Repository files navigation

Java idiomatic client forCloud Datastore.

• Product Documentation
• Client Library Documentation

If you are using Maven withBOM, add this to your pom.xml file:

<dependencyManagement>  <dependencies>    <dependency>      <groupId>com.google.cloud</groupId>      <artifactId>libraries-bom</artifactId>      <version>26.62.0</version>      <type>pom</type>      <scope>import</scope>    </dependency>  </dependencies></dependencyManagement><dependencies>  <dependency>    <groupId>com.google.cloud</groupId>    <artifactId>google-cloud-datastore</artifactId>  </dependency>

If you are using Maven without the BOM, add this to your dependencies:

<dependency>  <groupId>com.google.cloud</groupId>  <artifactId>google-cloud-datastore</artifactId>  <version>2.31.2</version></dependency>

If you are using Gradle 5.x or later, add this to your dependencies:

implementation platform('com.google.cloud:libraries-bom:26.72.0')implementation'com.google.cloud:google-cloud-datastore'

If you are using Gradle without BOM, add this to your dependencies:

implementation'com.google.cloud:google-cloud-datastore:2.33.1'

If you are using SBT, add this to your dependencies:

libraryDependencies+="com.google.cloud"%"google-cloud-datastore"%"2.33.1"

See theAuthentication section in the base directory's README.

The client application making API calls must be grantedauthorization scopes required for the desired Cloud Datastore APIs, and the authenticated principal must have theIAM role(s) required to access GCP resources using the Cloud Datastore API calls.

You will need aGoogle Cloud Platform Console project with the Cloud DatastoreAPI enabled.You will need toenable billing to use Google Cloud Datastore.Follow these instructions to get your project set up. You will also need to set up the local development environment byinstalling the Google Cloud Command Line Interface and running the following commands in command line:gcloud auth login andgcloud config set project [YOUR PROJECT ID].

You'll need to obtain thegoogle-cloud-datastore library. See theQuickstart sectionto addgoogle-cloud-datastore as a dependency in your code.

Cloud Datastore is a fully managed, schemaless database for\nstoring non-relational data. Cloud Datastore automatically scales with\nyour users and supports ACID transactions, high availability of reads and\nwrites, strong consistency for reads and ancestor queries, and eventual\nconsistency for all other queries.

See theCloud Datastore client library docs to learn how touse this Cloud Datastore Client Library.

See the [Google Cloud Datastore docs][cloud-datastore-activation] for more details on how to activateCloud Datastore for your project.

See the [Datastore client library docs][datastore-client-lib-docs] to learn how to interactwith the Cloud Datastore using this Client Library.

To make authenticated requests to Google Cloud Datastore, you must create a service object with credentials. You can then make API calls by calling methods on the Datastore service object. The simplest way to authenticate is to useApplication Default Credentials. These credentials are automatically inferred from your environment, so you only need the following code to create your service object:

importcom.google.cloud.datastore.Datastore;importcom.google.cloud.datastore.DatastoreOptions;Datastoredatastore =DatastoreOptions.getDefaultInstance().getService();

For other authentication options, see theAuthentication page.

Objects in Datastore are known as entities. Entities are grouped by "kind" and have keys for easy access. In this code snippet, we will create a new entity representing a person and store that data by the person's email. First, add the following imports at the top of your file:

importcom.google.cloud.datastore.Entity;importcom.google.cloud.datastore.Key;importcom.google.cloud.datastore.KeyFactory;

Then add the following code to put an entity in Datastore.

KeyFactorykeyFactory =datastore.newKeyFactory().setKind("Person");Keykey =keyFactory.newKey("john.doe@gmail.com");Entityentity =Entity.newBuilder(key)    .set("name","John Doe")    .set("age",51)    .set("favorite_food","pizza")    .build();datastore.put(entity);

Later, if you want to get this entity back, add the following to your code:

EntityjohnEntity =datastore.get(key);

In addition to retrieving entities by their keys, you can perform queries to retrieve entities bythe values of their properties. A typical query includes an entity kind, filters to select entitieswith matching values, and sort orders to sequence the results.google-cloud-datastore supports twotypes of queries:StructuredQuery (that allows you to construct query elements) andGqlQuery(which operates usingGQL syntax)in string format. In this tutorial, we will use a simpleStructuredQuery.

Suppose that you've added more people to Datastore, and now you want to find all people whose favorite food is pizza. Import the following:

importcom.google.cloud.datastore.Query;importcom.google.cloud.datastore.QueryResults;importcom.google.cloud.datastore.StructuredQuery;importcom.google.cloud.datastore.StructuredQuery.PropertyFilter;

Then add the following code to your program:

Query<Entity>query =Query.newEntityQueryBuilder()    .setKind("Person")    .setFilter(PropertyFilter.eq("favorite_food","pizza"))    .build();QueryResults<Entity>results =datastore.run(query);while (results.hasNext()) {EntitycurrentEntity =results.next();System.out.println(currentEntity.getString("name") +", you're invited to a pizza party!");}

Cloud Datastore relies on indexing to run queries. Indexing is turned on by default for most types of properties. To read more about indexing, see theCloud Datastore Index Configuration documentation.

