Query Data

Action ID: query_data

Description

Query, filter, and sort rows in a dataset with advanced filtering capabilities.

Input Parameters

Name	Type	Required	Default	Description
dataset	dropdown	✓	-	The dataset to query.
conditions	array	-	[]	List of filter conditions (empty = return all rows).
logic	dropdown	-	and	How to combine conditions (AND/OR). Options: and, or
select_columns	multi-select dropdown	-	[]	Columns to return in results (empty = return all columns).
sort_by_column	dropdown	-	null	Column to sort results by (must be in selected columns if specified).
sort_order	dropdown	-	asc	Ascending or descending order. Options: asc, desc
limit	integer	-	100	Maximum number of rows to return (1-1000).

Filter Condition Structure

Each condition in the conditions array contains:

Field	Type	Description
column	string	Column name to filter by
operator	dropdown	Comparison operator: equals, not_equals, contains, greater_than, less_than, in
value	string	Value to compare against. For 'in' operator, provide comma-separated values or JSON array

View JSON Schema

{
  "description": "Query Data node input.",
  "properties": {
    "dataset": {
      "description": "The dataset to query.",
      "title": "Dataset",
      "type": "string"
    },
    "conditions": {
      "default": [],
      "description": "List of filter conditions (empty = return all rows).",
      "items": {
        "properties": {
          "column": {
            "description": "Column name to filter by",
            "title": "Column",
            "type": "string"
          },
          "operator": {
            "default": "equals",
            "description": "Comparison operator",
            "enum": ["equals", "not_equals", "contains", "greater_than", "less_than", "in"],
            "title": "Operator",
            "type": "string"
          },
          "value": {
            "description": "Value to compare against. For 'in' operator, provide comma-separated values or JSON array",
            "title": "Value",
            "type": "string"
          }
        },
        "required": ["column", "value"],
        "type": "object"
      },
      "title": "Query Conditions",
      "type": "array"
    },
    "logic": {
      "default": "and",
      "description": "How to combine conditions (AND/OR).",
      "enum": ["and", "or"],
      "title": "Logic Operator",
      "type": "string"
    },
    "select_columns": {
      "default": [],
      "description": "Columns to return in results (empty = return all columns).",
      "items": {
        "type": "string"
      },
      "title": "Select Columns",
      "type": "array"
    },
    "sort_by_column": {
      "default": null,
      "description": "Column to sort results by (must be in selected columns if specified).",
      "title": "Sort By Column",
      "type": ["string", "null"]
    },
    "sort_order": {
      "default": "asc",
      "description": "Ascending or descending order.",
      "enum": ["asc", "desc"],
      "title": "Sort Order",
      "type": "string"
    },
    "limit": {
      "default": 100,
      "description": "Maximum number of rows to return.",
      "minimum": 1,
      "maximum": 1000,
      "title": "Limit",
      "type": "integer"
    }
  },
  "required": ["dataset"],
  "title": "QueryDataNodeInput",
  "type": "object"
}

Output Parameters

Name	Type	Description
rows	array	The rows that match the query criteria.
total	integer	Total number of matching rows (before limit).

View JSON Schema

{
  "description": "Query Data node output.",
  "properties": {
    "rows": {
      "description": "The rows that match the query criteria.",
      "items": {
        "type": "object"
      },
      "title": "Rows",
      "type": "array"
    },
    "total": {
      "description": "Total number of matching rows (before limit).",
      "title": "Total",
      "type": "integer"
    }
  },
  "required": ["rows", "total"],
  "title": "QueryDataNodeOutput",
  "type": "object"
}

How It Works

This node performs advanced filtering and querying on dataset rows. It applies filter conditions using the specified logic operator (AND/OR), supports multiple comparison operators, allows column selection for optimized data retrieval, and provides sorting capabilities. The node returns both the filtered rows and the total count of matching records, enabling pagination and result analysis.

