This page describes how to insert, update, and delete Spanner data using
Data Manipulation Language (DML) statements. You can run DML statements
using the client libraries, the
Google Cloud console, and the gcloud
command-line tool. You can run Partitioned DML
statements using the client libraries and the gcloud
command-line tool.
For the complete DML syntax reference, see Data Manipulation Language syntax for GoogleSQL-dialect databases or PostgreSQL data manipulation language for PostgreSQL-dialect databases
Use DML
DML supports INSERT, UPDATE, and DELETE statements in the
Google Cloud console, Google Cloud CLI, and client libraries.
Locking
You execute DML statements inside read-write transactions. When Spanner reads data, it
acquires shared read locks on limited portions of the row ranges that you read. Specifically, it
acquires these locks only on the columns you access. The locks can include data that does not
satisfy the filter condition of the WHERE clause.
When Spanner modifies data using DML statements, it acquires exclusive locks on the specific data that you are modifying. In addition, it acquires shared locks in the same way as when you read data. If your request includes large row ranges, or an entire table, the shared locks might prevent other transactions from making progress in parallel.
To modify data as efficiently as possible, use a WHERE clause that enables
Spanner to read only the necessary rows. You can achieve this goal with a filter on the
primary key, or on the key of a secondary index. The WHERE clause limits the scope of
the shared locks and enables Spanner to process the update more efficiently.
For example, suppose that one of the musicians in the Singers table changes their
first name, and you need to update the name in your database. You could execute the following DML
statement, but it forces Spanner to scan the entire table and acquires shared locks that
cover the entire table. As a result, Spanner must read more data than necessary, and
concurrent transactions cannot modify the data in parallel:
-- ANTI-PATTERN: SENDING AN UPDATE WITHOUT THE PRIMARY KEY COLUMN
-- IN THE WHERE CLAUSE
UPDATE Singers SET FirstName = "Marcel"
WHERE FirstName = "Marc" AND LastName = "Richards";
To make the update more efficient, include the SingerId column in the
WHERE clause. The SingerId column is the only primary key column for
the Singers table:
-- ANTI-PATTERN: SENDING AN UPDATE THAT MUST SCAN THE ENTIRE TABLE
UPDATE Singers SET FirstName = "Marcel"
WHERE FirstName = "Marc" AND LastName = "Richards"
If there is no index on FirstName or LastName, you need to
scan the entire table to find the target singers. If you don't want to add a secondary
index to make the update more efficient, then include the SingerId column
in the WHERE clause.
The SingerId column is the only primary key column for the
Singers table. To find it, run SELECT in a separate,
read-only transaction prior to the update transaction:
SELECT SingerId
FROM Singers
WHERE FirstName = "Marc" AND LastName = "Richards"
-- Recommended: Including a seekable filter in the where clause
UPDATE Singers SET FirstName = "Marcel"
WHERE SingerId = 1;
Concurrency
Spanner sequentially executes all the SQL statements (SELECT,
INSERT, UPDATE, and DELETE) within a transaction. They are not executed
concurrently. The only exception is that Spanner might execute multiple
SELECT statements concurrently, because they are read-only operations.
Transaction limits
A transaction that includes DML statements has the same limits as any other transaction. If you have large-scale changes, consider using Partitioned DML.
If the DML statements in a transaction result in more than 80,000 mutations, the DML statement that pushes the transaction over the limit returns a
BadUsageerror with a message about too many mutations.If the DML statements in a transaction result in a transaction that is larger than 100 MB, the DML statement that pushes the transaction over the limit returns a
BadUsageerror with a message about the transaction exceeding the size limit.
Mutations performed using DML are not returned to the client. They are merged into the commit request when it is committed, and they count towards the maximum size limits. Even if the size of the commit request that you send is small, the transaction might still exceed the allowed size limit.
Run statements in the Google Cloud console
Use the following steps to execute a DML statement in the Google Cloud console.
Go to the Spanner Instances page.
Select your project in the drop-down list in the toolbar.
Click the name of the instance that contains your database to go to the Instance details page.
In the Overview tab, click the name of your database. The Database details page appears.
Click Spanner Studio.
Enter a DML statement. For example, the following statement adds a new row to the
Singerstable.INSERT Singers (SingerId, FirstName, LastName) VALUES (1, 'Marc', 'Richards')Click Run query. The Google Cloud console displays the result.
Execute statements with the Google Cloud CLI
To execute DML statements, use the gcloud spanner databases execute-sql
command. The following example adds a new row to the Singers table.
gcloud spanner databases execute-sql example-db --instance=test-instance \ --sql="INSERT Singers (SingerId, FirstName, LastName) VALUES (1, 'Marc', 'Richards')"
Modify data using the client library
To execute DML statements using the client library:
- Create a read-write transaction.
- Call the client library method for DML execution and pass in the DML statement.
- Use the return value of the DML execution method to get the number of rows inserted, updated, or deleted.
The following code example inserts a new row into the Singers table.
C++
You use the ExecuteDml() function to execute a DML statement.
void DmlStandardInsert(google::cloud::spanner::Client client) {
using ::google::cloud::StatusOr;
namespace spanner = ::google::cloud::spanner;
std::int64_t rows_inserted;
auto commit_result = client.Commit(
[&client, &rows_inserted](
spanner::Transaction txn) -> StatusOr<spanner::Mutations> {
auto insert = client.ExecuteDml(
std::move(txn),
spanner::SqlStatement(
"INSERT INTO Singers (SingerId, FirstName, LastName)"
" VALUES (10, 'Virginia', 'Watson')"));
if (!insert) return std::move(insert).status();
rows_inserted = insert->RowsModified();
return spanner::Mutations{};
});
if (!commit_result) throw std::move(commit_result).status();
std::cout << "Rows inserted: " << rows_inserted;
std::cout << "Insert was successful [spanner_dml_standard_insert]\n";
}C#
You use the ExecuteNonQueryAsync() method to execute a DML statement.
using Google.Cloud.Spanner.Data;
using System;
using System.Threading.Tasks;
public class InsertUsingDmlCoreAsyncSample
{
public async Task<int> InsertUsingDmlCoreAsync(string projectId, string instanceId, string databaseId)
{
string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";
using var connection = new SpannerConnection(connectionString);
await connection.OpenAsync();
using var cmd = connection.CreateDmlCommand("INSERT Singers (SingerId, FirstName, LastName) VALUES (10, 'Virginia', 'Watson')");
int rowCount = await cmd.ExecuteNonQueryAsync();
Console.WriteLine($"{rowCount} row(s) inserted...");
return rowCount;
}
}Go
You use the Update() method to execute a DML statement.
import (
"context"
"fmt"
"io"
"cloud.google.com/go/spanner"
)
func insertUsingDML(w io.Writer, db string) error {
ctx := context.Background()
client, err := spanner.NewClient(ctx, db)
if err != nil {
return err
}
defer client.Close()
_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
stmt := spanner.Statement{
SQL: `INSERT Singers (SingerId, FirstName, LastName)
VALUES (10, 'Virginia', 'Watson')`,
}
rowCount, err := txn.Update(ctx, stmt)
if err != nil {
return err
}
fmt.Fprintf(w, "%d record(s) inserted.\n", rowCount)
return nil
})
return err
}
Java
You use the executeUpdate() method to execute a DML statement.
static void insertUsingDml(DatabaseClient dbClient) {
dbClient
.readWriteTransaction()
.run(transaction -> {
String sql =
"INSERT INTO Singers (SingerId, FirstName, LastName) "
+ " VALUES (10, 'Virginia', 'Watson')";
long rowCount = transaction.executeUpdate(Statement.of(sql));
System.out.printf("%d record inserted.\n", rowCount);
return null;
});
}Node.js
You use the runUpdate() method to execute a DML statement.
// Imports the Google Cloud client library
const {Spanner} = require('@google-cloud/spanner');
/**
* TODO(developer): Uncomment the following lines before running the sample.
*/
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';
// Creates a client
const spanner = new Spanner({
projectId: projectId,
});
// Gets a reference to a Cloud Spanner instance and database
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);
database.runTransaction(async (err, transaction) => {
if (err) {
console.error(err);
return;
}
try {
const [rowCount] = await transaction.runUpdate({
sql: 'INSERT Singers (SingerId, FirstName, LastName) VALUES (10, @firstName, @lastName)',
params: {
firstName: 'Virginia',
lastName: 'Watson',
},
});
console.log(
`Successfully inserted ${rowCount} record into the Singers table.`
);
await transaction.commit();
} catch (err) {
console.error('ERROR:', err);
} finally {
// Close the database when finished.
database.close();
}
});PHP
You use the executeUpdate() method to execute a DML statement.
use Google\Cloud\Spanner\SpannerClient;
use Google\Cloud\Spanner\Transaction;
/**
* Inserts sample data into the given database with a DML statement.
*
* The database and table must already exist and can be created using
* `create_database`.
* Example:
* ```
* insert_data($instanceId, $databaseId);
* ```
*
* @param string $instanceId The Spanner instance ID.
* @param string $databaseId The Spanner database ID.
*/
function insert_data_with_dml(string $instanceId, string $databaseId): void
{
$spanner = new SpannerClient();
$instance = $spanner->instance($instanceId);
$database = $instance->database($databaseId);
$database->runTransaction(function (Transaction $t) {
$rowCount = $t->executeUpdate(
'INSERT Singers (SingerId, FirstName, LastName) '
. " VALUES (10, 'Virginia', 'Watson')");
$t->commit();
printf('Inserted %d row(s).' . PHP_EOL, $rowCount);
});
}Python
You use the execute_update() method to execute a DML statement.
# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)
def insert_singers(transaction):
row_ct = transaction.execute_update(
"INSERT INTO Singers (SingerId, FirstName, LastName) "
" VALUES (10, 'Virginia', 'Watson')"
)
print("{} record(s) inserted.".format(row_ct))
database.run_in_transaction(insert_singers)Ruby
You use the execute_update() method to execute a DML statement.
# project_id = "Your Google Cloud project ID"
# instance_id = "Your Spanner instance ID"
# database_id = "Your Spanner database ID"
require "google/cloud/spanner"
spanner = Google::Cloud::Spanner.new project: project_id
client = spanner.client instance_id, database_id
row_count = 0
client.transaction do |transaction|
row_count = transaction.execute_update(
"INSERT INTO Singers (SingerId, FirstName, LastName) VALUES (10, 'Virginia', 'Watson')"
)
end
puts "#{row_count} record inserted."The following code example updates the MarketingBudget column of the Albums
table based on a WHERE clause.
C++
void DmlStandardUpdate(google::cloud::spanner::Client client) {
using ::google::cloud::StatusOr;
namespace spanner = ::google::cloud::spanner;
auto commit_result = client.Commit(
[&client](spanner::Transaction txn) -> StatusOr<spanner::Mutations> {
auto update = client.ExecuteDml(
std::move(txn),
spanner::SqlStatement(
"UPDATE Albums SET MarketingBudget = MarketingBudget * 2"
" WHERE SingerId = 1 AND AlbumId = 1"));
if (!update) return std::move(update).status();
return spanner::Mutations{};
});
if (!commit_result) throw std::move(commit_result).status();
std::cout << "Update was successful [spanner_dml_standard_update]\n";
}C#
using Google.Cloud.Spanner.Data;
using System;
using System.Threading.Tasks;
public class UpdateUsingDmlCoreAsyncSample
{
public async Task<int> UpdateUsingDmlCoreAsync(string projectId, string instanceId, string databaseId)
{
string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";
using var connection = new SpannerConnection(connectionString);
await connection.OpenAsync();
using var cmd = connection.CreateDmlCommand("UPDATE Albums SET MarketingBudget = MarketingBudget * 2 WHERE SingerId = 1 and AlbumId = 1");
int rowCount = await cmd.ExecuteNonQueryAsync();
Console.WriteLine($"{rowCount} row(s) updated...");
return rowCount;
}
}Go
import (
"context"
"fmt"
"io"
"cloud.google.com/go/spanner"
)
func updateUsingDML(w io.Writer, db string) error {
ctx := context.Background()
client, err := spanner.NewClient(ctx, db)
if err != nil {
return err
}
defer client.Close()
_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
stmt := spanner.Statement{
SQL: `UPDATE Albums
SET MarketingBudget = MarketingBudget * 2
WHERE SingerId = 1 and AlbumId = 1`,
}
rowCount, err := txn.Update(ctx, stmt)
if err != nil {
return err
}
fmt.Fprintf(w, "%d record(s) updated.\n", rowCount)
return nil
})
return err
}
Java
static void updateUsingDml(DatabaseClient dbClient) {
dbClient
.readWriteTransaction()
.run(transaction -> {
String sql =
"UPDATE Albums "
+ "SET MarketingBudget = MarketingBudget * 2 "
+ "WHERE SingerId = 1 and AlbumId = 1";
long rowCount = transaction.executeUpdate(Statement.of(sql));
System.out.printf("%d record updated.\n", rowCount);
return null;
});
}Node.js
// Imports the Google Cloud client library
const {Spanner} = require('@google-cloud/spanner');
/**
* TODO(developer): Uncomment the following lines before running the sample.
*/
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';
// Creates a client
const spanner = new Spanner({
projectId: projectId,
});
// Gets a reference to a Cloud Spanner instance and database
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);
database.runTransaction(async (err, transaction) => {
if (err) {
console.error(err);
return;
}
try {
const [rowCount] = await transaction.runUpdate({
sql: `UPDATE Albums SET MarketingBudget = MarketingBudget * 2
WHERE SingerId = 1 and AlbumId = 1`,
});
console.log(`Successfully updated ${rowCount} record.`);
await transaction.commit();
} catch (err) {
console.error('ERROR:', err);
} finally {
// Close the database when finished.
database.close();
}
});PHP
use Google\Cloud\Spanner\SpannerClient;
use Google\Cloud\Spanner\Transaction;
/**
* Updates sample data in the database with a DML statement.
*
* This requires the `MarketingBudget` column which must be created before
* running this sample. You can add the column by running the `add_column`
* sample or by running this DDL statement against your database:
*
* ALTER TABLE Albums ADD COLUMN MarketingBudget INT64
*
* Example:
* ```
* update_data($instanceId, $databaseId);
* ```
*
* @param string $instanceId The Spanner instance ID.
