Minh Vu
Software Engineer
Hi 👋, I'm a software engineer (backend, applied AI, Elastic Stack). My blog shares practical tutorials, mostly on the Elastic Stack and Next.js. LeetCode 1756 (top 10.4% globally, Sep 2026). Actively seeking SDE roles — let's get in touch!
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In this tutorial, I will show you how to parse data from a CSV file in Logstash using the csv filter plugin.
To parse data from a CSV file in Logstash, we can use the csv filter plugin. For example:
input { file { path => "/home/dminhvu/elastic/example.csv" start_position => "beginning" sincedb_path => "/dev/null" codec => multiline { pattern => "\n" what => "next" } } } filter { csv { separator => "," # specify the separator source => "message" # parse the message field as CSV columns => ["name", "age", "location", "gender"] # specify the columns } # do anything you want with the parsed CSV data # ... } output { file { path => "/home/dminhvu/elastic/output.log" codec => "json_lines" # write to JSON lines format } }
Suppose I have the following CSV file:
Minh Vu,21,Vietnam,Male Desmond,25,United States,Male Nhi,30,Hong Kong,Female
Using the above config yields the following results:
{ "age": "21", "gender": "Male", "location": "Vietnam", "message": "Minh Vu,21,Vietnam,Male", "name": "Minh Vu" } { "age": "25", "gender": "Male", "location": "United States", "message": "Desmond,25,United States,Male", "name": "Desmond" } { "age": "30", "gender": "Female", "location": "Hong Kong", "message": "Nhi,30,Hong Kong,Female", "name": "Nhi" }
As you can see, we parsed the CSV data into JSON format. Now, we can do anything we want with the parsed data.
Suppose your CSV file contains headers, you can use the skip_header option and set to true to skip the first line:
name,age,location,gender Minh Vu,21,Vietnam,Male Desmond,25,United States,Male Nhi,30,Hong Kong,Female
The config will look like this:
filter { csv { skip_header => "true" # skip the first line separator => "," # specify the separator source => "message" # parse the message field as CSV columns => ["name", "age", "location", "gender"] # specify the columns } }
If your CSV file uses a custom separator, you can specify it using the separator option:
Minh Vu|21|Vietnam|Male Desmond|25|United States|Male Nhi|30|Hong Kong|Female
The config will look like this:
filter { csv { separator => "|" # specify the separator source => "message" # parse the message field as CSV columns => ["name", "age", "location", "gender"] # specify the columns } }
If you don't want to specify the column names, you can use the autodetect_column_names option and set to true:
filter { csv { autodetect_column_names => "true" # autodetect the columns separator => "," # specify the separator source => "message" # parse the message field as CSV } }
This only works when your first row contains headers.
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