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Elasticsearchquery~10 mins

Ingest processors (grok, date, rename) in Elasticsearch - Step-by-Step Execution

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Concept Flow - Ingest processors (grok, date, rename)
Start: Receive document
Apply grok processor
Apply date processor
Apply rename processor
Output: Transformed document
The document flows through grok to parse text, then date to convert strings to dates, and finally rename to change field names.
Execution Sample
Elasticsearch
PUT _ingest/pipeline/my_pipeline
{
  "processors": [
    {"grok": {"field": "message", "patterns": ["%{COMMONAPACHELOG}"]}},
    {"date": {"field": "timestamp", "formats": ["dd/MMM/yyyy:HH:mm:ss Z"]}},
    {"rename": {"field": "clientip", "target_field": "ip_address"}}
  ]
}
This pipeline parses an Apache log message, converts the timestamp to a date, and renames the client IP field.
Execution Table
StepProcessorInput DocumentActionOutput Document
1grok{"message": "127.0.0.1 - frank [10/Oct/2000:13:55:36 -0700] \"GET /apache.gif HTTP/1.0\" 200 2326"}Parse message into fields like clientip, timestamp, verb, etc.{"message": "127.0.0.1 - frank [10/Oct/2000:13:55:36 -0700] \"GET /apache.gif HTTP/1.0\" 200 2326", "clientip": "127.0.0.1", "timestamp": "10/Oct/2000:13:55:36 -0700", "verb": "GET", "request": "/apache.gif", "response": "200", "bytes": "2326"}
2date{"message": "127.0.0.1 - frank [10/Oct/2000:13:55:36 -0700] \"GET /apache.gif HTTP/1.0\" 200 2326", "clientip": "127.0.0.1", "timestamp": "10/Oct/2000:13:55:36 -0700", "verb": "GET", "request": "/apache.gif", "response": "200", "bytes": "2326"}Convert timestamp string to ISO8601 date format{"message": "127.0.0.1 - frank [10/Oct/2000:13:55:36 -0700] \"GET /apache.gif HTTP/1.0\" 200 2326", "clientip": "127.0.0.1", "timestamp": "2000-10-10T13:55:36-07:00", "verb": "GET", "request": "/apache.gif", "response": "200", "bytes": "2326"}
3rename{"message": "127.0.0.1 - frank [10/Oct/2000:13:55:36 -0700] \"GET /apache.gif HTTP/1.0\" 200 2326", "clientip": "127.0.0.1", "timestamp": "2000-10-10T13:55:36-07:00", "verb": "GET", "request": "/apache.gif", "response": "200", "bytes": "2326"}Rename field 'clientip' to 'ip_address'{"message": "127.0.0.1 - frank [10/Oct/2000:13:55:36 -0700] \"GET /apache.gif HTTP/1.0\" 200 2326", "ip_address": "127.0.0.1", "timestamp": "2000-10-10T13:55:36-07:00", "verb": "GET", "request": "/apache.gif", "response": "200", "bytes": "2326"}
💡 All processors applied, document transformed with parsed fields, date converted, and field renamed.
Variable Tracker
VariableStartAfter grokAfter dateAfter rename
document{"message": "127.0.0.1 - frank [10/Oct/2000:13:55:36 -0700] \"GET /apache.gif HTTP/1.0\" 200 2326"}{"message": "127.0.0.1 - frank [10/Oct/2000:13:55:36 -0700] \"GET /apache.gif HTTP/1.0\" 200 2326", "clientip": "127.0.0.1", "timestamp": "10/Oct/2000:13:55:36 -0700", "verb": "GET", "request": "/apache.gif", "response": "200", "bytes": "2326"}{"message": "127.0.0.1 - frank [10/Oct/2000:13:55:36 -0700] \"GET /apache.gif HTTP/1.0\" 200 2326", "clientip": "127.0.0.1", "timestamp": "2000-10-10T13:55:36-07:00", "verb": "GET", "request": "/apache.gif", "response": "200", "bytes": "2326"}{"message": "127.0.0.1 - frank [10/Oct/2000:13:55:36 -0700] \"GET /apache.gif HTTP/1.0\" 200 2326", "ip_address": "127.0.0.1", "timestamp": "2000-10-10T13:55:36-07:00", "verb": "GET", "request": "/apache.gif", "response": "200", "bytes": "2326"}
Key Moments - 3 Insights
Why does the 'timestamp' field change format after the date processor?
The date processor converts the timestamp string from a custom format to a standard ISO8601 date format, as shown in execution_table step 2.
What happens if the rename processor tries to rename a field that does not exist?
The rename processor will fail or skip renaming if the source field is missing; in our example, it successfully renames 'clientip' to 'ip_address' as shown in step 3.
How does the grok processor extract multiple fields from a single message string?
Grok uses patterns to parse the message and create new fields like 'clientip' and 'timestamp', demonstrated in execution_table step 1.
Visual Quiz - 3 Questions
Test your understanding
Look at the execution table, what is the value of 'timestamp' after the date processor runs?
A"2000-10-10T13:55:36-07:00"
B"10/Oct/2000:13:55:36 -0700"
C"13:55:36"
D"Oct 10 2000"
💡 Hint
Check execution_table row 2, Output Document column.
At which step is the field 'clientip' renamed to 'ip_address'?
AStep 1
BStep 2
CStep 3
DNo renaming happens
💡 Hint
Look at execution_table step 3, Action and Output Document.
If the grok processor fails to parse the message, what happens to the document in the pipeline?
AThe document proceeds unchanged to the date processor
BThe pipeline stops with an error
CThe rename processor runs anyway
DThe timestamp field is automatically created
💡 Hint
Grok parsing failure usually stops the pipeline; see key_moments about grok processor behavior.
Concept Snapshot
Ingest processors transform documents step-by-step.
Grok parses text into fields using patterns.
Date converts string timestamps to date objects.
Rename changes field names.
Processors run in order, modifying the document.
Errors in processors can stop the pipeline.
Full Transcript
This visual execution shows how an Elasticsearch ingest pipeline processes a document using grok, date, and rename processors. First, the grok processor parses a log message string into multiple fields like clientip and timestamp. Then, the date processor converts the timestamp string into a standard date format. Finally, the rename processor changes the field name clientip to ip_address. The execution table traces each step with input and output documents, showing how the document changes. The variable tracker highlights the document state after each processor. Key moments clarify common confusions such as why the timestamp format changes and what happens if rename targets a missing field. The quiz tests understanding by asking about field values and processor effects. This step-by-step flow helps beginners see exactly how ingest processors transform data in Elasticsearch.