* @param string $databaseId The Spanner database ID.
*/
function update_data_with_dml(string $instanceId, string $databaseId): void
{
$spanner = new SpannerClient();
$instance = $spanner->instance($instanceId);
$database = $instance->database($databaseId);
$database->runTransaction(function (Transaction $t) {
$rowCount = $t->executeUpdate(
'UPDATE Albums '
. 'SET MarketingBudget = MarketingBudget * 2 '
. 'WHERE SingerId = 1 and AlbumId = 1');
$t->commit();
printf('Updated %d row(s).' . PHP_EOL, $rowCount);
});
}Python
# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)
def update_albums(transaction):
row_ct = transaction.execute_update(
"UPDATE Albums "
"SET MarketingBudget = MarketingBudget * 2 "
"WHERE SingerId = 1 and AlbumId = 1"
)
print("{} record(s) updated.".format(row_ct))
database.run_in_transaction(update_albums)Ruby
# project_id = "Your Google Cloud project ID"
# instance_id = "Your Spanner instance ID"
# database_id = "Your Spanner database ID"
require "google/cloud/spanner"
spanner = Google::Cloud::Spanner.new project: project_id
client = spanner.client instance_id, database_id
row_count = 0
client.transaction do |transaction|
row_count = transaction.execute_update(
"UPDATE Albums
SET MarketingBudget = MarketingBudget * 2
WHERE SingerId = 1 and AlbumId = 1"
)
end
puts "#{row_count} record updated."The following code example deletes all the rows in the Singers table where
the FirstName column is Alice.
C++
void DmlStandardDelete(google::cloud::spanner::Client client) {
using ::google::cloud::StatusOr;
namespace spanner = ::google::cloud::spanner;
auto commit_result = client.Commit([&client](spanner::Transaction txn)
-> StatusOr<spanner::Mutations> {
auto dele = client.ExecuteDml(
std::move(txn),
spanner::SqlStatement("DELETE FROM Singers WHERE FirstName = 'Alice'"));
if (!dele) return std::move(dele).status();
return spanner::Mutations{};
});
if (!commit_result) throw std::move(commit_result).status();
std::cout << "Delete was successful [spanner_dml_standard_delete]\n";
}C#
using Google.Cloud.Spanner.Data;
using System;
using System.Threading.Tasks;
public class DeleteUsingDmlCoreAsyncSample
{
public async Task<int> DeleteUsingDmlCoreAsync(string projectId, string instanceId, string databaseId)
{
string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";
using var connection = new SpannerConnection(connectionString);
await connection.OpenAsync();
using var cmd = connection.CreateDmlCommand("DELETE FROM Singers WHERE FirstName = 'Alice'");
int rowCount = await cmd.ExecuteNonQueryAsync();
Console.WriteLine($"{rowCount} row(s) deleted...");
return rowCount;
}
}Go
import (
"context"
"fmt"
"io"
"cloud.google.com/go/spanner"
)
func deleteUsingDML(w io.Writer, db string) error {
ctx := context.Background()
client, err := spanner.NewClient(ctx, db)
if err != nil {
return err
}
defer client.Close()
_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
stmt := spanner.Statement{SQL: `DELETE FROM Singers WHERE FirstName = 'Alice'`}
rowCount, err := txn.Update(ctx, stmt)
if err != nil {
return err
}
fmt.Fprintf(w, "%d record(s) deleted.\n", rowCount)
return nil
})
return err
}
Java
static void deleteUsingDml(DatabaseClient dbClient) {
dbClient
.readWriteTransaction()
.run(transaction -> {
String sql = "DELETE FROM Singers WHERE FirstName = 'Alice'";
long rowCount = transaction.executeUpdate(Statement.of(sql));
System.out.printf("%d record deleted.\n", rowCount);
return null;
});
}Node.js
// Imports the Google Cloud client library
const {Spanner} = require('@google-cloud/spanner');
/**
* TODO(developer): Uncomment the following lines before running the sample.
*/
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';
// Creates a client
const spanner = new Spanner({
projectId: projectId,
});
// Gets a reference to a Cloud Spanner instance and database
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);
database.runTransaction(async (err, transaction) => {
if (err) {
console.error(err);
return;
}
try {
const [rowCount] = await transaction.runUpdate({
sql: "DELETE FROM Singers WHERE FirstName = 'Alice'",
});
console.log(`Successfully deleted ${rowCount} record.`);
await transaction.commit();
} catch (err) {
console.error('ERROR:', err);
} finally {
// Close the database when finished.
database.close();
}
});PHP
use Google\Cloud\Spanner\SpannerClient;
use Google\Cloud\Spanner\Transaction;
/**
* Deletes sample data in the database with a DML statement.
*
* @param string $instanceId The Spanner instance ID.
* @param string $databaseId The Spanner database ID.
*/
function delete_data_with_dml(string $instanceId, string $databaseId): void
{
$spanner = new SpannerClient();
$instance = $spanner->instance($instanceId);
$database = $instance->database($databaseId);
$database->runTransaction(function (Transaction $t) {
$rowCount = $t->executeUpdate(
"DELETE FROM Singers WHERE FirstName = 'Alice'");
$t->commit();
printf('Deleted %d row(s).' . PHP_EOL, $rowCount);
});
}Python
# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)
def delete_singers(transaction):
row_ct = transaction.execute_update(
"DELETE FROM Singers WHERE FirstName = 'Alice'"
)
print("{} record(s) deleted.".format(row_ct))
database.run_in_transaction(delete_singers)Ruby
# project_id = "Your Google Cloud project ID"
# instance_id = "Your Spanner instance ID"
# database_id = "Your Spanner database ID"
require "google/cloud/spanner"
spanner = Google::Cloud::Spanner.new project: project_id
client = spanner.client instance_id, database_id
row_count = 0
client.transaction do |transaction|
row_count = transaction.execute_update(
"DELETE FROM Singers WHERE FirstName = 'Alice'"
)
end
puts "#{row_count} record deleted."The following example, for GoogleSQL-dialect databases only, uses a
STRUCT with bound parameters
to update the LastName in rows filtered by FirstName and LastName.
GoogleSQL
C++
void DmlStructs(google::cloud::spanner::Client client) {
namespace spanner = ::google::cloud::spanner;
std::int64_t rows_modified = 0;
auto commit_result =
client.Commit([&client, &rows_modified](spanner::Transaction const& txn)
-> google::cloud::StatusOr<spanner::Mutations> {
auto singer_info = std::make_tuple("Marc", "Richards");
auto sql = spanner::SqlStatement(
"UPDATE Singers SET FirstName = 'Keith' WHERE "
"STRUCT<FirstName String, LastName String>(FirstName, LastName) "
"= @name",
{{"name", spanner::Value(std::move(singer_info))}});
auto dml_result = client.ExecuteDml(txn, std::move(sql));
if (!dml_result) return std::move(dml_result).status();
rows_modified = dml_result->RowsModified();
return spanner::Mutations{};
});
if (!commit_result) throw std::move(commit_result).status();
std::cout << rows_modified
<< " update was successful [spanner_dml_structs]\n";
}C#
using Google.Cloud.Spanner.Data;
using System;
using System.Threading.Tasks;
public class UpdateUsingDmlWithStructCoreAsyncSample
{
public async Task<int> UpdateUsingDmlWithStructCoreAsync(string projectId, string instanceId, string databaseId)
{
var nameStruct = new SpannerStruct
{
{ "FirstName", SpannerDbType.String, "Timothy" },
{ "LastName", SpannerDbType.String, "Campbell" }
};
string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";
using var connection = new SpannerConnection(connectionString);
await connection.OpenAsync();
using var cmd = connection.CreateDmlCommand("UPDATE Singers SET LastName = 'Grant' WHERE STRUCT<FirstName STRING, LastName STRING>(FirstName, LastName) = @name");
cmd.Parameters.Add("name", nameStruct.GetSpannerDbType(), nameStruct);
int rowCount = await cmd.ExecuteNonQueryAsync();
Console.WriteLine($"{rowCount} row(s) updated...");
return rowCount;
}
}Go
import (
"context"
"fmt"
"io"
"cloud.google.com/go/spanner"
)
func updateUsingDMLStruct(w io.Writer, db string) error {
ctx := context.Background()
client, err := spanner.NewClient(ctx, db)
if err != nil {
return err
}
defer client.Close()
_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
type name struct {
FirstName string
LastName string
}
var singerInfo = name{"Timothy", "Campbell"}
stmt := spanner.Statement{
SQL: `Update Singers Set LastName = 'Grant'
WHERE STRUCT<FirstName String, LastName String>(Firstname, LastName) = @name`,
Params: map[string]interface{}{"name": singerInfo},
}
rowCount, err := txn.Update(ctx, stmt)
if err != nil {
return err
}
fmt.Fprintf(w, "%d record(s) inserted.\n", rowCount)
return nil
})
return err
}
Java
static void updateUsingDmlWithStruct(DatabaseClient dbClient) {
Struct name =
Struct.newBuilder().set("FirstName").to("Timothy").set("LastName").to("Campbell").build();
Statement s =
Statement.newBuilder(
"UPDATE Singers SET LastName = 'Grant' "
+ "WHERE STRUCT<FirstName STRING, LastName STRING>(FirstName, LastName) "
+ "= @name")
.bind("name")
.to(name)
.build();
dbClient
.readWriteTransaction()
.run(transaction -> {
long rowCount = transaction.executeUpdate(s);
System.out.printf("%d record updated.\n", rowCount);
return null;
});
}Node.js
// Imports the Google Cloud client library
const {Spanner} = require('@google-cloud/spanner');
const nameStruct = Spanner.struct({
FirstName: 'Timothy',
LastName: 'Campbell',
});
/**
* TODO(developer): Uncomment the following lines before running the sample.
*/
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';
// Creates a client
const spanner = new Spanner({
projectId: projectId,
});
// Gets a reference to a Cloud Spanner instance and database
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);
database.runTransaction(async (err, transaction) => {
if (err) {
console.error(err);
return;
}
try {
const [rowCount] = await transaction.runUpdate({
sql: `UPDATE Singers SET LastName = 'Grant'
WHERE STRUCT<FirstName STRING, LastName STRING>(FirstName, LastName) = @name`,
params: {
name: nameStruct,
},
});
console.log(`Successfully updated ${rowCount} record.`);
await transaction.commit();
} catch (err) {
console.error('ERROR:', err);
} finally {
// Close the database when finished.
database.close();
}
});PHP
use Google\Cloud\Spanner\SpannerClient;
use Google\Cloud\Spanner\Database;
use Google\Cloud\Spanner\Transaction;
use Google\Cloud\Spanner\StructType;
use Google\Cloud\Spanner\StructValue;
/**
* Update data with a DML statement using Structs.
*
* The database and table must already exist and can be created using
* `create_database`.
* Example:
* ```
* insert_data($instanceId, $databaseId);
* ```
*
* @param string $instanceId The Spanner instance ID.
* @param string $databaseId The Spanner database ID.
*/
function update_data_with_dml_structs(string $instanceId, string $databaseId): void
{
$spanner = new SpannerClient();
$instance = $spanner->instance($instanceId);
$database = $instance->database($databaseId);
$database->runTransaction(function (Transaction $t) {
$nameValue = (new StructValue)
->add('FirstName', 'Timothy')
->add('LastName', 'Campbell');
$nameType = (new StructType)
->add('FirstName', Database::TYPE_STRING)
->add('LastName', Database::TYPE_STRING);
$rowCount = $t->executeUpdate(
"UPDATE Singers SET LastName = 'Grant' "
. 'WHERE STRUCT<FirstName STRING, LastName STRING>(FirstName, LastName) '
. '= @name',
[
'parameters' => [
'name' => $nameValue
],
'types' => [
'name' => $nameType
]
]);
$t->commit();
printf('Updated %d row(s).' . PHP_EOL, $rowCount);
});
}Python
# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)
record_type = param_types.Struct(
[
param_types.StructField("FirstName", param_types.STRING),
param_types.StructField("LastName", param_types.STRING),
]
)
record_value = ("Timothy", "Campbell")
def write_with_struct(transaction):
row_ct = transaction.execute_update(
"UPDATE Singers SET LastName = 'Grant' "
"WHERE STRUCT<FirstName STRING, LastName STRING>"
"(FirstName, LastName) = @name",
params={"name": record_value},
param_types={"name": record_type},
)
print("{} record(s) updated.".format(row_ct))
database.run_in_transaction(write_with_struct)Ruby
# project_id = "Your Google Cloud project ID"
# instance_id = "Your Spanner instance ID"
# database_id = "Your Spanner database ID"
require "google/cloud/spanner"
spanner = Google::Cloud::Spanner.new project: project_id
client = spanner.client instance_id, database_id
row_count = 0
name_struct = { FirstName: "Timothy", LastName: "Campbell" }
client.transaction do |transaction|
row_count = transaction.execute_update(
"UPDATE Singers SET LastName = 'Grant'
WHERE STRUCT<FirstName STRING, LastName STRING>(FirstName, LastName) = @name",
params: { name: name_struct }
)
end
puts "#{row_count} record updated."Modify data with the returning DML statements
The THEN RETURN clause (GoogleSQL-dialect databases)
or RETURNING clause (PostgreSQL-dialect databases)
is intended for scenarios where you want to fetch data from modified rows. This
is especially useful when you want to view unspecified values in the DML
statements, default values, or generated columns.
To execute returning DML statements using the client library:
- Create a read-write transaction.
- Call the client library method for query execution and pass in the returning DML statement to obtain results.
The following code example inserts a new row into the Singers table, and it
returns the generated column FullName of the inserted records.
