{"attributes":{"description":"","kibanaSavedObjectMeta":{"searchSourceJSON":"{\"query\":{\"query\":\"\",\"language\":\"kuery\"},\"filter\":[],\"indexRefName\":\"kibanaSavedObjectMeta.searchS...

	}

	p2 := Product{Code: "update_callback", Price: 100}
	DB.Save(&p2)

	p2.Code = "dont_update"
	if DB.Save(&p2).Error == nil {
		t.Fatalf("An error from before update callbacks happened when update with invalid value")
	}

	if DB.Where("code = ?", "update_callback").First(&Product{}).Error != nil {
		t.Fatalf("Record Should not be updated due to errors happened in before update callback")
	}

                    }
                } else {
                    update = updateCheckManager.isUpdateRequired(metadata, repository, file);
                }

                if (update) {
                    getLogger().info(metadata.getKey() + ": checking for updates from " + repository.getId());
                    try {

  // for updates. During a rolling update, all pods from ordinal Replicas-1 to
  // Partition are updated. All pods from ordinal Partition-1 to 0 remain untouched.
  // This is helpful in being able to do a canary based deployment. The default value is 0.
  // +optional
  optional int32 partition = 1;

  // The maximum number of pods that can be unavailable during the update.

          <identifier>true</identifier>
        </field>
        <field>
          <name>updated</name>
          <version>1.1.0+</version>
          <type>String</type>
          <description>The timestamp when this version information was last updated. The timestamp is expressed using UTC in the format yyyyMMddHHmmss.</description>
          <identifier>true</identifier>
        </field>

  worker_server.release();

  // Update the server def with a new set of names (worker instead of
  // localhost).
  tensorflow::ServerDef updated_server_def = GetServerDef("worker", 2);
  serialized = updated_server_def.SerializeAsString();

  updated_server_def.set_task_index(1);
  tensorflow::Status s = tensorflow::GrpcServer::Create(
      updated_server_def, tensorflow::Env::Default(), &worker_server);

 *  **Request cancellation fixes.** This update fixes a bug where synchronous
    requests couldn't be canceled by tag. This update avoids crashing when
    `onResponse()` throws an `IOException`. That failure will now be logged
    instead of notifying the thread's uncaught exception handler. We've added a
    new API, `Call.isCanceled()` to check if a call has been canceled.

 *  New: Update `MultipartBuilder` to support content length.

  /**
   * Computes the function of current and new value. Subclasses should open-code this update
   * function for most uses, but the virtualized form is needed within retryUpdate.
   *
   * @param currentValue the current value (of either base or a cell)
   * @param newValue the argument from a user update call
   * @return result of the update function
   */
  abstract long fn(long currentValue, long newValue);

  /**

  /**
   * Computes the function of current and new value. Subclasses should open-code this update
   * function for most uses, but the virtualized form is needed within retryUpdate.
   *
   * @param currentValue the current value (of either base or a cell)
   * @param newValue the argument from a user update call
   * @return result of the update function
   */
  abstract long fn(long currentValue, long newValue);

  /**

	exit 1
fi

## Check if latest updated rules get replicated to all sites post re-enable of ILM expiry rules replication
sleep 30s
count1=$(./mc ilm rule list sitea/bucket --json | jq '.config.Rules[0].Expiration.Days')
count2=$(./mc ilm rule list siteb/bucket --json | jq '.config.Rules[0].Expiration.Days')
if [ $count1 -ne 888 ]; then
	echo "BUG: Latest expiration days not updated on 'sitea'"
	exit 1
fi