
[ivy:resolve]     confs: [buildJar]
[ivy:resolve]     found com.sun.jersey#jersey-core;1.8 in maven2
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[ivy:resolve]     found tomcat#jasper-compiler;5.5.12 in maven2
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[ivy:resolve]     found org.mortbay.jetty#jsp-2.1;6.1.14 in maven2
[ivy:resolve]     found org.eclipse.jdt#core;3.1.1 in maven2
[ivy:resolve]     found ant#ant;1.6.5 in maven2
[ivy:resolve]     found commons-el#commons-el;1.0 in maven2
[ivy:resolve]     found net.java.dev.jets3t#jets3t;0.7.1 in maven2
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[ivy:resolve]     found org.slf4j#slf4j-api;1.5.2 in maven2
[ivy:resolve]     found org.apache.ftpserver#ftpserver-core;1.0.0 in maven2
[ivy:resolve]     found org.apache.ftpserver#ftpserver-deprecated;1.0.0-M2 in maven2
[ivy:resolve]     found log4j#log4j;1.2.16 in maven2
[ivy:resolve]     found org.slf4j#slf4j-log4j12;1.6.1 in maven2
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[ivy:resolve]     found org.apache.avro#avro;1.5.3 in maven2
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[ivy:resolve]     found org.apache.hive#hive-exec;0.8.0 in maven2
[ivy:resolve] downloading http://repo2.maven.org/maven2/junit/junit/4.5/junit-4.5.jar ...
[ivy:resolve] ....................................................................................................................................................................................................................................................................................................................................................................................... (194kB)
[ivy:resolve] ... (0kB)
[ivy:resolve]     [SUCCESSFUL ] junit#junit;4.5!junit.jar (822ms)
[ivy:resolve] downloading http://repo2.maven.org/maven2/org/apache/hive/hive-exec/0.8.0/hive-exec-0.8.0.jar ...
[ivy:resolve] 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(3372kB)
[ivy:resolve] .. (0kB)
[ivy:resolve]     [SUCCESSFUL ] org.apache.hive#hive-exec;0.8.0!hive-exec.jar (2262ms)
[ivy:resolve] :: resolution report :: resolve 9172ms :: artifacts dl 3114ms
[ivy:resolve]     :: evicted modules:
[ivy:resolve]     junit#junit;3.8.1 by [junit#junit;4.5] in [buildJar]
[ivy:resolve]     commons-logging#commons-logging;1.0.3 by [commons-logging#commons-logging;1.1.1] in [buildJar]
[ivy:resolve]     commons-codec#commons-codec;1.2 by [commons-codec#commons-codec;1.4] in [buildJar]
[ivy:resolve]     commons-logging#commons-logging;1.1 by [commons-logging#commons-logging;1.1.1] in [buildJar]
[ivy:resolve]     commons-codec#commons-codec;1.3 by [commons-codec#commons-codec;1.4] in [buildJar]
[ivy:resolve]     commons-httpclient#commons-httpclient;3.1 by [commons-httpclient#commons-httpclient;3.0.1] in [buildJar]
[ivy:resolve]     org.codehaus.jackson#jackson-mapper-asl;1.0.1 by [org.codehaus.jackson#jackson-mapper-asl;1.7.3] in [buildJar]
[ivy:resolve]     org.slf4j#slf4j-api;1.5.2 by [org.slf4j#slf4j-api;1.6.1] in [buildJar]
[ivy:resolve]     org.apache.mina#mina-core;2.0.0-M4 by [org.apache.mina#mina-core;2.0.0-M5] in [buildJar]
[ivy:resolve]     org.apache.ftpserver#ftplet-api;1.0.0-M2 by [org.apache.ftpserver#ftplet-api;1.0.0] in [buildJar]
[ivy:resolve]     org.apache.ftpserver#ftpserver-core;1.0.0-M2 by [org.apache.ftpserver#ftpserver-core;1.0.0] in [buildJar]
[ivy:resolve]     org.apache.mina#mina-core;2.0.0-M2 by [org.apache.mina#mina-core;2.0.0-M5] in [buildJar]
[ivy:resolve]     commons-cli#commons-cli;1.0 by [commons-cli#commons-cli;1.2] in [buildJar]
[ivy:resolve]     org.antlr#antlr-runtime;3.3 by [org.antlr#antlr-runtime;3.4] in [buildJar]
    ---------------------------------------------------------------------
    |                  |            modules            ||   artifacts   |
    |       conf       | number| search|dwnlded|evicted|| number|dwnlded|
    ---------------------------------------------------------------------
    |     buildJar     |   74  |   2   |   2   |   14  ||   61  |   2   |
    ---------------------------------------------------------------------
[ivy:retrieve] :: retrieving :: org.apache.pig#Pig
[ivy:retrieve]     confs: [buildJar]
[ivy:retrieve]     3 artifacts copied, 58 already retrieved (3855kB/20ms)