GoogleSQL
C++
void InsertUsingDmlReturning(google::cloud::spanner::Client client) {
// Insert records into SINGERS table and return the generated column
// FullName of the inserted records using `THEN RETURN FullName`.
auto commit = client.Commit(
[&client](google::cloud::spanner::Transaction txn)
-> google::cloud::StatusOr<google::cloud::spanner::Mutations> {
auto sql = google::cloud::spanner::SqlStatement(R"""(
INSERT INTO Singers (SingerId, FirstName, LastName)
VALUES (12, 'Melissa', 'Garcia'),
(13, 'Russell', 'Morales'),
(14, 'Jacqueline', 'Long'),
(15, 'Dylan', 'Shaw')
THEN RETURN FullName
)""");
using RowType = std::tuple<std::string>;
auto rows = client.ExecuteQuery(std::move(txn), std::move(sql));
// Note: This mutator might be re-run, or its effects discarded, so
// changing non-transactional state (e.g., by producing output) is,
// in general, not something to be imitated.
for (auto& row : google::cloud::spanner::StreamOf<RowType>(rows)) {
if (!row) return std::move(row).status();
std::cout << "FullName: " << std::get<0>(*row) << "\n";
}
std::cout << "Inserted row(s) count: " << rows.RowsModified() << "\n";
return google::cloud::spanner::Mutations{};
});
if (!commit) throw std::move(commit).status();
}C#
using Google.Cloud.Spanner.Data;
using System;
using System.Collections.Generic;
using System.Threading.Tasks;
public class InsertUsingDmlReturningAsyncSample
{
public async Task<List<string>> InsertUsingDmlReturningAsync(string projectId, string instanceId, string databaseId)
{
string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";
using var connection = new SpannerConnection(connectionString);
await connection.OpenAsync();
// Insert records into the SINGERS table and return the
// generated column FullName of the inserted records using
// 'THEN RETURN FullName'.
// It is also possible to return all columns of all the
// inserted records by using 'THEN RETURN *'.
using var cmd = connection.CreateDmlCommand(
@"INSERT INTO Singers(SingerId, FirstName, LastName) VALUES
(6, 'Melissa', 'Garcia'),
(7, 'Russell', 'Morales'),
(8, 'Jacqueline', 'Long'),
(9, 'Dylan', 'Shaw') THEN RETURN FullName");
var reader = await cmd.ExecuteReaderAsync();
var insertedSingerNames = new List<string>();
while (await reader.ReadAsync())
{
insertedSingerNames.Add(reader.GetFieldValue<string>("FullName"));
}
Console.WriteLine($"{insertedSingerNames.Count} row(s) inserted...");
return insertedSingerNames;
}
}Go
import (
"context"
"fmt"
"io"
"cloud.google.com/go/spanner"
"google.golang.org/api/iterator"
)
func insertUsingDMLReturning(w io.Writer, db string) error {
ctx := context.Background()
client, err := spanner.NewClient(ctx, db)
if err != nil {
return err
}
defer client.Close()
// Insert records into the SINGERS table and returns the
// generated column FullName of the inserted records using
// 'THEN RETURN FullName'.
// It is also possible to return all columns of all the
// inserted records by using 'THEN RETURN *'.
_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
stmt := spanner.Statement{
SQL: `INSERT INTO Singers (SingerId, FirstName, LastName)
VALUES (21, 'Melissa', 'Garcia'),
(22, 'Russell', 'Morales'),
(23, 'Jacqueline', 'Long'),
(24, 'Dylan', 'Shaw')
THEN RETURN FullName`,
}
iter := txn.Query(ctx, stmt)
defer iter.Stop()
for {
row, err := iter.Next()
if err == iterator.Done {
break
}
if err != nil {
return err
}
var fullName string
if err := row.Columns(&fullName); err != nil {
return err
}
fmt.Fprintf(w, "%s\n", fullName)
}
fmt.Fprintf(w, "%d record(s) inserted.\n", iter.RowCount)
return nil
})
return err
}
Java
import com.google.cloud.spanner.DatabaseClient;
import com.google.cloud.spanner.DatabaseId;
import com.google.cloud.spanner.ResultSet;
import com.google.cloud.spanner.Spanner;
import com.google.cloud.spanner.SpannerOptions;
import com.google.cloud.spanner.Statement;
public class InsertUsingDmlReturningSample {
static void insertUsingDmlReturning() {
// TODO(developer): Replace these variables before running the sample.
final String projectId = "my-project";
final String instanceId = "my-instance";
final String databaseId = "my-database";
insertUsingDmlReturning(projectId, instanceId, databaseId);
}
static void insertUsingDmlReturning(String projectId, String instanceId, String databaseId) {
try (Spanner spanner =
SpannerOptions.newBuilder()
.setProjectId(projectId)
.build()
.getService()) {
final DatabaseClient dbClient =
spanner.getDatabaseClient(DatabaseId.of(projectId, instanceId, databaseId));
// Insert records into the SINGERS table and returns the
// generated column FullName of the inserted records using
// ‘THEN RETURN FullName’.
// It is also possible to return all columns of all the
// inserted records by using ‘THEN RETURN *’.
dbClient
.readWriteTransaction()
.run(
transaction -> {
String sql =
"INSERT INTO Singers (SingerId, FirstName, LastName) VALUES "
+ "(12, 'Melissa', 'Garcia'), "
+ "(13, 'Russell', 'Morales'), "
+ "(14, 'Jacqueline', 'Long'), "
+ "(15, 'Dylan', 'Shaw') THEN RETURN FullName";
// readWriteTransaction.executeQuery(..) API should be used for executing
// DML statements with RETURNING clause.
try (ResultSet resultSet = transaction.executeQuery(Statement.of(sql))) {
while (resultSet.next()) {
System.out.println(resultSet.getString(0));
}
System.out.printf(
"Inserted row(s) count: %d\n", resultSet.getStats().getRowCountExact());
}
return null;
});
}
}
}Node.js
// Imports the Google Cloud client library.
const {Spanner} = require('@google-cloud/spanner');
/**
* TODO(developer): Uncomment the following lines before running the sample.
*/
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';
// Creates a client
const spanner = new Spanner({
projectId: projectId,
});
function insertUsingDmlReturning(instanceId, databaseId) {
// Gets a reference to a Cloud Spanner instance and database.
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);
database.runTransaction(async (err, transaction) => {
if (err) {
console.error(err);
return;
}
try {
const [rows, stats] = await transaction.run({
sql: 'INSERT Singers (SingerId, FirstName, LastName) VALUES (@id, @firstName, @lastName) THEN RETURN FullName',
params: {
id: 18,
firstName: 'Virginia',
lastName: 'Watson',
},
});
const rowCount = Math.floor(stats[stats.rowCount]);
console.log(
`Successfully inserted ${rowCount} record into the Singers table.`
);
rows.forEach(row => {
console.log(row.toJSON().FullName);
});
await transaction.commit();
} catch (err) {
console.error('ERROR:', err);
} finally {
// Close the database when finished.
database.close();
}
});
}
insertUsingDmlReturning(instanceId, databaseId);PHP
use Google\Cloud\Spanner\SpannerClient;
/**
* Inserts sample data into the given database using DML returning.
*
* @param string $instanceId The Spanner instance ID.
* @param string $databaseId The Spanner database ID.
*/
function insert_dml_returning(string $instanceId, string $databaseId): void
{
$spanner = new SpannerClient();
$instance = $spanner->instance($instanceId);
$database = $instance->database($databaseId);
// Insert records into SINGERS table and returns the generated column
// FullName of the inserted records using ‘THEN RETURN FullName’. It is also
// possible to return all columns of all the inserted records by using
// ‘THEN RETURN *’.
$sql = 'INSERT INTO Singers (SingerId, FirstName, LastName) '
. "VALUES (12, 'Melissa', 'Garcia'), "
. "(13, 'Russell', 'Morales'), "
. "(14, 'Jacqueline', 'Long'), "
. "(15, 'Dylan', 'Shaw') "
. 'THEN RETURN FullName';
$transaction = $database->transaction();
$result = $transaction->execute($sql);
foreach ($result->rows() as $row) {
printf(
'%s inserted.' . PHP_EOL,
$row['FullName'],
);
}
printf(
'Inserted row(s) count: %d' . PHP_EOL,
$result->stats()['rowCountExact']
);
$transaction->commit();
}Python
# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)
# Insert records into the SINGERS table and returns the
# generated column FullName of the inserted records using
# 'THEN RETURN FullName'.
# It is also possible to return all columns of all the
# inserted records by using 'THEN RETURN *'.
def insert_singers(transaction):
results = transaction.execute_sql(
"INSERT INTO Singers (SingerId, FirstName, LastName) VALUES "
"(21, 'Luann', 'Chizoba'), "
"(22, 'Denis', 'Patricio'), "
"(23, 'Felxi', 'Ronan'), "
"(24, 'Dominik', 'Martyna') "
"THEN RETURN FullName"
)
for result in results:
print("FullName: {}".format(*result))
print("{} record(s) inserted.".format(results.stats.row_count_exact))
database.run_in_transaction(insert_singers)Ruby
require "google/cloud/spanner"
##
# This is a snippet for showcasing how to use DML return feature with insert
# operation.
#
# @param project_id [String] The ID of the Google Cloud project.
# @param instance_id [String] The ID of the spanner instance.
# @param database_id [String] The ID of the database.
#
def spanner_insert_dml_returning project_id:, instance_id:, database_id:
spanner = Google::Cloud::Spanner.new project: project_id
client = spanner.client instance_id, database_id
client.transaction do |transaction|
# Insert records into the SINGERS table and returns the generated column
# FullName of the inserted records using ‘THEN RETURN FullName’.
# It is also possible to return all columns of all the inserted records
# by using ‘THEN RETURN *’.
results = transaction.execute_query "INSERT INTO Singers (SingerId, FirstName, LastName)
VALUES (12, 'Melissa', 'Garcia'), (13, 'Russell', 'Morales'), (14, 'Jacqueline', 'Long'), (15, 'Dylan', 'Shaw')
THEN RETURN FullName"
results.rows.each do |row|
puts "Inserted singers with FullName: #{row[:FullName]}"
end
puts "Inserted row(s) count: #{results.row_count}"
end
end
PostgreSQL
C++
void InsertUsingDmlReturning(google::cloud::spanner::Client client) {
// Insert records into SINGERS table and return the generated column
// FullName of the inserted records using `RETURNING FullName`.
auto commit = client.Commit(
[&client](google::cloud::spanner::Transaction txn)
-> google::cloud::StatusOr<google::cloud::spanner::Mutations> {
auto sql = google::cloud::spanner::SqlStatement(R"""(
INSERT INTO Singers (SingerId, FirstName, LastName)
VALUES (12, 'Melissa', 'Garcia'),
(13, 'Russell', 'Morales'),
(14, 'Jacqueline', 'Long'),
(15, 'Dylan', 'Shaw')
RETURNING FullName
)""");
using RowType = std::tuple<std::string>;
auto rows = client.ExecuteQuery(std::move(txn), std::move(sql));
for (auto& row : google::cloud::spanner::StreamOf<RowType>(rows)) {
if (!row) return std::move(row).status();
std::cout << "FullName: " << std::get<0>(*row) << "\n";
}
std::cout << "Inserted row(s) count: " << rows.RowsModified() << "\n";
return google::cloud::spanner::Mutations{};
});
if (!commit) throw std::move(commit).status();
}C#
using Google.Cloud.Spanner.Data;
using System;
using System.Collections.Generic;
using System.Threading.Tasks;
public class InsertUsingDmlReturningAsyncPostgresSample
{
public async Task<List<string>> InsertUsingDmlReturningAsyncPostgres(string projectId, string instanceId, string databaseId)
{
string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";
using var connection = new SpannerConnection(connectionString);
await connection.OpenAsync();
// Insert records into SINGERS table and return the
// generated column FullName of the inserted records
// using 'RETURNING FullName'.
// It is also possible to return all columns of all the
// inserted records by using 'RETURNING *'.
using var cmd = connection.CreateDmlCommand(
@"INSERT INTO Singers(SingerId, FirstName, LastName) VALUES
(6, 'Melissa', 'Garcia'),
(7, 'Russell', 'Morales'),
(8, 'Jacqueline', 'Long'),
(9, 'Dylan', 'Shaw') RETURNING FullName");
var reader = await cmd.ExecuteReaderAsync();
var insertedSingerNames = new List<string>();
while (await reader.ReadAsync())
{
insertedSingerNames.Add(reader.GetFieldValue<string>("fullname"));
}
Console.WriteLine($"{insertedSingerNames.Count} row(s) inserted...");
return insertedSingerNames;
}
}Go
import (
"context"
"fmt"
"io"
"cloud.google.com/go/spanner"
"google.golang.org/api/iterator"
)
func pgInsertUsingDMLReturning(w io.Writer, db string) error {
ctx := context.Background()
client, err := spanner.NewClient(ctx, db)
if err != nil {
return err
}
defer client.Close()
// Insert records into the SINGERS table and returns the
// generated column FullName of the inserted records using
// 'RETURNING FullName'.
// It is also possible to return all columns of all the
// inserted records by using 'RETURNING *'.
_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
stmt := spanner.Statement{
SQL: `INSERT INTO Singers (SingerId, FirstName, LastName)
VALUES (21, 'Melissa', 'Garcia'),
(22, 'Russell', 'Morales'),
(23, 'Jacqueline', 'Long'),
(24, 'Dylan', 'Shaw')
RETURNING FullName`,
}
iter := txn.Query(ctx, stmt)
defer iter.Stop()
for {
row, err := iter.Next()
if err == iterator.Done {
break
}
if err != nil {
return err
}
var fullName string
if err := row.Columns(&fullName); err != nil {
return err
}
fmt.Fprintf(w, "%s\n", fullName)
}
fmt.Fprintf(w, "%d record(s) inserted.\n", iter.RowCount)
return nil
})
return err
}
Java
import com.google.cloud.spanner.DatabaseClient;
import com.google.cloud.spanner.DatabaseId;
import com.google.cloud.spanner.ResultSet;
import com.google.cloud.spanner.Spanner;
import com.google.cloud.spanner.SpannerOptions;
import com.google.cloud.spanner.Statement;
public class PgInsertUsingDmlReturningSample {
static void insertUsingDmlReturning() {
// TODO(developer): Replace these variables before running the sample.
final String projectId = "my-project";
final String instanceId = "my-instance";
final String databaseId = "my-database";
insertUsingDmlReturning(projectId, instanceId, databaseId);
}
static void insertUsingDmlReturning(String projectId, String instanceId, String databaseId) {
try (Spanner spanner =
SpannerOptions.newBuilder()
.setProjectId(projectId)
.build()
.getService()) {
final DatabaseClient dbClient =
spanner.getDatabaseClient(DatabaseId.of(projectId, instanceId, databaseId));
// Insert records into SINGERS table and returns the
// generated column FullName of the inserted records
// using ‘RETURNING FullName’.
