Find documents

Finds documents in a collection using filter and sort clauses.

Result

  • Python

  • TypeScript

  • Java

  • curl

Returns a cursor (Cursor) for iterating over documents that match the specified filter and sort clauses. For vector search (with $vector or $vectorize), returns a single page of up to 1000 documents (or a lower amount if specified) instead of a cursor.

The fields included in the returned documents depend on the subset of fields that were requested in the projection.

If requested and applicable, each document will also include a $similarity key with a numeric similarity score that represents the closeness of the sort vector and the document’s vector.

If requested when executing a vector search with vectorize, the result will also include the sort vector.

The cursor is compatible with for loops. You must iterate over the cursor to fetch matching documents. The cursor transitions through the following statuses: . initialized: no documents have been consumed . running: some but not all of the documents have been consumed . exhausted: all documents have been consumed

If you need a list of all results, you can call list() on the cursor instead of iterating over the cursor. However, the time and memory required for this operation depend on the number of results.

Returns a cursor (FindCursor<FoundDoc<Schema>>) for iterating over documents that match the specified filter and sort clauses.

For vector search (with $vector or $vectorize), returns a single page of up to 1000 documents (or a lower amount if specified) instead of a cursor.

The fields included in the returned documents depend on the subset of fields that were requested in the projection.

If requested and applicable, each document will also include a $similarity key with a numeric similarity score that represents the closeness of the sort vector and the document’s vector.

If requested when executing a vector search with vectorize, the result will also include the sort vector.

The cursor is compatible with for loops. You must iterate over the cursor to fetch matching documents. The cursor transitions through the following statuses: . initialized: no documents have been consumed . running: some but not all of the documents have been consumed . exhausted: all documents have been consumed

If you need a list of all results, you can call list() on the cursor instead of iterating over the cursor. However, the time and memory required for this operation depend on the number of results.

Returns a cursor (FindIterable<T>) for iterating over documents that match the specified filter and sort clauses.

For vector search (with $vector or $vectorize), returns a single page of up to 1000 documents (or a lower amount if specified) instead of a cursor.

The fields included in the returned documents depend on the subset of fields that were requested in the projection.

If requested and applicable, each document will also include a $similarity key with a numeric similarity score that represents the closeness of the sort vector and the document’s vector.

If requested when executing a vector search with vectorize, the result will also include the sort vector.

The cursor is an Iterable and is compatible with for loops. You must iterate over the cursor to fetch matching documents.

If you need a list of all results, you can use .all() to exhaust the cursor. However, the time and memory required for this operation depend on the number of results.

The response includes a data.documents property, which is an array of objects representing documents that match the specified filter and sort clauses.

The fields included in the returned documents depend on the subset of fields that were requested in the projection. If requested and applicable, each document will also include a $similarity key with a numeric similarity score that represents the closeness of the sort vector and the document’s vector.

If the query supports pagination, the response also includes a data.nextPageState property, which indicates the ID of the next page of results, if any. For non-vector searches, the results will be paginated if more than 20 documents match the specified filter and sort clauses.

For vector search (with $vector or $vectorize), returns a single page of up to 1000 documents (or a lower amount if specified) instead of a cursor.

If requested when executing a vector search with vectorize, the result also includes a status.sortVector property, which is the sort vector used for the search.

Example response:

{
  "data": {
    "documents":[
      {
        "_id":"85a54382-9227-4075-a543-829227407556",
        "title":"Within Silence of the Past",
        "isCheckedOut":false
      },
      {
        "_id":"aa762475-4fc1-4477-b624-754fc1f477c7",
        "title":"Beyond Dreams and Forgotten Worlds",
        "isCheckedOut":false
      }
    ],
    "nextPageState":"LQAAAAEBAAAAJGQ2OTk5NzY2LTgyODQtNDc3Mi05OTk3LTY2ODI4NGU3NzJjYQDwf///6wA="
  }
}

Example response if no documents were found:

{
  "data": {
    "documents": [],
    "nextPageState": null
  }
}

Parameters

  • Python

  • TypeScript

  • Java

  • curl

Name Type Summary

filter

Optional[Dict[str, Any]]

A predicate expressed as a dictionary according to the Data API filter syntax. For example: {}, {"name": "John"}, {"price": {"$lt": 100}}, {"$and": [{"name": "John"}, {"price": {"$lt": 100}}]}. For a list of available operators, see Data API operators. If you apply selective indexing when you create a collection, you can’t reference non-indexed fields in sort or filter queries.

projection

Optional[Union[Iterable[str], Dict[str, bool]]]

Select a subset of fields to include in the response for each returned document. If empty or unset, the default projection is used. The default projection doesn’t always include all document fields. For more information and examples, see Projection clauses.

skip

Optional[int]

Specify a number of documents to bypass (skip) before returning documents. The first n documents matching the query are discarded from the results, and the results begin at the skip+1 document. For example, if skip=5, the first 5 documents are discarded, and the results begin at the 6th document.

You can use this parameter only in conjunction with an explicit sort criterion of the ascending/descending type. It is not valid with vector search (with $vector or $vectorize).

limit

Optional[int]

Limit the total number of documents returned. Once limit is reached, or the cursor is exhausted due to lack of matching documents, nothing more is returned.

include_similarity

Optional[bool]

If true, the response includes a $similarity key with the numeric similarity score that represents the closeness of the sort vector and the document’s vector. Only valid for vector search with $vector or $vectorize.

include_sort_vector

Optional[bool]

If true, the response includes the sortVector. The default is false. This is only relevant if sort includes either $vector or $vectorize and you want the response to include the sort vector. This can be useful for $vectorize because you don’t know the sort vector in advance.

