Find a row

Tables with the Data API are currently in public preview. Development is ongoing, and the features and functionality are subject to change. Hyper-Converged Database (HCD), and the use of such, is subject to the DataStax Preview Terms.

Finds a single row in a table using filter and sort clauses, including vector search.

For general information about working with tables and rows, see About tables with the Data API.

Ready to write code? See the examples for this method to get started. If you are new to the Data API, check out the quickstart.

Result

  • Python

  • TypeScript

  • Java

  • curl

Returns a dictionary representation of a row that matches the specified filter and sort clauses, or returns None if no row was found.

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

Returns a promise that resolves to a row that matches the specified filter and sort clauses (Schema), or to null if no row was found.

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

Returns a row that matches the specified filter and sort clauses (Optional<R>), or returns Optional.empty() if no row was found.

If rowClass is not specified, then the type R is the same type as that of the rows in the table.

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

Returns a dictionary representation of a row that matches the specified filter and sort clauses, or returns null if no row was found.

The columns included in the returned row depend on the subset of columns that were requested in the projection. If requested and applicable, the row will also include a $similarity key with a numeric similarity score that represents the closeness of the sort vector and the row’s vector. The response omits any columns with null values, regardless of the projection.

Example response:

{
  "data": {
    "document": {
      "_id": 101,
      "name": "John Doe",
      "$vector": [0.12, 0.52, 0.32]
    }
  }
}

Example null response:

{
  "data": {
    "document": null
  }
}

Parameters

  • Python

  • TypeScript

  • Java

  • curl

Use the find_one method, which belongs to the astrapy.Table class.

Method signature 
find_one(
  filter: Dict[str, Any],
  *,
  projection: Iterable[str] | Dict[str, bool],
  include_similarity: bool,
  sort: Dict[str, Any],
  general_method_timeout_ms: int,
  request_timeout_ms: int,
  timeout_ms: int,
) -> Dict[str, Any] | None

For best performance, filter and sort on indexed columns, partition keys, and clustering keys.

Filtering on non-indexed columns is inefficient and resource-intensive, especially for large datasets. With the Data API clients, such operations can hit the client timeout limit before the underlying HTTP operation is complete. If you filter on non-indexed columns, the Data API will give a warning.

An empty filter or omitted filter may also result in an inefficient and long-running operation.

Additionally, the Data API can perform in-memory sorting, depending on the columns you sort on, the table’s partitioning structure, and whether the sorted columns are indexed. In-memory sorts can have performance implications.
Name Type Summary

filter

Dict[str, Any]

Optional. An object that defines filter criteria using the Data API filter syntax. The method only finds rows that match the filter criteria.

For a list of available filter operators and more examples, see Filter operators for tables.

To perform a vector search, use sort instead of filter.

Default: No filter

See Use filters to find a row for an example.

sort

Dict[str, Any]

Optional. Sorts rows by one or more columns, or performs a vector search.

For more information, see Sort clauses for tables.

See Use sorting to find a row and Use vector search with a search vector to find a row.

projection

Dict[str, bool]

Optional. Controls which columns are included or excluded in the returned rows.

For more information, see Projections for tables.

DataStax recommends a projection to avoid unnecessarily returning large columns, such as vector columns with highly dimensional embeddings.

Default: All columns

See Include only specific columns in the response and Exclude specific columns from the response for examples.

include_similarity

bool

Optional. Whether to include a $similarity property in the response. The $similarity value represents the closeness of the sort vector and the row’s vector.

This parameter only applies if you use a vector search.

Default: false

See Include the similarity score with the result for an example.

general_method_timeout_ms

int

Optional. The maximum time, in milliseconds, that the client should wait for the underlying HTTP request.

This parameter is aliased as request_timeout_ms and timeout_ms for convenience.

Default: The default value for the table. This default is 30 seconds unless you specified a different default when you initialized the Table or DataAPIClient object. For more information, see Timeout options.

Use the findOne method, which belongs to the Table class.

Method signature 
async findOne(
  filter: TableFilter<Schema>,
  options?: {
    sort?: Sort,
    projection?: Projection,
    includeSimilarity?: boolean,
    timeout?: number | TimeoutDescriptor,
  },
): Schema | null

For best performance, filter and sort on indexed columns, partition keys, and clustering keys.