// It is also possible to return all columns of all the
// inserted records by using ‘RETURNING *’.
dbClient
.readWriteTransaction()
.run(
transaction -> {
String sql =
"INSERT INTO Singers (SingerId, FirstName, LastName) VALUES "
+ "(12, 'Melissa', 'Garcia'), "
+ "(13, 'Russell', 'Morales'), "
+ "(14, 'Jacqueline', 'Long'), "
+ "(15, 'Dylan', 'Shaw') RETURNING FullName";
// readWriteTransaction.executeQuery(..) API should be used for executing
// DML statements with RETURNING clause.
try (ResultSet resultSet = transaction.executeQuery(Statement.of(sql))) {
while (resultSet.next()) {
System.out.println(resultSet.getString(0));
}
System.out.printf(
"Inserted row(s) count: %d\n", resultSet.getStats().getRowCountExact());
}
return null;
});
}
}
}Node.js
// Imports the Google Cloud client library.
const {Spanner} = require('@google-cloud/spanner');
/**
* TODO(developer): Uncomment the following lines before running the sample.
*/
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';
// Creates a client
const spanner = new Spanner({
projectId: projectId,
});
function pgInsertUsingDmlReturning(instanceId, databaseId) {
// Gets a reference to a Cloud Spanner instance and database.
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);
database.runTransaction(async (err, transaction) => {
if (err) {
console.error(err);
return;
}
try {
const [rows, stats] = await transaction.run({
sql: 'INSERT Into Singers (SingerId, FirstName, LastName) VALUES ($1, $2, $3) RETURNING FullName',
params: {
p1: 18,
p2: 'Virginia',
p3: 'Watson',
},
});
const rowCount = Math.floor(stats[stats.rowCount]);
console.log(
`Successfully inserted ${rowCount} record into the Singers table.`
);
rows.forEach(row => {
console.log(row.toJSON().fullname);
});
await transaction.commit();
} catch (err) {
console.error('ERROR:', err);
} finally {
// Close the database when finished.
database.close();
}
});
}
pgInsertUsingDmlReturning(instanceId, databaseId);PHP
use Google\Cloud\Spanner\SpannerClient;
/**
* Inserts sample data into the given postgresql database using DML returning.
*
* @param string $instanceId The Spanner instance ID.
* @param string $databaseId The Spanner database ID.
*/
function pg_insert_dml_returning(string $instanceId, string $databaseId): void
{
$spanner = new SpannerClient();
$instance = $spanner->instance($instanceId);
$database = $instance->database($databaseId);
// Insert records into SINGERS table and returns the generated column
// FullName of the inserted records using ‘RETURNING FullName’. It is also
// possible to return all columns of all the inserted records by using
// ‘RETURNING *’.
$sql = 'INSERT INTO Singers (Singerid, FirstName, LastName) '
. "VALUES (12, 'Melissa', 'Garcia'), "
. "(13, 'Russell', 'Morales'), "
. "(14, 'Jacqueline', 'Long'), "
. "(15, 'Dylan', 'Shaw') "
. 'RETURNING FullName';
$transaction = $database->transaction();
$result = $transaction->execute($sql);
foreach ($result->rows() as $row) {
printf(
'%s inserted.' . PHP_EOL,
$row['fullname'],
);
}
printf(
'Inserted row(s) count: %d' . PHP_EOL,
$result->stats()['rowCountExact']
);
$transaction->commit();
}Python
# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)
# Insert records into the SINGERS table and returns the
# generated column FullName of the inserted records using
# 'RETURNING FullName'.
# It is also possible to return all columns of all the
# inserted records by using 'RETURNING *'.
def insert_singers(transaction):
results = transaction.execute_sql(
"INSERT INTO Singers (SingerId, FirstName, LastName) VALUES "
"(21, 'Luann', 'Chizoba'), "
"(22, 'Denis', 'Patricio'), "
"(23, 'Felxi', 'Ronan'), "
"(24, 'Dominik', 'Martyna') "
"RETURNING FullName"
)
for result in results:
print("FullName: {}".format(*result))
print("{} record(s) inserted.".format(results.stats.row_count_exact))
database.run_in_transaction(insert_singers)Ruby
require "google/cloud/spanner"
##
# This is a snippet for showcasing how to use DML return feature with insert
# operation in PostgreSql.
#
# @param project_id [String] The ID of the Google Cloud project.
# @param instance_id [String] The ID of the spanner instance.
# @param database_id [String] The ID of the database.
#
def spanner_postgresql_insert_dml_returning project_id:, instance_id:, database_id:
spanner = Google::Cloud::Spanner.new project: project_id
client = spanner.client instance_id, database_id
client.transaction do |transaction|
# Insert records into SINGERS table and returns the generated column
# FullName of the inserted records using ‘RETURNING FullName’.
# It is also possible to return all columns of all the inserted
# records by using ‘RETURNING *’.
results = transaction.execute_query "INSERT INTO Singers (SingerId, FirstName, LastName)
VALUES (12, 'Melissa', 'Garcia'), (13, 'Russell', 'Morales'), (14, 'Jacqueline', 'Long'), (15, 'Dylan', 'Shaw')
RETURNING FullName"
results.rows.each do |row|
puts "Inserted singers with FullName: #{row[:fullname]}"
end
puts "Inserted row(s) count: #{results.row_count}"
end
end
The following code example updates the MarketingBudget column of the Albums
table based on a WHERE clause, and it returns the modified MarketingBudget
column of the updated records.
GoogleSQL
C++
void UpdateUsingDmlReturning(google::cloud::spanner::Client client) {
// Update MarketingBudget column for records satisfying a particular
// condition and return the modified MarketingBudget column of the
// updated records using `THEN RETURN MarketingBudget`.
auto commit = client.Commit(
[&client](google::cloud::spanner::Transaction txn)
-> google::cloud::StatusOr<google::cloud::spanner::Mutations> {
auto sql = google::cloud::spanner::SqlStatement(R"""(
UPDATE Albums SET MarketingBudget = MarketingBudget * 2
WHERE SingerId = 1 AND AlbumId = 1
THEN RETURN MarketingBudget
)""");
using RowType = std::tuple<absl::optional<std::int64_t>>;
auto rows = client.ExecuteQuery(std::move(txn), std::move(sql));
// Note: This mutator might be re-run, or its effects discarded, so
// changing non-transactional state (e.g., by producing output) is,
// in general, not something to be imitated.
for (auto& row : google::cloud::spanner::StreamOf<RowType>(rows)) {
if (!row) return std::move(row).status();
std::cout << "MarketingBudget: ";
if (std::get<0>(*row).has_value()) {
std::cout << *std::get<0>(*row);
} else {
std::cout << "NULL";
}
std::cout << "\n";
}
std::cout << "Updated row(s) count: " << rows.RowsModified() << "\n";
return google::cloud::spanner::Mutations{};
});
if (!commit) throw std::move(commit).status();
}C#
using Google.Cloud.Spanner.Data;
using System;
using System.Collections.Generic;
using System.Threading.Tasks;
public class UpdateUsingDmlReturningAsyncSample
{
public async Task<List<long>> UpdateUsingDmlReturningAsync(string projectId, string instanceId, string databaseId)
{
string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";
using var connection = new SpannerConnection(connectionString);
await connection.OpenAsync();
// Update MarketingBudget column for records satisfying
// a particular condition and return the modified
// MarketingBudget column of the updated records using
// 'THEN RETURN MarketingBudget'.
// It is also possible to return all columns of all the
// updated records by using 'THEN RETURN *'.
using var cmd = connection.CreateDmlCommand("UPDATE Albums SET MarketingBudget = MarketingBudget * 2 WHERE SingerId = 1 and AlbumId = 1 THEN RETURN MarketingBudget");
var reader = await cmd.ExecuteReaderAsync();
var updatedMarketingBudgets = new List<long>();
while (await reader.ReadAsync())
{
updatedMarketingBudgets.Add(reader.GetFieldValue<long>("MarketingBudget"));
}
Console.WriteLine($"{updatedMarketingBudgets.Count} row(s) updated...");
return updatedMarketingBudgets;
}
}Go
import (
"context"
"fmt"
"io"
"cloud.google.com/go/spanner"
"google.golang.org/api/iterator"
)
func updateUsingDMLReturning(w io.Writer, db string) error {
ctx := context.Background()
client, err := spanner.NewClient(ctx, db)
if err != nil {
return err
}
defer client.Close()
// Update MarketingBudget column for records satisfying
// a particular condition and returns the modified
// MarketingBudget column of the updated records using
// 'THEN RETURN MarketingBudget'.
// It is also possible to return all columns of all the
// updated records by using 'THEN RETURN *'.
_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
stmt := spanner.Statement{
SQL: `UPDATE Albums
SET MarketingBudget = MarketingBudget * 2
WHERE SingerId = 1 and AlbumId = 1
THEN RETURN MarketingBudget`,
}
iter := txn.Query(ctx, stmt)
defer iter.Stop()
for {
row, err := iter.Next()
if err == iterator.Done {
break
}
if err != nil {
return err
}
var marketingBudget int64
if err := row.Columns(&marketingBudget); err != nil {
return err
}
fmt.Fprintf(w, "%d\n", marketingBudget)
}
fmt.Fprintf(w, "%d record(s) updated.\n", iter.RowCount)
return nil
})
return err
}
Java
import com.google.cloud.spanner.DatabaseClient;
import com.google.cloud.spanner.DatabaseId;
import com.google.cloud.spanner.ResultSet;
import com.google.cloud.spanner.Spanner;
import com.google.cloud.spanner.SpannerOptions;
import com.google.cloud.spanner.Statement;
public class UpdateUsingDmlReturningSample {
static void updateUsingDmlReturning() {
// TODO(developer): Replace these variables before running the sample.
final String projectId = "my-project";
final String instanceId = "my-instance";
final String databaseId = "my-database";
updateUsingDmlReturning(projectId, instanceId, databaseId);
}
static void updateUsingDmlReturning(String projectId, String instanceId, String databaseId) {
try (Spanner spanner =
SpannerOptions.newBuilder()
.setProjectId(projectId)
.build()
.getService()) {
final DatabaseClient dbClient =
spanner.getDatabaseClient(DatabaseId.of(projectId, instanceId, databaseId));
// Update MarketingBudget column for records satisfying
// a particular condition and returns the modified
// MarketingBudget column of the updated records using
// ‘THEN RETURN MarketingBudget’.
// It is also possible to return all columns of all the
// updated records by using ‘THEN RETURN *’.
dbClient
.readWriteTransaction()
.run(
transaction -> {
String sql =
"UPDATE Albums "
+ "SET MarketingBudget = MarketingBudget * 2 "
+ "WHERE SingerId = 1 and AlbumId = 1 "
+ "THEN RETURN MarketingBudget";
// readWriteTransaction.executeQuery(..) API should be used for executing
// DML statements with RETURNING clause.
try (ResultSet resultSet = transaction.executeQuery(Statement.of(sql))) {
while (resultSet.next()) {
System.out.printf("%d\n", resultSet.getLong(0));
}
System.out.printf(
"Updated row(s) count: %d\n", resultSet.getStats().getRowCountExact());
}
return null;
});
}
}
}Node.js
// Imports the Google Cloud client library.
const {Spanner} = require('@google-cloud/spanner');
/**
* TODO(developer): Uncomment the following lines before running the sample.
*/
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';
// Creates a client
const spanner = new Spanner({
projectId: projectId,
});
function updateUsingDmlReturning(instanceId, databaseId) {
// Gets a reference to a Cloud Spanner instance and database.
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);
database.runTransaction(async (err, transaction) => {
if (err) {
console.error(err);
return;
}
try {
const [rows, stats] = await transaction.run({
sql: 'UPDATE Albums SET MarketingBudget = 2000000 WHERE SingerId = 1 and AlbumId = 1 THEN RETURN MarketingBudget',
});
const rowCount = Math.floor(stats[stats.rowCount]);
console.log(
`Successfully updated ${rowCount} record into the Albums table.`
);
rows.forEach(row => {
console.log(row.toJSON().MarketingBudget);
});
await transaction.commit();
} catch (err) {
console.error('ERROR:', err);
} finally {
// Close the database when finished.
database.close();
}
});
}
updateUsingDmlReturning(instanceId, databaseId);PHP
use Google\Cloud\Spanner\SpannerClient;
/**
* Update the given database using DML returning.
*
* @param string $instanceId The Spanner instance ID.
* @param string $databaseId The Spanner database ID.
*/
function update_dml_returning(string $instanceId, string $databaseId): void
{
$spanner = new SpannerClient();
$instance = $spanner->instance($instanceId);
$database = $instance->database($databaseId);
$transaction = $database->transaction();
// Update MarketingBudget column for records satisfying a particular
// condition and returns the modified MarketingBudget column of the updated
// records using ‘THEN RETURN MarketingBudget’. It is also possible to return
// all columns of all the updated records by using ‘THEN RETURN *’.