buildJar:
     [echo] svnString exported
      [jar] Building jar: /home/anil/hadoop/pig/pig-0.9.2/build/pig-0.9.3-SNAPSHOT-core.jar
      [jar] Building jar: /home/anil/hadoop/pig/pig-0.9.2/build/pig-0.9.3-SNAPSHOT.jar
  [taskdef] Could not load definitions from resource net/sf/antcontrib/antcontrib.properties. It could not be found.

include-meta:
     [copy] Copying 1 file to /home/anil/hadoop/pig/pig-0.9.2
  [taskdef] Could not load definitions from resource net/sf/antcontrib/antcontrib.properties. It could not be found.

jarWithOutSvn:

jar-withouthadoop:
  [taskdef] Could not load definitions from resource net/sf/antcontrib/antcontrib.properties. It could not be found.

jar-withouthadoopWithSvn:
  [taskdef] Could not load definitions from resource net/sf/antcontrib/antcontrib.properties. It could not be found.

ivy-download:
      [get] Getting: http://repo2.maven.org/maven2/org/apache/ivy/ivy/2.2.0/ivy-2.2.0.jar
      [get] To: /home/anil/hadoop/pig/pig-0.9.2/ivy/ivy-2.2.0.jar
      [get] Not modified - so not downloaded

ivy-init-dirs:

ivy-probe-antlib:

ivy-init-antlib:

ivy-init:

ivy-buildJar:
[ivy:resolve] :: resolving dependencies :: org.apache.pig#Pig;0.9.3-SNAPSHOT
[ivy:resolve]     confs: [buildJar]
[ivy:resolve]     found com.sun.jersey#jersey-core;1.8 in maven2
[ivy:resolve]     found org.apache.hadoop#hadoop-core;1.0.0 in maven2
[ivy:resolve]     found commons-cli#commons-cli;1.2 in maven2
[ivy:resolve]     found xmlenc#xmlenc;0.52 in maven2
[ivy:resolve]     found commons-httpclient#commons-httpclient;3.0.1 in maven2
[ivy:resolve]     found commons-codec#commons-codec;1.4 in maven2
[ivy:resolve]     found org.apache.commons#commons-math;2.1 in maven2
[ivy:resolve]     found commons-configuration#commons-configuration;1.6 in maven2
[ivy:resolve]     found commons-collections#commons-collections;3.2.1 in maven2
[ivy:resolve]     found commons-lang#commons-lang;2.4 in maven2
[ivy:resolve]     found commons-logging#commons-logging;1.1.1 in maven2
[ivy:resolve]     found commons-digester#commons-digester;1.8 in maven2
[ivy:resolve]     found commons-beanutils#commons-beanutils;1.7.0 in maven2
[ivy:resolve]     found commons-beanutils#commons-beanutils-core;1.8.0 in maven2
[ivy:resolve]     found commons-net#commons-net;1.4.1 in maven2
[ivy:resolve]     found oro#oro;2.0.8 in maven2
[ivy:resolve]     found org.mortbay.jetty#jetty;6.1.26 in maven2
[ivy:resolve]     found org.mortbay.jetty#jetty-util;6.1.26 in maven2
[ivy:resolve]     found org.mortbay.jetty#servlet-api;2.5-20081211 in maven2
[ivy:resolve]     found tomcat#jasper-runtime;5.5.12 in maven2
[ivy:resolve]     found tomcat#jasper-compiler;5.5.12 in maven2
[ivy:resolve]     found org.mortbay.jetty#jsp-api-2.1;6.1.14 in maven2
[ivy:resolve]     found org.mortbay.jetty#servlet-api-2.5;6.1.14 in maven2
[ivy:resolve]     found org.mortbay.jetty#jsp-2.1;6.1.14 in maven2
[ivy:resolve]     found org.eclipse.jdt#core;3.1.1 in maven2
[ivy:resolve]     found ant#ant;1.6.5 in maven2
[ivy:resolve]     found commons-el#commons-el;1.0 in maven2
[ivy:resolve]     found net.java.dev.jets3t#jets3t;0.7.1 in maven2
[ivy:resolve]     found net.sf.kosmosfs#kfs;0.3 in maven2
[ivy:resolve]     found hsqldb#hsqldb;1.8.0.10 in maven2
[ivy:resolve]     found org.apache.hadoop#hadoop-test;1.0.0 in maven2
[ivy:resolve]     found org.apache.ftpserver#ftplet-api;1.0.0 in maven2
[ivy:resolve]     found org.apache.mina#mina-core;2.0.0-M5 in maven2
[ivy:resolve]     found org.slf4j#slf4j-api;1.5.2 in maven2
[ivy:resolve]     found org.apache.ftpserver#ftpserver-core;1.0.0 in maven2
[ivy:resolve]     found org.apache.ftpserver#ftpserver-deprecated;1.0.0-M2 in maven2
[ivy:resolve]     found log4j#log4j;1.2.16 in maven2
[ivy:resolve]     found org.slf4j#slf4j-log4j12;1.6.1 in maven2
[ivy:resolve]     found org.slf4j#slf4j-api;1.6.1 in maven2
[ivy:resolve]     found org.apache.avro#avro;1.5.3 in maven2
[ivy:resolve]     found com.googlecode.json-simple#json-simple;1.1 in maven2
[ivy:resolve]     found com.jcraft#jsch;0.1.38 in maven2
[ivy:resolve]     found jline#jline;0.9.94 in maven2
[ivy:resolve]     found net.java.dev.javacc#javacc;4.2 in maven2
[ivy:resolve]     found org.codehaus.jackson#jackson-mapper-asl;1.7.3 in maven2
[ivy:resolve]     found org.codehaus.jackson#jackson-core-asl;1.7.3 in maven2
[ivy:resolve]     found joda-time#joda-time;1.6 in maven2
[ivy:resolve]     found com.google.guava#guava;11.0 in maven2
[ivy:resolve]     found org.python#jython;2.5.0 in maven2
[ivy:resolve]     found rhino#js;1.7R2 in maven2
[ivy:resolve]     found org.antlr#antlr;3.4 in maven2
[ivy:resolve]     found org.antlr#antlr-runtime;3.4 in maven2
[ivy:resolve]     found org.antlr#stringtemplate;3.2.1 in maven2
[ivy:resolve]     found antlr#antlr;2.7.7 in maven2
[ivy:resolve]     found org.antlr#ST4;4.0.4 in maven2
[ivy:resolve]     found org.apache.zookeeper#zookeeper;3.3.3 in maven2
[ivy:resolve]     found org.jboss.netty#netty;3.2.2.Final in maven2
[ivy:resolve]     found org.apache.hbase#hbase;0.90.0 in maven2
[ivy:resolve]     found org.vafer#jdeb;0.8 in maven2
[ivy:resolve]     found junit#junit;4.5 in maven2
[ivy:resolve]     found org.apache.hive#hive-exec;0.8.0 in maven2
[ivy:resolve] :: resolution report :: resolve 168ms :: artifacts dl 15ms
[ivy:resolve]     :: evicted modules:
[ivy:resolve]     junit#junit;3.8.1 by [junit#junit;4.5] in [buildJar]
[ivy:resolve]     commons-logging#commons-logging;1.0.3 by [commons-logging#commons-logging;1.1.1] in [buildJar]
[ivy:resolve]     commons-codec#commons-codec;1.2 by [commons-codec#commons-codec;1.4] in [buildJar]
[ivy:resolve]     commons-logging#commons-logging;1.1 by [commons-logging#commons-logging;1.1.1] in [buildJar]
[ivy:resolve]     commons-codec#commons-codec;1.3 by [commons-codec#commons-codec;1.4] in [buildJar]
[ivy:resolve]     commons-httpclient#commons-httpclient;3.1 by [commons-httpclient#commons-httpclient;3.0.1] in [buildJar]
[ivy:resolve]     org.codehaus.jackson#jackson-mapper-asl;1.0.1 by [org.codehaus.jackson#jackson-mapper-asl;1.7.3] in [buildJar]
[ivy:resolve]     org.slf4j#slf4j-api;1.5.2 by [org.slf4j#slf4j-api;1.6.1] in [buildJar]
[ivy:resolve]     org.apache.mina#mina-core;2.0.0-M4 by [org.apache.mina#mina-core;2.0.0-M5] in [buildJar]
[ivy:resolve]     org.apache.ftpserver#ftplet-api;1.0.0-M2 by [org.apache.ftpserver#ftplet-api;1.0.0] in [buildJar]
[ivy:resolve]     org.apache.ftpserver#ftpserver-core;1.0.0-M2 by [org.apache.ftpserver#ftpserver-core;1.0.0] in [buildJar]
[ivy:resolve]     org.apache.mina#mina-core;2.0.0-M2 by [org.apache.mina#mina-core;2.0.0-M5] in [buildJar]
[ivy:resolve]     commons-cli#commons-cli;1.0 by [commons-cli#commons-cli;1.2] in [buildJar]
[ivy:resolve]     org.antlr#antlr-runtime;3.3 by [org.antlr#antlr-runtime;3.4] in [buildJar]
    ---------------------------------------------------------------------
    |                  |            modules            ||   artifacts   |
    |       conf       | number| search|dwnlded|evicted|| number|dwnlded|
    ---------------------------------------------------------------------
    |     buildJar     |   74  |   0   |   0   |   14  ||   61  |   0   |
    ---------------------------------------------------------------------
[ivy:retrieve] :: retrieving :: org.apache.pig#Pig
[ivy:retrieve]     confs: [buildJar]
[ivy:retrieve]     0 artifacts copied, 61 already retrieved (0kB/9ms)