Another thing you'll probably want to do is update your data. The following snippet shows how to update a Datastore entity if it exists.

KeyFactorykeyFactory =datastore.newKeyFactory().setKind("keyKind");Keykey =keyFactory.newKey("keyName");Entityentity =datastore.get(key);if (entity !=null) {System.out.println("Updating access_time for " +entity.getString("name"));entity =Entity.newBuilder(entity)      .set("access_time",DateTime.now())      .build();datastore.update(entity);}

The complete source code can be found atUpdateEntity.java.

InAddEntitiesAndRunQuery.javawe put together all the code to store data and run queries into one program. The program assumes that you arerunning on Compute Engine or from your own desktop. To run the example on App Engine, simply movethe code from the main method to your application's servlet class and change the print statements todisplay on your webpage.

TheJava Datastore client now offers gRPC as a transport layer option with experimental support. UsinggRPC connection pooling enables distributing RPCs over multiple connections which may improve performance.

To use this feature, please upgrade your Java-datastore SDK to version v2.28.0 or a newer release. You can find the latest versionshere.

To opt-in to the gRPC transport behavior, simply add the below line of code (setTransportOptions) to your Datastore client instantiation.

Example:

DatastoreOptionsdatastoreOptions =DatastoreOptions.newBuilder()             .setProjectId("my-project")             .setDatabaseId("my-database")             .setTransportOptions(GrpcTransportOptions.newBuilder().build())             .build();

Setting the transport options explicitly toGrpcTransportOptions will signal the client to use gRPC instead of HTTP when making calls to the server.

To revert back to the existing stable behavior and transport, simply remove the transport options line or replace it withHttpTransportOptions. Please note this will require an application rebuild and restart.Example:

// will default to existing HTTP transport behaviorDatastoreOptionsdatastoreOptions =DatastoreOptions.newBuilder()    .setProjectId("my-project")    .setDatabaseId("my-database")    .build();// will also default to existing HTTP transport behaviorDatastoreOptionsdatastoreOptions =DatastoreOptions.newBuilder()              .setProjectId("my-project")              .setDatabaseId("my-database")              .setTransportOptions(HttpTransportOptions.newBuilder()              .setConnectTimeout(1000)              .build()).build();

Note: client instantiations that already usesetTransportOptions withHttpTransportOptions will continue to have the same behavior. Only transports that are explicitly set to gRPC will change.

To verify which type of TransportOptions you have successfully configured, you can use the below lines of code to compare transport options type:

// checks if using gRPC transport optionsbooleanisGRPC =datastore.getOptions().getTransportOptions()instanceofGrpcTransportOptions;// checks if using HTTP transport optionsbooleanisHTTP =datastore.getOptions().getTransportOptions()instanceofHTTPTransportOptions;

There are new gRPC specific features available to use in this update.

A connection pool, also known as a channel pool, is a cache of database connections that are shared and reused to improve connection latency and performance. With this update, now you will be able to configure the channel pool to improve application performance. This section guides you in determining the optimal connection pool size and configuring it within the Java datastore client.To customize the number of channels your client uses, you can update the channel provider in the DatastoreOptions.

The default connection pool size is right for most applications, and in most cases there's no need to change it.

However sometimes you may want to change your connection pool size due to high throughput or buffered requests. Ideally, to leave room for traffic fluctuations, a connection pool has about twice the number of connections it takes for maximum saturation. Because a connection can handle a maximum of 100 concurrent requests, between 10 and 50 outstanding requests per connection is optimal. The limit of 100 concurrent streams per gRPC connection is enforced in Google's middleware layer, and you are not able to reconfigure this number.

The following steps help you calculate the optimal number of connections in your channel pool using estimate per-client QPS and average latency numbers.

To calculate the optimal connections, gather the following information:

1. The maximum number of queries per second (QPS) per client when your application is running a typical workload.
2. The average latency (the response time for a single request) in ms.
3. Determine the number of requests that you can send serially per second by dividing 1,000 by the average latency value.
4. Divide the QPS in seconds by the number of serial requests per second.
5. Divide the result by 50 requests per channel to determine the minimum optimal channel pool size. (If your calculation is less than 2, use at least 2 channels anyway, to ensure redundancy.)
6. Divide the same result by 10 requests per channel to determine the maximum optimal channel pool size.

These steps are expressed in the following equations:

(QPS ÷ (1,000 ÷latencyms)) ÷50streams =Minimumoptimalnumberofconnections(QPS ÷ (1,000 ÷latencyms)) ÷10streams =Maximumoptimalnumberofconnections

Your application typically sends 50,000 requests per second, and the average latency is 10 ms. Divide 1,000 by 10 ms to determine that you can send 100 requests serially per second.Divide that number into 50,000 to get the parallelism needed to send 50,000 QPS: 500. Each channel can have at most 100 requests out concurrently, and your target channel utilizationis between 10 and 50 concurrent streams. Therefore, to calculate the minimum, divide 500 by 50 to get 10. To find the maximum, divide 500 by 10 to get 50. This means that your channelpool size for this example should be between 10 and 50 connections.