You can’t use include_sort_vector with find_one(). However, you can use include_sort_vector and limit=1 with find().

sort

Optional[Dict[str, Any]]

Use this dictionary parameter to perform a vector search or set the order in which documents are returned. For vector searches, this parameter can use either $vector or $vectorize, but not both in the same request. For more information and examples, see Sort clauses. If you apply selective indexing when you create a collection, you can’t reference non-indexed fields in sort or filter queries.

max_time_ms

Optional[int]

A timeout, in milliseconds, for each underlying HTTP request used to fetch documents as you iterate over the cursor. This method uses the collection-level timeout by default.
Name Type Summary

filter

Filter<Schema>

A filter to select the documents to find. For a list of available operators, see Data API operators. If you apply selective indexing when you create a collection, you can’t reference non-indexed fields in sort or filter queries.

options?

FindOptions

The options for this operation.

Options (FindOptions):

Name Type Summary

projection?

Projection

Specifies which fields to include or exclude in the returned documents. If empty or unset, the default projection is used. The default projection doesn’t always include all document fields. For more information and examples, see Projection clauses.

When specifying a projection, make sure that you handle the return type carefully. Consider type-casting.

includeSimilarity?

boolean

If true, the response includes a $similarity key with the numeric similarity score that represents the closeness of the sort vector and the document’s vector. Only valid for vector search with $vector or $vectorize.

includeSortVector?

boolean

If true, the response includes the sortVector. The default is false. This is only relevant if sort includes either $vector or $vectorize and you want the response to include the sort vector. This can be useful for $vectorize because you don’t know the sort vector in advance.

You can’t use includeSortVector with findOne(), but you can use includeSortVector and limit: 1 with find(). However, because vector search is approximate (as in approximate nearest neighbor), the lower your limit, the more likely you are to find an approximate, but not maximal, match.

You can also access this through await cursor.getSortVector().

sort?

Sort

Perform a vector search or set the order in which documents are returned. For vector searches, this parameter can use either $vector or $vectorize, but not both in the same request. For more information and examples, see Sort clauses. If you apply selective indexing when you create a collection, you can’t reference non-indexed fields in sort or filter queries.

skip?

number

Specify a number of documents to bypass (skip) before returning documents. The first n documents matching the query are discarded from the results, and the results begin at the skip+1 document. For example, if skip: 5, the first 5 documents are discarded, and the results begin at the 6th document.

You can use this parameter only in conjunction with an explicit sort criterion of the ascending/descending type. It is not valid with vector search (with $vector or $vectorize).

limit?

number

Limit the total number of documents returned in the lifetime of the cursor. Once limit is reached, or the cursor is exhausted due to lack of matching documents, nothing more is returned.

maxTimeMS?

number

The maximum time in milliseconds that the client should wait for the operation to complete each underlying HTTP request as you iterate over the cursor.
Name Type Summary

filter

Filter

Criteria list to filter documents. The filter is a JSON object that can contain any valid Data API filter expression. For a list of available operators, see Data API operators. If you apply selective indexing when you create a collection, you can’t reference non-indexed fields in sort or filter queries.

options (optional)

FindOptions

Set the different options for the find operation, including the following:

  • sort(): Perform a vector search or set the order in which documents are returned. For vector searches, this parameter can use either $vector or $vectorize, but not both in the same request. For more information and examples, see Sort clauses. If you apply selective indexing when you create a collection, you can’t reference non-indexed fields in sort or filter queries.

  • projection(): A list of flags that select a subset of fields to include in the response for each returned document. If empty or unset, the default projection is used. The default projection doesn’t always include all document fields. For more information and examples, see Projection clauses.

  • includeSimilarity(): If true, the response includes a $similarity key with the numeric similarity score that represents the closeness of the sort vector and the document’s vector. This is only valid for vector search with $vector or $vectorize.

  • includeSortVector(): If true, the response includes the sortVector. The default is false. This is only relevant if sort includes either $vector or $vectorize and you want the response to include the sort vector. This can be useful for $vectorize because you don’t know the sort vector in advance.

    You can’t use includeSortVector with findOne(). However, you can use includeSortVector and limit(1) with find().

  • limit: Limit the total number of documents returned. Once limit is reached, or the cursor is exhausted due to lack of matching documents, nothing more is returned.

  • skip: Specify a number of documents to bypass (skip) before returning documents. The first n documents matching the query are discarded from the results, and the results begin at the skip+1 document. For example, if skip: 5, the first 5 documents are discarded, and the results begin at the 6th document.

    You can use this parameter only in conjunction with an explicit sort criterion of the ascending/descending type. It is not valid with vector search (with $vector or $vectorize).
Name Type Summary

find

command

The Data API command to retrieve multiple document in a collection based on one or more of filter, sort, projection, and options.

filter

object

An object that defines filter criteria using the Data API filter syntax. For example: {}, {"name": "John"}, {"price": {"$lt": 100}}, {"$and": [{"name": "John"}, {"price": {"$lt": 100}}]}. For a list of available operators, see Data API operators. If you apply selective indexing when you create a collection, you can’t reference non-indexed fields in sort or filter queries.

sort

object

Perform a vector search or set the order in which documents are returned. For vector searches, this parameter can use either $vector or $vectorize, but not both in the same request. For more information and examples, see Sort clauses. If you apply selective indexing when you create a collection, you can’t reference non-indexed fields in sort or filter queries.

projection

object

Select a subset of fields to include in the response for each returned document. If empty or unset, the default projection is used. The default projection doesn’t always include all document fields. For more information and examples, see Projection clauses.

options.includeSimilarity

boolean

If true, the response includes a $similarity key with the numeric similarity score that represents the closeness of the sort vector and each document’s vector. This is only valid for vector search with $vector or $vectorize.

"options": { "includeSimilarity": true }

options.includeSortVector

boolean

If true, the response includes the sortVector. The default is false. This is only relevant if sort includes either $vector or $vectorize and you want the response to include the sort vector. This can be useful for $vectorize because you don’t know the sort vector in advance.

