Spring Data Cloud Spanner

Spring Data is an abstraction for storing and retrieving POJOs in numerous storage technologies. Spring Framework on Google Cloud adds Spring Data support for Google Cloud Spanner.

Maven coordinates for this module only, using Spring Framework on Google Cloud BOM:

<dependency>
    <groupId>com.google.cloud</groupId>
    <artifactId>spring-cloud-gcp-data-spanner</artifactId>
</dependency>

Gradle coordinates:

dependencies {
    implementation("com.google.cloud:spring-cloud-gcp-data-spanner")
}

We provide a Spring Boot Starter for Spring Data Spanner, with which you can leverage our recommended auto-configuration setup. To use the starter, see the coordinates see below.

Maven:

<dependency>
    <groupId>com.google.cloud</groupId>
    <artifactId>spring-cloud-gcp-starter-data-spanner</artifactId>
</dependency>

Gradle:

dependencies {
    implementation("com.google.cloud:spring-cloud-gcp-starter-data-spanner")
}

This setup takes care of bringing in the latest compatible version of Cloud Java Cloud Spanner libraries as well.

Configuration

To setup Spring Data Cloud Spanner, you have to configure the following:

  • Setup the connection details to Google Cloud Spanner.

  • Enable Spring Data Repositories (optional).

Cloud Spanner settings

You can use the Spring Boot Starter for Spring Data Spanner to autoconfigure Google Cloud Spanner in your Spring application. It contains all the necessary setup that makes it easy to authenticate with your Google Cloud project. The following configuration options are available:

Name

Description

Required

Default value

spring.cloud.gcp.spanner.enabled

Enables the Cloud Spanner client

No

true

spring.cloud.gcp.spanner.instance-id

Cloud Spanner instance to use

Yes

spring.cloud.gcp.spanner.database

Cloud Spanner database to use

Yes

spring.cloud.gcp.spanner.project-id

Google Cloud project ID where the Google Cloud Spanner API is hosted, if different from the one in the Spring Framework on Google Cloud Core Module

No

spring.cloud.gcp.spanner.credentials.location

OAuth2 credentials for authenticating with the Google Cloud Spanner API, if different from the ones in the Spring Framework on Google Cloud Core Module

No

spring.cloud.gcp.spanner.credentials.encoded-key

Base64-encoded OAuth2 credentials for authenticating with the Google Cloud Spanner API, if different from the ones in the Spring Framework on Google Cloud Core Module

No

spring.cloud.gcp.spanner.credentials.scopes

OAuth2 scope for Spring Framework on Google CloudSpanner credentials

No

https://www.googleapis.com/auth/spanner.data

spring.cloud.gcp.spanner.createInterleavedTableDdlOnDeleteCascade

If true, then schema statements generated by SpannerSchemaUtils for tables with interleaved parent-child relationships will be "ON DELETE CASCADE". The schema for the tables will be "ON DELETE NO ACTION" if false.

No

true

spring.cloud.gcp.spanner.numRpcChannels

Number of gRPC channels used to connect to Cloud Spanner

No

4 - Determined by Cloud Spanner client library

spring.cloud.gcp.spanner.prefetchChunks

Number of chunks prefetched by Cloud Spanner for read and query

No

4 - Determined by Cloud Spanner client library

spring.cloud.gcp.spanner.minSessions

Minimum number of sessions maintained in the session pool

No

0 - Determined by Cloud Spanner client library

spring.cloud.gcp.spanner.maxSessions

Maximum number of sessions session pool can have

No

400 - Determined by Cloud Spanner client library

spring.cloud.gcp.spanner.maxIdleSessions

Maximum number of idle sessions session pool will maintain

No

0 - Determined by Cloud Spanner client library

spring.cloud.gcp.spanner.writeSessionsFraction

Fraction of sessions to be kept prepared for write transactions

No

0.2 - Determined by Cloud Spanner client library

spring.cloud.gcp.spanner.keepAliveIntervalMinutes

How long to keep idle sessions alive

No

30 - Determined by Cloud Spanner client library

spring.cloud.gcp.spanner.failIfPoolExhausted

If all sessions are in use, fail the request by throwing an exception. Otherwise, by default, block until a session becomes available.

No

false

spring.cloud.gcp.spanner.emulator.enabled

Enables the usage of an emulator. If this is set to true, then you should set the spring.cloud.gcp.spanner.emulator-host to the host:port of your locally running emulator instance.

No

false

spring.cloud.gcp.spanner.emulator-host

The host and port of the Spanner emulator; can be overridden to specify connecting to an already-running Spanner emulator instance.

No

localhost:9010
For further customization of the client library SpannerOptions, provide a bean implementing SpannerOptionsCustomizer, with a single method that accepts a SpannerOptions.Builder and modifies it as necessary.

Repository settings

Spring Data Repositories can be configured via the @EnableSpannerRepositories annotation on your main @Configuration class. With our Spring Boot Starter for Spring Data Cloud Spanner, @EnableSpannerRepositories is automatically added. It is not required to add it to any other class, unless there is a need to override finer grain configuration parameters provided by @EnableSpannerRepositories.

Autoconfiguration

Our Spring Boot autoconfiguration creates the following beans available in the Spring application context:

  • an instance of SpannerTemplate

  • an instance of SpannerDatabaseAdminTemplate for generating table schemas from object hierarchies and creating and deleting tables and databases

  • an instance of all user-defined repositories extending SpannerRepository, CrudRepository, PagingAndSortingRepository, when repositories are enabled

  • an instance of DatabaseClient from the Google Cloud Java Client for Spanner, for convenience and lower level API access

Object Mapping

Spring Data Cloud Spanner allows you to map domain POJOs to Cloud Spanner tables via annotations:

@Table(name = "traders")
public class Trader {

	@PrimaryKey
	@Column(name = "trader_id")
	String traderId;

	String firstName;

	String lastName;

	@NotMapped
	Double temporaryNumber;
}

Spring Data Cloud Spanner will ignore any property annotated with @NotMapped. These properties will not be written to or read from Spanner.

