Filtering Explained

Zilliz Cloud provides powerful filtering capabilities that enable precise querying of your data. Filter expressions allow you to target specific scalar fields and refine search results with different conditions. This guide explains how to use filter expressions in Zilliz Cloud clusters, with examples focused on query operations. You can also apply these filters in search and delete requests.

Basic operators

Zilliz Cloud supports several basic operators for filtering data:

• Comparison Operators: ==, !=, >, \<, >=, and <= allow filtering based on numeric or text fields.

• Range Filters: IN and LIKE help match specific value ranges or sets.

• Arithmetic Operators: +, -, *, /, %, and ** are used for calculations involving numeric fields.

• Logical Operators: AND, OR, and NOT combine multiple conditions into complex expressions.

Example: Filtering by Color

To find entities with primary colors (red, green, or blue) in a scalar field color, use the following filter expression:

filter='color in ["red", "green", "blue"]'

Example: Filtering JSON Fields

Zilliz Cloud allows referencing keys in JSON fields. For instance, if you have a JSON field product with keys price and model, and want to find products with a specific model and price lower than 1,850, use this filter expression:

filter='product["model"] == "JSN-087" AND product["price"] < 1850'

Example: Filtering Array Fields

If you have an array field history_temperatures containing the records of average temperatures reported by observatories since the year 2000, and want to find observatories where the temperature in 2009 (the 10th recorded ) exceeds 23°C, use this expression:

filter='history_temperatures[10] > 23'

For more information on these basic operators, refer to Basic Operators.

Data type-specific operators

Zilliz Cloud provides advanced filtering operators for specific data types, such as JSON, ARRAY, and VARCHAR fields.

JSON field-specific operators

Zilliz Cloud offers advanced operators for querying JSON fields, enabling precise filtering within complex JSON structures:

JSON_CONTAINS(identifier, jsonExpr): Checks if a JSON expression exists in the field.

# JSON data: {"tags": ["electronics", "sale", "new"]}
filter='json_contains(tags, "sale")'

JSON_CONTAINS_ALL(identifier, jsonExpr): Ensures all elements of the JSON expression are present.

# JSON data: {"tags": ["electronics", "sale", "new", "discount"]}
filter='json_contains_all(tags, ["electronics", "sale", "new"])'

JSON_CONTAINS_ANY(identifier, jsonExpr): Filters for entities where at least one element exists in the JSON expression.

# JSON data: {"tags": ["electronics", "sale", "new"]}
filter='json_contains_any(tags, ["electronics", "new", "clearance"])'

For more details on JSON operators, refer to JSON Operators.

ARRAY field-specific operators

Zilliz Cloud provides advanced filtering operators for array fields, such as ARRAY_CONTAINS, ARRAY_CONTAINS_ALL, ARRAY_CONTAINS_ANY, and ARRAY_LENGTH, which allow fine-grained control over array data:

ARRAY_CONTAINS: Filters entities containing a specific element.

filter="ARRAY_CONTAINS(history_temperatures, 23)"

ARRAY_CONTAINS_ALL: Filters entities where all elements in a list are present.

filter="ARRAY_CONTAINS_ALL(history_temperatures, [23, 24])"

ARRAY_CONTAINS_ANY: Filters entities containing any element from the list.

filter="ARRAY_CONTAINS_ANY(history_temperatures, [23, 24])"

ARRAY_LENGTH: Filters based on the length of the array.

filter="ARRAY_LENGTH(history_temperatures) < 10"

For more details on array operators, see ARRAY Operators.