"options": { "includeSortVector": true }

You can’t use includeSortVector with findOne, but you can use includeSortVector and limit: 1 with find. However, because vector search is approximate (as in approximate nearest neighbor), the lower your limit, the more likely you are to find an approximate, but not maximal, match.

options.skip

integer

Specify a number of documents to bypass (skip) before returning documents. The first n documents matching the query are discarded from the results, and the results begin at the skip+1 document. For example, if "skip": 5, the first 5 documents are discarded, and the results begin at the 6th document.

You can use this parameter only in conjunction with an explicit sort criterion of the ascending/descending type. It is not valid with vector search (with $vector or $vectorize).

options.limit

integer

Limit the total number of documents returned. Pagination can occur if more than 20 documents are returned in the current set of matching documents. Once the limit is reached, either in a single response or the last page of a paginated response, nothing more is returned.

Examples

The following examples demonstrate how to find documents in a collection.

Use filters to find documents

You can use a filter to find documents that match specific criteria. For example, you can find documents with an isCheckedOut value of false and a numberOfPages value less than 300.

For a list of available filter operators and more examples, see Data API operators.

Filters can use only indexed fields. If you apply selective indexing when you create a collection, you can’t reference non-indexed fields in a filter.

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
database = client.get_database("ASTRA_DB_API_ENDPOINT")
collection = database.get_collection("COLLECTION_NAME")

# Find documents
cursor = collection.find(
    {
        "$and": [
            {"isCheckedOut": False},
            {"numberOfPages": {"$lt": 300}},
        ]
    }
)

# Iterate over the found documents
for document in cursor:
    print(document)
import { DataAPIClient } from '@datastax/astra-db-ts';

// Get an existing collection
const client = new DataAPIClient('ASTRA_DB_APPLICATION_TOKEN');
const database = client.db('ASTRA_DB_API_ENDPOINT');
const collection = database.collection('COLLECTION_NAME');

(async function () {
  // Find documents
  const cursor = collection.find({
    $and: [{ isCheckedOut: false }, { numberOfPages: { $lt: 300 } }],
  });

  // Iterate over the found documents
  for await (const document of cursor) {
    console.log(document);
  }
})();
package com.datastax.astra.client.collection;

import com.datastax.astra.client.Collection;
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.model.Document;
import com.datastax.astra.client.model.Filter;
import com.datastax.astra.client.model.Filters;
import com.datastax.astra.client.model.FindOptions;
import com.datastax.astra.client.model.FindIterable;

public class Find {

    public static void main(String[] args) {
        // Get an existing collection
        Collection<Document> collection = new DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
            .getDatabase("ASTRA_DB_API_ENDPOINT")
            .getCollection("COLLECTION_NAME");

        // Find documents
        Filter filter = Filters.and(
          Filters.eq("isCheckedOut", false),
          Filters.lt("numberOfPages", 300));
        FindIterable<Document> cursor = collection.find(filter);

        // Iterate over the found documents
        for (Document document : cursor) {
            System.out.println(document);
        }
    }
}
curl -sS -L -X POST "ASTRA_DB_API_ENDPOINT/api/json/v1/ASTRA_DB_KEYSPACE/ASTRA_DB_COLLECTION" \
--header "Token: ASTRA_DB_APPLICATION_TOKEN" \
--header "Content-Type: application/json" \
--data '{
  "find": {
    "filter": {"$and": [
      {"isCheckedOut": false},
      {"numberOfPages": {"$lt": 300}}
    ]}
  }
}'

Use vector search to find documents

To find the documents whose $vector value is most similar to a given vector, use a sort with the vector embeddings that you want to match. For more information, see Perform a vector search.

Vector search is only available for vector-enabled collections. For more information, see Vector and vectorize.

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
database = client.get_database("ASTRA_DB_API_ENDPOINT")
collection = database.get_collection("COLLECTION_NAME")

# Find documents
cursor = collection.find(
    {},
    sort={"$vector": [.12, .52, .32]}
)

# Iterate over the found documents
for document in cursor:
    print(document)
import { DataAPIClient } from '@datastax/astra-db-ts';

// Get an existing collection
const client = new DataAPIClient('ASTRA_DB_APPLICATION_TOKEN');
const database = client.db('ASTRA_DB_API_ENDPOINT');
const collection = database.collection('COLLECTION_NAME');

// Find documents
(async function () {
  const cursor = collection.find(
    {},
    { sort: { $vector: [.12, .52, .32] } }
  );

  // Iterate over the found documents
  for await (const document of cursor) {
    console.log(document);
  }
})();
package com.datastax.astra.client.collection;

import com.datastax.astra.client.Collection;
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.model.Document;
import com.datastax.astra.client.model.Filter;
import com.datastax.astra.client.model.Filters;
import com.datastax.astra.client.model.FindOptions;
import com.datastax.astra.client.model.FindIterable;

public class Find {

    public static void main(String[] args) {
        // Get an existing collection
        Collection<Document> collection = new DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
            .getDatabase("ASTRA_DB_API_ENDPOINT")
            .getCollection("COLLECTION_NAME");

        // Find documents
        FindOptions options = new FindOptions()
            .sort(new float[] {0.12f, 0.52f, 0.32f});
        FindIterable<Document> cursor = collection.find(options);
        // Iterate over the found documents
        for (Document document : cursor) {
            System.out.println(document);
        }
    }
}
curl -sS -L -X POST "ASTRA_DB_API_ENDPOINT/api/json/v1/ASTRA_DB_KEYSPACE/ASTRA_DB_COLLECTION" \
--header "Token: ASTRA_DB_APPLICATION_TOKEN" \
--header "Content-Type: application/json" \
--data '{
  "find": {
    "sort": { "$vector": [.12, .52, .32] }
  }
}'

Use vector search and vectorize to find documents

To find the document whose $vector value is most similar to the $vector value of a given search string, use a sort with the search string that you want to vectorize and match. For more information, see Perform a vector search.

