.readme-partials.yaml

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  #### Calling Cloud Spanner
  Here is a code snippet showing a simple usage example. Add the following imports
  at the top of your file:

  ```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;

  ```

  Then, to make a query to Spanner, use the following code:
  ```java
  // Instantiates a client
  SpannerOptions options = SpannerOptions.newBuilder().build();
  Spanner spanner = options.getService();
  String instance = "my-instance";
  String database = "my-database";
  try {
    // Creates a database client
    DatabaseClient dbClient = spanner.getDatabaseClient(
      DatabaseId.of(options.getProjectId(), instance, database));
    // Queries the database
    try (ResultSet resultSet = dbClient.singleUse().executeQuery(Statement.of("SELECT 1"))) {
      // Prints the results
      while (resultSet.next()) {
        System.out.printf("%d\n", resultSet.getLong(0));
      }
    }
  } finally {
    // Closes the client which will free up the resources used
    spanner.close();
  }
  ```

  #### Complete source code

  In [DatabaseSelect.java](https://github.com/googleapis/google-cloud-java/tree/master/google-cloud-examples/src/main/java/com/google/cloud/examples/spanner/snippets/DatabaseSelect.java) we put together all the code shown above in a single program.

  ## Session Pool

  The Cloud Spanner client maintains a session pool, as sessions are expensive to create and are
  intended to be long-lived. The client automatically takes a session from the pool and uses this
  executing queries and transactions.
  See [Session Pool and Channel Pool Configuration](session-and-channel-pool-configuration.md)
  for in-depth background information about sessions and gRPC channels and how these are handled in
  the Cloud Spanner Java client.

  ## Metrics

  Cloud Spanner client supports [client-side metrics](https://cloud.google.com/spanner/docs/view-manage-client-side-metrics) that you can use along with server-side metrics to optimize performance and troubleshoot performance issues if they occur.
  
  Client-side metrics are measured from the time a request leaves your application to the time your application receives the response. 
  In contrast, server-side metrics are measured from the time Spanner receives a request until the last byte of data is sent to the client.
  
  These metrics are enabled by default. You can opt out of using client-side metrics with the following code:
  
  ```
  SpannerOptions options = SpannerOptions.newBuilder()
    .setBuiltInMetricsEnabled(false)
    .build();
  ```
  
  You can also disable these metrics by setting `SPANNER_DISABLE_BUILTIN_METRICS` to `true`.
  
  > Note: Client-side metrics needs `monitoring.timeSeries.create` IAM permission to export metrics data. Ask your administrator to grant your service account the [Monitoring Metric Writer](https://cloud.google.com/iam/docs/roles-permissions/monitoring#monitoring.metricWriter) (roles/monitoring.metricWriter) IAM role on the project.

  ## Traces
  Cloud Spanner client supports OpenTelemetry Traces, which gives insight into the client internals and aids in debugging/troubleshooting production issues. 

  By default, the functionality is disabled. You need to add OpenTelemetry dependencies, enable OpenTelemetry traces and must configure the OpenTelemetry with appropriate exporters at the startup of your application.

  See [Configure client-side tracing](https://cloud.google.com/spanner/docs/set-up-tracing#configure-client-side-tracing) for more details on configuring traces.
  
  #### OpenTelemetry Dependencies

  If you are using Maven, add this to your pom.xml file
  ```xml
  <dependency>
        <groupId>io.opentelemetry</groupId>
        <artifactId>opentelemetry-sdk</artifactId>
        <version>{opentelemetry.version}</version>
  </dependency>
  <dependency>
        <groupId>io.opentelemetry</groupId>
        <artifactId>opentelemetry-sdk-trace</artifactId>
        <version>{opentelemetry.version}</version>
  </dependency>
  <dependency>
      <groupId>io.opentelemetry</groupId>
      <artifactId>opentelemetry-exporter-otlp</artifactId>
      <version>{opentelemetry.version}</version>
  </dependency>
  ```
  If you are using Gradle, add this to your dependencies
  ```Groovy
  compile 'io.opentelemetry:opentelemetry-sdk:{opentelemetry.version}'
  compile 'io.opentelemetry:opentelemetry-sdk-trace:{opentelemetry.version}'
  compile 'io.opentelemetry:opentelemetry-exporter-oltp:{opentelemetry.version}'
  ```
  #### OpenTelemetry Configuration