Usage Examples

Example 1: Query All Rows

Input:

dataset: "01K8ZM9T72FNBZAGA629KZFXR5"
conditions: []
select_columns: []
limit: 100

Output:

rows: [
  {"id": "1", "name": "Alice", "age": 30, "status": "active"},
  {"id": "2", "name": "Bob", "age": 25, "status": "inactive"},
  ...
]
total: 250

Example 2: Filter by Single Condition

Input:

dataset: "01K8ZM9T72FNBZAGA629KZFXR5"
conditions: [
  {
    "column": "status",
    "operator": "equals",
    "value": "active"
  }
]
limit: 50

Output:

rows: [
  {"id": "1", "name": "Alice", "age": 30, "status": "active"},
  {"id": "5", "name": "Charlie", "age": 28, "status": "active"}
]
total: 120

Example 3: Multiple Conditions with AND Logic

Input:

dataset: "01K8ZM9T72FNBZAGA629KZFXR5"
conditions: [
  {
    "column": "status",
    "operator": "equals",
    "value": "active"
  },
  {
    "column": "age",
    "operator": "greater_than",
    "value": "25"
  }
]
logic: "and"
select_columns: ["name", "age", "status"]
sort_by_column: "age"
sort_order: "desc"
limit: 20

Output:

rows: [
  {"name": "Alice", "age": 30, "status": "active"},
  {"name": "Charlie", "age": 28, "status": "active"}
]
total: 45

Example 4: Using IN Operator

Input:

dataset: "01K8ZM9T72FNBZAGA629KZFXR5"
conditions: [
  {
    "column": "department",
    "operator": "in",
    "value": "sales,marketing,support"
  }
]
limit: 100

Output:

rows: [
  {"id": "1", "name": "Alice", "department": "sales"},
  {"id": "2", "name": "Bob", "department": "marketing"},
  {"id": "3", "name": "Charlie", "department": "support"}
]
total: 78

Example 5: Contains Search

Input:

dataset: "01K8ZM9T72FNBZAGA629KZFXR5"
conditions: [
  {
    "column": "email",
    "operator": "contains",
    "value": "@company.com"
  }
]
select_columns: ["name", "email"]
limit: 50

Output:

rows: [
  {"name": "Alice", "email": "[email protected]"},
  {"name": "Bob", "email": "[email protected]"}
]
total: 156

Common Use Cases

• Data Retrieval: Fetch specific records from datasets based on business logic

• Search Functionality: Implement search features using contains operator for text matching

• Analytics and Reporting: Extract filtered data subsets for analysis and visualization

• Data Export: Query and prepare data before exporting to external systems

• Workflow Triggers: Find records matching specific criteria to trigger downstream actions

• Pagination: Use limit and total to implement paginated data views in applications

• Multi-Condition Filtering: Combine multiple filter criteria with AND/OR logic for complex queries

• Sorted Results: Retrieve data in specific order for ranking or time-based analysis

Error Handling

Error Type	Cause	Solution
Dataset Not Found	Dataset ID doesn't exist	Verify the dataset ID is correct and the dataset exists
Invalid Column	Column name in condition doesn't exist	Check available columns in the dataset schema
Invalid Operator	Operator value not in allowed list	Use one of: equals, not_equals, contains, greater_than, less_than, in
Sort Column Not Selected	sort_by_column not in select_columns	Include sort column in select_columns or leave it empty
Invalid Limit	Limit outside 1-1000 range	Set limit between 1 and 1000
Empty Dataset	Dataset has no rows	Verify dataset has been populated with data
Invalid Logic	Logic value not 'and' or 'or'	Use either 'and' or 'or' for logic parameter
Malformed Condition	Missing required fields in condition	Ensure each condition has column, operator, and value

Notes

• Performance: Use select_columns to retrieve only needed fields for better performance with large datasets.

• Pagination: The total field shows all matching records, while rows respects the limit for pagination implementation.

• Dynamic Dropdowns: The dataset, select_columns, and sort_by_column fields dynamically populate based on your available datasets and their schemas.

• IN Operator Format: For the 'in' operator, values can be comma-separated ("val1,val2,val3") or JSON array format (["val1","val2","val3"]).

• Empty Conditions: If conditions array is empty, all rows from the dataset will be returned (subject to limit).

• Limit Range: Maximum limit is capped at 1000 rows per query for performance and resource management.

• Case Sensitivity: The contains operator behavior may vary based on database configuration. Test with your specific dataset.

• Null Values: Be aware of how comparison operators handle null values in your dataset columns.

• Query Optimization: For frequently accessed queries, consider creating filtered views or using appropriate indexes on dataset columns.