Filtering on non-indexed columns is inefficient and resource-intensive, especially for large datasets. With the Data API clients, such operations can hit the client timeout limit before the underlying HTTP operation is complete. If you filter on non-indexed columns, the Data API will give a warning.

An empty filter or omitted filter may also result in an inefficient and long-running operation.

Additionally, the Data API can perform in-memory sorting, depending on the columns you sort on, the table’s partitioning structure, and whether the sorted columns are indexed. In-memory sorts can have performance implications.
Name Type Summary

filter

TableFilter

Optional. An object that defines filter criteria using the Data API filter syntax. The method only finds rows that match the filter criteria.

For a list of available filter operators and more examples, see Filter operators for tables.

To perform a vector search, use sort instead of filter.

Default: No filter

See Use filters to find a row for an example.

options

TableFindOneOptions

Optional. The options for this operation. See Properties of options for more details.
Properties of options
Name Type Summary

sort

Sort

Optional. Sorts rows by one or more columns, or performs a vector search.

For more information, see Sort clauses for tables.

See Use sorting to find a row and Use vector search with a search vector to find a row.

projection

Projection

Optional. Controls which columns are included or excluded in the returned rows.

For more information, see Projections for tables.

DataStax recommends a projection to avoid unnecessarily returning large columns, such as vector columns with highly dimensional embeddings.

Default: All columns

See Include only specific columns in the response and Exclude specific columns from the response for examples.

includeSimilarity

boolean

Optional. Whether to include a $similarity property in the response. The $similarity value represents the closeness of the sort vector and the row’s vector.

This parameter only applies if you use a vector search.

Default: false

If you use a projection and you set the includeSimlarity parameter to true for a vector search, you must manually include $similarity in the type of the returned rows.

See Include the similarity score with the result for an example.

timeout

number | TimeoutDescriptor

Optional. The timeout to apply to this method.

Use the findOne method, which belongs to the com.datastax.astra.client.tables.Table class.

Method signature 
Optional<T> findOne(
  Filter filter
)
Optional<T> findOne(
  TableFindOneOptions options
)
Optional<T> findOne(
  Filter filter,
  TableFindOneOptions options
)
<R> Optional<R> findOne(
  Filter filter,
  Class<R> rowClass
)
<R> Optional<R> findOne(
  Filter filter,
  TableFindOneOptions options,
  Class<R> rowClass
)

For best performance, filter and sort on indexed columns, partition keys, and clustering keys.

Filtering on non-indexed columns is inefficient and resource-intensive, especially for large datasets. With the Data API clients, such operations can hit the client timeout limit before the underlying HTTP operation is complete. If you filter on non-indexed columns, the Data API will give a warning.

An empty filter or omitted filter may also result in an inefficient and long-running operation.

Additionally, the Data API can perform in-memory sorting, depending on the columns you sort on, the table’s partitioning structure, and whether the sorted columns are indexed. In-memory sorts can have performance implications.
Name Type Summary

filter

Filter

Optional. An object that defines filter criteria using the Data API filter syntax. The method only finds rows that match the filter criteria.

For a list of available filter operators and more examples, see Filter operators for tables.

To perform a vector search, use sort instead of filter.

Default: No filter

See Use filters to find a row for an example.

rowClass

Class<?>

Optional. A specification of the class of the returned row object.

This parameter is useful if your code is strictly typed and you use a projection.

Default: The same class as the rows in the table. If you didn’t specify this when you instantiated the Table object, the row type defaulted to Row, which is close to a Map object.

options

TableFindOneOptions

Optional. The options for this operation. See Methods of the TableFindOneOptions class for more details.
Methods of the TableFindOneOptions class
Method Parameters Summary

sort()

Sort

Optional. Sorts rows by one or more columns, or performs a vector search.

For more information, see Sort clauses for tables.

See Use sorting to find a row and Use vector search with a search vector to find a row.

projection()

Projection

Optional. Controls which columns are included or excluded in the returned rows.

For more information, see Projections for tables.

DataStax recommends a projection to avoid unnecessarily returning large columns, such as vector columns with highly dimensional embeddings.

Default: All columns

See Include only specific columns in the response and Exclude specific columns from the response for examples.

includeSimilarity()

boolean

Optional. Whether to include a $similarity property in the response. The $similarity value represents the closeness of the sort vector and the row’s vector.

