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How |
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to |
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use |
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compression |
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with |
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Pentaho |
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MapReduce. |
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guide
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uses
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the
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Snappy
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compression
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codec
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in
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its
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examples,
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but
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you
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may
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use
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any
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compression
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codec
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you
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choose
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that
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is
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supported
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in
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Hadoop.
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The
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following
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scenarios
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are
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covered:
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- Reading
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- Compressed
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- Files
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- Writing
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- Compressed
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- Files
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- Compressing
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- Intermediate
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- Data
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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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- Hadoop
- Pentaho Data Integration
- Pentaho Hadoop Distribution
- Compression Codec Installed on Hadoop
Step-By-Step
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Instructions
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Reading
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Compressed
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Files
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Normally
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there
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is
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nothing
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you
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need
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to
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do
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to
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have
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Pentaho
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MapReduce
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use
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a
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compressed
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file
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as
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the
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the
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input.
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Pentaho
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MapReduce
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will
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automatically
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decompress
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any
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compression
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codec
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installed
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on
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the
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Hadoop
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cluster.
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Writing
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Compressed
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Files
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- Start
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- PDI
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- on
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- your
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- desktop.
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- Once
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- it
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- is
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- running
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- choose
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- 'File'
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- ->
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- 'Open',
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- browse
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- to
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- and
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- select
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- your
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- job
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- running
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- Pentaho
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- MapReduce,
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- then
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- click
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- 'OK'.
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- Configure
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- the
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- Compression
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- Codec:
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- Double
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- click
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- on
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- the
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- 'Pentaho
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- MapReduce'
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- step,
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- switch
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- to
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- the
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- 'User
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- Defined'
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- tab
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- and
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- enter
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- the
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- following
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- information:
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Name
Value
mapred.output.compression.codec
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The
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compression
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codec
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to
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use.
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For
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example
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org.apache.hadoop.io.compress.SnappyCodec
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mapred.output.compress
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true
mapred.output.compression.type
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BLOCK
- Run your job
The output from the job should be compressed using the codec you specified.
Compressing Intermediate Data
You may want to compress the intermediate data that is passed between the Pentaho Mappers and Reducers to reduce network i/o and in some cases improve performance.
- Start PDI on your desktop. Once it is running choose 'File' -> 'Open', browse to and select your job running Pentaho MapReduce, then click 'OK'.
- Configure the Compression Codec: Double click on the 'Pentaho MapReduce' step, switch to the 'User Defined' tab and enter the following information:
Name
Value
mapred.map.output.compression.codec
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The
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compression
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codec
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to
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use.
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For
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example
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org.apache.hadoop.io.compress.SnappyCodec
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mapred.compress.map.output
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true
- Run your job