Constructors

Simple constructors are supported on POJOs. The constructor arguments can be a subset of the persistent properties. Every constructor argument needs to have the same name and type as a persistent property on the entity and the constructor should set the property from the given argument. Arguments that are not directly set to properties are not supported.

@Table(name = "traders")
public class Trader {
	@PrimaryKey
	@Column(name = "trader_id")
	String traderId;

	String firstName;

	String lastName;

	@NotMapped
	Double temporaryNumber;

	public Trader(String traderId, String firstName) {
	    this.traderId = traderId;
	    this.firstName = firstName;
	}
}

Table

The @Table annotation can provide the name of the Cloud Spanner table that stores instances of the annotated class, one per row. This annotation is optional, and if not given, the name of the table is inferred from the class name with the first character uncapitalized.

SpEL expressions for table names

In some cases, you might want the @Table table name to be determined dynamically. To do that, you can use Spring Expression Language.

For example:

@Table(name = "trades_#{tableNameSuffix}")
public class Trade {
	// ...
}

The table name will be resolved only if the tableNameSuffix value/bean in the Spring application context is defined. For example, if tableNameSuffix has the value "123", the table name will resolve to trades_123.

Primary Keys

For a simple table, you may only have a primary key consisting of a single column. Even in that case, the @PrimaryKey annotation is required. @PrimaryKey identifies the one or more ID properties corresponding to the primary key.

Spanner has first class support for composite primary keys of multiple columns. You have to annotate all of your POJO’s fields that the primary key consists of with @PrimaryKey as below:

@Table(name = "trades")
public class Trade {
	@PrimaryKey(keyOrder = 2)
	@Column(name = "trade_id")
	private String tradeId;

	@PrimaryKey(keyOrder = 1)
	@Column(name = "trader_id")
	private String traderId;

	private String action;

	private BigDecimal price;

	private Double shares;

	private String symbol;
}

The keyOrder parameter of @PrimaryKey identifies the properties corresponding to the primary key columns in order, starting with 1 and increasing consecutively. Order is important and must reflect the order defined in the Cloud Spanner schema. In our example the DDL to create the table and its primary key is as follows:

CREATE TABLE trades (
    trader_id STRING(MAX),
    trade_id STRING(MAX),
    action STRING(15),
    symbol STRING(10),
    price NUMERIC,
    shares FLOAT64
) PRIMARY KEY (trader_id, trade_id)

Spanner does not have automatic ID generation. For most use-cases, sequential IDs should be used with caution to avoid creating data hotspots in the system. Read Spanner Primary Keys documentation for a better understanding of primary keys and recommended practices.

Columns

All accessible properties on POJOs are automatically recognized as a Cloud Spanner column. Column naming is generated by the PropertyNameFieldNamingStrategy by default defined on the SpannerMappingContext bean. The @Column annotation optionally provides a different column name than that of the property and some other settings:

  • name is the optional name of the column

  • spannerTypeMaxLength specifies for STRING and BYTES columns the maximum length. This setting is only used when generating DDL schema statements based on domain types.

  • nullable specifies if the column is created as NOT NULL. This setting is only used when generating DDL schema statements based on domain types.

  • spannerType is the Cloud Spanner column type you can optionally specify. If this is not specified then a compatible column type is inferred from the Java property type.

  • spannerCommitTimestamp is a boolean specifying if this property corresponds to an auto-populated commit timestamp column. Any value set in this property will be ignored when writing to Cloud Spanner.

Embedded Objects

If an object of type B is embedded as a property of A, then the columns of B will be saved in the same Cloud Spanner table as those of A.

If B has primary key columns, those columns will be included in the primary key of A. B can also have embedded properties. Embedding allows reuse of columns between multiple entities, and can be useful for implementing parent-child situations, because Cloud Spanner requires child tables to include the key columns of their parents.

For example:

class X {
  @PrimaryKey
  String grandParentId;

  long age;
}

class A {
  @PrimaryKey
  @Embedded
  X grandParent;

  @PrimaryKey(keyOrder = 2)
  String parentId;

  String value;
}

@Table(name = "items")
class B {
  @PrimaryKey
  @Embedded
  A parent;

  @PrimaryKey(keyOrder = 2)
  String id;

  @Column(name = "child_value")
  String value;
}

Entities of B can be stored in a table defined as:

CREATE TABLE items (
    grandParentId STRING(MAX),
    parentId STRING(MAX),
    id STRING(MAX),
    value STRING(MAX),
    child_value STRING(MAX),
    age INT64
) PRIMARY KEY (grandParentId, parentId, id)

Note that the following restrictions apply when you use embedded objects:

  • Embedded properties' column names must all be unique.

  • Embedded properties must not be passed through a constructor and the property must be mutable; otherwise you’ll get an error, such as SpannerDataException: Column not found. Be careful about this restriction when you use Kotlin’s data class to hold an embedded property.

Relationships

Spring Data Cloud Spanner supports parent-child relationships using the Cloud Spanner parent-child interleaved table mechanism. Cloud Spanner interleaved tables enforce the one-to-many relationship and provide efficient queries and operations on entities of a single domain parent entity. These relationships can be up to 7 levels deep. Cloud Spanner also provides automatic cascading delete or enforces the deletion of child entities before parents.

While one-to-one and many-to-many relationships can be implemented in Cloud Spanner and Spring Data Cloud Spanner using constructs of interleaved parent-child tables, only the parent-child relationship is natively supported.

For example, the following Java entities:

@Table(name = "Singers")
class Singer {
  @PrimaryKey
  long SingerId;

  String FirstName;

  String LastName;

  byte[] SingerInfo;

  @Interleaved
  List<Album> albums;
}

@Table(name = "Albums")
class Album {
  @PrimaryKey
  long SingerId;

  @PrimaryKey(keyOrder = 2)
  long AlbumId;

  String AlbumTitle;
}

These classes can correspond to an existing pair of interleaved tables. The @Interleaved annotation may be applied to Collection properties and the inner type is resolved as the child entity type. The schema needed to create them can also be generated using the SpannerSchemaUtils and run by using the SpannerDatabaseAdminTemplate:

@Autowired
SpannerSchemaUtils schemaUtils;

@Autowired
SpannerDatabaseAdminTemplate databaseAdmin;
...