buildJar-withouthadoop:
     [echo] svnString exported
      [jar] Building jar: /home/anil/hadoop/pig/pig-0.9.2/build/pig-0.9.3-SNAPSHOT-withouthadoop.jar
     [copy] Copying 1 file to /home/anil/hadoop/pig/pig-0.9.2
  [taskdef] Could not load definitions from resource net/sf/antcontrib/antcontrib.properties. It could not be found.

jar-withouthadoopWithOutSvn:

jar-all:

BUILD SUCCESSFUL
Total time: 5 minutes 38 seconds
==========================

Looks like Pig was build successfully.  This step was needed to build piggybank.

Now go to the directory where piggybank resides.

=====================
anil@sadbhav:~/hadoop/pig/pig-0.9.2/contrib/piggybank/java$ ant
Buildfile: /home/anil/hadoop/pig/pig-0.9.2/contrib/piggybank/java/build.xml

init:

compile:
     [echo]  *** Compiling Pig UDFs ***
    [javac] /home/anil/hadoop/pig/pig-0.9.2/contrib/piggybank/java/build.xml:92: warning: 'includeantruntime' was not set, defaulting to build.sysclasspath=last; set to false for repeatable builds
    [javac] Compiling 153 source files to /home/anil/hadoop/pig/pig-0.9.2/contrib/piggybank/java/build/classes
    [javac] Note: Some input files use or override a deprecated API.
    [javac] Note: Recompile with -Xlint:deprecation for details.

jar:
     [echo]  *** Creating pigudf.jar ***
      [jar] Building jar: /home/anil/hadoop/pig/pig-0.9.2/contrib/piggybank/java/piggybank.jar

BUILD SUCCESSFUL
Total time: 3 seconds
======================================


3)  Now I have a directory to test my pig scripts.
Let us call it "anilpig".