$result = $transaction->execute(
'UPDATE Albums '
. 'SET MarketingBudget = MarketingBudget * 2 '
. 'WHERE SingerId = 1 and AlbumId = 1 '
. 'THEN RETURN MarketingBudget'
);
foreach ($result->rows() as $row) {
printf('MarketingBudget: %s' . PHP_EOL, $row['MarketingBudget']);
}
printf(
'Updated row(s) count: %d' . PHP_EOL,
$result->stats()['rowCountExact']
);
$transaction->commit();
}Python
# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)
# Update MarketingBudget column for records satisfying
# a particular condition and returns the modified
# MarketingBudget column of the updated records using
# 'THEN RETURN MarketingBudget'.
# It is also possible to return all columns of all the
# updated records by using 'THEN RETURN *'.
def update_albums(transaction):
results = transaction.execute_sql(
"UPDATE Albums "
"SET MarketingBudget = MarketingBudget * 2 "
"WHERE SingerId = 1 and AlbumId = 1 "
"THEN RETURN MarketingBudget"
)
for result in results:
print("MarketingBudget: {}".format(*result))
print("{} record(s) updated.".format(results.stats.row_count_exact))
database.run_in_transaction(update_albums)Ruby
require "google/cloud/spanner"
##
# This is a snippet for showcasing how to use DML return feature with update
# operation.
#
# @param project_id [String] The ID of the Google Cloud project.
# @param instance_id [String] The ID of the spanner instance.
# @param database_id [String] The ID of the database.
#
def spanner_update_dml_returning project_id:, instance_id:, database_id:
spanner = Google::Cloud::Spanner.new project: project_id
client = spanner.client instance_id, database_id
client.transaction do |transaction|
# Update MarketingBudget column for records satisfying a particular
# condition and returns the modified MarketingBudget column of the
# updated records using ‘THEN RETURN MarketingBudget’.
#
# It is also possible to return all columns of all the updated records
# by using ‘THEN RETURN *’.
results = transaction.execute_query "UPDATE Albums SET MarketingBudget = MarketingBudget * 2
WHERE SingerId = 1 and AlbumId = 1
THEN RETURN MarketingBudget"
results.rows.each do |row|
puts "Updated Album with MarketingBudget: #{row[:MarketingBudget]}"
end
puts "Updated row(s) count: #{results.row_count}"
end
end
PostgreSQL
C++
void UpdateUsingDmlReturning(google::cloud::spanner::Client client) {
// Update MarketingBudget column for records satisfying a particular
// condition and return the modified MarketingBudget column of the
// updated records using `RETURNING MarketingBudget`.
auto commit = client.Commit(
[&client](google::cloud::spanner::Transaction txn)
-> google::cloud::StatusOr<google::cloud::spanner::Mutations> {
auto sql = google::cloud::spanner::SqlStatement(R"""(
UPDATE Albums SET MarketingBudget = MarketingBudget * 2
WHERE SingerId = 1 AND AlbumId = 1
RETURNING MarketingBudget
)""");
using RowType = std::tuple<absl::optional<std::int64_t>>;
auto rows = client.ExecuteQuery(std::move(txn), std::move(sql));
for (auto& row : google::cloud::spanner::StreamOf<RowType>(rows)) {
if (!row) return std::move(row).status();
std::cout << "MarketingBudget: ";
if (std::get<0>(*row).has_value()) {
std::cout << *std::get<0>(*row);
} else {
std::cout << "NULL";
}
std::cout << "\n";
}
std::cout << "Updated row(s) count: " << rows.RowsModified() << "\n";
return google::cloud::spanner::Mutations{};
});
if (!commit) throw std::move(commit).status();
}C#
using Google.Cloud.Spanner.Data;
using System;
using System.Collections.Generic;
using System.Threading.Tasks;
public class UpdateUsingDmlReturningAsyncPostgresSample
{
public async Task<List<long>> UpdateUsingDmlReturningAsyncPostgres(string projectId, string instanceId, string databaseId)
{
string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";
using var connection = new SpannerConnection(connectionString);
await connection.OpenAsync();
// Update MarketingBudget column for records satisfying
// a particular condition and return the modified
// MarketingBudget column of the updated records using
// 'RETURNING MarketingBudget'.
// It is also possible to return all columns of all the
// updated records by using 'RETURNING *'.
using var cmd = connection.CreateDmlCommand("UPDATE Albums SET MarketingBudget = MarketingBudget * 2 WHERE SingerId = 14 and AlbumId = 20 RETURNING MarketingBudget");
var reader = await cmd.ExecuteReaderAsync();
var updatedMarketingBudgets = new List<long>();
while (await reader.ReadAsync())
{
updatedMarketingBudgets.Add(reader.GetFieldValue<long>("marketingbudget"));
}
Console.WriteLine($"{updatedMarketingBudgets.Count} row(s) updated...");
return updatedMarketingBudgets;
}
}Go
import (
"context"
"fmt"
"io"
"cloud.google.com/go/spanner"
"google.golang.org/api/iterator"
)
func pgUpdateUsingDMLReturning(w io.Writer, db string) error {
ctx := context.Background()
client, err := spanner.NewClient(ctx, db)
if err != nil {
return err
}
defer client.Close()
// Update MarketingBudget column for records satisfying
// a particular condition and returns the modified
// MarketingBudget column of the updated records using
// 'RETURNING MarketingBudget'.
// It is also possible to return all columns of all the
// updated records by using 'RETURNING *'.
_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
stmt := spanner.Statement{
SQL: `UPDATE Albums
SET MarketingBudget = MarketingBudget * 2
WHERE SingerId = 1 and AlbumId = 1
RETURNING MarketingBudget`,
}
iter := txn.Query(ctx, stmt)
defer iter.Stop()
for {
row, err := iter.Next()
if err == iterator.Done {
break
}
if err != nil {
return err
}
var marketingBudget int64
if err := row.Columns(&marketingBudget); err != nil {
return err
}
fmt.Fprintf(w, "%d\n", marketingBudget)
}
fmt.Fprintf(w, "%d record(s) updated.\n", iter.RowCount)
return nil
})
return err
}
Java
import com.google.cloud.spanner.DatabaseClient;
import com.google.cloud.spanner.DatabaseId;
import com.google.cloud.spanner.ResultSet;
import com.google.cloud.spanner.Spanner;
import com.google.cloud.spanner.SpannerOptions;
import com.google.cloud.spanner.Statement;
public class PgUpdateUsingDmlReturningSample {
static void updateUsingDmlReturning() {
// TODO(developer): Replace these variables before running the sample.
final String projectId = "my-project";
final String instanceId = "my-instance";
final String databaseId = "my-database";
updateUsingDmlReturning(projectId, instanceId, databaseId);
}
static void updateUsingDmlReturning(String projectId, String instanceId, String databaseId) {
try (Spanner spanner =
SpannerOptions.newBuilder()
.setProjectId(projectId)
.build()
.getService()) {
final DatabaseClient dbClient =
spanner.getDatabaseClient(DatabaseId.of(projectId, instanceId, databaseId));
// Update MarketingBudget column for records satisfying
// a particular condition and returns the modified
// MarketingBudget column of the updated records using
// ‘RETURNING MarketingBudget’.
// It is also possible to return all columns of all the
// updated records by using ‘RETURNING *’.
dbClient
.readWriteTransaction()
.run(
transaction -> {
String sql =
"UPDATE Albums "
+ "SET MarketingBudget = MarketingBudget * 2 "
+ "WHERE SingerId = 1 and AlbumId = 1 "
+ "RETURNING MarketingBudget";
// readWriteTransaction.executeQuery(..) API should be used for executing
// DML statements with RETURNING clause.
try (ResultSet resultSet = transaction.executeQuery(Statement.of(sql))) {
while (resultSet.next()) {
System.out.printf("%d\n", resultSet.getLong(0));
}
System.out.printf(
"Updated row(s) count: %d\n", resultSet.getStats().getRowCountExact());
}
return null;
});
}
}
}Node.js
// Imports the Google Cloud client library.
const {Spanner} = require('@google-cloud/spanner');
/**
* TODO(developer): Uncomment the following lines before running the sample.
*/
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';
// Creates a client
const spanner = new Spanner({
projectId: projectId,
});
function pgUpdateUsingDmlReturning(instanceId, databaseId) {
// Gets a reference to a Cloud Spanner instance and database.
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);
database.runTransaction(async (err, transaction) => {
if (err) {
console.error(err);
return;
}
try {
const [rows, stats] = await transaction.run({
sql: 'UPDATE singers SET FirstName = $1, LastName = $2 WHERE singerid = $3 RETURNING FullName',
params: {
p1: 'Virginia1',
p2: 'Watson1',
p3: 18,
},
});
const rowCount = Math.floor(stats[stats.rowCount]);
console.log(
`Successfully updated ${rowCount} record into the Singers table.`
);
rows.forEach(row => {
console.log(row.toJSON().fullname);
});
await transaction.commit();
} catch (err) {
console.error('ERROR:', err);
} finally {
// Close the database when finished.
database.close();
}
});
}
pgUpdateUsingDmlReturning(instanceId, databaseId);PHP
use Google\Cloud\Spanner\SpannerClient;
/**
* Update the given postgresql database using DML returning.
*
* @param string $instanceId The Spanner instance ID.
* @param string $databaseId The Spanner database ID.
*/
function pg_update_dml_returning(string $instanceId, string $databaseId): void
{
$spanner = new SpannerClient();
$instance = $spanner->instance($instanceId);
$database = $instance->database($databaseId);
$transaction = $database->transaction();
// Update MarketingBudget column for records satisfying a particular
// condition and returns the modified MarketingBudget column of the updated
// records using ‘RETURNING MarketingBudget’. It is also possible to return
// all columns of all the updated records by using ‘RETURNING *’.
$result = $transaction->execute(
'UPDATE Albums '
. 'SET MarketingBudget = MarketingBudget * 2 '
. 'WHERE SingerId = 1 and AlbumId = 1'
. 'RETURNING MarketingBudget'
);
foreach ($result->rows() as $row) {
printf('MarketingBudget: %s' . PHP_EOL, $row['marketingbudget']);
}
printf(
'Updated row(s) count: %d' . PHP_EOL,
$result->stats()['rowCountExact']
);
$transaction->commit();
}Python
# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)
# Update MarketingBudget column for records satisfying
# a particular condition and returns the modified
# MarketingBudget column of the updated records using
# 'RETURNING MarketingBudget'.
# It is also possible to return all columns of all the
# updated records by using 'RETURNING *'.
def update_albums(transaction):
results = transaction.execute_sql(
"UPDATE Albums "
"SET MarketingBudget = MarketingBudget * 2 "
"WHERE SingerId = 1 and AlbumId = 1 "
"RETURNING MarketingBudget"
)
for result in results:
print("MarketingBudget: {}".format(*result))
print("{} record(s) updated.".format(results.stats.row_count_exact))
database.run_in_transaction(update_albums)Ruby
require "google/cloud/spanner"
##
# This is a snippet for showcasing how to use DML return feature with update
# operation in PostgreSql.
#
# @param project_id [String] The ID of the Google Cloud project.
# @param instance_id [String] The ID of the spanner instance.
# @param database_id [String] The ID of the database.
#
def spanner_postgresql_update_dml_returning project_id:, instance_id:, database_id:
spanner = Google::Cloud::Spanner.new project: project_id
client = spanner.client instance_id, database_id
client.transaction do |transaction|
# Update MarketingBudget column for records satisfying a particular
# condition and returns the modified MarketingBudget column of the
# updated records using ‘RETURNING MarketingBudget’.
# It is also possible to return all columns of all the updated records
# by using ‘RETURNING *’.
results = transaction.execute_query "UPDATE Albums SET MarketingBudget = MarketingBudget * 2
WHERE SingerId = 1 and AlbumId = 1
RETURNING MarketingBudget"
results.rows.each do |row|
puts "Updated Albums with MarketingBudget: #{row[:marketingbudget]}"
end
puts "Updated row(s) count: #{results.row_count}"
end
end
The following code example deletes all the rows in the Singers table where the
FirstName column is Alice, and it returns the SingerId and FullName
column of the deleted records.
GoogleSQL
C++
void DeleteUsingDmlReturning(google::cloud::spanner::Client client) {
// Delete records from SINGERS table satisfying a particular condition
// and return the SingerId and FullName column of the deleted records
// using `THEN RETURN SingerId, FullName'.
auto commit = client.Commit(
[&client](google::cloud::spanner::Transaction txn)
-> google::cloud::StatusOr<google::cloud::spanner::Mutations> {
auto sql = google::cloud::spanner::SqlStatement(R"""(
DELETE FROM Singers
WHERE FirstName = 'Alice'
THEN RETURN SingerId, FullName
)""");
using RowType = std::tuple<std::int64_t, std::string>;
auto rows = client.ExecuteQuery(std::move(txn), std::move(sql));
// Note: This mutator might be re-run, or its effects discarded, so
// changing non-transactional state (e.g., by producing output) is,
// in general, not something to be imitated.
for (auto& row : google::cloud::spanner::StreamOf<RowType>(rows)) {
if (!row) return std::move(row).status();
std::cout << "SingerId: " << std::get<0>(*row) << " ";
std::cout << "FullName: " << std::get<1>(*row) << "\n";
}
std::cout << "Deleted row(s) count: " << rows.RowsModified() << "\n";
return google::cloud::spanner::Mutations{};
});
if (!commit) throw std::move(commit).status();
}C#
using Google.Cloud.Spanner.Data;
using System;
using System.Collections.Generic;
using System.Threading;
using System.Threading.Tasks;
public class DeleteUsingDmlReturningAsyncSample
{
public async Task<List<string>> DeleteUsingDmlReturningAsync(string projectId, string instanceId, string databaseId)
{
string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";
using var connection = new SpannerConnection(connectionString);
await connection.OpenAsync();
// Delete records from SINGERS table satisfying a
// particular condition and return the SingerId
// and FullName column of the deleted records using
// 'THEN RETURN SingerId, FullName'.
// It is also possible to return all columns of all the
// deleted records by using 'THEN RETURN *'.
using var cmd = connection.CreateDmlCommand("DELETE FROM Singers WHERE FirstName = 'Alice' THEN RETURN SingerId, FullName");
var reader = await cmd.ExecuteReaderAsync();
var deletedSingerNames = new List<string>();
while (await reader.ReadAsync())
{
deletedSingerNames.Add(reader.GetFieldValue<string>("FullName"));
}
Console.WriteLine($"{deletedSingerNames.Count} row(s) deleted...");
return deletedSingerNames;
}
}Go
import (
"context"
"fmt"
"io"
"cloud.google.com/go/spanner"
"google.golang.org/api/iterator"
)
func deleteUsingDMLReturning(w io.Writer, db string) error {
ctx := context.Background()
client, err := spanner.NewClient(ctx, db)
if err != nil {
return err
}
defer client.Close()
// Delete records from SINGERS table satisfying a
// particular condition and returns the SingerId
// and FullName column of the deleted records using
// 'THEN RETURN SingerId, FullName'.
// It is also possible to return all columns of all the
// deleted records by using 'THEN RETURN *'.