// Get the create statmenets for all tables in the table structure rooted at Singer
List<String> createStrings = this.schemaUtils.getCreateTableDdlStringsForInterleavedHierarchy(Singer.class);

// Create the tables and also create the database if necessary
this.databaseAdmin.executeDdlStrings(createStrings, true);

The createStrings list contains table schema statements using column names and types compatible with the provided Java type and any resolved child relationship types contained within based on the configured custom converters.

CREATE TABLE Singers (
  SingerId   INT64 NOT NULL,
  FirstName  STRING(1024),
  LastName   STRING(1024),
  SingerInfo BYTES(MAX),
) PRIMARY KEY (SingerId);

CREATE TABLE Albums (
  SingerId     INT64 NOT NULL,
  AlbumId      INT64 NOT NULL,
  AlbumTitle   STRING(MAX),
) PRIMARY KEY (SingerId, AlbumId),
  INTERLEAVE IN PARENT Singers ON DELETE CASCADE;

The ON DELETE CASCADE clause indicates that Cloud Spanner will delete all Albums of a singer if the Singer is deleted. The alternative is ON DELETE NO ACTION, where a Singer cannot be deleted until all of its Albums have already been deleted. When using SpannerSchemaUtils to generate the schema strings, the spring.cloud.gcp.spanner.createInterleavedTableDdlOnDeleteCascade boolean setting determines if these schema are generated as ON DELETE CASCADE for true and ON DELETE NO ACTION for false.

Cloud Spanner restricts these relationships to 7 child layers. A table may have multiple child tables.

On updating or inserting an object to Cloud Spanner, all of its referenced children objects are also updated or inserted in the same request, respectively. On read, all of the interleaved child rows are also all read.

Lazy Fetch

@Interleaved properties are retrieved eagerly by default, but can be fetched lazily for performance in both read and write:

@Interleaved(lazy = true)
List<Album> albums;

Lazily-fetched interleaved properties are retrieved upon the first interaction with the property. If a property marked for lazy fetching is never retrieved, then it is also skipped when saving the parent entity.

If used inside a transaction, subsequent operations on lazily-fetched properties use the same transaction context as that of the original parent entity.

Declarative Filtering with @Where

The @Where annotation could be applied to an entity class or to an interleaved property. This annotation provides an SQL where clause that will be applied at the fetching of interleaved collections or the entity itself.

Let’s say we have an Agreement with a list of Participants which could be assigned to it. We would like to fetch a list of currently active participants. For security reasons, all records should remain in the database forever, even if participants become inactive. That can be easily achieved with the @Where annotation, which is demonstrated by this example:

@Table(name = "participants")
public class Participant {
  //...
  boolean active;
  //...
}

@Table(name = "agreements")
public class Agreement {
  //...
  @Interleaved
  @Where("active = true")
  List<Participant> participants;
  Person person;
  //...
}

Supported Types

Spring Data Cloud Spanner natively supports the following types for regular fields but also utilizes custom converters (detailed in following sections) and dozens of pre-defined Spring Data custom converters to handle other common Java types.

Natively supported types:

  • com.google.cloud.ByteArray

  • com.google.cloud.Date

  • com.google.cloud.Timestamp

  • java.lang.Boolean, boolean

  • java.lang.Double, double

  • java.lang.Long, long

  • java.lang.Integer, int

  • java.lang.String

  • double[]

  • long[]

  • boolean[]

  • java.util.Date

  • java.time.Instant

  • java.sql.Date

  • java.time.LocalDate

  • java.time.LocalDateTime

JSON fields

Spanner supports JSON and ARRAY<JSON> type for columns. Such property needs to be annotated with @Column(spannerType = TypeCode.JSON). JSON columns are mapped to custom POJOs and ARRAY<JSON> columns are mapped to List of custom POJOs. Read, write and query with custom SQL query are supported for JSON annotated fields.

Spring Boot autoconfigures a Gson bean by default. This Gson instance is used by default to convert to and from JSON representation. To customize, use spring.gson.* configuration properties or GsonBuilderCustomizer bean as instructed in Spring Boot documentation here. Alternatively, you can also provide a customized bean of type Gson in your application. 
@Table(name = "traders")
public class Trader {

	@PrimaryKey
	@Column(name = "trader_id")
	String traderId;

	@Column(spannerType = TypeCode.JSON)
	Details details;
}

public class Details {
    String name;
    String affiliation;
    Boolean isActive;
}

Lists

Spanner supports ARRAY types for columns. ARRAY columns are mapped to List fields in POJOs.

Example:

List<Double> curve;

The types inside the lists can be any singular property type.

Lists of Structs

Cloud Spanner queries can construct STRUCT values that appear as columns in the result. Cloud Spanner requires STRUCT values appear in ARRAYs at the root level: SELECT ARRAY(SELECT STRUCT(1 as val1, 2 as val2)) as pair FROM Users.

Spring Data Cloud Spanner will attempt to read the column STRUCT values into a property that is an Iterable of an entity type compatible with the schema of the column STRUCT value.

For the previous array-select example, the following property can be mapped with the constructed ARRAY<STRUCT> column: List<TwoInts> pair; where the TwoInts type is defined:

class TwoInts {

  int val1;

  int val2;
}

Custom types

Custom converters can be used to extend the type support for user defined types.

  1. Converters need to implement the org.springframework.core.convert.converter.Converter interface in both directions.

  2. The user defined type needs to be mapped to one of the basic types supported by Spanner:

    • com.google.cloud.ByteArray

    • com.google.cloud.Date

    • com.google.cloud.Timestamp

    • java.lang.Boolean, boolean

    • java.lang.Double, double

    • java.lang.Long, long

    • java.lang.String

    • double[]

    • long[]

    • boolean[]

    • enum types

  3. An instance of both Converters needs to be passed to a ConverterAwareMappingSpannerEntityProcessor, which then has to be made available as a @Bean for SpannerEntityProcessor.

