Mocked Data

mocked_data

The Mocked Data adapter generates sample log data locally without requiring any external data source. Use this adapter for testing, learning QQL, or creating demos.

When to Use

Learning: Explore QQL syntax without setting up a backend
Demos: Show Cruncher capabilities without production data
Testing: Verify queries and configurations before connecting to real data
Offline work: No external dependencies or network access needed

Generated Data

The mocked data adapter generates synthetic log records with the following fields:

Field	Type	Example
`timestamp`	number	Unix timestamp in milliseconds
`name`	string	`"Alice"`, `"Bob"`, `"Charlie"`, etc.
`age`	number	Random age between 20-80
`address`	string	Random street address
`tags`	string	Comma-separated values like `"tag1,tag2"`
`key`	string	Random UUID-like identifier
`field0` - `field9`	number	Random numeric fields (0-9) for testing aggregations

Example Generated Record

{
  "timestamp": 1704067200000,
  "name": "Alice",
  "age": 42,
  "address": "123 Main St, Springfield",
  "tags": "important,urgent",
  "key": "abc-123-def",
  "field0": 5,
  "field1": 8,
  "field2": 3,
  ...
}

Configuration

The mocked data adapter requires no parameters:

connectors:
  - type: mocked_data
    name: test_data

That’s it! Cruncher will automatically generate data when you query this adapter.

Query Examples

Basic Filtering

where age > 40 | table name, age, address

Display names, ages, and addresses for people over 40.

Aggregation

| stats count, avg(age) by name

Group records by name and show count and average age.

Time Series

| timechart count by field0

Count records over time, grouped by the field0 numeric value.

String Operations

where contains(address, "Street") | eval address_upper = upper(address) | table address, address_upper

Find addresses containing “Street” and create an uppercase version.

Complex Pipeline

where age > 30 |
  eval age_group = if(age > 60, "senior", "adult") |
  stats count, avg(field1) by age_group |
  sort -count

Categorize by age group, aggregate, and sort by count.

Tips

Test QQL: Use mocked data to test complex queries before running them against production
Learn functions: Practice with all QQL functions without affecting real data
Profile switching: Include the mocked data adapter in a “testing” profile for quick switching

Ready to Try Real Data?

Once you’ve learned QQL with mocked data, connect to real log sources:

🐳

Docker

docker

Stream logs from local Docker containers

☸️

Kubernetes

k8s

Query pod logs from your cluster

🔷

Grafana Loki

grafana_browser

Query logs from Grafana Loki

For QQL reference, see QQL Documentation.