Adding and Reading Talend Headers and Trailers

Adding a header and trailer to a file

Let us look at how to add a custom header, footer to file. This is often required for file processing and validation.

Requirement: Create a delimited file with below structure.

Header Part

File Name: Name of the actual File.
PID : process ID.
Header Columns.

Body Part

Text Data. 

Footer Part

File Created Date: Date & Time.
Number of Records: record count.

This is our final job design.

Final Job Design

Final Job Design

Step 1: We`ll create Header part first.

Step 2: Add tFixedFlowInput component and configure as below.

  • Add one column “value” with string type.
  • Select “Use inline table” option and add three rows.
  • Add each line of below code to the each line created previously.
"File Name: CustomerDetails.csv"
"PID :"+pid
  • See the image for more details.

tFixedFlowInput Setting

tFixedFlowInput Setting

Step 3: Add tFileOutputDelimited and connect with tFixedFlowInput component using Main flow, then configured as follows.

  • Add file path name “C:/home/CustomerDetails.csv”.(you can change this)
  • Row separator=”n”
  • Field Separator=”,”

Step 4: Add tRowGenerator

Step 5: Copy Paste tFileOutputDelimited_1 component which was  created in Step 3, then connect  tFileOutputDelimited_2 with tRowGenerator using main flow. Configure as follows.

  • Select Option “Append”.
  • Click on  “Main” flow and go to the “Advance setting” tab and select the option “Monitor this connection”.
  • Unchecked “Use Input Connection as Label”. It will show you a “Label” and text box to write, write “Number Of Records:” in the same text box.

Step 6: Create a context variable named as “NumberOfRows”, then copy and paste tFixedFlowInput_1.

Step 7: Configure newly pasted tFixedFlowInput_2 component.

  • Delete second last line from the list.
  • On second line, add this code "File Created Date: "+TalendDate.getDate("dd-MMM-yyyy HH:mm:ss").
  • On third line add the context variable. context.NumberOfRows. 

Step 8: Copy paste tFileOutputDelimited_2 and connect with tFixedFlowInput_2 using main flow. No need to do any additional configuration.

Step 9: Add tFlowMeterCatcher component and add tJavaRow and connect each other using main flow, don`t click on “Synch” button on tJavaRow. Write below code in tJavaRow component.


Step 10: Run the job, it will create files with Header part, Data part and footer part. Below is our final output.

Header and Footer Output

Header and Footer Output

Reading headers and trailers using tMap

This recipe shows how to parse a file that has a header and trailer records, and a record type at the start of a line.

Getting ready

Open the jo_cook_ch08_0060_headTrailtMap job.

How to accomplish it…

The steps for reading headers and trailers using tMap are as follows:

  • Drag a tMap component onto the canvas.
  • Connect the tFileInputFullRow to tMap, and rename the flow to customerIn.
  • Open tMap, and create three new outputs. Name them header, detail, and trailer.
  • Copy the input field line into each of the new outputs.
  • Add the expression filter line.startsWith(“00”) to the header output table.
  • Add the expression filter line.startsWith(“01”) to the detail output table.
  • Add the expression filter line.startsWith(“99”) to the trailer output table.
  • Your tMap should now look like the one shown as follows:


  • Close tMap, and drag three tExtractDelimitedFields components to the canvas, along with three tLogRow
  • Join each output from tMap to each of the tExtractDelimitedFields components.
  • Change the delimiter in each of the tExtractDelimitedFields components to comma (,).
  • Open the tLogRow components, and assign each one a schema from those listed, as follows. This can be easily done by dragging the metadata onto the tLogRow component as described in, Metadata and Schemas.
  • Link the tExtractDelimitedFields to the tLogRows, making sure that you accept the output schema.
  • Your job should now look like this:


  • Change the tLogRow components to the output Mode of Vertical, and run the job.

How it works…

tFileInputFullRow allows us to read a row of any format into tMap. This is important, because we do not want records to be rejected due to schema errors at this stage.

The start of each row is then tested for the record type; 00, 01, or 02, the header, detail, or trailer records respectively.

The different rows are then passed to a tExtractDelimitedFields component for breaking down into the individual schema columns.

There’s more…

This isn’t the only method of reading files with headers and trailers, and in fact, the best Talend method would be to use the tFileInputMSDelimited component, for this example.

This method, however, is much more flexible, in which the conditions for sending in the data as an output to each of the flows does not depend upon a fixed field being present.

Reading headers and trailers with no identifiers

This recipe shows how to parse a file that has a header and trailer records, but does not have an associated record type. Instead, the header is the first record in the file, and the trailer is the last record in the file.

Getting ready

Open the jo_cook_ch08_0070_headTrailtMapNoType job. You will see that it is a slightly changed version of the completed job from the previous recipe; the output schemas have changed.

How to achieve it…

The steps for reading headers and trailers with no identifiers are as follows:

  • Drag a tFileRowCount component onto the canvas.
  • Open the tFileRowCount, and change File Name to

           which is the same as our input file.

  • Connect an onSubJobOk trigger from the tFileRowCount component to the tFileInputDelimited.
  • Open the tMap, and add a new variable rowCount. Set its expression to Numeric.sequence(“rowNumber”,1,1).
  • Change the Filter expressions for header, detail, and trailer to those shown as follows:
Var.rowNumber == 1
Var.rowNumber !=
Var.rowNumber ==
  • Set the detail and trailer output options to Catch output rejects.
  • Your tMap should now look like this:

reading talend headers

  • Run the job, and you should see the individual row types being printed.

How it works…

The tFileRowCount component tells us how many rows are present in the file.

In the tMap, we use a sequence to calculate the current line number. If the line number is 1, then we have a header row. If it is equal to the row count (held in globalMap), then we have a trailer row, and all other rows are detail rows.

We then use the tExtractDelimitedFields to extract the individual delimited fields into a different schema for each of the row types.

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