Vector search with vectorize is only available for collections that have vectorize enabled. For more information, see Vector and vectorize.

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
database = client.get_database("ASTRA_DB_API_ENDPOINT")
collection = database.get_collection("COLLECTION_NAME")

# Find documents
cursor = collection.find(
    {},
    sort={"$vectorize": "Text to vectorize"}
)

# Iterate over the found documents
for document in cursor:
    print(document)
import { DataAPIClient } from '@datastax/astra-db-ts';

// Get an existing collection
const client = new DataAPIClient('ASTRA_DB_APPLICATION_TOKEN');
const database = client.db('ASTRA_DB_API_ENDPOINT');
const collection = database.collection('COLLECTION_NAME');

// Find documents
(async function () {
  const cursor = collection.find(
    {},
    { sort: { $vectorize: "Text to vectorize" } }
  );

  // Iterate over the found documents
  for await (const document of cursor) {
    console.log(document);
  }
})();
package com.datastax.astra.client.collection;

import com.datastax.astra.client.Collection;
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.model.Document;
import com.datastax.astra.client.model.Filter;
import com.datastax.astra.client.model.Filters;
import com.datastax.astra.client.model.FindOptions;
import com.datastax.astra.client.model.FindIterable;

public class Find {

    public static void main(String[] args) {
        // Get an existing collection
        Collection<Document> collection = new DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
            .getDatabase("ASTRA_DB_API_ENDPOINT")
            .getCollection("COLLECTION_NAME");

        // Find documents
        FindOptions options = new FindOptions()
            .sort("Text to vectorize");
        FindIterable<Document> cursor = collection.find(options);

        // Iterate over the found documents
        for (Document document : cursor) {
            System.out.println(document);
        }
    }
}
curl -sS -L -X POST "ASTRA_DB_API_ENDPOINT/api/json/v1/ASTRA_DB_KEYSPACE/ASTRA_DB_COLLECTION" \
--header "Token: ASTRA_DB_APPLICATION_TOKEN" \
--header "Content-Type: application/json" \
--data '{
  "find": {
    "sort": { "$vectorize": "Text to vectorize" }
  }
}'

Use sorting to find documents

You can use a sort clause to sort documents by one or more fields.

For more information, see Sort clauses.

Sort clauses can use only indexed fields. If you apply selective indexing when you create a collection, you can’t reference non-indexed fields in sort queries.

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient, constants

# Get an existing collection
client = DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
database = client.get_database("ASTRA_DB_API_ENDPOINT")
collection = database.get_collection("COLLECTION_NAME")

# Find documents
cursor = collection.find(
    {"metadata.language": "English"},
    sort={
        "rating": constants.SortDocuments.ASCENDING,
        "title": constants.SortDocuments.DESCENDING,
    }
)

# Iterate over the found documents
for document in cursor:
    print(document)
import { DataAPIClient } from '@datastax/astra-db-ts';

// Get an existing collection
const client = new DataAPIClient('ASTRA_DB_APPLICATION_TOKEN');
const database = client.db('ASTRA_DB_API_ENDPOINT');
const collection = database.collection('COLLECTION_NAME');

// Find documents
(async function () {
  const cursor = collection.find(
    { "metadata.language": "English" },
    { sort: {
      rating: 1, // ascending
      title: -1 // descending
    } }
  );

  // Iterate over the found documents
  for await (const document of cursor) {
    console.log(document);
  }
})();
package com.datastax.astra.client.collection;

import com.datastax.astra.client.Collection;
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.model.Document;
import com.datastax.astra.client.model.Filter;
import com.datastax.astra.client.model.Filters;
import com.datastax.astra.client.model.FindOptions;
import com.datastax.astra.client.model.FindIterable;

public class Find {

    public static void main(String[] args) {
        // Get an existing collection
        Collection<Document> collection = new DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
            .getDatabase("ASTRA_DB_API_ENDPOINT")
            .getCollection("COLLECTION_NAME");

        // Find documents
        Filter filter = Filters.eq("metadata.language", "English");
        FindOptions options = new FindOptions()
            .sort(Sorts.ascending("rating"))
            .sort(Sorts.descending("title"));
        FindIterable<Document> cursor = collection.find(filter, options);

        // Iterate over the found documents
        for (Document document : cursor) {
            System.out.println(document);
        }
    }
}
curl -sS -L -X POST "ASTRA_DB_API_ENDPOINT/api/json/v1/ASTRA_DB_KEYSPACE/ASTRA_DB_COLLECTION" \
--header "Token: ASTRA_DB_APPLICATION_TOKEN" \
--header "Content-Type: application/json" \
--data '{
  "find": {
    "filter": { "metadata.language": "English" },
    "sort": {
      "rating": 1,
      "title": -1
    }
  }
}'

Use an empty filter to find all documents

To find all documents, use an empty filter.

You should avoid this if you have a large number of documents.

