Pentaho Data Integration - CSV File Input with parallel execution enabled

CSV file input is a commonly used input step to read delimited files. Options are similar to text file input steps. Here are the general configurable options.

  1. File name - Input file name.
  2. Delimiter - Support common delimiters like coma, tab, pipe e.t.c
  3. Enclosure - Optional enclosures like double quotes.
  4. NIO buffer size - Read buffer size.
  5. Lazy Conversion - Significant performance improvement by avoiding data type conversions. Check this option only if the logic is mere pass through.
  6. Header row present - Enable in case the file has header row.
  7. Add file name to result - File name or file names will be added to the result in memory and can be passed into the next job entry.
  8. Running in Parallel - This step can run in multiple copies and will read separate blocks of the file. Configure along with clustered or copy mode.
  9. File encoding - UTF-8, ASCII e.t.c.

Here are step wise illustrations on how to use CSV input step.

 Without Parallel Execution Option

Step 1 
Create a new transformation for demo and drag the CSV input file into the canvas.












Step 2
Double click on the CSV input step and configure options.

  • File name : Browse and select from local server.
  • Delimiter : Coma for demo purposes.
  • Lazy conversion : Disabled.
  • Running in parallel : Disabled.
  • File encoding : UTF-8 selected for demo.












Step 3
Click on "Get Fields" to populate field names based on sample data.
Configure appropriate trim type.

Here are the results of document scan. 
Result after scanning 100 lines.
---------------------------------------
Field nr. 1 :
 Field name           : id  Field type           : Integer
Field nr. 2 :
 Field name           : code  Field type           : String  Maximum length       : 10 Minimum value        : PRD_CD_ACF Maximum value        : PRD_CD_ZWQ  Nr of null values    : 1
Field nr. 3 :
 Field name           : description Field type           : String Maximum length       : 13 Minimum value        : aafwtscm-desc Maximum value        : zyirgmfn-desc Nr of null values    : 1
Field nr. 4 :
 Field name           : category Field type           : String  Maximum length       : 1 Minimum value        : A Maximum value        : Z Nr of null values    : 1
Field nr. 5 :
 Field name           : price Field type           : Number Estimated length     : 15 Estimated precision  : 5 Number format        : #.# WARNING: More then 1 number format seems to match all sampled records: Number format        : #.# Trim Type            : 0 Minimum value      : 252.44767Maximum value      : 1246.517 Example            : #.#, number [252.44767] gives 252.44767


Step 4
Add a dummy step to complete the flow.













Step 5
Here are the execution results for the demo transformation.
Step  Metrics









Preview Data














Execution Log
  General - Logging plugin type found with ID: CheckpointLogTable
  General - Starting agile-bi
  Version checker - OK
  class org.pentaho.agilebi.platform.JettyServer - WebServer.Log.CreateListener localhost:10000
  Spoon - Transformation opened.
  Spoon - Launching transformation [trf_Demo_Load_CSV_File]...
  Spoon - Started the transformation execution.
  trf_Demo_Load_CSV_File - Dispatching started for transformation [trf_Demo_Load_CSV_File]
  CSV file input.0 - Header row skipped in file 'products_data.csv'
  CSV file input.0 - Finished processing (I=10001, O=0, R=0, W=10000, U=0, E=0)
  Dummy (do nothing).0 - Finished processing (I=0, O=0, R=10000, W=10000, U=0, E=0)
  Spoon - The transformation has finished!!


 With Parallel Execution Option

Step 6
Enable "Running in parallel" option.











Step 7 
Change number of copies to start with from 1 to say 5 for demo purpose. 
Step 8
Select data movement as "Round robin".











Step 9
Execute the demo transformation. 5 parallel copies of the input step got executed, each reading a different block of the input file.









Step 10
Execution Log
 Spoon - Transformation opened.
 Spoon - Launching transformation [trf_Demo_Load_CSV_File]...
 Spoon - Started the transformation execution.
 trf_Demo_Load_CSV_File - Dispatching started for transformation [trf_Demo_Load_CSV_File]
 CSV file input.0 - We start to read from file 'products_data.csv' (430326 bytes).  Then we skip 0 bytes to the starting position and read   86065 bytes.
 CSV file input.1 - We start to read from file 'products_data.csv' (430326 bytes).  Then we skip 86065 bytes to the starting position and  read 86065 bytes.
 CSV file input.0 - Header row skipped in file 'products_data.csv'
 CSV file input.4 - We start to read from file 'products_data.csv' (430326 bytes).  Then we skip 344260 bytes to the starting position and read 86065 bytes.
 CSV file input.1 - Finished processing (I=1995, O=0, R=0, W=1995, U=0, E=0)
 CSV file input.0 - Finished processing (I=2022, O=0, R=0, W=2021, U=0, E=0)
 CSV file input.2 - We start to read from file 'products_data.csv' (430326 bytes).  Then we skip 172130 bytes to the starting position and read 86065 bytes.
 CSV file input.3 - We start to read from file 'products_data.csv' (430326 bytes).  Then we skip 258195 bytes to the starting position and read 86065 bytes.
 CSV file input.4 - Finished processing (I=1995, O=0, R=0, W=1995, U=0, E=0)
 CSV file input.2 - Finished processing (I=1993, O=0, R=0, W=1993, U=0, E=0)
 CSV file input.3 - Finished processing (I=1996, O=0, R=0, W=1996, U=0, E=0)
 Dummy (do nothing).0 - Finished processing (I=0, O=0, R=10000, W=10000, U=0, E=0)
 Spoon - The transformation has finished!!

2 comments :

Anupam said...

nice article buddy :)
i am expecting similar kind of explanation of all three data movement options. i.e round robin, load balance and copy data to next step.

kic said...

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