For example:

We would like to have a field of type Person on our Trade POJO:

@Table(name = "trades")
public class Trade {
  //...
  Person person;
  //...
}

Where Person is a simple class:

public class Person {

  public String firstName;
  public String lastName;

}

We have to define the two converters:

  public class PersonWriteConverter implements Converter<Person, String> {

    @Override
    public String convert(Person person) {
      return person.firstName + " " + person.lastName;
    }
  }

  public class PersonReadConverter implements Converter<String, Person> {

    @Override
    public Person convert(String s) {
      Person person = new Person();
      person.firstName = s.split(" ")[0];
      person.lastName = s.split(" ")[1];
      return person;
    }
  }

That will be configured in our @Configuration file:

@Configuration
public class ConverterConfiguration {

	@Bean
	public SpannerEntityProcessor spannerEntityProcessor(SpannerMappingContext spannerMappingContext) {
		return new ConverterAwareMappingSpannerEntityProcessor(spannerMappingContext,
				Arrays.asList(new PersonWriteConverter()),
				Arrays.asList(new PersonReadConverter()));
	}
}

Note that ConverterAwareMappingSpannerEntityProcessor takes a list of Converters for write and read operations to support multiple user-defined types. When there are duplicate Converters for a user-defined class in the list, it chooses the first matching item in the lists. This means that, for a user-defined class U, write operations use the first Converter<U, …​> from the write Converters and read operations use the first Converter<…​, U> from the read Converters.

Custom Converter for Struct Array Columns

If a Converter<Struct, A> is provided, then properties of type List<A> can be used in your entity types.

Spanner Operations & Template

SpannerOperations and its implementation, SpannerTemplate, provides the Template pattern familiar to Spring developers. It provides:

  • Resource management

  • One-stop-shop to Spanner operations with the Spring Data POJO mapping and conversion features

  • Exception conversion

Using the autoconfigure provided by our Spring Boot Starter for Spanner, your Spring application context will contain a fully configured SpannerTemplate object that you can easily autowire in your application:

@SpringBootApplication
public class SpannerTemplateExample {

	@Autowired
	SpannerTemplate spannerTemplate;

	public void doSomething() {
		this.spannerTemplate.delete(Trade.class, KeySet.all());
		//...
		Trade t = new Trade();
		//...
		this.spannerTemplate.insert(t);
		//...
		List<Trade> tradesByAction = spannerTemplate.findAll(Trade.class);
		//...
	}
}

The Template API provides convenience methods for:

  • Reads, and by providing SpannerReadOptions and SpannerQueryOptions

    • Stale read

    • Read with secondary indices

    • Read with limits and offsets

    • Read with sorting

  • Queries

  • DML operations (delete, insert, update, upsert)

  • Partial reads

    • You can define a set of columns to be read into your entity

  • Partial writes

    • Persist only a few properties from your entity

  • Read-only transactions

  • Locking read-write transactions

SQL Query

Cloud Spanner has SQL support for running read-only queries. All the query related methods start with query on SpannerTemplate. By using SpannerTemplate, you can run SQL queries that map to POJOs:

List<Trade> trades = this.spannerTemplate.query(Trade.class, Statement.of("SELECT * FROM trades"));

Read

Spanner exposes a Read API for reading single row or multiple rows in a table or in a secondary index.

Using SpannerTemplate you can run reads, as the following example shows:

List<Trade> trades = this.spannerTemplate.readAll(Trade.class);

Main benefit of reads over queries is reading multiple rows of a certain pattern of keys is much easier using the features of the KeySet class.

Advanced reads

Stale read

All reads and queries are strong reads by default. A strong read is a read at a current time and is guaranteed to see all data that has been committed up until the start of this read. An exact staleness read is read at a timestamp in the past. Cloud Spanner allows you to determine how current the data should be when you read data. With SpannerTemplate you can specify the Timestamp by setting it on SpannerQueryOptions or SpannerReadOptions to the appropriate read or query methods:

Reads:

// a read with options:
SpannerReadOptions spannerReadOptions = new SpannerReadOptions().setTimestamp(myTimestamp);
List<Trade> trades = this.spannerTemplate.readAll(Trade.class, spannerReadOptions);

Queries:

// a query with options:
SpannerQueryOptions spannerQueryOptions = new SpannerQueryOptions().setTimestamp(myTimestamp);
List<Trade> trades = this.spannerTemplate.query(Trade.class, Statement.of("SELECT * FROM trades"), spannerQueryOptions);

You can also read with bounded staleness by setting .setTimestampBound(TimestampBound.ofMinReadTimestamp(myTimestamp)) on the query and read options objects. Bounded staleness lets Cloud Spanner choose any point in time later than or equal to the given timestampBound, but it cannot be used inside transactions.

Read from a secondary index

Using a secondary index is available for Reads via the Template API and it is also implicitly available via SQL for Queries.

The following shows how to read rows from a table using a secondary index simply by setting index on SpannerReadOptions:

SpannerReadOptions spannerReadOptions = new SpannerReadOptions().setIndex("TradesByTrader");
List<Trade> trades = this.spannerTemplate.readAll(Trade.class, spannerReadOptions);
Read with offsets and limits

Limits and offsets are only supported by Queries. The following will get only the first two rows of the query:

SpannerQueryOptions spannerQueryOptions = new SpannerQueryOptions().setLimit(2).setOffset(3);
List<Trade> trades = this.spannerTemplate.query(Trade.class, Statement.of("SELECT * FROM trades"), spannerQueryOptions);

Note that the above is equivalent of running SELECT * FROM trades LIMIT 2 OFFSET 3.

Sorting

Reads by keys do not support sorting. However, queries on the Template API support sorting through standard SQL and also via Spring Data Sort API:

List<Trade> trades = this.spannerTemplate.queryAll(Trade.class, Sort.by("action"));

If the provided sorted field name is that of a property of the domain type, then the column name corresponding to that property will be used in the query. Otherwise, the given field name is assumed to be the name of the column in the Cloud Spanner table. Sorting on columns of Cloud Spanner types STRING and BYTES can be done while ignoring case:

Sort.by(Order.desc("action").ignoreCase())
Partial read

Partial read is only possible when using Queries. In case the rows returned by the query have fewer columns than the entity that it will be mapped to, Spring Data will map the returned columns only. This setting also applies to nested structs and their corresponding nested POJO properties.