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
database = client.get_database("ASTRA_DB_API_ENDPOINT")
collection = database.get_collection("COLLECTION_NAME")

# Find documents
cursor = collection.find({})

# Iterate over the found documents
for document in cursor:
    print(document)
import { DataAPIClient } from '@datastax/astra-db-ts';

// Get an existing collection
const client = new DataAPIClient('ASTRA_DB_APPLICATION_TOKEN');
const database = client.db('ASTRA_DB_API_ENDPOINT');
const collection = database.collection('COLLECTION_NAME');

(async function () {
  // Find documents
  const cursor = collection.find({});

  // Iterate over the found documents
  for await (const document of cursor) {
    console.log(document);
  }
})();
package com.datastax.astra.client.collection;

import com.datastax.astra.client.Collection;
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.model.Document;
import com.datastax.astra.client.model.Filter;
import com.datastax.astra.client.model.Filters;
import com.datastax.astra.client.model.FindOptions;
import com.datastax.astra.client.model.FindIterable;

public class Find {

    public static void main(String[] args) {
        // Get an existing collection
        Collection<Document> collection = new DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
            .getDatabase("ASTRA_DB_API_ENDPOINT")
            .getCollection("COLLECTION_NAME");

        // Find documents
        FindIterable<Document> cursor = collection.find();

        // Iterate over the found documents
        for (Document document : cursor) {
            System.out.println(document);
        }
    }
}
curl -sS -L -X POST "ASTRA_DB_API_ENDPOINT/api/json/v1/ASTRA_DB_KEYSPACE/ASTRA_DB_COLLECTION" \
--header "Token: ASTRA_DB_APPLICATION_TOKEN" \
--header "Content-Type: application/json" \
--data '{
  "find": {
    "filter": {}
  }
}'

Include the similarity score with the result

If you use a vector search to find documents, you can also include a $similarity property for each document in the result. The $similarity value represents the closeness of the sort vector and the document’s vector.

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
database = client.get_database("ASTRA_DB_API_ENDPOINT")
collection = database.get_collection("COLLECTION_NAME")

# Find documents
cursor = collection.find(
    {},
    sort={"$vectorize": "Text to vectorize"},
    include_similarity=True
)

# Iterate over the found documents
for document in cursor:
    print(document)
import { DataAPIClient } from '@datastax/astra-db-ts';

// Get an existing collection
const client = new DataAPIClient('ASTRA_DB_APPLICATION_TOKEN');
const database = client.db('ASTRA_DB_API_ENDPOINT');
const collection = database.collection('COLLECTION_NAME');

// Find documents
(async function () {
  const cursor = collection.find(
    {},
    {
      sort: { $vectorize: "Text to vectorize" },
      includeSimilarity: true
    },
  );

  // Iterate over the found documents
  for await (const document of cursor) {
    console.log(document);
  }
})();
package com.datastax.astra.client.collection;

import com.datastax.astra.client.Collection;
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.model.Document;
import com.datastax.astra.client.model.Filter;
import com.datastax.astra.client.model.Filters;
import com.datastax.astra.client.model.FindOptions;
import com.datastax.astra.client.model.FindIterable;

public class Find {

    public static void main(String[] args) {
        // Get an existing collection
        Collection<Document> collection = new DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
            .getDatabase("ASTRA_DB_API_ENDPOINT")
            .getCollection("COLLECTION_NAME");

        // Find documents
        FindOptions options = new FindOptions()
            .sort("Text to vectorize")
            .includeSimilarity();
        FindIterable<Document> cursor = collection.find(options);

        // Iterate over the found documents
        for (Document document : cursor) {
            System.out.println(document);
        }
    }
}
curl -sS -L -X POST "ASTRA_DB_API_ENDPOINT/api/json/v1/ASTRA_DB_KEYSPACE/ASTRA_DB_COLLECTION" \
--header "Token: ASTRA_DB_APPLICATION_TOKEN" \
--header "Content-Type: application/json" \
--data '{
  "find": {
    "sort": { "$vectorize": "Text to vectorize" },
    "options": { "includeSimilarity": true }
  }
}'

Include the sort vector with the result

If you use a vector search to find documents, you can also include the sort vector in the result. This can be useful if you do a vector search with $vectorize, since you don’t know the sort vector in advance.

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
database = client.get_database("ASTRA_DB_API_ENDPOINT")
collection = database.get_collection("COLLECTION_NAME")

# Find documents
cursor = collection.find(
    {},
    sort={"$vectorize": "Text to vectorize"},
    include_sort_vector=True
)

# Get the sort vector from the result
vector = cursor.get_sort_vector()
import { DataAPIClient } from '@datastax/astra-db-ts';

// Get an existing collection
const client = new DataAPIClient('ASTRA_DB_APPLICATION_TOKEN');
const database = client.db('ASTRA_DB_API_ENDPOINT');
const collection = database.collection('COLLECTION_NAME');

// Find documents
(async function () {
  const cursor = collection.find(
    {},
    {
      sort: { $vectorize: "Text to vectorize" },
      includeSortVector: true
    },
  );

  // Get the sort vector from the result
  const vector = await cursor.getSortVector();
  console.log(vector);
})();
package com.datastax.astra.client.collection;

import com.datastax.astra.client.Collection;
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.model.Document;
import com.datastax.astra.client.model.Filter;
import com.datastax.astra.client.model.Filters;
import com.datastax.astra.client.model.FindOptions;
import com.datastax.astra.client.model.FindIterable;

public class Find {

    public static void main(String[] args) {
        // Get an existing collection
        Collection<Document> collection = new DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
            .getDatabase("ASTRA_DB_API_ENDPOINT")
            .getCollection("COLLECTION_NAME");

        // Find documents
        FindOptions options = new FindOptions()
            .sort("Text to vectorize")
            .includeSortVector();
        FindIterable<Document> cursor = collection.find(options);

        // Get the sort vector from the result
        System.out.println(cursor.getSortVector());
    }
}
curl -sS -L -X POST "ASTRA_DB_API_ENDPOINT/api/json/v1/ASTRA_DB_KEYSPACE/ASTRA_DB_COLLECTION" \
--header "Token: ASTRA_DB_APPLICATION_TOKEN" \
--header "Content-Type: application/json" \
--data '{
  "find": {
    "sort": { "$vectorize": "Text to vectorize" },
    "options": { "includeSortVector": true }
  }
}'

Returns an object with a status.sortVector property:

{
  "data": {
    "documents": [
      {
        "_id":"cdb92916-1f6b-413b-b929-161f6b313b96",
        "author":"Rachel Jacobson",
        "numberOfPages":223
      },{
        "_id":"582e9ed9-913c-40a6-ae9e-d9913ce0a6b0",
        "author":"Jon Hill",
        "numberOfPages":716
      }
    ],
    "nextPageState":null
  },
  "status":{
    "sortVector": [0.28, 0.36, 0.45, ...]
  }
}

Include only specific fields in the response

To specify which fields to include or exclude in the returned document, use a projection.