_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
stmt := spanner.Statement{
SQL: `DELETE FROM Singers WHERE FirstName = 'Alice'
THEN RETURN SingerId, FullName`,
}
iter := txn.Query(ctx, stmt)
defer iter.Stop()
for {
row, err := iter.Next()
if err == iterator.Done {
break
}
if err != nil {
return err
}
var (
singerID int64
fullName string
)
if err := row.Columns(&singerID, &fullName); err != nil {
return err
}
fmt.Fprintf(w, "%d %s\n", singerID, fullName)
}
fmt.Fprintf(w, "%d record(s) deleted.\n", iter.RowCount)
return nil
})
return err
}
Java
import com.google.cloud.spanner.DatabaseClient;
import com.google.cloud.spanner.DatabaseId;
import com.google.cloud.spanner.ResultSet;
import com.google.cloud.spanner.Spanner;
import com.google.cloud.spanner.SpannerOptions;
import com.google.cloud.spanner.Statement;
public class DeleteUsingDmlReturningSample {
static void deleteUsingDmlReturningSample() {
// TODO(developer): Replace these variables before running the sample.
final String projectId = "my-project";
final String instanceId = "my-instance";
final String databaseId = "my-database";
deleteUsingDmlReturningSample(projectId, instanceId, databaseId);
}
static void deleteUsingDmlReturningSample(
String projectId, String instanceId, String databaseId) {
try (Spanner spanner =
SpannerOptions.newBuilder()
.setProjectId(projectId)
.build()
.getService()) {
final DatabaseClient dbClient =
spanner.getDatabaseClient(DatabaseId.of(projectId, instanceId, databaseId));
// Delete records from SINGERS table satisfying a
// particular condition and returns the SingerId
// and FullName column of the deleted records using
// ‘THEN RETURN SingerId, FullName’.
// It is also possible to return all columns of all the
// deleted records by using ‘THEN RETURN *’.
dbClient
.readWriteTransaction()
.run(
transaction -> {
String sql =
"DELETE FROM Singers WHERE FirstName = 'Alice' THEN RETURN SingerId, FullName";
// readWriteTransaction.executeQuery(..) API should be used for executing
// DML statements with RETURNING clause.
try (ResultSet resultSet = transaction.executeQuery(Statement.of(sql))) {
while (resultSet.next()) {
System.out.printf("%d %s\n", resultSet.getLong(0), resultSet.getString(1));
}
System.out.printf(
"Deleted row(s) count: %d\n", resultSet.getStats().getRowCountExact());
}
return null;
});
}
}
}Node.js
// Imports the Google Cloud client library.
const {Spanner} = require('@google-cloud/spanner');
/**
* TODO(developer): Uncomment the following lines before running the sample.
*/
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';
// Creates a client
const spanner = new Spanner({
projectId: projectId,
});
function deleteUsingDmlReturning(instanceId, databaseId) {
// Gets a reference to a Cloud Spanner instance and database.
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);
database.runTransaction(async (err, transaction) => {
if (err) {
console.error(err);
return;
}
try {
const [rows, stats] = await transaction.run({
sql: 'DELETE FROM Singers WHERE SingerId = 18 THEN RETURN FullName',
});
const rowCount = Math.floor(stats[stats.rowCount]);
console.log(
`Successfully deleted ${rowCount} record from the Singers table.`
);
rows.forEach(row => {
console.log(row.toJSON().FullName);
});
await transaction.commit();
} catch (err) {
console.error('ERROR:', err);
} finally {
// Close the database when finished.
database.close();
}
});
}
deleteUsingDmlReturning(instanceId, databaseId);PHP
use Google\Cloud\Spanner\SpannerClient;
/**
* Delete data from the given database using DML returning.
*
* @param string $instanceId The Spanner instance ID.
* @param string $databaseId The Spanner database ID.
*/
function delete_dml_returning(string $instanceId, string $databaseId): void
{
$spanner = new SpannerClient();
$instance = $spanner->instance($instanceId);
$database = $instance->database($databaseId);
$transaction = $database->transaction();
// Delete records from SINGERS table satisfying a particular condition and
// returns the SingerId and FullName column of the deleted records using
// 'THEN RETURN SingerId, FullName'. It is also possible to return all columns
// of all the deleted records by using 'THEN RETURN *'.
$result = $transaction->execute(
"DELETE FROM Singers WHERE FirstName = 'Alice' "
. 'THEN RETURN SingerId, FullName',
);
foreach ($result->rows() as $row) {
printf(
'%d %s.' . PHP_EOL,
$row['SingerId'],
$row['FullName']
);
}
printf(
'Deleted row(s) count: %d' . PHP_EOL,
$result->stats()['rowCountExact']
);
$transaction->commit();
}Python
# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)
# Delete records from SINGERS table satisfying a
# particular condition and returns the SingerId
# and FullName column of the deleted records using
# 'THEN RETURN SingerId, FullName'.
# It is also possible to return all columns of all the
# deleted records by using 'THEN RETURN *'.
def delete_singers(transaction):
results = transaction.execute_sql(
"DELETE FROM Singers WHERE FirstName = 'David' "
"THEN RETURN SingerId, FullName"
)
for result in results:
print("SingerId: {}, FullName: {}".format(*result))
print("{} record(s) deleted.".format(results.stats.row_count_exact))
database.run_in_transaction(delete_singers)Ruby
require "google/cloud/spanner"
##
# This is a snippet for showcasing how to use DML return feature with delete
# operation.
#
# @param project_id [String] The ID of the Google Cloud project.
# @param instance_id [String] The ID of the spanner instance.
# @param database_id [String] The ID of the database.
#
def spanner_delete_dml_returning project_id:, instance_id:, database_id:
spanner = Google::Cloud::Spanner.new project: project_id
client = spanner.client instance_id, database_id
client.transaction do |transaction|
# Delete records from SINGERS table satisfying a particular condition and
# returns the SingerId and FullName column of the deleted records using
# ‘THEN RETURN SingerId, FullName’.
# It is also possible to return all columns of all the deleted records
# by using ‘THEN RETURN *’.
results = transaction.execute_query "DELETE FROM Singers WHERE FirstName = 'Alice' THEN RETURN SingerId, FullName"
results.rows.each do |row|
puts "Deleted singer with SingerId: #{row[:SingerId]}, FullName: #{row[:FullName]}"
end
puts "Deleted row(s) count: #{results.row_count}"
end
end
PostgreSQL
C++
void DeleteUsingDmlReturning(google::cloud::spanner::Client client) {
// Delete records from SINGERS table satisfying a particular condition
// and return the SingerId and FullName column of the deleted records
// using `RETURNING SingerId, FullName'.
auto commit = client.Commit(
[&client](google::cloud::spanner::Transaction txn)
-> google::cloud::StatusOr<google::cloud::spanner::Mutations> {
auto sql = google::cloud::spanner::SqlStatement(R"""(
DELETE FROM Singers
WHERE FirstName = 'Alice'
RETURNING SingerId, FullName
)""");
using RowType = std::tuple<std::int64_t, std::string>;
auto rows = client.ExecuteQuery(std::move(txn), std::move(sql));
for (auto& row : google::cloud::spanner::StreamOf<RowType>(rows)) {
if (!row) return std::move(row).status();
std::cout << "SingerId: " << std::get<0>(*row) << " ";
std::cout << "FullName: " << std::get<1>(*row) << "\n";
}
std::cout << "Deleted row(s) count: " << rows.RowsModified() << "\n";
return google::cloud::spanner::Mutations{};
});
if (!commit) throw std::move(commit).status();
}C#
using Google.Cloud.Spanner.Data;
using System;
using System.Collections.Generic;
using System.Threading.Tasks;
public class DeleteUsingDmlReturningAsyncPostgresSample
{
public async Task<List<string>> DeleteUsingDmlReturningAsyncPostgres(string projectId, string instanceId, string databaseId)
{
string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";
using var connection = new SpannerConnection(connectionString);
await connection.OpenAsync();
// Delete records from SINGERS table satisfying a
// particular condition and return the SingerId
// and FullName column of the deleted records using
// 'RETURNING SingerId, FullName'.
// It is also possible to return all columns of all the
// deleted records by using 'RETURNING *'.
using var cmd = connection.CreateDmlCommand("DELETE FROM Singers WHERE FirstName = 'Lata' RETURNING SingerId, FullName");
var reader = await cmd.ExecuteReaderAsync();
var deletedSingerNames = new List<string>();
while (await reader.ReadAsync())
{
deletedSingerNames.Add(reader.GetFieldValue<string>("fullname"));
}
Console.WriteLine($"{deletedSingerNames.Count} row(s) deleted...");
return deletedSingerNames;
}
}Go
import (
"context"
"fmt"
"io"
"cloud.google.com/go/spanner"
"google.golang.org/api/iterator"
)
func pgDeleteUsingDMLReturning(w io.Writer, db string) error {
ctx := context.Background()
client, err := spanner.NewClient(ctx, db)
if err != nil {
return err
}
defer client.Close()
// Delete records from SINGERS table satisfying a
// particular condition and returns the SingerId
// and FullName column of the deleted records using
// 'RETURNING SingerId, FullName'.
// It is also possible to return all columns of all the
// deleted records by using 'RETURNING *'.
_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
stmt := spanner.Statement{
SQL: `DELETE FROM Singers WHERE FirstName = 'Alice'
RETURNING SingerId, FullName`,
}
iter := txn.Query(ctx, stmt)
defer iter.Stop()
for {
row, err := iter.Next()
if err == iterator.Done {
break
}
if err != nil {
return err
}
var (
singerID int64
fullName string
)
if err := row.Columns(&singerID, &fullName); err != nil {
return err
}
fmt.Fprintf(w, "%d %s\n", singerID, fullName)
}
fmt.Fprintf(w, "%d record(s) deleted.\n", iter.RowCount)
return nil
})
return err
}
Java
import com.google.cloud.spanner.DatabaseClient;
import com.google.cloud.spanner.DatabaseId;
import com.google.cloud.spanner.ResultSet;
import com.google.cloud.spanner.Spanner;
import com.google.cloud.spanner.SpannerOptions;
import com.google.cloud.spanner.Statement;
public class PgDeleteUsingDmlReturningSample {
static void deleteUsingDmlReturningSample() {
// TODO(developer): Replace these variables before running the sample.
final String projectId = "my-project";
final String instanceId = "my-instance";
final String databaseId = "my-database";
deleteUsingDmlReturningSample(projectId, instanceId, databaseId);
}
static void deleteUsingDmlReturningSample(
String projectId, String instanceId, String databaseId) {
try (Spanner spanner =
SpannerOptions.newBuilder()
.setProjectId(projectId)
.build()
.getService()) {
final DatabaseClient dbClient =
spanner.getDatabaseClient(DatabaseId.of(projectId, instanceId, databaseId));
// Delete records from SINGERS table satisfying a
// particular condition and returns the SingerId
// and FullName column of the deleted records using
// ‘RETURNING SingerId, FullName’.
// It is also possible to return all columns of all the
// deleted records by using ‘RETURNING *’.
dbClient
.readWriteTransaction()
.run(
transaction -> {
String sql =
"DELETE FROM Singers WHERE FirstName = 'Alice' RETURNING SingerId, FullName";
// readWriteTransaction.executeQuery(..) API should be used for executing
// DML statements with RETURNING clause.
try (ResultSet resultSet = transaction.executeQuery(Statement.of(sql))) {
while (resultSet.next()) {
System.out.printf("%d %s\n", resultSet.getLong(0), resultSet.getString(1));
}
System.out.printf(
"Deleted row(s) count: %d\n", resultSet.getStats().getRowCountExact());
}
return null;
});
}
}
}Node.js
// Imports the Google Cloud client library.
const {Spanner} = require('@google-cloud/spanner');
/**
* TODO(developer): Uncomment the following lines before running the sample.
*/
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';
// Creates a client
const spanner = new Spanner({
projectId: projectId,
});
function pgDeleteUsingDmlReturning(instanceId, databaseId) {
// Gets a reference to a Cloud Spanner instance and database.
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);
database.runTransaction(async (err, transaction) => {
if (err) {
console.error(err);
return;
}
try {
const [rows, stats] = await transaction.run({
sql: 'DELETE FROM Singers WHERE SingerId = 18 RETURNING FullName',
});
const rowCount = Math.floor(stats[stats.rowCount]);
console.log(
`Successfully deleted ${rowCount} record from the Singers table.`
);
rows.forEach(row => {
console.log(row.toJSON().fullname);
});
await transaction.commit();
} catch (err) {
console.error('ERROR:', err);
} finally {
// Close the database when finished.
database.close();
}
});
}
pgDeleteUsingDmlReturning(instanceId, databaseId);PHP
use Google\Cloud\Spanner\SpannerClient;
/**
* Delete data from the given postgresql database using DML returning.
*
* @param string $instanceId The Spanner instance ID.
* @param string $databaseId The Spanner database ID.
*/
function pg_delete_dml_returning(string $instanceId, string $databaseId): void
{
$spanner = new SpannerClient();
$instance = $spanner->instance($instanceId);
$database = $instance->database($databaseId);
$transaction = $database->transaction();
// Delete records from SINGERS table satisfying a particular condition and
// returns the SingerId and FullName column of the deleted records using
// ‘RETURNING SingerId, FullName’. It is also possible to return all columns
// of all the deleted records by using ‘RETURNING *’.