List<Trade> trades = this.spannerTemplate.query(Trade.class, Statement.of("SELECT action, symbol FROM trades"),
    new SpannerQueryOptions().setAllowMissingResultSetColumns(true));

If the setting is set to false, then an exception will be thrown if there are missing columns in the query result.

Summary of options for Query vs Read

Feature

Query supports it

Read supports it

SQL

yes

no

Partial read

yes

no

Limits

yes

no

Offsets

yes

no

Secondary index

yes

yes

Read using index range

no

yes

Sorting

yes

no

Write / Update

The write methods of SpannerOperations accept a POJO and writes all of its properties to Spanner. The corresponding Spanner table and entity metadata is obtained from the given object’s actual type.

If a POJO was retrieved from Spanner and its primary key properties values were changed and then written or updated, the operation will occur as if against a row with the new primary key values. The row with the original primary key values will not be affected.

Insert

The insert method of SpannerOperations accepts a POJO and writes all of its properties to Spanner, which means the operation will fail if a row with the POJO’s primary key already exists in the table.

Trade t = new Trade();
this.spannerTemplate.insert(t);
Update

The update method of SpannerOperations accepts a POJO and writes all of its properties to Spanner, which means the operation will fail if the POJO’s primary key does not already exist in the table.

// t was retrieved from a previous operation
this.spannerTemplate.update(t);
Upsert

The upsert method of SpannerOperations accepts a POJO and writes all of its properties to Spanner using update-or-insert.

// t was retrieved from a previous operation or it's new
this.spannerTemplate.upsert(t);
Partial Update

The update methods of SpannerOperations operate by default on all properties within the given object, but also accept String[] and Optional<Set<String>> of column names. If the Optional of set of column names is empty, then all columns are written to Spanner. However, if the Optional is occupied by an empty set, then no columns will be written.

// t was retrieved from a previous operation or it's new
this.spannerTemplate.update(t, "symbol", "action");

DML

DML statements can be run by using SpannerOperations.executeDmlStatement. Inserts, updates, and deletions can affect any number of rows and entities.

You can run partitioned DML updates by using the executePartitionedDmlStatement method. Partitioned DML queries have performance benefits but also have restrictions and cannot be used inside transactions.

Transactions

SpannerOperations provides methods to run java.util.Function objects within a single transaction while making available the read and write methods from SpannerOperations.

Read/Write Transaction

Read and write transactions are provided by SpannerOperations via the performReadWriteTransaction method:

@Autowired
SpannerOperations mySpannerOperations;

public String doWorkInsideTransaction() {
  return mySpannerOperations.performReadWriteTransaction(
    transActionSpannerOperations -> {
      // Work with transActionSpannerOperations here.
      // It is also a SpannerOperations object.

      return "transaction completed";
    }
  );
}

The performReadWriteTransaction method accepts a Function that is provided an instance of a SpannerOperations object. The final returned value and type of the function is determined by the user. You can use this object just as you would a regular SpannerOperations with a few exceptions:

  • Its read functionality cannot perform stale reads, because all reads and writes happen at the single point in time of the transaction.

  • It cannot perform sub-transactions via performReadWriteTransaction or performReadOnlyTransaction.

As these read-write transactions are locking, it is recommended that you use the performReadOnlyTransaction if your function does not perform any writes.

Read-only Transaction

The performReadOnlyTransaction method is used to perform read-only transactions using a SpannerOperations:

@Autowired
SpannerOperations mySpannerOperations;

public String doWorkInsideTransaction() {
  return mySpannerOperations.performReadOnlyTransaction(
    transActionSpannerOperations -> {
      // Work with transActionSpannerOperations here.
      // It is also a SpannerOperations object.

      return "transaction completed";
    }
  );
}

The performReadOnlyTransaction method accepts a Function that is provided an instance of a SpannerOperations object. This method also accepts a ReadOptions object, but the only attribute used is the timestamp used to determine the snapshot in time to perform the reads in the transaction. If the timestamp is not set in the read options the transaction is run against the current state of the database. The final returned value and type of the function is determined by the user. You can use this object just as you would a regular SpannerOperations with a few exceptions:

  • Its read functionality cannot perform stale reads (other than the staleness set on the entire transaction), because all reads happen at the single point in time of the transaction.

  • It cannot perform sub-transactions via performReadWriteTransaction or performReadOnlyTransaction

  • It cannot perform any write operations.

Because read-only transactions are non-locking and can be performed on points in time in the past, these are recommended for functions that do not perform write operations.

Declarative Transactions with @Transactional Annotation

This feature requires a bean of SpannerTransactionManager, which is provided when using spring-cloud-gcp-starter-data-spanner.

SpannerTemplate and SpannerRepository support running methods with the @Transactional annotation as transactions. If a method annotated with @Transactional calls another method also annotated, then both methods will work within the same transaction. performReadOnlyTransaction and performReadWriteTransaction cannot be used in @Transactional annotated methods because Cloud Spanner does not support transactions within transactions.

Other Google Cloud database-related integrations like Spanner and Firestore can introduce PlatformTransactionManager beans, and can interfere with Datastore Transaction Manager. To disambiguate, explicitly specify the name of the transaction manager bean for such @Transactional methods. Example:

@Transactional(transactionManager = "spannerTransactionManager")

DML Statements

SpannerTemplate supports DML Statements. DML statements can also be run in transactions by using performReadWriteTransaction or by using the @Transactional annotation.

Repositories

Spring Data Repositories are a powerful abstraction that can save you a lot of boilerplate code.

For example:

public interface TraderRepository extends SpannerRepository<Trader, String> {
}

Spring Data generates a working implementation of the specified interface, which can be conveniently autowired into an application.

The Trader type parameter to SpannerRepository refers to the underlying domain type. The second type parameter, String in this case, refers to the type of the key of the domain type.