This parameter only applies if you use a vector search.

Default: false

See Include the similarity score with the result for an example.

timeout()

long | Duration

Optional. The timeout(s) to apply to HTTP request(s) originating from this method.

Default: The default value for the table. This default is 30 seconds unless you specified a different default when you initialized the Table or DataAPIClient object.

Use the findOne command.

Command signature 
curl -sS -L -X POST "API_ENDPOINT/api/json/v1/KEYSPACE_NAME/TABLE_NAME" \
--header "Token: APPLICATION_TOKEN" \
--header "Content-Type: application/json" \
--data '{
  "findOne": {
    "filter": FILTER,
    "sort": SORT,
    "projection": PROJECTION,
    "options": {
      "includeSimilarity": BOOLEAN
    }
  }
}'

For best performance, filter and sort on indexed columns, partition keys, and clustering keys.

Filtering on non-indexed columns is inefficient and resource-intensive, especially for large datasets. With the Data API clients, such operations can hit the client timeout limit before the underlying HTTP operation is complete. If you filter on non-indexed columns, the Data API will give a warning.

An empty filter or omitted filter may also result in an inefficient and long-running operation.

Additionally, the Data API can perform in-memory sorting, depending on the columns you sort on, the table’s partitioning structure, and whether the sorted columns are indexed. In-memory sorts can have performance implications.
Name Type Summary

filter

object

Optional. An object that defines filter criteria using the Data API filter syntax. The method only finds rows that match the filter criteria.

For a list of available filter operators and more examples, see Filter operators for tables.

To perform a vector search, use sort instead of filter.

Default: No filter

See Use filters to find a row for an example.

sort

object

Optional. Sorts rows by one or more columns, or performs a vector search.

For more information, see Sort clauses for tables.

See Use sorting to find a row and Use vector search with a search vector to find a row.

projection

object

Optional. Controls which columns are included or excluded in the returned rows.

For more information, see Projections for tables.

DataStax recommends a projection to avoid unnecessarily returning large columns, such as vector columns with highly dimensional embeddings.

Default: All columns

See Include only specific columns in the response and Exclude specific columns from the response for examples.

options.includeSimilarity

boolean

Optional. Whether to include a $similarity property in the response. The $similarity value represents the closeness of the sort vector and the row’s vector.

This parameter only applies if you use a vector search.

If you use a projection and you set the includeSimlarity parameter to true for a vector search, you must manually include $similarity in the type of the returned rows.

Default: false

See Include the similarity score with the result for an example.

Examples

The following examples demonstrate how to find a row in a table.

Use filters to find a row

You can use a filter to find a row that matches specific criteria. For example, you can find a row with an is_checked_out value of false and a number_of_pages value less than 300.

For optimal performance, only filter on indexed columns. The Data API returns a warning if you filter on a non-indexed column.

For a list of available filter operators, see Filter operators for tables.

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient
from astrapy.authentication import UsernamePasswordTokenProvider
from astrapy.constants import Environment

# Get an existing table
client = DataAPIClient(environment=Environment.HCD)
database = client.get_database(
    "API_ENDPOINT",
    token=UsernamePasswordTokenProvider("USERNAME", "PASSWORD"),
)
table = database.get_table("TABLE_NAME", keyspace="KEYSPACE_NAME")

# Find a row
result = table.find_one(
    {
        "$and": [
            {"is_checked_out": False},
            {"number_of_pages": {"$lt": 300}},
        ]
    }
)

print(result)
import {
  DataAPIClient,
  UsernamePasswordTokenProvider,
} from "@datastax/astra-db-ts";

// Get an existing table
const client = new DataAPIClient({ environment: "hcd" });
const database = client.db("API_ENDPOINT", {
  token: new UsernamePasswordTokenProvider("USERNAME", "PASSWORD"),
});
const table = database.table("TABLE_NAME", {
  keyspace: "KEYSPACE_NAME",
});