Certain fields, like $vector and $vectorize, are excluded by default and will only be returned if you specify that they should be included. Certain fields, like _id, are included by default.

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
database = client.get_database("ASTRA_DB_API_ENDPOINT")
collection = database.get_collection("COLLECTION_NAME")

# Find documents
cursor = collection.find(
    {"metadata.language": "English"},
    projection={"isCheckedOut": True, "title": True}
)

# Iterate over the found documents
for document in cursor:
    print(document)
import { DataAPIClient } from '@datastax/astra-db-ts';

// Get an existing collection
const client = new DataAPIClient('ASTRA_DB_APPLICATION_TOKEN');
const database = client.db('ASTRA_DB_API_ENDPOINT');
const collection = database.collection('COLLECTION_NAME');

(async function () {
  // Find documents
  const cursor = collection.find(
    { "metadata.language": "English" },
    { projection: { isCheckedOut: true, title: true} },
  );

  // Iterate over the found documents
  for await (const document of cursor) {
    console.log(document);
  }
})();
package com.datastax.astra.client.collection;

import com.datastax.astra.client.Collection;
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.model.Document;
import com.datastax.astra.client.model.Filter;
import com.datastax.astra.client.model.Filters;
import com.datastax.astra.client.model.FindOptions;
import com.datastax.astra.client.model.FindIterable;

public class Find {

    public static void main(String[] args) {
        // Get an existing collection
        Collection<Document> collection = new DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
            .getDatabase("ASTRA_DB_API_ENDPOINT")
            .getCollection("COLLECTION_NAME");

        // Find documents
        Filter filter = Filters.eq("metadata.language", "English");
        FindOptions options = new FindOptions()
            .projection(Projections.include("isCheckedOut", "title"));
        FindIterable<Document> cursor = collection.find(filter, options);

        // Iterate over the found documents
        for (Document document : cursor) {
            System.out.println(document);
        }
    }
}
curl -sS -L -X POST "ASTRA_DB_API_ENDPOINT/api/json/v1/ASTRA_DB_KEYSPACE/ASTRA_DB_COLLECTION" \
--header "Token: ASTRA_DB_APPLICATION_TOKEN" \
--header "Content-Type: application/json" \
--data '{
  "find": {
    "filter": {"metadata.language": "English"},
    "projection": {"isCheckedOut": true, "title": true}
  }
}'

Exclude specific fields from the response

To specify which fields to include or exclude in the returned document, use a projection.

Certain fields, like $vector and $vectorize, are excluded by default and will only be returned if you specify that they should be included. Certain fields, like _id, are included by default.

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
database = client.get_database("ASTRA_DB_API_ENDPOINT")
collection = database.get_collection("COLLECTION_NAME")

# Find documents
cursor = collection.find(
    {"metadata.language": "English"},
    projection={"isCheckedOut": False, "title": False}
)

# Iterate over the found documents
for document in cursor:
    print(document)
import { DataAPIClient } from '@datastax/astra-db-ts';

// Get an existing collection
const client = new DataAPIClient('ASTRA_DB_APPLICATION_TOKEN');
const database = client.db('ASTRA_DB_API_ENDPOINT');
const collection = database.collection('COLLECTION_NAME');

(async function () {
  // Find documents
  const cursor = collection.find(
    { "metadata.language": "English" },
    { projection: { isCheckedOut: false, title: false} },
  );

  // Iterate over the found documents
  for await (const document of cursor) {
    console.log(document);
  }
})();
package com.datastax.astra.client.collection;

import com.datastax.astra.client.Collection;
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.model.Document;
import com.datastax.astra.client.model.Filter;
import com.datastax.astra.client.model.Filters;
import com.datastax.astra.client.model.FindOptions;
import com.datastax.astra.client.model.FindIterable;

public class Find {

    public static void main(String[] args) {
        // Get an existing collection
        Collection<Document> collection = new DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
            .getDatabase("ASTRA_DB_API_ENDPOINT")
            .getCollection("COLLECTION_NAME");

        // Find documents
        Filter filter = Filters.eq("metadata.language", "English");
        FindOptions options = new FindOptions()
            .projection(Projections.exclude("isCheckedOut", "title"));
        FindIterable<Document> cursor = collection.find(filter, options);

        // Iterate over the found documents
        for (Document document : cursor) {
            System.out.println(document);
        }
    }
}
curl -sS -L -X POST "ASTRA_DB_API_ENDPOINT/api/json/v1/ASTRA_DB_KEYSPACE/ASTRA_DB_COLLECTION" \
--header "Token: ASTRA_DB_APPLICATION_TOKEN" \
--header "Content-Type: application/json" \
--data '{
  "find": {
    "filter": {"metadata.language": "English"},
    "projection": {"isCheckedOut": false, "title": false}
  }
}'

Limit the number of documents returned

Specify a limit to only fetch up to a certain number of documents.