For POJOs with a composite primary key, this ID type parameter can be any descendant of Object[] compatible with all primary key properties, any descendant of Iterable, or com.google.cloud.spanner.Key. If the domain POJO type only has a single primary key column, then the primary key property type can be used or the Key type.

For example in case of Trades, that belong to a Trader, TradeRepository would look like this:

public interface TradeRepository extends SpannerRepository<Trade, String[]> {

}

public class MyApplication {

	@Autowired
	SpannerTemplate spannerTemplate;

	@Autowired
	StudentRepository studentRepository;

	public void demo() {

		this.tradeRepository.deleteAll();
		String traderId = "demo_trader";
		Trade t = new Trade();
		t.symbol = stock;
		t.action = action;
		t.traderId = traderId;
		t.price = new BigDecimal("100.0");
		t.shares = 12345.6;
		this.spannerTemplate.insert(t);

		Iterable<Trade> allTrades = this.tradeRepository.findAll();

		int count = this.tradeRepository.countByAction("BUY");

	}
}

CRUD Repository

CrudRepository methods work as expected, with one thing Spanner specific: the save and saveAll methods work as update-or-insert.

Paging and Sorting Repository

You can also use PagingAndSortingRepository with Spanner Spring Data. The sorting and pageable findAll methods available from this interface operate on the current state of the Spanner database. As a result, beware that the state of the database (and the results) might change when moving page to page.

Spanner Repository

The SpannerRepository extends the PagingAndSortingRepository, but adds the read-only and the read-write transaction functionality provided by Spanner. These transactions work very similarly to those of SpannerOperations, but is specific to the repository’s domain type and provides repository functions instead of template functions.

For example, this is a read-only transaction:

@Autowired
SpannerRepository myRepo;

public String doWorkInsideTransaction() {
  return myRepo.performReadOnlyTransaction(
    transactionSpannerRepo -> {
      // Work with the single-transaction transactionSpannerRepo here.
      // This is a SpannerRepository object.

      return "transaction completed";
    }
  );
}

When creating custom repositories for your own domain types and query methods, you can extend SpannerRepository to access Cloud Spanner-specific features as well as all features from PagingAndSortingRepository and CrudRepository.

Query Methods

SpannerRepository supports Query Methods. Described in the following sections, these are methods residing in your custom repository interfaces of which implementations are generated based on their names and annotations. Query Methods can read, write, and delete entities in Cloud Spanner. Parameters to these methods can be any Cloud Spanner data type supported directly or via custom configured converters. Parameters can also be of type Struct or POJOs. If a POJO is given as a parameter, it will be converted to a Struct with the same type-conversion logic as used to create write mutations. Comparisons using Struct parameters are limited to what is available with Cloud Spanner.

Query methods by convention

public interface TradeRepository extends SpannerRepository<Trade, String[]> {
    List<Trade> findByAction(String action);

	int countByAction(String action);

	// Named methods are powerful, but can get unwieldy
	List<Trade> findTop3DistinctByActionAndSymbolIgnoreCaseOrTraderIdOrderBySymbolDesc(
  			String action, String symbol, String traderId);
}

In the example above, the query methods in TradeRepository are generated based on the name of the methods, using the Spring Data Query creation naming convention.

List<Trade> findByAction(String action) would translate to a SELECT * FROM trades WHERE action = ?.

The function List<Trade> findTop3DistinctByActionAndSymbolIgnoreCaseOrTraderIdOrderBySymbolDesc(String action, String symbol, String traderId); will be translated as the equivalent of this SQL query:

SELECT DISTINCT * FROM trades
WHERE ACTION = ? AND LOWER(SYMBOL) = LOWER(?) AND TRADER_ID = ?
ORDER BY SYMBOL DESC
LIMIT 3

The following filter options are supported:

  • Equality

  • Greater than or equals

  • Greater than

  • Less than or equals

  • Less than

  • Is null

  • Is not null

  • Is true

  • Is false

  • Like a string

  • Not like a string

  • Contains a string

  • Not contains a string

  • In

  • Not in

Note that the phrase SymbolIgnoreCase is translated to LOWER(SYMBOL) = LOWER(?) indicating a non-case-sensitive matching. The IgnoreCase phrase may only be appended to fields that correspond to columns of type STRING or BYTES. The Spring Data "AllIgnoreCase" phrase appended at the end of the method name is not supported.

The Like or NotLike naming conventions:

List<Trade> findBySymbolLike(String symbolFragment);

The param symbolFragment can contain wildcard characters for string matching such as _ and %.

The Contains and NotContains naming conventions:

List<Trade> findBySymbolContains(String symbolFragment);

The param symbolFragment is a regular expression that is checked for occurrences.

The In and NotIn keywords must be used with Iterable corresponding parameters.

Delete queries are also supported. For example, query methods such as deleteByAction or removeByAction delete entities found by findByAction. The delete operation happens in a single transaction.

Delete queries can have the following return types: * An integer type that is the number of entities deleted * A collection of entities that were deleted * void

Custom SQL/DML query methods

The example above for List<Trade> fetchByActionNamedQuery(String action) does not match the Spring Data Query creation naming convention, so we have to map a parametrized Spanner SQL query to it.

The SQL query for the method can be mapped to repository methods in one of two ways:

  • namedQueries properties file

  • using the @Query annotation

The names of the tags of the SQL correspond to the @Param annotated names of the method parameters.

Interleaved properties are loaded eagerly, unless they are annotated with @Interleaved(lazy = true).

Custom SQL query methods can accept a single Sort or Pageable parameter that is applied on top of the specified custom query. It is the recommended way to control the sort order of the results, which is not guaranteed by the ORDER BY clause in the SQL query. This is due to the fact that the user-provided query is used as a sub-query, and Cloud Spanner doesn’t preserve order in subquery results.

You might want to use ORDER BY with LIMIT to obtain the top records, according to a specified order. However, to ensure the correct sort order of the final result set, sort options have to be passed in with a Pageable.