// Find a row
(async function () {
  const result = await table.findOne({
    $and: [{ is_checked_out: false }, { number_of_pages: { $lt: 300 } }],
  });

  console.log(result);
})();
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.DataAPIClients;
import com.datastax.astra.client.core.query.Filter;
import com.datastax.astra.client.core.query.Filters;
import com.datastax.astra.client.databases.Database;
import com.datastax.astra.client.tables.Table;
import com.datastax.astra.client.tables.definition.rows.Row;
import java.util.Optional;

public class Example {

  public static void main(String[] args) {
    // Get an existing table
    DataAPIClient client = DataAPIClients.clientHCD("USERNAME", "PASSWORD");
    Database database = client.getDatabase("API_ENDPOINT", "KEYSPACE_NAME");
    Table<Row> table = database.getTable("TABLE_NAME");

    // Find a row
    Filter filter =
        Filters.and(Filters.eq("is_checked_out", false), Filters.lt("number_of_pages", 300));

    Optional<Row> result = table.findOne(filter);

    System.out.println(result);
  }
}
curl -sS -L -X POST "API_ENDPOINT/v1/KEYSPACE_NAME/TABLE_NAME" \
  --header "Token: APPLICATION_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
  "findOne": {
    "filter": {"$and": [
      {"is_checked_out": false},
      {"number_of_pages": {"$lt": 300}}
    ]}
  }
}'

Use vector search with a search vector to find a row

Perform a vector search by providing a search vector in the sort clause. This returns the row whose vector column value is most similar to the provided search vector.

The vector column must be indexed.

If your table has multiple vector columns, you can only sort on one vector column at a time.

  • Python

  • TypeScript

  • Java

  • curl

You can use the astrapy.data_types.DataAPIVector class to binary-encode your search vector. DataStax recommends that you always use a DataAPIVector object instead of a list of floats to improve performance.

When you read the value of a vector column, the client always returns a DataAPIVector object, unless you change the default serialization/deserialization behavior.

from astrapy import DataAPIClient
from astrapy.authentication import UsernamePasswordTokenProvider
from astrapy.constants import Environment
from astrapy.data_types import DataAPIVector

# Get an existing table
client = DataAPIClient(environment=Environment.HCD)
database = client.get_database(
    "API_ENDPOINT",
    token=UsernamePasswordTokenProvider("USERNAME", "PASSWORD"),
)
table = database.get_table("TABLE_NAME", keyspace="KEYSPACE_NAME")

# Find a row
result = table.find_one(
    {}, sort={"summary_genres_vector": DataAPIVector([0.12, -0.46, 0.35, 0.52, -0.32])}
)

print(result)

You can use the DataAPIVector class to binary-encode your search vector. DataStax recommends that you always use a DataAPIVector object instead of a list of floats to improve performance.

When you read the value of a vector column, the client always returns a DataAPIVector object, unless you change the default serialization/deserialization behavior. You can use vector.asArray() to lazily convert a DataAPIVector object to an array.

import {
  DataAPIClient,
  UsernamePasswordTokenProvider,
} from "@datastax/astra-db-ts";

// Get an existing table
const client = new DataAPIClient({ environment: "hcd" });
const database = client.db("API_ENDPOINT", {
  token: new UsernamePasswordTokenProvider("USERNAME", "PASSWORD"),
});
const table = database.table("TABLE_NAME", {
  keyspace: "KEYSPACE_NAME",
});

// Find a row
(async function () {
  const result = await table.findOne(
    {},
    { sort: { summary_genres_vector: [0.12, -0.46, 0.35, 0.52, -0.32] } },
  );

  console.log(result);
})();

You can use the DataAPIVector class to binary-encode your search vector. DataStax recommends that you always use a DataAPIVector object instead of a list of floats to improve performance.

When you read the value of a vector column, the client always returns a DataAPIVector object, unless you change the default serialization/deserialization behavior.

import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.DataAPIClients;
import com.datastax.astra.client.core.query.Sort;
import com.datastax.astra.client.core.vector.DataAPIVector;
import com.datastax.astra.client.databases.Database;
import com.datastax.astra.client.tables.Table;
import com.datastax.astra.client.tables.commands.options.TableFindOneOptions;
import com.datastax.astra.client.tables.definition.rows.Row;
import java.util.Optional;

public class Example {

  public static void main(String[] args) {
    // Get an existing table
    DataAPIClient client = DataAPIClients.clientHCD("USERNAME", "PASSWORD");
    Database database = client.getDatabase("API_ENDPOINT", "KEYSPACE_NAME");
    Table<Row> table = database.getTable("TABLE_NAME");

    // Find a row
    TableFindOneOptions options =
        new TableFindOneOptions()
            .sort(
                Sort.vector(
                    "summary_genres_vector",
                    new DataAPIVector(new float[] {0.12f, -0.46f, 0.35f, 0.52f, -0.32f})));
    Optional<Row> result = table.findOne(options);
    System.out.println(result);
  }
}

You can provide the search vector as an array of floats, or you can use $binary to provide the search vector as a Base64-encoded string. $binary can be more performant.