$result = $transaction->execute(
"DELETE FROM Singers WHERE FirstName = 'Alice' "
. 'RETURNING SingerId, FullName',
);
foreach ($result->rows() as $row) {
printf(
'%d %s.' . PHP_EOL,
$row['singerid'],
$row['fullname']
);
}
printf(
'Deleted row(s) count: %d' . PHP_EOL,
$result->stats()['rowCountExact']
);
$transaction->commit();
}Python
# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)
# Delete records from SINGERS table satisfying a
# particular condition and returns the SingerId
# and FullName column of the deleted records using
# 'RETURNING SingerId, FullName'.
# It is also possible to return all columns of all the
# deleted records by using 'RETURNING *'.
def delete_singers(transaction):
results = transaction.execute_sql(
"DELETE FROM Singers WHERE FirstName = 'David' "
"RETURNING SingerId, FullName"
)
for result in results:
print("SingerId: {}, FullName: {}".format(*result))
print("{} record(s) deleted.".format(results.stats.row_count_exact))
database.run_in_transaction(delete_singers)Ruby
require "google/cloud/spanner"
##
# This is a snippet for showcasing how to use DML return feature with delete
# operation in PostgreSql.
#
# @param project_id [String] The ID of the Google Cloud project.
# @param instance_id [String] The ID of the spanner instance.
# @param database_id [String] The ID of the database.
#
def spanner_postgresql_delete_dml_returning project_id:, instance_id:, database_id:
spanner = Google::Cloud::Spanner.new project: project_id
client = spanner.client instance_id, database_id
client.transaction do |transaction|
# Delete records from SINGERS table satisfying a particular condition and
# returns the SingerId and FullName column of the deleted records using
# ‘RETURNING SingerId, FullName’.
# It is also possible to return all columns of all the deleted records
# by using ‘RETURNING *’.
results = transaction.execute_query "DELETE FROM singers WHERE firstname = 'Alice' RETURNING SingerId, FullName"
results.rows.each do |row|
puts "Deleted singer with SingerId: #{row[:singerid]}, FullName: #{row[:fullname]}"
end
puts "Deleted row(s) count: #{results.row_count}"
end
end
Read data written in the same transaction
Changes you make using DML statements are visible to subsequent statements in the same transaction. This is different from using mutations, where changes are not visible until the transaction commits.
Spanner checks the constraints after every DML statement. This is different from using mutations, where Spanner buffers mutations in the client until commit and checks constraints at commit time. Evaluating the constraints after each statement allows Spanner to guarantee that the data that a DML statement returns is consistent with the schema.
The following example updates a row in the Singers table, then executes a
SELECT statement to print the new values.
C++
void DmlWriteThenRead(google::cloud::spanner::Client client) {
namespace spanner = ::google::cloud::spanner;
using ::google::cloud::StatusOr;
auto commit_result = client.Commit(
[&client](spanner::Transaction txn) -> StatusOr<spanner::Mutations> {
auto insert = client.ExecuteDml(
txn, spanner::SqlStatement(
"INSERT INTO Singers (SingerId, FirstName, LastName)"
" VALUES (11, 'Timothy', 'Campbell')"));
if (!insert) return std::move(insert).status();
// Read newly inserted record.
spanner::SqlStatement select(
"SELECT FirstName, LastName FROM Singers where SingerId = 11");
using RowType = std::tuple<std::string, std::string>;
auto rows = client.ExecuteQuery(std::move(txn), std::move(select));
// Note: This mutator might be re-run, or its effects discarded, so
// changing non-transactional state (e.g., by producing output) is,
// in general, not something to be imitated.
for (auto const& row : spanner::StreamOf<RowType>(rows)) {
if (!row) return std::move(row).status();
std::cout << "FirstName: " << std::get<0>(*row) << "\t";
std::cout << "LastName: " << std::get<1>(*row) << "\n";
}
return spanner::Mutations{};
});
if (!commit_result) throw std::move(commit_result).status();
std::cout << "Write then read succeeded [spanner_dml_write_then_read]\n";
}C#
using Google.Cloud.Spanner.Data;
using System;
using System.Threading.Tasks;
public class WriteAndReadUsingDmlCoreAsyncSample
{
public async Task<int> WriteAndReadUsingDmlCoreAsync(string projectId, string instanceId, string databaseId)
{
string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";
using var connection = new SpannerConnection(connectionString);
await connection.OpenAsync();
using var createDmlCmd = connection.CreateDmlCommand(@"INSERT Singers (SingerId, FirstName, LastName) VALUES (11, 'Timothy', 'Campbell')");
int rowCount = await createDmlCmd.ExecuteNonQueryAsync();
Console.WriteLine($"{rowCount} row(s) inserted...");
// Read newly inserted record.
using var createSelectCmd = connection.CreateSelectCommand(@"SELECT FirstName, LastName FROM Singers WHERE SingerId = 11");
using var reader = await createSelectCmd.ExecuteReaderAsync();
while (await reader.ReadAsync())
{
Console.WriteLine($"{reader.GetFieldValue<string>("FirstName")} {reader.GetFieldValue<string>("LastName")}");
}
return rowCount;
}
}Go
import (
"context"
"fmt"
"io"
"cloud.google.com/go/spanner"
"google.golang.org/api/iterator"
)
func writeAndReadUsingDML(w io.Writer, db string) error {
ctx := context.Background()
client, err := spanner.NewClient(ctx, db)
if err != nil {
return err
}
defer client.Close()
_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
// Insert Record
stmt := spanner.Statement{
SQL: `INSERT Singers (SingerId, FirstName, LastName)
VALUES (11, 'Timothy', 'Campbell')`,
}
rowCount, err := txn.Update(ctx, stmt)
if err != nil {
return err
}
fmt.Fprintf(w, "%d record(s) inserted.\n", rowCount)
// Read newly inserted record
stmt = spanner.Statement{SQL: `SELECT FirstName, LastName FROM Singers WHERE SingerId = 11`}
iter := txn.Query(ctx, stmt)
defer iter.Stop()
for {
row, err := iter.Next()
if err == iterator.Done || err != nil {
break
}
var firstName, lastName string
if err := row.ColumnByName("FirstName", &firstName); err != nil {
return err
}
if err := row.ColumnByName("LastName", &lastName); err != nil {
return err
}
fmt.Fprintf(w, "Found record name with %s, %s", firstName, lastName)
}
return err
})
return err
}
Java
static void writeAndReadUsingDml(DatabaseClient dbClient) {
dbClient
.readWriteTransaction()
.run(transaction -> {
// Insert record.
String sql =
"INSERT INTO Singers (SingerId, FirstName, LastName) "
+ " VALUES (11, 'Timothy', 'Campbell')";
long rowCount = transaction.executeUpdate(Statement.of(sql));
System.out.printf("%d record inserted.\n", rowCount);
// Read newly inserted record.
sql = "SELECT FirstName, LastName FROM Singers WHERE SingerId = 11";
// We use a try-with-resource block to automatically release resources held by
// ResultSet.
try (ResultSet resultSet = transaction.executeQuery(Statement.of(sql))) {
while (resultSet.next()) {
System.out.printf(
"%s %s\n",
resultSet.getString("FirstName"), resultSet.getString("LastName"));
}
}
return null;
});
}Node.js
// Imports the Google Cloud client library
const {Spanner} = require('@google-cloud/spanner');
/**
* TODO(developer): Uncomment the following lines before running the sample.
*/
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';
// Creates a client
const spanner = new Spanner({
projectId: projectId,
});
// Gets a reference to a Cloud Spanner instance and database
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);
database.runTransaction(async (err, transaction) => {
if (err) {
console.error(err);
return;
}
try {
await transaction.runUpdate({
sql: `INSERT Singers (SingerId, FirstName, LastName)
VALUES (11, 'Timothy', 'Campbell')`,
});
const [rows] = await transaction.run({
sql: 'SELECT FirstName, LastName FROM Singers',
});
rows.forEach(row => {
const json = row.toJSON();
console.log(`${json.FirstName} ${json.LastName}`);
});
await transaction.commit();
} catch (err) {
console.error('ERROR:', err);
} finally {
// Close the database when finished.
database.close();
}
});PHP
use Google\Cloud\Spanner\SpannerClient;
use Google\Cloud\Spanner\Transaction;
/**
* Writes then reads data inside a Transaction with a DML statement.
*
* The database and table must already exist and can be created using
* `create_database`.
* Example:
* ```
* insert_data($instanceId, $databaseId);
* ```
*
* @param string $instanceId The Spanner instance ID.
* @param string $databaseId The Spanner database ID.
*/
function write_read_with_dml(string $instanceId, string $databaseId): void
{
$spanner = new SpannerClient();
$instance = $spanner->instance($instanceId);
$database = $instance->database($databaseId);
$database->runTransaction(function (Transaction $t) {
$rowCount = $t->executeUpdate(
'INSERT Singers (SingerId, FirstName, LastName) '
. " VALUES (11, 'Timothy', 'Campbell')");
printf('Inserted %d row(s).' . PHP_EOL, $rowCount);
$results = $t->execute('SELECT FirstName, LastName FROM Singers WHERE SingerId = 11');
foreach ($results as $row) {
printf('%s %s' . PHP_EOL, $row['FirstName'], $row['LastName']);
}
$t->commit();
});
}Python
# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)
def write_then_read(transaction):
# Insert record.
row_ct = transaction.execute_update(
"INSERT INTO Singers (SingerId, FirstName, LastName) "
" VALUES (11, 'Timothy', 'Campbell')"
)
print("{} record(s) inserted.".format(row_ct))
# Read newly inserted record.
results = transaction.execute_sql(
"SELECT FirstName, LastName FROM Singers WHERE SingerId = 11"
)
for result in results:
print("FirstName: {}, LastName: {}".format(*result))
database.run_in_transaction(write_then_read)Ruby
# project_id = "Your Google Cloud project ID"
# instance_id = "Your Spanner instance ID"
# database_id = "Your Spanner database ID"
require "google/cloud/spanner"
spanner = Google::Cloud::Spanner.new project: project_id
client = spanner.client instance_id, database_id
row_count = 0
client.transaction do |transaction|
row_count = transaction.execute_update(
"INSERT INTO Singers (SingerId, FirstName, LastName) VALUES (11, 'Timothy', 'Campbell')"
)
puts "#{row_count} record updated."
transaction.execute("SELECT FirstName, LastName FROM Singers WHERE SingerId = 11").rows.each do |row|
puts "#{row[:FirstName]} #{row[:LastName]}"
end
endGet the query plan
You can retrieve a query plan
using the Google Cloud console, the client libraries, and the gcloud
command-line tool.
Use Partitioned DML
Partitioned DML is designed for bulk updates and deletes, particularly periodic cleanup and backfilling.
Execute statements with the Google Cloud CLI
To execute a Partitioned DML statement, use the
gcloud spanner databases execute-sql command with the
--enable-partitioned-dml option. The following example updates rows in the
Albums table.
gcloud spanner databases execute-sql example-db \ --instance=test-instance --enable-partitioned-dml \ --sql='UPDATE Albums SET MarketingBudget = 0 WHERE MarketingBudget IS NULL'
Modify data using the client library
The following code example updates the MarketingBudget column of the Albums
table.
C++
You use the ExecutePartitionedDml() function to execute a Partitioned DML statement.
void DmlPartitionedUpdate(google::cloud::spanner::Client client) {
namespace spanner = ::google::cloud::spanner;
auto result = client.ExecutePartitionedDml(
spanner::SqlStatement("UPDATE Albums SET MarketingBudget = 100000"
" WHERE SingerId > 1"));
if (!result) throw std::move(result).status();
std::cout << "Updated at least " << result->row_count_lower_bound
<< " row(s) [spanner_dml_partitioned_update]\n";
}C#
You use the ExecutePartitionedUpdateAsync() method to execute a Partitioned DML statement.
using Google.Cloud.Spanner.Data;
using System;
using System.Threading.Tasks;
public class UpdateUsingPartitionedDmlCoreAsyncSample
{
public async Task<long> UpdateUsingPartitionedDmlCoreAsync(string projectId, string instanceId, string databaseId)
{
string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";
using var connection = new SpannerConnection(connectionString);
await connection.OpenAsync();
using var cmd = connection.CreateDmlCommand("UPDATE Albums SET MarketingBudget = 100000 WHERE SingerId > 1");
long rowCount = await cmd.ExecutePartitionedUpdateAsync();
Console.WriteLine($"{rowCount} row(s) updated...");
return rowCount;
}
}Go
You use the PartitionedUpdate() method to execute a Partitioned DML statement.
import (
"context"
"fmt"
"io"
"cloud.google.com/go/spanner"
)
func updateUsingPartitionedDML(w io.Writer, db string) error {
ctx := context.Background()
client, err := spanner.NewClient(ctx, db)
if err != nil {
return err
}
defer client.Close()
stmt := spanner.Statement{SQL: "UPDATE Albums SET MarketingBudget = 100000 WHERE SingerId > 1"}
rowCount, err := client.PartitionedUpdate(ctx, stmt)
if err != nil {
return err
}
fmt.Fprintf(w, "%d record(s) updated.\n", rowCount)
return nil
}
Java
You use the executePartitionedUpdate() method to execute a Partitioned DML statement.
static void updateUsingPartitionedDml(DatabaseClient dbClient) {
String sql = "UPDATE Albums SET MarketingBudget = 100000 WHERE SingerId > 1";
long rowCount = dbClient.executePartitionedUpdate(Statement.of(sql));
System.out.printf("%d records updated.\n", rowCount);
}Node.js
You use the runPartitionedUpdate() method to execute a Partitioned DML statement.
// Imports the Google Cloud client library
const {Spanner} = require('@google-cloud/spanner');
/**
* TODO(developer): Uncomment the following lines before running the sample.
*/
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';
// Creates a client
const spanner = new Spanner({
projectId: projectId,
});
// Gets a reference to a Cloud Spanner instance and database
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);
try {
const [rowCount] = await database.runPartitionedUpdate({
sql: 'UPDATE Albums SET MarketingBudget = 100000 WHERE SingerId > 1',
});
console.log(`Successfully updated ${rowCount} records.`);
} catch (err) {
console.error('ERROR:', err);
} finally {
// Close the database when finished.
database.close();
}PHP
You use the executePartitionedUpdate() method to execute a Partitioned DML statement.
use Google\Cloud\Spanner\SpannerClient;
/**
* Updates sample data in the database by partition with a DML statement.
*
* This updates the `MarketingBudget` column which must be created before
* running this sample. You can add the column by running the `add_column`
* sample or by running this DDL statement against your database:
*
* ALTER TABLE Albums ADD COLUMN MarketingBudget INT64
*
* Example:
* ```
* update_data($instanceId, $databaseId);
* ```
*
* @param string $instanceId The Spanner instance ID.
* @param string $databaseId The Spanner database ID.
*/
function update_data_with_partitioned_dml(string $instanceId, string $databaseId): void
{
$spanner = new SpannerClient();
$instance = $spanner->instance($instanceId);
$database = $instance->database($databaseId);
$rowCount = $database->executePartitionedUpdate(
'UPDATE Albums SET MarketingBudget = 100000 WHERE SingerId > 1'
);
printf('Updated %d row(s).' . PHP_EOL, $rowCount);
}Python
You use the execute_partitioned_dml() method to execute a Partitioned DML statement.
# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)
row_ct = database.execute_partitioned_dml(
"UPDATE Albums SET MarketingBudget = 100000 WHERE SingerId > 1"
)
print("{} records updated.".format(row_ct))Ruby
You use the execute_partitioned_update() method to execute a Partitioned DML statement.
# project_id = "Your Google Cloud project ID"
# instance_id = "Your Spanner instance ID"
# database_id = "Your Spanner database ID"
require "google/cloud/spanner"
spanner = Google::Cloud::Spanner.new project: project_id
client = spanner.client instance_id, database_id
row_count = client.execute_partition_update(
"UPDATE Albums SET MarketingBudget = 100000 WHERE SingerId > 1"
)
puts "#{row_count} records updated."The following code example deletes rows from the Singers table, based on the
SingerId column.
C++
void DmlPartitionedDelete(google::cloud::spanner::Client client) {
namespace spanner = ::google::cloud::spanner;
auto result = client.ExecutePartitionedDml(
spanner::SqlStatement("DELETE FROM Singers WHERE SingerId > 10"));
if (!result) throw std::move(result).status();
std::cout << "Deleted at least " << result->row_count_lower_bound
<< " row(s) [spanner_dml_partitioned_delete]\n";
}C#
using Google.Cloud.Spanner.Data;
using System;
using System.Threading.Tasks;
public class DeleteUsingPartitionedDmlCoreAsyncSample
{
public async Task<long> DeleteUsingPartitionedDmlCoreAsync(string projectId, string instanceId, string databaseId)
{
string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";
using var connection = new SpannerConnection(connectionString);
await connection.OpenAsync();
using var cmd = connection.CreateDmlCommand("DELETE FROM Singers WHERE SingerId > 10");
long rowCount = await cmd.ExecutePartitionedUpdateAsync();
Console.WriteLine($"{rowCount} row(s) deleted...");
return rowCount;
}
}Go
import (
"context"
"fmt"
"io"
"cloud.google.com/go/spanner"
)
func deleteUsingPartitionedDML(w io.Writer, db string) error {
ctx := context.Background()
client, err := spanner.NewClient(ctx, db)
if err != nil {
return err
}
defer client.Close()
stmt := spanner.Statement{SQL: "DELETE FROM Singers WHERE SingerId > 10"}
rowCount, err := client.PartitionedUpdate(ctx, stmt)
if err != nil {
return err
}
fmt.Fprintf(w, "%d record(s) deleted.", rowCount)
return nil
}
Java
static void deleteUsingPartitionedDml(DatabaseClient dbClient) {
String sql = "DELETE FROM Singers WHERE SingerId > 10";
long rowCount = dbClient.executePartitionedUpdate(Statement.of(sql));
System.out.printf("%d records deleted.\n", rowCount);
}Node.js
// Imports the Google Cloud client library
const {Spanner} = require('@google-cloud/spanner');
/**
* TODO(developer): Uncomment the following lines before running the sample.
*/
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';
// Creates a client
const spanner = new Spanner({
projectId: projectId,
});
// Gets a reference to a Cloud Spanner instance and database
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);
try {
const [rowCount] = await database.runPartitionedUpdate({
sql: 'DELETE FROM Singers WHERE SingerId > 10',
});
console.log(`Successfully deleted ${rowCount} records.`);
} catch (err) {
console.error('ERROR:', err);
} finally {
// Close the database when finished.
database.close();
}PHP
use Google\Cloud\Spanner\SpannerClient;
/**
* Delete sample data in the database by partition with a DML statement.
*
* This updates the `MarketingBudget` column which must be created before
* running this sample. You can add the column by running the `add_column`
* sample or by running this DDL statement against your database:
*
* ALTER TABLE Albums ADD COLUMN MarketingBudget INT64
*
* Example:
* ```
* update_data($instanceId, $databaseId);
* ```
*
* @param string $instanceId The Spanner instance ID.
* @param string $databaseId The Spanner database ID.
*/
function delete_data_with_partitioned_dml(string $instanceId, string $databaseId): void
{
$spanner = new SpannerClient();
$instance = $spanner->instance($instanceId);
$database = $instance->database($databaseId);
$rowCount = $database->executePartitionedUpdate(
'DELETE FROM Singers WHERE SingerId > 10'
);
printf('Deleted %d row(s).' . PHP_EOL, $rowCount);
}Python
# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)
row_ct = database.execute_partitioned_dml("DELETE FROM Singers WHERE SingerId > 10")
print("{} record(s) deleted.".format(row_ct))Ruby
# project_id = "Your Google Cloud project ID"
# instance_id = "Your Spanner instance ID"
# database_id = "Your Spanner database ID"
require "google/cloud/spanner"
spanner = Google::Cloud::Spanner.new project: project_id
client = spanner.client instance_id, database_id
row_count = client.execute_partition_update(
"DELETE FROM Singers WHERE SingerId > 10"
)
puts "#{row_count} records deleted."Use batch DML
If you need to avoid the extra latency incurred from multiple serial requests,
use batch DML to send multiple INSERT, UPDATE, or DELETE statements in a
single transaction:
C++
Use the ExecuteBatchDml() function to execute a list of DML statements.
void DmlBatchUpdate(google::cloud::spanner::Client client) {
namespace spanner = ::google::cloud::spanner;
auto commit_result =
client.Commit([&client](spanner::Transaction const& txn)
-> google::cloud::StatusOr<spanner::Mutations> {
std::vector<spanner::SqlStatement> statements = {
spanner::SqlStatement("INSERT INTO Albums"
" (SingerId, AlbumId, AlbumTitle,"
" MarketingBudget)"
" VALUES (1, 3, 'Test Album Title', 10000)"),
spanner::SqlStatement("UPDATE Albums"
" SET MarketingBudget = MarketingBudget * 2"
" WHERE SingerId = 1 and AlbumId = 3")};
auto result = client.ExecuteBatchDml(txn, statements);
if (!result) return std::move(result).status();
// Note: This mutator might be re-run, or its effects discarded, so
// changing non-transactional state (e.g., by producing output) is,
// in general, not something to be imitated.
for (std::size_t i = 0; i < result->stats.size(); ++i) {
std::cout << result->stats[i].row_count << " rows affected"
<< " for the statement " << (i + 1) << ".\n";
}
// Batch operations may have partial failures, in which case
// ExecuteBatchDml returns with success, but the application should
// verify that all statements completed successfully
if (!result->status.ok()) return result->status;
return spanner::Mutations{};
});
if (!commit_result) throw std::move(commit_result).status();
std::cout << "Update was successful [spanner_dml_batch_update]\n";
}C#
Use the connection.CreateBatchDmlCommand() method to create your batch
command, use the Add method to add DML statements, and execute the
statements with the ExecuteNonQueryAsync() method.
using Google.Cloud.Spanner.Data;
using System;
using System.Collections.Generic;
using System.Linq;
using System.Threading.Tasks;
public class UpdateUsingBatchDmlCoreAsyncSample
{
public async Task<int> UpdateUsingBatchDmlCoreAsync(string projectId, string instanceId, string databaseId)
{
string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";
using var connection = new SpannerConnection(connectionString);
await connection.OpenAsync();
SpannerBatchCommand cmd = connection.CreateBatchDmlCommand();
cmd.Add("INSERT INTO Albums (SingerId, AlbumId, AlbumTitle, MarketingBudget) VALUES (1, 3, 'Test Album Title', 10000)");
cmd.Add("UPDATE Albums SET MarketingBudget = MarketingBudget * 2 WHERE SingerId = 1 and AlbumId = 3");
IEnumerable<long> affectedRows = await cmd.ExecuteNonQueryAsync();
Console.WriteLine($"Executed {affectedRows.Count()} " + "SQL statements using Batch DML.");
return affectedRows.Count();
}
}Go
Use the BatchUpdate() method to execute an array of DML Statement objects.
import (
"context"
"fmt"
"io"
"cloud.google.com/go/spanner"
)
func updateUsingBatchDML(w io.Writer, db string) error {
ctx := context.Background()
client, err := spanner.NewClient(ctx, db)
if err != nil {
return err
}
defer client.Close()
_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
stmts := []spanner.Statement{
{SQL: `INSERT INTO Albums
(SingerId, AlbumId, AlbumTitle, MarketingBudget)
VALUES (1, 3, 'Test Album Title', 10000)`},
{SQL: `UPDATE Albums
SET MarketingBudget = MarketingBudget * 2
WHERE SingerId = 1 and AlbumId = 3`},
}
rowCounts, err := txn.BatchUpdate(ctx, stmts)
if err != nil {
return err
}
fmt.Fprintf(w, "Executed %d SQL statements using Batch DML.\n", len(rowCounts))
return nil
})
return err
}
Java
Use the transaction.batchUpdate() method to execute an ArrayList of
multiple DML Statement objects.
static void updateUsingBatchDml(DatabaseClient dbClient) {
dbClient
.readWriteTransaction()
.run(transaction -> {
List<Statement> stmts = new ArrayList<Statement>();
String sql =
"INSERT INTO Albums "
+ "(SingerId, AlbumId, AlbumTitle, MarketingBudget) "
+ "VALUES (1, 3, 'Test Album Title', 10000) ";
stmts.add(Statement.of(sql));
sql =
"UPDATE Albums "
+ "SET MarketingBudget = MarketingBudget * 2 "
+ "WHERE SingerId = 1 and AlbumId = 3";
stmts.add(Statement.of(sql));
long[] rowCounts;
try {
rowCounts = transaction.batchUpdate(stmts);
} catch (SpannerBatchUpdateException e) {
rowCounts = e.getUpdateCounts();
}
for (int i = 0; i < rowCounts.length; i++) {
System.out.printf("%d record updated by stmt %d.\n", rowCounts[i], i);
}
return null;
});
}Node.js
Use transaction.batchUpdate() to execute a list of DML statements.
// Imports the Google Cloud client library
const {Spanner} = require('@google-cloud/spanner');
/**
* TODO(developer): Uncomment the following lines before running the sample.
*/
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';
// Creates a client
const spanner = new Spanner({
projectId: projectId,
});
// Gets a reference to a Cloud Spanner instance and database
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);
const insert = {
sql: `INSERT INTO Albums (SingerId, AlbumId, AlbumTitle, MarketingBudget)
VALUES (1, 3, "Test Album Title", 10000)`,
};
const update = {
sql: `UPDATE Albums SET MarketingBudget = MarketingBudget * 2
WHERE SingerId = 1 and AlbumId = 3`,
};
const dmlStatements = [insert, update];
try {
await database.runTransactionAsync(async transaction => {
const [rowCounts] = await transaction.batchUpdate(dmlStatements);
await transaction.commit();
console.log(
`Successfully executed ${rowCounts.length} SQL statements using Batch DML.`
);
});
} catch (err) {
console.error('ERROR:', err);
throw err;
} finally {
// Close the database when finished.
database.close();
}PHP
Use executeUpdateBatch() to create a list of DML statements, then use
commit() to execute the statements.
use Google\Cloud\Spanner\SpannerClient;
use Google\Cloud\Spanner\Transaction;
/**
* Updates sample data in the database with Batch DML.
*
* This requires the `MarketingBudget` column which must be created before
* running this sample. You can add the column by running the `add_column`
* sample or by running this DDL statement against your database:
*
* ALTER TABLE Albums ADD COLUMN MarketingBudget INT64
*
* Example:
* ```
* update_data_with_batch_dml($instanceId, $databaseId);
* ```
*
* @param string $instanceId The Spanner instance ID.
* @param string $databaseId The Spanner database ID.
*/
function update_data_with_batch_dml(string $instanceId, string $databaseId): void
{
$spanner = new SpannerClient();
$instance = $spanner->instance($instanceId);
$database = $instance->database($databaseId);
$batchDmlResult = $database->runTransaction(function (Transaction $t) {
$result = $t->executeUpdateBatch([
[
'sql' => 'INSERT INTO Albums '
. '(SingerId, AlbumId, AlbumTitle, MarketingBudget) '
. "VALUES (1, 3, 'Test Album Title', 10000)"
],
[
'sql' => 'UPDATE Albums '
. 'SET MarketingBudget = MarketingBudget * 2 '
. 'WHERE SingerId = 1 and AlbumId = 3'
],
]);
$t->commit();
$rowCounts = count($result->rowCounts());
printf('Executed %s SQL statements using Batch DML.' . PHP_EOL,
$rowCounts);
});
}Python
Use transaction.batch_update() to execute multiple DML statement strings.
from google.rpc.code_pb2 import OK
# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)
insert_statement = (
"INSERT INTO Albums "
"(SingerId, AlbumId, AlbumTitle, MarketingBudget) "
"VALUES (1, 3, 'Test Album Title', 10000)"
)
update_statement = (
"UPDATE Albums "
"SET MarketingBudget = MarketingBudget * 2 "
"WHERE SingerId = 1 and AlbumId = 3"
)
def update_albums(transaction):
status, row_cts = transaction.batch_update([insert_statement, update_statement])
if status.code != OK:
# Do handling here.
# Note: the exception will still be raised when
# `commit` is called by `run_in_transaction`.
return
print("Executed {} SQL statements using Batch DML.".format(len(row_cts)))
database.run_in_transaction(update_albums)Ruby
Use transaction.batch_update to execute multiple DML statement strings.
# project_id = "Your Google Cloud project ID"
# instance_id = "Your Spanner instance ID"
# database_id = "Your Spanner database ID"
require "google/cloud/spanner"
spanner = Google::Cloud::Spanner.new project: project_id
client = spanner.client instance_id, database_id
row_counts = nil
client.transaction do |transaction|
row_counts = transaction.batch_update do |b|
b.batch_update(
"INSERT INTO Albums " \
"(SingerId, AlbumId, AlbumTitle, MarketingBudget) " \
"VALUES (1, 3, 'Test Album Title', 10000)"
)
b.batch_update(
"UPDATE Albums " \
"SET MarketingBudget = MarketingBudget * 2 " \
"WHERE SingerId = 1 and AlbumId = 3"
)
end
end
statement_count = row_counts.count
puts "Executed #{statement_count} SQL statements using Batch DML."