	@Query("SELECT * FROM trades")
	List<Trade> fetchTrades(Pageable pageable);

	@Query("SELECT * FROM trades ORDER BY price DESC LIMIT 1")
 	Trade topTrade(Pageable pageable);

This can be used:

	List<Trade> customSortedTrades = tradeRepository.fetchTrades(PageRequest
  				.of(2, 2, org.springframework.data.domain.Sort.by(Order.asc("id"))));

The results would be sorted by "id" in ascending order.

Your query method can also return non-entity types:

  	@Query("SELECT COUNT(1) FROM trades WHERE action = @action")
  	int countByActionQuery(String action);

  	@Query("SELECT EXISTS(SELECT COUNT(1) FROM trades WHERE action = @action)")
  	boolean existsByActionQuery(String action);

  	@Query("SELECT action FROM trades WHERE action = @action LIMIT 1")
  	String getFirstString(@Param("action") String action);

  	@Query("SELECT action FROM trades WHERE action = @action")
  	List<String> getFirstStringList(@Param("action") String action);

DML statements can also be run by query methods, but the only possible return value is a long representing the number of affected rows. The dmlStatement boolean setting must be set on @Query to indicate that the query method is run as a DML statement.

  	@Query(value = "DELETE FROM trades WHERE action = @action", dmlStatement = true)
  	long deleteByActionQuery(String action);
Query methods with named queries properties

By default, the namedQueriesLocation attribute on @EnableSpannerRepositories points to the META-INF/spanner-named-queries.properties file. You can specify the query for a method in the properties file by providing the SQL as the value for the "interface.method" property:

Trade.fetchByActionNamedQuery=SELECT * FROM trades WHERE trades.action = @tag0
public interface TradeRepository extends SpannerRepository<Trade, String[]> {
	// This method uses the query from the properties file instead of one generated based on name.
	List<Trade> fetchByActionNamedQuery(@Param("tag0") String action);
}
Query methods with annotation

Using the @Query annotation:

public interface TradeRepository extends SpannerRepository<Trade, String[]> {
    @Query("SELECT * FROM trades WHERE trades.action = @tag0")
    List<Trade> fetchByActionNamedQuery(@Param("tag0") String action);
}

Table names can be used directly. For example, "trades" in the above example. Alternatively, table names can be resolved from the @Table annotation on domain classes as well. In this case, the query should refer to table names with fully qualified class names between : characters: :fully.qualified.ClassName:. A full example would look like:

@Query("SELECT * FROM :com.example.Trade: WHERE trades.action = @tag0")
List<Trade> fetchByActionNamedQuery(String action);

This allows table names evaluated with SpEL to be used in custom queries.

SpEL can also be used to provide SQL parameters:

@Query("SELECT * FROM :com.example.Trade: WHERE trades.action = @tag0
  AND price > #{#priceRadius * -1} AND price < #{#priceRadius * 2}")
List<Trade> fetchByActionNamedQuery(String action, Double priceRadius);

When using the IN SQL clause, remember to use IN UNNEST(@iterableParam) to specify a single Iterable parameter. You can also use a fixed number of singular parameters such as IN (@stringParam1, @stringParam2).

Projections

Spring Data Spanner supports projections. You can define projection interfaces based on domain types and add query methods that return them in your repository:

public interface TradeProjection {

	String getAction();

	@Value("#{target.symbol + ' ' + target.action}")
	String getSymbolAndAction();
}

public interface TradeRepository extends SpannerRepository<Trade, Key> {

	List<Trade> findByTraderId(String traderId);

	List<TradeProjection> findByAction(String action);

	@Query("SELECT action, symbol FROM trades WHERE action = @action")
	List<TradeProjection> findByQuery(String action);
}

Projections can be provided by name-convention-based query methods as well as by custom SQL queries. If using custom SQL queries, you can further restrict the columns retrieved from Spanner to just those required by the projection to improve performance.

Properties of projection types defined using SpEL use the fixed name target for the underlying domain object. As a result accessing underlying properties take the form target.<property-name>.

Empty result handling in repository methods

Java java.util.Optional can be used to indicate the potential absence of a return value.

Alternatively, query methods can return the result without a wrapper. In that case the absence of a query result is indicated by returning null. Repository methods returning collections are guaranteed never to return null but rather the corresponding empty collection.

You can enable nullability checks. For more details please see Spring Framework’s nullability docs.

REST Repositories

When running with Spring Boot, repositories can be exposed as REST services by simply adding this dependency to your pom file:

<dependency>
  <groupId>org.springframework.boot</groupId>
  <artifactId>spring-boot-starter-data-rest</artifactId>
</dependency>

If you prefer to configure parameters (such as path), you can use @RepositoryRestResource annotation:

@RepositoryRestResource(collectionResourceRel = "trades", path = "trades")
public interface TradeRepository extends SpannerRepository<Trade, Key> {
}
For classes that have composite keys (multiple @PrimaryKey fields), only the Key type is supported for the repository ID type.

For example, you can retrieve all Trade objects in the repository by using curl http://<server>:<port>/trades, or any specific trade via curl http://<server>:<port>/trades/<trader_id>,<trade_id>.

The separator between your primary key components, id and trader_id in this case, is a comma by default, but can be configured to any string not found in your key values by extending the SpannerKeyIdConverter class:

@Component
class MySpecialIdConverter extends SpannerKeyIdConverter {

    @Override
    protected String getUrlIdSeparator() {
        return ":";
    }
}

You can also write trades using curl -XPOST -H"Content-Type: application/json" -d@test.json http://<server>:<port>/trades/ where the file test.json holds the JSON representation of a Trade object.

Database and Schema Admin

Databases and tables inside Spanner instances can be created automatically from SpannerPersistentEntity objects:

@Autowired
private SpannerSchemaUtils spannerSchemaUtils;

@Autowired
private SpannerDatabaseAdminTemplate spannerDatabaseAdminTemplate;

public void createTable(SpannerPersistentEntity entity) {
	if(!spannerDatabaseAdminTemplate.tableExists(entity.tableName()){

	  // The boolean parameter indicates that the database will be created if it does not exist.
	  spannerDatabaseAdminTemplate.executeDdlStrings(Arrays.asList(
            spannerSchemaUtils.getCreateTableDDLString(entity.getType())), true);
	}
}

Schemas can be generated for entire object hierarchies with interleaved relationships and composite keys.