Vector binary encodings specification

A d-dimensional vector is a list of d floating-point numbers that can be binary encoded.

To prepare for encoding, the list must be transformed into a sequence of bytes where each float is represented as four bytes in big-endian format. Then, the byte sequence is Base64-encoded, with = padding, if needed. For example, here are some vectors and their resulting Base64 encoded strings:

[0.1, -0.2, 0.3] = "PczMzb5MzM0+mZma"
[0.1, 0.2] = "PczMzT5MzM0="
[10, 10.5, 100, -91.19] = "QSAAAEEoAABCyAAAwrZhSA=="

Once encoded, you use $binary to pass the Base64 string to the Data API:

{ "$binary": "BASE64_STRING" }

You can use a script to encode your vectors, for example:

python
import base64
import struct

input_vector = [0.1, -0.2, 0.3]
d = len(input_vector)
pack_format = ">" + "f" * d
binary_encode = base64.b64encode(struct.pack(pack_format, *input_vector)).decode()

  • Array of floats

  • $binary

curl -sS -L -X POST "API_ENDPOINT/v1/KEYSPACE_NAME/TABLE_NAME" \
  --header "Token: APPLICATION_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
  "findOne": {
    "sort": { "summary_genres_vector": {"$binary": "PfXCjz8FHrg+o9cK"} }
  }
}'
curl -sS -L -X POST "API_ENDPOINT/v1/KEYSPACE_NAME/TABLE_NAME" \
  --header "Token: APPLICATION_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
  "findOne": {
    "sort": { "summary_genres_vector": [0.12, -0.46, 0.35, 0.52, -0.32] }
  }
}'

Use sorting to find a row

You can use a sort clause to sort rows by one or more columns.

For best performance, only sort on columns that are indexed or that are part of the primary key.

For more information, see Sort clauses for tables.

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient
from astrapy.authentication import UsernamePasswordTokenProvider
from astrapy.constants import Environment
from astrapy.constants import SortMode

# Get an existing table
client = DataAPIClient(environment=Environment.HCD)
database = client.get_database(
    "API_ENDPOINT",
    token=UsernamePasswordTokenProvider("USERNAME", "PASSWORD"),
)
table = database.get_table("TABLE_NAME", keyspace="KEYSPACE_NAME")

# Find a row
result = table.find_one(
    {"is_checked_out": False},
    sort={
        "rating": SortMode.ASCENDING,
        "title": SortMode.DESCENDING,
    },
)

print(result)
import {
  DataAPIClient,
  UsernamePasswordTokenProvider,
} from "@datastax/astra-db-ts";

// Get an existing table
const client = new DataAPIClient({ environment: "hcd" });
const database = client.db("API_ENDPOINT", {
  token: new UsernamePasswordTokenProvider("USERNAME", "PASSWORD"),
});
const table = database.table("TABLE_NAME", {
  keyspace: "KEYSPACE_NAME",
});

// Find a row
(async function () {
  const result = await table.findOne(
    { is_checked_out: false },
    {
      sort: {
        rating: 1, // ascending
        title: -1, // descending
      },
    },
  );

  console.log(result);
})();
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.DataAPIClients;
import com.datastax.astra.client.core.query.Filter;
import com.datastax.astra.client.core.query.Filters;
import com.datastax.astra.client.core.query.Sort;
import com.datastax.astra.client.databases.Database;
import com.datastax.astra.client.tables.Table;
import com.datastax.astra.client.tables.commands.options.TableFindOneOptions;
import com.datastax.astra.client.tables.definition.rows.Row;
import java.util.Optional;

public class Example {

  public static void main(String[] args) {
    // Get an existing table
    DataAPIClient client = DataAPIClients.clientHCD("USERNAME", "PASSWORD");
    Database database = client.getDatabase("API_ENDPOINT", "KEYSPACE_NAME");
    Table<Row> table = database.getTable("TABLE_NAME");

