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{excerpt}How to use Pentaho MapReduce to convert raw weblog data into parsed, delimited records.{excerpt}
The steps in this guide include
# Loading the sample data file into CLDB
# Developing a PDI transformation which will serve as a Mapper
# Developing a PDI job which will invoke a Pentaho MapReduce step that runs a map-only job, using the developed mapper transformation.
# Executing and reviewing output

h1. Prerequisites

In order to follow along with this how-to guide you will need the following:
* MapR
* Pentaho Data Integration
* Pentaho Hadoop Node Distribution

h1. Sample Files

The sample data file needed for this guide is:
| File Name | Content |
| [How To's^weblogs_rebuild.txt.zip] | Unparsed, raw weblog data |
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NOTE:  If you have completed the [Loading Data into CLDBthe MapR filesystem] guide, then the necessary file will already be in the proper location.
This file should be placed in CLDB at /weblogs/raw using the following commands.
{code}hadoop fs -mkdir /weblogs
hadoop fs -mkdir /weblogs/raw
hadoop fs -put weblogs_rebuild.txt /weblogs/raw/{code}

h1. Step-By-Step Instructions


h2. Setup

Start MapR if it is not already running.

{include:Create Mapper Transformation to Parse Weblog File}

h2. Create a PDI Job to Execute a Map Only MapReduce Process

In this task you will create a job that will execute a "map-only" MapReduce process using the mapper transformation you created in the previous section.
{tip:title=Speed Tip}You can download the Kettle Job [weblog_parse_mr.kjb|Using Pentaho MapReduce to Parse Weblog Data in MapR^weblog_parse_mr.kjb] already completed{tip}
# Within PDI, choose 'File' \-> 'New' \-> 'Job' from the menu system or click on the 'New file' icon on the toolbar and choose the 'Job' option.
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# *Add a Start Job Entry:* You need to tell PDI where to start the job, so expand the 'General' section of the Design palette and drag a 'Start' node onto the job canvas.  Your canvas should look like:
!BAD:Common Images^Add a Start Job Entry.png|width=524,height=292!\\
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# *Add a Pentaho MapReduce Job Entry:* Expand the 'Big Data' section of the Design palette and drag a 'Pentaho MapReduce' job entry onto the job canvas.  Your canvas should look like:
!BAD:Common Images^AddPentahoMapReduceJobEntry.PNG|width=391,height=188!\\
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# *Connect the Start and MapReduce Job Entries*: Hover the mouse over the 'Delete folders' job entry and a tooltip will appear. Click on the output connector (the green arrow pointing to the right) and drag a connector arrow to the 'Pentaho MapReduce' job entry.
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Your canvas should look like this:
!BAD:Common Images^Connect Start and Pentaho MapReduce.PNG|width=192,height=146!\\
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# *Edit the MapReduce Job Entry*: Double-click on the 'Pentaho MapReduce' job entry to edit its properties. Enter this information:
## Hadoop Job Name: Enter 'Web Log Parser'
## Mapper Transformation: Enter <PATH>/weblog{anchor:_GoBack}\_parse_mapper.ktr
<PATH> is the folder path you saved the mapper in.
## Mapper Input Step Name: Enter 'Map/Reduce Input'
## Mapper Output Step Name: Enter 'Map/Reduce Output'
When you are done the window should look like:
!BAD:Common Images^ConfigureMapperParseMR.PNG|width=589,height=301!\\
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# *Configure the MapReduce Job:* Switch to the 'Job Setup' tab.  Enter this information:
## Check 'Suppress Output of Map Key'
## Input Path: Enter '/weblogs/raw'
## Output Path: Enter '/weblogs/parse'
## Input Format: Enter 'org.apache.hadoop.mapred.TextInputFormat'
## Output Format: Enter 'org.apache.hadoop.mapred.TextOutputFormat'
## Check 'Clean output path before execution'
When you are done your window should look like:
!EditPMRJobSetup.PNG|width=600,height=393!\\
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# *Configure the Cluster Properties:* Switch to the 'Cluster' tab.  Enter this information:
## Hadoop distribution: Select 'MapR'
## Working Directory: Enter '/tmp'
## HDFS Hostname, HDFS Port, Job Tracker Hostname, Job Tracker Port: Your connection information.  For a local single node cluster leave blank.
## Number of Mapper Tasks: Enter '3'.  You can play around with this to get the best performance based on the size of your data and the number of nodes in your cluster.
## Number of Reducer Tasks: Enter '0'
## Check 'Enable Blocking'
## Logging Interval: Enter '10'.  The number of seconds between pinging MapR for completion status messages
When you are done your window should look like:
!EditPMRCluster.PNG|width=586,height=384!
Click 'OK' to close the window.
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# *Save the Job*: Choose 'File' \-> 'Save as...' from the menu system. Save the transformation as 'weblogs_parse_mr.kjb' into a folder of your choice.
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# *Run the Job*: Choose 'Action' \-> 'Run' from the menu system or click on the green run button on the job toolbar. An 'Execute a job' window will open. Click on the 'Launch' button. An 'Execution Results' panel will open at the bottom of the PDI window and it will show you the progress of the job as it runs. After a few seconds the job should finish successfully:
\\  !RunJob.PNG|width=767,height=178!

If any errors occurred the job entry that failed will be highlighted in red and you can use the 'Logging' tab to view error messages.

h2. Check MapR for Parsed Weblog Data

# If you have mounted your MapR CLDB onto your local machine you may verify the file loaded by navigating to the MapR directory.{code}ls /mapr/my.cluster.com/weblogs/parse{code}
This should return:
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\_logs  part-00000  part-00001  part-00002  \_SUCCESS
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# If you have not mounted your MapR CLDB onto your local machine you may alternatively check MapR by:{code}hadoop fs \-ls /weblogs/parse{code}
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This should return:
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\-rwxrwxrwx   3 demo demo   27132365 2012-01-04 16:52 /weblogs/parse/part-00001
\-rwxrwxrwx   3 demo demo          0 2012-01-04 16:52 /weblogs/parse/_SUCCESS
\-rwxrwxrwx   3 demo demo   27188268 2012-01-04 16:52 /weblogs/parse/part-00002
drwxrwxrwx   - demo demo          1 2012-01-04 16:52 /weblogs/parse/_logs
\-rwxrwxrwx   3 demo demo   27147417 2012-01-04 16:52 /weblogs/parse/part-00000

h1. Summary

During this guide you learned how to create and execute a Pentaho MapReduce job to parse raw weblog data.

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