Events

Spring Data Cloud Spanner publishes events extending the Spring Framework’s ApplicationEvent to the context that can be received by ApplicationListener beans you register.

Type Description Contents

AfterReadEvent

Published immediately after entities are read by key from Cloud Spanner by SpannerTemplate

The entities loaded. The read options and key-set originally specified for the load operation.

AfterQueryEvent

Published immediately after entities are read by query from Cloud Spanner by SpannerTemplate

The entities loaded. The query options and query statement originally specified for the load operation.

BeforeExecuteDmlEvent

Published immediately before DML statements are executed by SpannerTemplate

The DML statement to execute.

AfterExecuteDmlEvent

Published immediately after DML statements are executed by SpannerTemplate

The DML statement to execute and the number of rows affected by the operation as reported by Cloud Spanner.

BeforeSaveEvent

Published immediately before upsert/update/insert operations are executed by SpannerTemplate

The mutations to be sent to Cloud Spanner, the entities to be saved, and optionally the properties in those entities to save.

AfterSaveEvent

Published immediately after upsert/update/insert operations are executed by SpannerTemplate

The mutations sent to Cloud Spanner, the entities to be saved, and optionally the properties in those entities to save.

BeforeDeleteEvent

Published immediately before delete operations are executed by SpannerTemplate

The mutations to be sent to Cloud Spanner. The target entities, keys, or entity type originally specified for the delete operation.

AfterDeleteEvent

Published immediately after delete operations are executed by SpannerTemplate

The mutations sent to Cloud Spanner. The target entities, keys, or entity type originally specified for the delete operation.

Auditing

Spring Data Cloud Spanner supports the @LastModifiedDate and @LastModifiedBy auditing annotations for properties:

@Table
public class SimpleEntity {
    @PrimaryKey
    String id;

    @LastModifiedBy
    String lastUser;

    @LastModifiedDate
    DateTime lastTouched;
}

Upon insert, update, or save, these properties will be set automatically by the framework before mutations are generated and saved to Cloud Spanner.

To take advantage of these features, add the @EnableSpannerAuditing annotation to your configuration class and provide a bean for an AuditorAware<A> implementation where the type A is the desired property type annotated by @LastModifiedBy:

@Configuration
@EnableSpannerAuditing
public class Config {

    @Bean
    public AuditorAware<String> auditorProvider() {
        return () -> Optional.of("YOUR_USERNAME_HERE");
    }
}

The AuditorAware interface contains a single method that supplies the value for fields annotated by @LastModifiedBy and can be of any type. One alternative is to use Spring Security’s User type:

class SpringSecurityAuditorAware implements AuditorAware<User> {

  public Optional<User> getCurrentAuditor() {

    return Optional.ofNullable(SecurityContextHolder.getContext())
			  .map(SecurityContext::getAuthentication)
			  .filter(Authentication::isAuthenticated)
			  .map(Authentication::getPrincipal)
			  .map(User.class::cast);
  }
}

You can also set a custom provider for properties annotated @LastModifiedDate by providing a bean for DateTimeProvider and providing the bean name to @EnableSpannerAuditing(dateTimeProviderRef = "customDateTimeProviderBean").

Multi-Instance Usage

Your application can be configured to use multiple Cloud Spanner instances or databases by providing a custom bean for DatabaseIdProvider. The default bean uses the instance ID, database name, and project ID options you configured in application.properties.

    @Bean
    public DatabaseIdProvider databaseIdProvider() {
        // return custom connection options provider
    }

The DatabaseId given by this provider is used as the target database name and instance of each operation Spring Data Cloud Spanner executes. By providing a custom implementation of this bean (for example, supplying a thread-local DatabaseId), you can direct your application to use multiple instances or databases.

Database administrative operations, such as creating tables using SpannerDatabaseAdminTemplate, will also utilize the provided DatabaseId.

If you would like to configure every aspect of each connection (such as pool size and retry settings), you can supply a bean for Supplier<DatabaseClient>.

Spring Boot Actuator Support

Cloud Spanner Health Indicator

If you are using Spring Boot Actuator, you can take advantage of the Cloud Spanner health indicator called spanner. The health indicator will verify whether Cloud Spanner is up and accessible by your application. To enable it, all you need to do is add the Spring Boot Actuator to your project.

The spanner indicator will then roll up to the overall application status visible at http://localhost:8080/actuator/health (use the management.endpoint.health.show-details property to view per-indicator details).

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
If your application already has actuator and Cloud Spanner starters, this health indicator is enabled by default. To disable the Cloud Spanner indicator, set management.health.spanner.enabled to false.

The health indicator validates the connection to Spanner by executing a query. A query to validate can be configured via spring.cloud.gcp.spanner.health.query property.

Name

Description

Required

Default value

management.health.spanner.enabled

Whether to enable the Spanner health indicator

No

true with Spring Boot Actuator, false otherwise

spring.cloud.gcp.spanner.health.query

A query to validate

No

SELECT 1

Cloud Spanner Emulator

The Cloud SDK provides a local, in-memory emulator for Cloud Spanner, which you can use to develop and test your application. As the emulator stores data only in memory, it will not persist data across runs. It is intended to help you use Cloud Spanner for local development and testing, not for production deployments.

In order to set up and start the emulator, you can follow these steps.

This command can be used to create Cloud Spanner instances:

$ gcloud spanner instances create <instance-name> --config=emulator-config --description="<description>" --nodes=1

Once the Spanner emulator is running, ensure that the following properties are set in your application.properties of your Spring application:

spring.cloud.gcp.spanner.emulator.enabled=true

Note that the default emulator hostname and port (i.e., localhost:9010) is used. If you prefer a customized value, ensure the following property is set in your application.properties of your Spring application:

spring.cloud.gcp.spanner.emulator-host=ip:port

Sample

There are two sample applications available:

  1. Sample application using Spanner Template directly

  2. Sample application using higher-level Spanner Repository capabilities

Test

Testcontainers provides a gcloud module which offers SpannerEmulatorContainer. See more at the docs