    // Find a row
    Filter filter = Filters.eq("is_checked_out", false);
    TableFindOneOptions options =
        new TableFindOneOptions().sort(Sort.ascending("rating"), Sort.descending("title"));
    Optional<Row> result = table.findOne(filter, options);
    System.out.println(result);
  }
}
curl -sS -L -X POST "API_ENDPOINT/v1/KEYSPACE_NAME/TABLE_NAME" \
  --header "Token: APPLICATION_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
  "findOne": {
    "filter": { "is_checked_out": false },
    "sort": {
      "rating": 1,
      "title": -1
    }
  }
}'

Include the similarity score with the result

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

  • Python

  • TypeScript

  • Java

  • curl

The client always returns the similarity score as a DataAPIVector object, unless you change the default serialization/deserialization behavior.

from astrapy import DataAPIClient
from astrapy.authentication import UsernamePasswordTokenProvider
from astrapy.constants import Environment

# Get an existing table
client = DataAPIClient(environment=Environment.HCD)
database = client.get_database(
    "API_ENDPOINT",
    token=UsernamePasswordTokenProvider("USERNAME", "PASSWORD"),
)
table = database.get_table("TABLE_NAME", keyspace="KEYSPACE_NAME")

# Find a row
result = table.find_one(
    {},
    sort={"summary_genres_vector": [0.12, -0.46, 0.35, 0.52, -0.32]},
    include_similarity=True,
)

print(result)

The client always returns the similarity score as a DataAPIVector object, unless you change the default serialization/deserialization behavior. You can use vector.asArray() to lazily convert a DataAPIVector object to an array.

import {
  DataAPIClient,
  UsernamePasswordTokenProvider,
} from "@datastax/astra-db-ts";

// Get an existing table
const client = new DataAPIClient({ environment: "hcd" });
const database = client.db("API_ENDPOINT", {
  token: new UsernamePasswordTokenProvider("USERNAME", "PASSWORD"),
});
const table = database.table("TABLE_NAME", {
  keyspace: "KEYSPACE_NAME",
});

// Find a row
(async function () {
  const result = await table.findOne(
    {},
    {
      sort: { summary_genres_vector: [0.12, -0.46, 0.35, 0.52, -0.32] },
      includeSimilarity: true,
    },
  );

  console.log(result);
})();

The client always returns the similarity score as a DataAPIVector object, unless you change the default serialization/deserialization behavior.

import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.DataAPIClients;
import com.datastax.astra.client.core.query.Sort;
import com.datastax.astra.client.core.vector.DataAPIVector;
import com.datastax.astra.client.databases.Database;
import com.datastax.astra.client.tables.Table;
import com.datastax.astra.client.tables.commands.options.TableFindOneOptions;
import com.datastax.astra.client.tables.definition.rows.Row;
import java.util.Optional;

public class Example {

  public static void main(String[] args) {
    // Get an existing table
    DataAPIClient client = DataAPIClients.clientHCD("USERNAME", "PASSWORD");
    Database database = client.getDatabase("API_ENDPOINT", "KEYSPACE_NAME");
    Table<Row> table = database.getTable("TABLE_NAME");

    // Find a row
    TableFindOneOptions options =
        new TableFindOneOptions()
            .sort(
                Sort.vector(
                    "summary_genres_vector",
                    new DataAPIVector(new float[] {0.12f, -0.46f, 0.35f, 0.52f, -0.32f})))
            .includeSimilarity(true);
    Optional<Row> result = table.findOne(options);
    System.out.println(result);
  }
}
curl -sS -L -X POST "API_ENDPOINT/v1/KEYSPACE_NAME/TABLE_NAME" \
  --header "Token: APPLICATION_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
  "findOne": {
    "sort": { "summary_genres_vector": [0.12, -0.46, 0.35, 0.52, -0.32] },
    "options": { "includeSimilarity": true }
  }
}'

Include only specific columns in the response

To specify which columns to include or exclude in the returned row, use a projection.

The following example demonstrates an inclusive projection.