I create the following pig script (distance.pig) which is a direct copy of what Alex has:

======================================
REGISTER /home/anil/hadoop/pig/pig-0.9.2/contrib/piggybank/java/piggybank.jar;

define radians org.apache.pig.piggybank.evaluation.math.toRadians();
define sin org.apache.pig.piggybank.evaluation.math.SIN();
define cos org.apache.pig.piggybank.evaluation.math.COS();
define sqrt org.apache.pig.piggybank.evaluation.math.SQRT();
define atan2 org.apache.pig.piggybank.evaluation.math.ATAN2();

geo = load 'haversine.csv' using PigStorage(';') as (id1: long, lat1: double, lon1: double);
geo2 = load 'haversine.csv' using PigStorage(';') as (id2: long, lat2: double, lon2: double);

geoCross = CROSS geo, geo2;

geoDist = FOREACH geoCross GENERATE id1, id2, 6371 * 2 * atan2(sqrt(sin(radians(lat2 - lat1) / 2) * sin(radians(lat2 - lat1) / 2) + cos(radians(lat1)) * cos(radians(lat2)) * sin(radians(lon2 - lon1) / 2) * sin(radians(lon2 - lon1) / 2)), sqrt(1 - (sin(radians(lat2 - lat1) / 2) * sin(radians(lat2 - lat1) / 2) + cos(radians(lat1)) * cos(radians(lat2)) * sin(radians(lon2 - lon1) / 2) * sin(radians(lon2 - lon1) / 2)))) as dist;

dump geoDist;
======================================

Please do not forget to update the path to piggybank.jar.

I also create the following haversine.csv file
===============
1;48.8583;2.2945
2;48.8738;2.295
================

4)  Let us run pig to see if the values match what Alex quotes in his blog post.

==================
~/hadoop/pig/anilpig$ ../pig-0.9.2/bin/pig -x local distance.pig

