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How |
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to |
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use |
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Pentaho |
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MapReduce |
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to |
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convert |
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raw |
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weblog |
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data |
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into |
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parsed, |
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delimited |
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records. |
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The
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steps
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in
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this
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guide
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include
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- Loading
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- the
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- sample
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- data
...
- file
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- into
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- CLDB
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- Developing
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- a
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- PDI
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- transformation
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- which
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- will
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- serve
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- as
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- a
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- Mapper
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- Developing
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- a
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- PDI
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- job
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- which
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- will
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- invoke
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- a
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- Pentaho
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- MapReduce
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- step
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- that
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- runs
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- a
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- map-only
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- job,
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- using
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- the
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- developed
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- mapper
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- transformation.
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- Executing
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- and
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- reviewing
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- output
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Prerequisites
In order to follow along with this how-to
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guide
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you
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will
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need
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the
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following:
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- MapR
- Pentaho Data Integration
- Pentaho Hadoop Node Distribution
Sample Files
The sample data file needed for this guide is:
File Name | Content |
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Unparsed, |
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raw |
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weblog |
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data |
NOTE:
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If
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you
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have
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completed
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the
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...
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into the MapR filesystem guide,
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then
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the
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necessary
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file
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will
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already
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be
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in
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the
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proper
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location.
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This
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file
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should
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be
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placed
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in
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CLDB
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at
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/weblogs/raw
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using
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the
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following
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commands.
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| Code Block |
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hadoop fs -mkdir /weblogs
hadoop fs -mkdir /weblogs/raw
hadoop fs -put weblogs_rebuild.txt /weblogs/raw/{code}
h1. |
Step-By-Step
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Instructions
Setup
Start MapR if it is not already running.
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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"
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MapReduce
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process
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using
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the
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mapper
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transformation
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you
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created
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in
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the
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previous
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section.
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| Tip | ||||||||
|---|---|---|---|---|---|---|---|---|
| =
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| }||||||
You can download the Kettle Job [|Using Pentaho MapReduce to Parse Weblog Data in MapR^weblog_parse_mr.kjb]already completed{tip} # Withincompleted |
- Within PDI,
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- choose
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- 'File'
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- ->
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- 'New'
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- ->
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- 'Job'
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- from
...
- the
...
- menu
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- system
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- or
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- click
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- on
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- the
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- 'New
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- file'
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- icon
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- on
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- the
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- toolbar
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- and
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- choose
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- the
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- 'Job'
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- 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:
- 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:
- 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.
Your canvas should look like this:
- 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
_parse_mapper.ktrAnchor _GoBack _GoBack
<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:
- 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'
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- Output
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- Format:
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- Enter
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- 'org.apache.hadoop.mapred.TextOutputFormat'
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- Check
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- 'Clean
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- output
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- path
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- before
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- execution'
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When
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- you
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- are
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- done
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- your
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- window
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- should
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- look
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- like:
- like:
- 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:
Click 'OK' to close the window.
- Save the Job: Choose 'File' -> 'Save as...' from the menu system. Save the transformation as 'weblogs_parse_mr.kjb'
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- into
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- a
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- folder
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- of
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- your
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- choice.
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- Run the Job: Choose 'Action'
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- ->
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- 'Run'
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- from
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- the
...
- menu
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- system
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- or
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- click
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- on
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- the
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- green
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- run
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- button
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- on
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- the
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- job
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- toolbar.
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- An
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- 'Execute
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- a
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- job'
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- window
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- will
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- open.
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- Click
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- on
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- the
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- 'Launch'
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- button.
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- An
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- 'Execution
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- Results'
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- panel
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- will
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- open
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- at
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- the
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- bottom
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- of
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- the
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- PDI
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- window
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- and
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- it
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- will
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- show
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- you
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- the
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- progress
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- of
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- the
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- job
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- as
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- it
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- runs.
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- After
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- a
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- few
...
- seconds
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- the
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- job
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- should
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- finish
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- successfully:
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.
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 Block ls /mapr/my.cluster.com/weblogs/parse
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This
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- should
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- return:
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_logs
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- part-00000
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- part-00001
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- part-00002
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- _SUCCESS
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- If you have not mounted your MapR CLDB onto your local machine you may alternatively check MapR by:
Code Block hadoop fs \-ls /weblogs/parse
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This should return:
-rwxrwxrwx 3 demo demo 27132365 2012-01-04
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- 16:52
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- /weblogs/parse/part-00001
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-rwxrwxrwx
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- 3
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- demo
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- demo
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- 0
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- 2012-01-04
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- 16:52
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- /weblogs/parse/_SUCCESS
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-rwxrwxrwx
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- 3
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- demo
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- demo
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- 27188268
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- 2012-01-04
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- 16:52
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- /weblogs/parse/part-00002
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drwxrwxrwx
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- -
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- demo
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- demo
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- 1
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- 2012-01-04
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- 16:52
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- /weblogs/parse/_logs
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-rwxrwxrwx
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- 3
...
- demo
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- demo
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- 27147417
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- 2012-01-04
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- 16:52
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- /weblogs/parse/part-00000
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Summary
During this guide you learned how to create and execute a Pentaho MapReduce job to parse raw weblog data.
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