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient
from astrapy.authentication import UsernamePasswordTokenProvider
from astrapy.constants import Environment

# Get an existing table
client = DataAPIClient(environment=Environment.HCD)
database = client.get_database(
    "API_ENDPOINT",
    token=UsernamePasswordTokenProvider("USERNAME", "PASSWORD"),
)
table = database.get_table("TABLE_NAME", keyspace="KEYSPACE_NAME")

# Find a row
result = table.find_one(
    {"number_of_pages": {"$lt": 300}},
    projection={"is_checked_out": True, "title": True},
)

print(result)
import {
  DataAPIClient,
  UsernamePasswordTokenProvider,
} from "@datastax/astra-db-ts";

// Get an existing table
const client = new DataAPIClient({ environment: "hcd" });
const database = client.db("API_ENDPOINT", {
  token: new UsernamePasswordTokenProvider("USERNAME", "PASSWORD"),
});
const table = database.table("TABLE_NAME", {
  keyspace: "KEYSPACE_NAME",
});

// Find a row
(async function () {
  const result = await table.findOne(
    { number_of_pages: { $lt: 300 } },
    { projection: { is_checked_out: true, title: true } },
  );

  console.log(result);
})();
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.DataAPIClients;
import com.datastax.astra.client.core.query.Filter;
import com.datastax.astra.client.core.query.Filters;
import com.datastax.astra.client.core.query.Projection;
import com.datastax.astra.client.databases.Database;
import com.datastax.astra.client.tables.Table;
import com.datastax.astra.client.tables.commands.options.TableFindOneOptions;
import com.datastax.astra.client.tables.definition.rows.Row;
import java.util.Optional;

public class Example {

  public static void main(String[] args) {
    // Get an existing table
    DataAPIClient client = DataAPIClients.clientHCD("USERNAME", "PASSWORD");
    Database database = client.getDatabase("API_ENDPOINT", "KEYSPACE_NAME");
    Table<Row> table = database.getTable("TABLE_NAME");

    // Find a row
    Filter filter = Filters.lt("number_of_pages", 300);
    TableFindOneOptions options =
        new TableFindOneOptions().projection(Projection.include("is_checked_out", "title"));
    Optional<Row> result = table.findOne(filter, options);
    System.out.println(result);
  }
}
curl -sS -L -X POST "API_ENDPOINT/v1/KEYSPACE_NAME/TABLE_NAME" \
  --header "Token: APPLICATION_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
  "findOne": {
    "filter": {"number_of_pages": {"$lt": 300}},
    "projection": {"is_checked_out": true, "title": true}
  }
}'

Exclude specific columns from the response

To specify which columns to include or exclude in the returned row, use a projection.

The following example demonstrates an exclusive projection.

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient
from astrapy.authentication import UsernamePasswordTokenProvider
from astrapy.constants import Environment

# Get an existing table
client = DataAPIClient(environment=Environment.HCD)
database = client.get_database(
    "API_ENDPOINT",
    token=UsernamePasswordTokenProvider("USERNAME", "PASSWORD"),
)
table = database.get_table("TABLE_NAME", keyspace="KEYSPACE_NAME")

# Find a row
result = table.find_one(
    {"number_of_pages": {"$lt": 300}},
    projection={"is_checked_out": False, "title": False},
)

print(result)
import {
  DataAPIClient,
  UsernamePasswordTokenProvider,
} from "@datastax/astra-db-ts";

// Get an existing table
const client = new DataAPIClient({ environment: "hcd" });
const database = client.db("API_ENDPOINT", {
  token: new UsernamePasswordTokenProvider("USERNAME", "PASSWORD"),
});
const table = database.table("TABLE_NAME", {
  keyspace: "KEYSPACE_NAME",
});

// Find a row
(async function () {
  const result = await table.findOne(
    { number_of_pages: { $lt: 300 } },
    { projection: { is_checked_out: false, title: false } },
  );

  console.log(result);
})();
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.DataAPIClients;
import com.datastax.astra.client.core.query.Filter;
import com.datastax.astra.client.core.query.Filters;
import com.datastax.astra.client.core.query.Projection;
import com.datastax.astra.client.databases.Database;
import com.datastax.astra.client.tables.Table;
import com.datastax.astra.client.tables.commands.options.TableFindOneOptions;
import com.datastax.astra.client.tables.definition.rows.Row;
import java.util.Optional;

public class Example {

  public static void main(String[] args) {
    // Get an existing table
    DataAPIClient client = DataAPIClients.clientHCD("USERNAME", "PASSWORD");
    Database database = client.getDatabase("API_ENDPOINT", "KEYSPACE_NAME");
    Table<Row> table = database.getTable("TABLE_NAME");