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
database = client.get_database("ASTRA_DB_API_ENDPOINT")
collection = database.get_collection("COLLECTION_NAME")

# Find documents
cursor = collection.find(
    {"metadata.language": "English"},
    limit=10
)

# Iterate over the found documents
for document in cursor:
    print(document)
import { DataAPIClient } from '@datastax/astra-db-ts';

// Get an existing collection
const client = new DataAPIClient('ASTRA_DB_APPLICATION_TOKEN');
const database = client.db('ASTRA_DB_API_ENDPOINT');
const collection = database.collection('COLLECTION_NAME');

(async function () {
  // Find documents
  const cursor = collection.find(
    { "metadata.language": "English" },
    { limit: 10 },
  );

  // Iterate over the found documents
  for await (const document of cursor) {
    console.log(document);
  }
})();
package com.datastax.astra.client.collection;

import com.datastax.astra.client.Collection;
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.model.Document;
import com.datastax.astra.client.model.Filter;
import com.datastax.astra.client.model.Filters;
import com.datastax.astra.client.model.FindOptions;
import com.datastax.astra.client.model.FindIterable;

public class Find {

    public static void main(String[] args) {
        // Get an existing collection
        Collection<Document> collection = new DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
            .getDatabase("ASTRA_DB_API_ENDPOINT")
            .getCollection("COLLECTION_NAME");

        // Find documents
        Filter filter = Filters.eq("metadata.language", "English");
        FindOptions options = new FindOptions()
            .limit(10);
        FindIterable<Document> cursor = collection.find(filter, options);

        // Iterate over the found documents
        for (Document document : cursor) {
            System.out.println(document);
        }
    }
}
curl -sS -L -X POST "ASTRA_DB_API_ENDPOINT/api/json/v1/ASTRA_DB_KEYSPACE/ASTRA_DB_COLLECTION" \
--header "Token: ASTRA_DB_APPLICATION_TOKEN" \
--header "Content-Type: application/json" \
--data '{
  "find": {
    "filter": {"metadata.language": "English"},
    "options": {
      "limit": 10
    }
  }
}'

Skip documents

You can specify a number of documents to skip (bypass) before returning documents.

You can only do this if your find explicitly includes an ascending or descending sort criterion. You cannot do this in conjunction with vector search.

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient, constants

# Get an existing collection
client = DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
database = client.get_database("ASTRA_DB_API_ENDPOINT")
collection = database.get_collection("COLLECTION_NAME")

# Find documents
cursor = collection.find(
    {"metadata.language": "English"},
    sort={
        "rating": constants.SortDocuments.ASCENDING,
        "title": constants.SortDocuments.DESCENDING,
    },
    skip=5
)

# Iterate over the found documents
for document in cursor:
    print(document)
import { DataAPIClient } from '@datastax/astra-db-ts';

// Get an existing collection
const client = new DataAPIClient('ASTRA_DB_APPLICATION_TOKEN');
const database = client.db('ASTRA_DB_API_ENDPOINT');
const collection = database.collection('COLLECTION_NAME');

// Find documents
(async function () {
  const cursor = collection.find(
    { "metadata.language": "English" },
    {
      sort: {
        rating: 1, // ascending
        title: -1 // descending
      },
    skip: 5
     }
  );

  // Iterate over the found documents
  for await (const document of cursor) {
    console.log(document);
  }
})();
package com.datastax.astra.client.collection;

import com.datastax.astra.client.Collection;
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.model.Document;
import com.datastax.astra.client.model.Filter;
import com.datastax.astra.client.model.Filters;
import com.datastax.astra.client.model.FindOptions;
import com.datastax.astra.client.model.FindIterable;

public class Find {

    public static void main(String[] args) {
        // Get an existing collection
        Collection<Document> collection = new DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
            .getDatabase("ASTRA_DB_API_ENDPOINT")
            .getCollection("COLLECTION_NAME");

        // Find documents
        Filter filter = Filters.eq("metadata.language", "English");
        FindOptions options = new FindOptions()
            .sort(Sorts.ascending("rating"))
            .sort(Sorts.descending("title"))
            .skip(5);
        FindIterable<Document> cursor = collection.find(filter, options);

        // Iterate over the found documents
        for (Document document : cursor) {
            System.out.println(document);
        }
    }
}
curl -sS -L -X POST "ASTRA_DB_API_ENDPOINT/api/json/v1/ASTRA_DB_KEYSPACE/ASTRA_DB_COLLECTION" \
--header "Token: ASTRA_DB_APPLICATION_TOKEN" \
--header "Content-Type: application/json" \
--data '{
  "find": {
    "filter": { "metadata.language": "English" },
    "sort": {
      "rating": 1,
      "title": -1
    },
    "options": {
      "skip": 5
    }
  }
}'

Use filter, sort, and projection together

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient, constants

# Get an existing collection
client = DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
database = client.get_database("ASTRA_DB_API_ENDPOINT")
collection = database.get_collection("COLLECTION_NAME")

# Find documents
cursor = collection.find(
    {
        "$and": [
            {"isCheckedOut": False},
            {"numberOfPages": {"$lt": 300}},
        ]
    },
    sort={
        "rating": constants.SortDocuments.ASCENDING,
        "title": constants.SortDocuments.DESCENDING,
    },
    projection={"isCheckedOut": True, "title": True}
)

# Iterate over the found documents
for document in cursor:
    print(document)
import { DataAPIClient } from '@datastax/astra-db-ts';

// Get an existing collection
const client = new DataAPIClient('ASTRA_DB_APPLICATION_TOKEN');
const database = client.db('ASTRA_DB_API_ENDPOINT');
const collection = database.collection('COLLECTION_NAME');

(async function () {
  // Find documents
  const cursor = collection.find(
    {
      $and: [{ isCheckedOut: false }, { numberOfPages: { $lt: 300 } }],
    },
    {
      sort: {
        rating: 1, // ascending
        title: -1, // descending
      },
      projection: {
        isCheckedOut: true,
        title: true,
      },
    },
  );

  // Iterate over the found documents
  for await (const document of cursor) {
    console.log(document);
  }
})();
package com.datastax.astra.client.collection;

import com.datastax.astra.client.Collection;
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.model.Document;
import com.datastax.astra.client.model.Filter;
import com.datastax.astra.client.model.Filters;
import com.datastax.astra.client.model.FindOptions;

import java.util.Optional;

public class Find {

    public static void main(String[] args) {
        // Get an existing collection
        Collection<Document> collection = new DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
            .getDatabase("ASTRA_DB_API_ENDPOINT")
            .getCollection("COLLECTION_NAME");

