PDF Report Generation

This guide explains how to configure automated PDF reports using the Auto Trigger feature. PDF reports allow you to visualize Elasticsearch query results with charts and deliver them on a schedule.

The schema defines the structure for configuring automated jobs.

Quick Start

To create a PDF report, add toPdf as your output format. The minimum configuration requires linking your data selections to chart entries.

Key principle: The variableName in your chart configuration must exactly match the variableName defined in your data selection.

Minimal Example

{
  "$schema": "/api/asyncJobs/schema",
  "name": "Daily Call Report",
  "description": "PDF report with call duration chart",
  "enabled": true,
  "metadata": {
    "schemaVersion": "2.0.0"
  },
  "schedule": {
    "cron": "0 6 * * *"
  },
  "type": "user",
  "pipeline": {
    "sources": [
      {
        "dataSource": "es",
        "variableName": "CallDurationOverTime",
        "parameters": [
          { "index": "calls" },
          {
            "size": 0,
            "query": {
              "bool": {
                "must": [{ "query_string": { "query": "attrs.type:call-end" } }]
              }
            },
            "aggs": {
              "agg": {
                "date_histogram": {
                  "field": "@timestamp",
                  "fixed_interval": "1h"
                }
              }
            }
          }
        ]
      }
    ],
    "transform": {
      "transformationType": "js",
      "codeFunctionReference": ""
    },
    "output": {
      "formats": [
        {
          "transformationType": "toPdf",
          "parameters": {
            "pageSize": "A4",
            "orientation": "landscape",
            "charts": [
              {
                "variableName": "CallDurationOverTime",
                "chartTitle": "Call Duration Over Time"
              }
            ]
          }
        }
      ]
    },
    "delivery": {
      "channels": []
    }
  }
}

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PDF-Specific Configuration

Page Settings

Setting	Options	Description
pageSize	A4, Letter, Legal	Page size: A4 (210 × 297 mm), Letter (8.5 × 11"), Legal (8.5 × 14")
orientation	portrait, landscape	Page orientation: vertical or horizontal

Chart Configuration

Property	Required	Description
variableName	Yes	Must match exactly the variableName from data selection
chartTitle	No	Chart title displayed above the visualization
chartType	No	Explicit visualization type (auto-inferred if omitted)
maxLength	No	Maximum items to display (for list and table types)

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Automatic Chart Type Inference

When you omit the chartType property, the system analyzes your data and automatically selects the most appropriate visualization.

Chart Selection by Data Type

Category	Condition	Chart
scalar	Single value	value
time-series	Nested buckets + nested value	multipleLine
time-series	Nested buckets only	stackedBar
time-series	No nesting	timedateBar
categorical	Nested + depth ≥ 2	sunburst
categorical	Nested + depth < 2	list
categorical	No nesting + ≤ 8 items	donut
categorical	No nesting + > 8 items	list
tabular	Tabular data	table
tuple	≤ 8 items	donut
tuple	> 8 items	list
unknown	Fallback	value

Tip: For most use cases, automatic inference produces optimal results. Only specify chartType explicitly when you need a specific visualization.

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Complete Example

A comprehensive example showing a PDF report with multiple data sources, transformations, and delivery.

Complete Example

{
  "$schema": "/api/asyncJobs/schema",
  "name": "Daily Call Summary",
  "description": "Comprehensive daily call metrics report",
  "enabled": true,
  "metadata": {
    "schemaVersion": "2.0.0"
  },
  "schedule": {
    "cron": "0 7 * * *"
  },
  "type": "user",
  "pipeline": {
    "sources": [
      {
        "dataSource": "es",
        "variableName": "CallVolume",
        "parameters": [
          { "index": "calls" },
          {
            "size": 0,
            "query": {
              "bool": {
                "must": [{ "query_string": { "query": "attrs.type:call-end" } }]
              }
            },
            "aggs": {
              "daily": {
                "date_histogram": {
                  "field": "@timestamp",
                  "calendar_interval": "day"
                },
                "aggs": {
                  "total_duration": { "sum": { "field": "duration" } }
                }
              }
            }
          }
        ]
      },
      {
        "dataSource": "es",
        "variableName": "AgentStats",
        "parameters": [
          { "index": "calls" },
          {
            "size": 0,
            "query": {
              "bool": {
                "must": [{ "query_string": { "query": "attrs.type:call-end" } }]
              }
            },
            "aggs": {
              "agents": {
                "terms": { "field": "attrs.agent" },
                "aggs": {
                  "calls": { "value_count": { "field": "duration" } },
                  "duration": { "avg": { "field": "duration" } }
                }
              }
            }
          }
        ]
      }
    ],
    "transform": {
      "transformationType": "js",
      "code": "return { callVolume: data[0], agentStats: data[1] };"
    },
    "output": {
      "formats": [
        {
          "transformationType": "toPdf",
          "parameters": {
            "pageSize": "A4",
            "orientation": "landscape",
            "charts": [
              {
                "variableName": "CallVolume",
                "chartTitle": "Daily Call Volume (Last 30 Days)",
                "chartType": "timedateBar"
              },
              {
                "variableName": "AgentStats",
                "chartTitle": "Top Agents by Call Count",
                "chartType": "list",
                "maxLength": 10
              }
            ]
          }
        },
        {
          "transformationType": "toCsv",
          "parameters": {}
        }
      ]
    },
    "delivery": {
      "channels": ["email-reporting-team"]
    },
    "action": [
      {
        "type": "saveToEs",
        "parameters": {
          "stream": "daily-call-reports",
          "timestampField": "@timestamp"
        }
      }
    ]
  }
}

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Best Practices

tip

Follow these best practices for creating effective PDF reports:

1. Use descriptive variable names — Names like CallDurationByHour are clearer than data1

2. Let inference work for you — Only specify chartType when you need a specific visualization

3. Match variable names exactly — Copy-paste to avoid typos between data selection and chart config

4. Use landscape for dashboards — Multiple charts display better in landscape orientation

5. Limit table rows — Use maxLength to keep table charts readable

6. Test with Run Now — Validate your configuration immediately before scheduling

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Troubleshooting

Common Issues

Issue	Cause	Solution
Chart shows "No Data"	Variable name mismatch between data selection and chart configuration	Verify exact spelling and case of variableName
Wrong chart type displayed	Inference selected a different type than expected	Explicitly set chartType to override automatic inference
Chart type validation error	Explicit chartType is incompatible with the data structure	Use a compatible chart type or adjust your Elasticsearch query
PDF document is excessively long	Table chart has too many rows	Add maxLength property to limit the number of displayed rows

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See Also

• Pipeline Configuration - General configuration reference for data selection, transformations, output formats, delivery channels, and actions
• Create New Report - Getting started guide