  > Note: Enabling OpenTelemetry traces will automatically disable OpenCensus traces.

  ```java
  // Enable OpenTelemetry traces
  SpannerOptions.enableOpenTelemetryTraces();

  // Create a new tracer provider
  SdkTracerProvider sdkTracerProvider = SdkTracerProvider.builder()
        // Use Otlp exporter or any other exporter of your choice.
        .addSpanProcessor(SimpleSpanProcessor.builder(OtlpGrpcSpanExporter
            .builder().build()).build())
            .build();


  OpenTelemetry openTelemetry = OpenTelemetrySdk.builder()
          .setTracerProvider(sdkTracerProvider)
          .build()

  SpannerOptions options = SpannerOptions.newBuilder()
  // Inject OpenTelemetry object via Spanner Options or register OpenTelmetry object as Global
    .setOpenTelemetry(openTelemetry)
    .build();

  Spanner spanner = options.getService();
  ```
  
  #### OpenTelemetry SQL Statement Tracing
  The OpenTelemetry traces that are generated by the Java client include any request and transaction
  tags that have been set. The traces can also include the SQL statements that are executed and the
  name of the thread that executes the statement. Enable this with the `enableExtendedTracing`
  option:

  ```
  SpannerOptions options = SpannerOptions.newBuilder()
    .setOpenTelemetry(openTelemetry)
    .setEnableExtendedTracing(true)
    .build();
  ```

  This option can also be enabled by setting the environment variable
  `SPANNER_ENABLE_EXTENDED_TRACING=true`.

  #### OpenTelemetry API Tracing
  You can enable tracing of each API call that the Spanner client executes with the `enableApiTracing`
  option. These traces also include any retry attempts for an API call:
    
  ```
  SpannerOptions options = SpannerOptions.newBuilder()
  .setOpenTelemetry(openTelemetry)
  .setEnableApiTracing(true)
  .build();
  ```
    
  This option can also be enabled by setting the environment variable
  `SPANNER_ENABLE_API_TRACING=true`.

  > Note: The attribute keys that are used for additional information about retry attempts and the number of requests might change in a future release.
  
  #### End-to-end Tracing 
              
  In addition to client-side tracing, you can opt in for [end-to-end tracing](https://cloud.google.com/spanner/docs/tracing-overview#end-to-end-side-tracing). End-to-end tracing helps you understand and debug latency issues that are specific to Spanner such as the following:
  * Identify whether the latency is due to network latency between your application and Spanner, or if the latency is occurring within Spanner.
  * Identify the Google Cloud regions that your application requests are being routed through and if there is a cross-region request. A cross-region request usually means higher latencies between your application and Spanner.
  
  ```
  SpannerOptions options = SpannerOptions.newBuilder()
  .setOpenTelemetry(openTelemetry)
  .setEnableEndToEndTracing(true)
  .build();
  ```
  
  Refer to [Configure end-to-end tracing](https://cloud.google.com/spanner/docs/set-up-tracing#configure-end-to-end-tracing) to configure end-to-end tracing and to understand its attributes.
  
  > Note: End-to-end traces can only be exported to [Cloud Trace](https://cloud.google.com/trace/docs).
  
  
  ## Instrument with OpenCensus

  > Note: OpenCensus project is deprecated. See [Sunsetting OpenCensus](https://opentelemetry.io/blog/2023/sunsetting-opencensus/).
  We recommend migrating to OpenTelemetry, the successor project.
  
  ## Migrate from OpenCensus to OpenTelemetry

  > Using the [OpenTelemetry OpenCensus Bridge](https://mvnrepository.com/artifact/io.opentelemetry/opentelemetry-opencensus-shim), you can immediately begin exporting your metrics and traces with OpenTelemetry.

  #### Disable OpenCensus metrics
  Disable OpenCensus metrics for Spanner by including the following code if you still possess OpenCensus dependencies and exporter.

  ```java
  SpannerOptions.disableOpenCensusMetrics();
  ```

  #### Disable OpenCensus traces
  Enabling OpenTelemetry traces for Spanner will automatically disable OpenCensus traces.

  ```java
  SpannerOptions.enableOpenTelemetryTraces();
  ```

  #### Remove OpenCensus Dependencies and Code
  Remove any OpenCensus-related code and dependencies from your codebase if all your dependencies are ready to move to OpenTelemetry.

  * Remove the OpenCensus Exporters which were configured [here](#configure-the-opencensus-exporter)
  * Remove SpannerRPCViews reference which were configured [here](#enable-rpc-views)
  * Remove the OpenCensus dependencies which were added [here](#opencensus-dependencies)

  #### Update your Dashboards and Alerts

  Update your dashboards and alerts to reflect below changes
  * **Metrics name** : `cloud.google.com/java` prefix has been removed from OpenTelemery metrics and instead has been added as Instrumenation Scope.
  * **Metrics namespace** : OpenTelmetry exporters uses `workload.googleapis.com` namespace opposed to `custom.googleapis.com` with OpenCensus.