which: no hadoop in (/usr/local/bin:/usr/bin:/bin:/usr/local/sbin:/usr/sbin:/sbin:/usr/bin:/usr/sbin:/usr/java/jdk1.6.0_30/bin:/opt/apache-maven-3.0.2/bin:/home/anil/.local/bin:/home/anil/bin:/usr/bin:/usr/sbin:/usr/java/jdk1.6.0_30/bin:/opt/apache-maven-3.0.2/bin)
2012-02-19 12:05:13,316 [main] INFO  org.apache.pig.Main - Logging error messages to: /home/anil/hadoop/pig/anilpig/pig_1329674713314.log
2012-02-19 12:05:13,409 [main] INFO  org.apache.pig.backend.hadoop.executionengine.HExecutionEngine - Connecting to hadoop file system at: file:///
2012-02-19 12:05:13,911 [main] WARN  org.apache.pig.PigServer - Encountered Warning IMPLICIT_CAST_TO_DOUBLE 10 time(s).
2012-02-19 12:05:13,916 [main] INFO  org.apache.pig.tools.pigstats.ScriptState - Pig features used in the script: CROSS
2012-02-19 12:05:14,051 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MRCompiler - File concatenation threshold: 100 optimistic? false
2012-02-19 12:05:14,083 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MRCompiler$LastInputStreamingOptimizer - Rewrite: POPackage->POForEach to POJoinPackage
2012-02-19 12:05:14,090 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MultiQueryOptimizer - MR plan size before optimization: 1
2012-02-19 12:05:14,090 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MultiQueryOptimizer - MR plan size after optimization: 1
2012-02-19 12:05:14,108 [main] INFO  org.apache.pig.tools.pigstats.ScriptState - Pig script settings are added to the job
2012-02-19 12:05:14,114 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - mapred.job.reduce.markreset.buffer.percent is not set, set to default 0.3
2012-02-19 12:05:14,133 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - Setting up single store job
2012-02-19 12:05:14,148 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - BytesPerReducer=1000000000 maxReducers=999 totalInputFileSize=66
2012-02-19 12:05:14,148 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - Neither PARALLEL nor default parallelism is set for this job. Setting number of reducers to 1
2012-02-19 12:05:14,224 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - 1 map-reduce job(s) waiting for submission.
2012-02-19 12:05:14,234 [Thread-2] WARN  org.apache.hadoop.util.NativeCodeLoader - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
2012-02-19 12:05:14,239 [Thread-2] WARN  org.apache.hadoop.mapred.JobClient - No job jar file set.  User classes may not be found. See JobConf(Class) or JobConf#setJar(String).
2012-02-19 12:05:14,315 [Thread-2] INFO  org.apache.hadoop.mapreduce.lib.input.FileInputFormat - Total input paths to process : 1
2012-02-19 12:05:14,315 [Thread-2] INFO  org.apache.pig.backend.hadoop.executionengine.util.MapRedUtil - Total input paths to process : 1
2012-02-19 12:05:14,323 [Thread-2] INFO  org.apache.pig.backend.hadoop.executionengine.util.MapRedUtil - Total input paths (combined) to process : 1
2012-02-19 12:05:14,329 [Thread-2] INFO  org.apache.hadoop.mapreduce.lib.input.FileInputFormat - Total input paths to process : 1
2012-02-19 12:05:14,329 [Thread-2] INFO  org.apache.pig.backend.hadoop.executionengine.util.MapRedUtil - Total input paths to process : 1
2012-02-19 12:05:14,329 [Thread-2] INFO  org.apache.pig.backend.hadoop.executionengine.util.MapRedUtil - Total input paths (combined) to process : 1
2012-02-19 12:05:14,562 [Thread-3] INFO  org.apache.hadoop.util.ProcessTree - setsid exited with exit code 0
2012-02-19 12:05:14,564 [Thread-3] INFO  org.apache.hadoop.mapred.Task -  Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@313816e0
2012-02-19 12:05:14,578 [Thread-3] INFO  org.apache.hadoop.mapred.MapTask - io.sort.mb = 100
2012-02-19 12:05:14,600 [Thread-3] INFO  org.apache.hadoop.mapred.MapTask - data buffer = 79691776/99614720
2012-02-19 12:05:14,600 [Thread-3] INFO  org.apache.hadoop.mapred.MapTask - record buffer = 262144/327680
2012-02-19 12:05:14,636 [Thread-3] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigRecordReader - Created input record counter: Input records from _0_haversine.csv
2012-02-19 12:05:14,638 [Thread-3] INFO  org.apache.hadoop.mapred.MapTask - Starting flush of map output
2012-02-19 12:05:14,643 [Thread-3] INFO  org.apache.hadoop.mapred.MapTask - Finished spill 0
2012-02-19 12:05:14,645 [Thread-3] INFO  org.apache.hadoop.mapred.Task - Task:attempt_local_0001_m_000000_0 is done. And is in the process of commiting
2012-02-19 12:05:14,725 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - HadoopJobId: job_local_0001
2012-02-19 12:05:14,725 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - 0% complete
2012-02-19 12:05:17,545 [Thread-3] INFO  org.apache.hadoop.mapred.LocalJobRunner -
2012-02-19 12:05:17,546 [Thread-3] INFO  org.apache.hadoop.mapred.Task - Task 'attempt_local_0001_m_000000_0' done.
2012-02-19 12:05:17,549 [Thread-3] INFO  org.apache.hadoop.mapred.Task -  Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@36d83365
2012-02-19 12:05:17,551 [Thread-3] INFO  org.apache.hadoop.mapred.MapTask - io.sort.mb = 100
2012-02-19 12:05:17,572 [Thread-3] INFO  org.apache.hadoop.mapred.MapTask - data buffer = 79691776/99614720
2012-02-19 12:05:17,572 [Thread-3] INFO  org.apache.hadoop.mapred.MapTask - record buffer = 262144/327680
2012-02-19 12:05:17,591 [Thread-3] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigRecordReader - Created input record counter: Input records from _1_haversine.csv
2012-02-19 12:05:17,592 [Thread-3] INFO  org.apache.hadoop.mapred.MapTask - Starting flush of map output
2012-02-19 12:05:17,593 [Thread-3] INFO  org.apache.hadoop.mapred.MapTask - Finished spill 0
2012-02-19 12:05:17,594 [Thread-3] INFO  org.apache.hadoop.mapred.Task - Task:attempt_local_0001_m_000001_0 is done. And is in the process of commiting
2012-02-19 12:05:20,547 [Thread-3] INFO  org.apache.hadoop.mapred.LocalJobRunner -
2012-02-19 12:05:20,548 [Thread-3] INFO  org.apache.hadoop.mapred.Task - Task 'attempt_local_0001_m_000001_0' done.
2012-02-19 12:05:20,560 [Thread-3] INFO  org.apache.hadoop.mapred.Task -  Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@2f2e43f1
2012-02-19 12:05:20,560 [Thread-3] INFO  org.apache.hadoop.mapred.LocalJobRunner -
2012-02-19 12:05:20,564 [Thread-3] INFO  org.apache.hadoop.mapred.Merger - Merging 2 sorted segments
2012-02-19 12:05:20,568 [Thread-3] INFO  org.apache.hadoop.mapred.Merger - Down to the last merge-pass, with 2 segments left of total size: 160 bytes
2012-02-19 12:05:20,568 [Thread-3] INFO  org.apache.hadoop.mapred.LocalJobRunner -
2012-02-19 12:05:20,623 [Thread-3] INFO  org.apache.hadoop.mapred.Task - Task:attempt_local_0001_r_000000_0 is done. And is in the process of commiting
2012-02-19 12:05:20,623 [Thread-3] INFO  org.apache.hadoop.mapred.LocalJobRunner -
2012-02-19 12:05:20,624 [Thread-3] INFO  org.apache.hadoop.mapred.Task - Task attempt_local_0001_r_000000_0 is allowed to commit now
2012-02-19 12:05:20,625 [Thread-3] INFO  org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter - Saved output of task 'attempt_local_0001_r_000000_0' to file:/tmp/temp371866094/tmp-1622554263
2012-02-19 12:05:23,558 [Thread-3] INFO  org.apache.hadoop.mapred.LocalJobRunner - reduce > reduce
2012-02-19 12:05:23,558 [Thread-3] INFO  org.apache.hadoop.mapred.Task - Task 'attempt_local_0001_r_000000_0' done.
2012-02-19 12:05:24,730 [main] WARN  org.apache.pig.tools.pigstats.PigStatsUtil - Failed to get RunningJob for job job_local_0001
2012-02-19 12:05:24,732 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - 100% complete
2012-02-19 12:05:24,732 [main] INFO  org.apache.pig.tools.pigstats.SimplePigStats - Detected Local mode. Stats reported below may be incomplete
2012-02-19 12:05:24,734 [main] INFO  org.apache.pig.tools.pigstats.SimplePigStats - Script Statistics:

HadoopVersion    PigVersion    UserId    StartedAt    FinishedAt    Features
1.0.0    0.9.3-SNAPSHOT    anil    2012-02-19 12:05:14    2012-02-19 12:05:24    CROSS

Success!

Job Stats (time in seconds):
JobId    Alias    Feature    Outputs
job_local_0001    geo,geo2,geoCross,geoDist        file:/tmp/temp371866094/tmp-1622554263,

Input(s):
Successfully read records from: "file:///home/anil/hadoop/pig/anilpig/haversine.csv"
Successfully read records from: "file:///home/anil/hadoop/pig/anilpig/haversine.csv"

Output(s):
Successfully stored records in: "file:/tmp/temp371866094/tmp-1622554263"

Job DAG:
job_local_0001


2012-02-19 12:05:24,736 [main] INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Success!
2012-02-19 12:05:24,739 [main] INFO  org.apache.hadoop.mapreduce.lib.input.FileInputFormat - Total input paths to process : 1
2012-02-19 12:05:24,739 [main] INFO  org.apache.pig.backend.hadoop.executionengine.util.MapRedUtil - Total input paths to process : 1
(1,1,0.0)
(1,2,1.7239093620868347)
(2,1,1.7239093620868347)
(2,2,0.0)
===================

Pig has kicked out map reduce in the background.

How much time did this script take?
Let us look at the first log entry and the last one.
-------------------------
2012-02-19 12:05:13,316 [main] INFO  org.apache.pig.Main - Logging error

 2012-02-19 12:05:24,739 [main] INFO  org.apache.pig.backend.hadoop.executionengine.util.MapRedUtil - Total input paths to process : 1
-------------------------
About 11 secs.

The run does show some stats:
---------------
HadoopVersion    PigVersion    UserId    StartedAt    FinishedAt    Features
1.0.0    0.9.3-SNAPSHOT    anil    2012-02-19 12:05:14    2012-02-19 12:05:24    CROSS
---------------------
About 10 secs.



As you can see, the values (1.724) match with what Alex quotes.  So I have been successful in testing the Haversine script from AlexP.  Next step is to play with the script further to try out Pig's extended functionality.

Additional Details:
CROSS is described here.  Computes the cross product of two or more relations.

References
http://fierydata.com/2012/05/11/hadoop-fundamentals-an-introduction-to-pig-2/


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