    // Find a row
    Filter filter = Filters.lt("number_of_pages", 300);
    TableFindOneOptions options =
        new TableFindOneOptions().projection(Projection.exclude("is_checked_out", "title"));
    Optional<Row> result = table.findOne(filter, options);
    System.out.println(result);
  }
}
curl -sS -L -X POST "API_ENDPOINT/v1/KEYSPACE_NAME/TABLE_NAME" \
  --header "Token: APPLICATION_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
  "findOne": {
    "filter": {"number_of_pages": {"$lt": 300}},
    "projection": {"is_checked_out": false, "title": false}
  }
}'

Use filter, sort, and projection together

  • Python

  • TypeScript

  • Java

  • curl

from astrapy import DataAPIClient
from astrapy.authentication import UsernamePasswordTokenProvider
from astrapy.constants import Environment
from astrapy.constants import SortMode

# Get an existing table
client = DataAPIClient(environment=Environment.HCD)
database = client.get_database(
    "API_ENDPOINT",
    token=UsernamePasswordTokenProvider("USERNAME", "PASSWORD"),
)
table = database.get_table("TABLE_NAME", keyspace="KEYSPACE_NAME")

# Find a row
result = table.find_one(
    {
        "$and": [
            {"is_checked_out": False},
            {"number_of_pages": {"$lt": 300}},
        ]
    },
    sort={
        "rating": SortMode.ASCENDING,
        "title": SortMode.DESCENDING,
    },
    projection={"is_checked_out": True, "title": True},
)

print(result)
import {
  DataAPIClient,
  UsernamePasswordTokenProvider,
} from "@datastax/astra-db-ts";

// Get an existing table
const client = new DataAPIClient({ environment: "hcd" });
const database = client.db("API_ENDPOINT", {
  token: new UsernamePasswordTokenProvider("USERNAME", "PASSWORD"),
});
const table = database.table("TABLE_NAME", {
  keyspace: "KEYSPACE_NAME",
});

// Find a row
(async function () {
  const result = await table.findOne(
    {
      $and: [{ is_checked_out: false }, { number_of_pages: { $lt: 300 } }],
    },
    {
      sort: {
        rating: 1, // ascending
        title: -1, // descending
      },
      projection: {
        is_checked_out: true,
        title: true,
      },
    },
  );

  console.log(result);
})();
import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.DataAPIClients;
import com.datastax.astra.client.core.query.Filter;
import com.datastax.astra.client.core.query.Filters;
import com.datastax.astra.client.core.query.Projection;
import com.datastax.astra.client.core.query.Sort;
import com.datastax.astra.client.databases.Database;
import com.datastax.astra.client.tables.Table;
import com.datastax.astra.client.tables.commands.options.TableFindOneOptions;
import com.datastax.astra.client.tables.definition.rows.Row;
import java.util.Optional;

public class Example {

  public static void main(String[] args) {
    // Get an existing table
    DataAPIClient client = DataAPIClients.clientHCD("USERNAME", "PASSWORD");
    Database database = client.getDatabase("API_ENDPOINT", "KEYSPACE_NAME");
    Table<Row> table = database.getTable("TABLE_NAME");

    // Find a row
    Filter filter =
        Filters.and(Filters.eq("is_checked_out", false), Filters.lt("number_of_pages", 300));
    TableFindOneOptions options =
        new TableFindOneOptions()
            .sort(Sort.ascending("rating"), Sort.descending("title"))
            .projection(Projection.include("is_checked_out", "title"));
    Optional<Row> result = table.findOne(filter, options);
    System.out.println(result);
  }
}
curl -sS -L -X POST "API_ENDPOINT/v1/KEYSPACE_NAME/TABLE_NAME" \
  --header "Token: APPLICATION_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
  "findOne": {
    "filter": {"$and": [
      {"is_checked_out": false},
      {"number_of_pages": {"$lt": 300}}
    ]},
    "sort": {
      "rating": 1,
      "title": -1
    },
    "projection": {"is_checked_out": true, "title": true}
  }
}'

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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