It is also important to monitor your traffic after making changes and adjust the number of connections in your pool if necessary.

The following code sample demonstrates how to configure the channel pool in the client libraries usingDatastoreOptions.SeeChannelPoolSettings andPerformance Best Practices for more information on channel pools and best practices for performance.

Code Example

InstantiatingGrpcChannelProviderchannelProvider =DatastoreSettings.defaultGrpcTransportProviderBuilder()              .setChannelPoolSettings(ChannelPoolSettings.builder()                              .setInitialChannelCount(MIN_VAL)                              .setMaxChannelCount(MAX_VAL)                              .build())              .build();DatastoreOptionsoptions =DatastoreOptions.newBuilder()                          .setProjectId("my-project")                          .setChannelProvider(channelProvider)                          .setTransportOptions(GrpcTransportOptions.newBuilder().build())                          .build();

This library has tools to help write tests for code that uses the Datastore.

You can test against a temporary local Datastore by following these steps:

1. Install Cloud SDK and start the emulator

To determine which host/port the emulator is running on:

$ gcloud beta emulators datastore env-init# Sample output:#   export DATASTORE_EMULATOR_HOST=localhost:8759

3. Point your client to the emulator

DatastoreOptionsoptions =DatastoreOptions.newBuilder().setProjectId(DatastoreOptions.getDefaultProjectId()).setHost(System.getenv("DATASTORE_EMULATOR_HOST")).setCredentials(NoCredentials.getInstance()).setRetrySettings(ServiceOptions.getNoRetrySettings()).build();Datastoredatastore =options.getService();

4. Run your tests

• Bookshelf - An App Engine app that manages a virtual bookshelf.
  • This app usesgoogle-cloud to interface with Cloud Datastore and Cloud Storage. It also uses Cloud SQL, another Google Cloud Platform service.
• Flexible Environment/Datastore example - A simple app that uses Cloud Datastore to list the last 10 IP addresses that visited your site.
• SparkDemo - An example of usinggoogle-cloud-datastore from within the SparkJava and App Engine Flexible Environment frameworks.
  • Read about how it works on the example'sREADME page.

Samples are in thesamples/ directory.

Sample	Source Code	Try it
Configure Connection Pool	source code
Quickstart Sample	source code
Avg Aggregation On Kind	source code
Avg Aggregation With Limit	source code
Avg Aggregation With Order By	source code
Avg Aggregation With Property Filter	source code
Count Aggregation In Transaction	source code
Count Aggregation On Kind	source code
Count Aggregation With Gql Query	source code
Count Aggregation With Limit	source code
Count Aggregation With Order By	source code
Count Aggregation With Property Filter	source code
Count Aggregation With Stale Read	source code
Multiple Aggregations In Gql Query	source code
Multiple Aggregations In Structured Query	source code
Sum Aggregation On Kind	source code
Sum Aggregation With Limit	source code
Sum Aggregation With Order By	source code
Sum Aggregation With Property Filter	source code
Indexing Consideration Query	source code
Create a union between two filters	source code
Order Fields Query	source code
Query Profile Explain	source code
Query Profile Explain Aggregation	source code
Query Profile Explain Analyze	source code
Query Profile Explain Analyze Aggregation	source code
Task List	source code

To get help, follow the instructions in theshared Troubleshooting document.

Cloud Datastore uses both gRPC and HTTP/JSON for the transport layer.

Java 8 or above is required for using this client.

Google's Java client libraries,Google Cloud Client LibrariesandGoogle Cloud API Libraries,follow theOracle Java SE support roadmap(see the Oracle Java SE Product Releases section).

In general, new feature development occurs with support for the lowest JavaLTS version covered by Oracle's Premier Support (which typically lasts 5 yearsfrom initial General Availability). If the minimum required JVM for a givenlibrary is changed, it is accompanied by asemver major release.

Java 11 and (in September 2021) Java 17 are the best choices for newdevelopment.

Google tests its client libraries with all current LTS versions covered byOracle's Extended Support (which typically lasts 8 years from initialGeneral Availability).

Google's client libraries support legacy versions of Java runtimes with longterm stable libraries that don't receive feature updates on a best efforts basisas it may not be possible to backport all patches.

Google provides updates on a best efforts basis to apps that continue to useJava 7, though apps might need to upgrade to current versions of the librarythat supports their JVM.

The latest versions and the supported Java versions are identified onthe individual GitHub repositorygithub.com/GoogleAPIs/java-SERVICENAMEand ongoogle-cloud-java.

This library followsSemantic Versioning.

Contributions to this library are always welcome and highly encouraged.

SeeCONTRIBUTING for more information how to get started.

Please note that this project is released with a Contributor Code of Conduct. By participating inthis project you agree to abide by its terms. SeeCode of Conduct for moreinformation.

Apache 2.0 - SeeLICENSE for more information.

Java Version	Status
Java 8
Java 8 OSX
Java 8 Windows
Java 11

Java is a registered trademark of Oracle and/or its affiliates.