        // Find documents
        Filter filter = Filters.and(
          Filters.eq("isCheckedOut", false),
          Filters.lt("numberOfPages", 300));
        FindOptions options = new FindOptions()
            .sort(Sorts.ascending("rating"))
            .sort(Sorts.descending("title"))
            .projection(Projections.include("isCheckedOut", "title"));
        FindIterable<Document> cursor = collection.find(filter);

        // Iterate over the found documents
        for (Document document : cursor) {
            System.out.println(document);
        }
    }
}
curl -sS -L -X POST "ASTRA_DB_API_ENDPOINT/api/json/v1/ASTRA_DB_KEYSPACE/ASTRA_DB_COLLECTION" \
--header "Token: ASTRA_DB_APPLICATION_TOKEN" \
--header "Content-Type: application/json" \
--data '{
  "find": {
    "filter": {"$and": [
      {"isCheckedOut": false},
      {"numberOfPages": {"$lt": 300}}
    ]},
    "sort": {
      "rating": 1,
      "title": -1
    },
    "projection": {"isCheckedOut": true, "title": true}
  }
}'

Iterate over found documents

  • Python

  • TypeScript

  • Java

  • curl

Use a for loop to iterate over the cursor. The client will periodically fetch more documents until no matching documents remain.

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
database = client.get_database("ASTRA_DB_API_ENDPOINT")
collection = database.get_collection("COLLECTION_NAME")

# Find documents
cursor = collection.find({
    "$and": [
      {"isCheckedOut": False},
      {"numberOfPages": {"$lt": 300}},
    ]
})

# Iterate over the found documents
for document in cursor:
    print(document)

The cursor returned by find() is compatible with for loops and next(). The client will periodically fetch more documents until no matching documents remain.

import { DataAPIClient } from '@datastax/astra-db-ts';

// Get an existing collection
const client = new DataAPIClient('ASTRA_DB_APPLICATION_TOKEN');
const database = client.db('ASTRA_DB_API_ENDPOINT');
const collection = database.collection('COLLECTION_NAME');

(async function () {
  // Find documents
  const cursor = collection.find({
    $and: [{ isCheckedOut: false }, { numberOfPages: { $lt: 300 } }],
  });

  // Get the next item in the cursor
  console.log(await cursor.next());

  // Iterate over the found documents
  for await (const document of cursor) {
    console.log(document);
  }
})();

The cursor returned by find() is an Iterable and is compatible with for loops. The client will periodically fetch more documents until no matching documents remain.

package com.datastax.astra.client.collection;

import com.datastax.astra.client.Collection;
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.model.Document;
import com.datastax.astra.client.model.Filter;
import com.datastax.astra.client.model.Filters;
import com.datastax.astra.client.model.FindOptions;
import com.datastax.astra.client.model.FindIterable;

public class Find {

    public static void main(String[] args) {
        // Get an existing collection
        Collection<Document> collection = new DataAPIClient("ASTRA_DB_APPLICATION_TOKEN")
            .getDatabase("ASTRA_DB_API_ENDPOINT")
            .getCollection("COLLECTION_NAME");

        // Find documents
        Filter filter = Filters.and(
          Filters.eq("isCheckedOut", false),
          Filters.lt("numberOfPages", 300));
        FindIterable<Document> cursor = collection.find(filter);

        // Iterate over the found documents
        for (Document document : cursor) {
            System.out.println(document);
        }
    }
}

If the response includes a non-null nextPageState, then the specified sort or filter operation supports pagination, and more documents than the ones already returned exist.

To fetch additional documents, you must send a request with the nextPageState value from your previous request. For example:

  1. Send an initial request

    curl -sS -L -X POST "ASTRA_DB_API_ENDPOINT/api/json/v1/ASTRA_DB_KEYSPACE/ASTRA_DB_COLLECTION" \
--header "Token: ASTRA_DB_APPLICATION_TOKEN" \
--header "Content-Type: application/json" \
--data '{
  "find": {
    "filter": {"isCheckedOut": false}
  }
}'

  2. Get the data.documents.nextPageState value from the response

    {
  "data": {
    "documents": [
      {
        "_id": { "$uuid": "018e65c9-df45-7913-89f8-175f28bd7f74" }
      },
      {
        "_id": { "$uuid": "018e65c9-e33d-749b-9386-e848739582f0" }
      }
    ],
    "nextPageState": "NEXT_PAGE_STATE"
  }
}

  3. Use the data.documents.nextPageState from the previous response to request the next page of results.

    curl -sS -L -X POST "ASTRA_DB_API_ENDPOINT/api/json/v1/ASTRA_DB_KEYSPACE/ASTRA_DB_COLLECTION" \
--header "Token: ASTRA_DB_APPLICATION_TOKEN" \
--header "Content-Type: application/json" \
--data '{
  "find": {
    "filter": {"isCheckedOut": false},
    "options": {
      "pageState": "NEXT_PAGE_STATE_FROM_PRIOR_RESPONSE"
    }
  }
}'

  4. Once nextPageState is null, you have fetched all matching documents.

    {
  "data": {
    "documents": [
      {
        "_id": { "$uuid": "018e65c9-df45-7913-89f8-175f28bd7f74" }
      },
      {
        "_id": { "$uuid": "018e65c9-e33d-749b-9386-e848739582f0" }
      }
    ],
    "nextPageState": null
  }
}

Client reference

  • Python

  • TypeScript

  • Java

  • curl

For more information, see the client reference.

For more information, see the client reference.

For more information, see the client reference.

Client reference documentation is not applicable for HTTP.

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