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Data Type Explorer

Introduction

The Data Type Explorer allows you to view and manage the Data Types you’ve created to persist data on the platform for your game using the Game Data Service.

Important! If you're working on a new game that was created after the new Game Data Service was launched in January 2018, you won't be able to create new Mongo Runtime collections in the Collections panel and you'll get an error if you try to do this or if you try to create a Runtime collection using Cloud Code. If you're working on a game that you started to develop before the Game Data Service was launched or if you've copied a Snapshot of a game you started to develop before the Game Data Service was launched into a new game, you'll be able to create Mongo Runtime collections. For details on how to work with Mongo collections, see NoSQL Explorer.

From the Data Types panel, you can quickly access your custom Data Types. When you open a Data Type, several actions are available to interact with its data - see the following section for details of how to work with these actions.

This topic introduces the Game Data Service and explains how to work with the Data Types you create to manage the custom data you want to persist against the platform for your game:


FAQs? You can review Frequently Asked Questions about working with the Data Type Explorer.

Why Game Data Service?

The Game Data Service allows you to manage the custom data that your game persists on the GameSparks platform in a controlled and streamlined way. You can:

When you follow these steps to use the Game Data Service, you'll be adopting a carefully considered and well-designed approach to data persistence for your game. In return for this data persistence set up work, you'll get the benefits of a data service that's been designed with your game’s performance under high player loads very much in mind, a service that ensures any frequent data retrieval operations, such as rich-querying against your game’s custom data, is done optimally and efficiently.

Using Game Data Service - Guidelines and Best Practices? For advice on how best to use the Game Data Service for persisting and managing the custom data structures in your game, we strongly recommend that you review the section on Custom Data>Using the Game Data Service in the Managing Data Persistence in the GameSparks Platform tutorial.

Opening Data Types

1. On the main navigation menu, select Data Explorer. The Data Types panel lists the custom Data Types you've created for persisting data on the platform.

2. If you want to set up indexed fields for your Data Types, click Configure Data Indexes to go directly to the Configurator>Game Data page:

3. Select a Data Type to open it:

Using Data Type Actions

When you open a Data Type, you can use several actions to interact with the data:

Warning! There is a limit of 500 Data Types per user. Any attempt to exceed this limit will fail.

Inserting Data

You can use the Insert option to insert a document into a Data Type:

1. In the Data Explorer, open the Data Type into which you want to insert data.

2. Select Insert. The tab adjusts.

3. Enter the details for the insert action:

Important! If you insert a document using the same ID as an existing document, then the Insert action overwrites the existing.

4. Click the Insert button. The tab adjusts and when the document has been inserted, the details are shown at the bottom of the tab:

5. We can repeat the Insert action to add two further Player documents. In each case, we’ll give these players the same CITY location as PlayerOne:

In the next section, we use the Find action against our custom Player Data Type.

Warning! Any document you insert must be less than 400Kb in size.

Finding Data

You can find and view individual documents by ID.

Note: You cannot retrieve all documents in a Data Type at once, but you can retrieve multiple documents by querying using indexed fields. See the following section.

To find a document by ID:

1. In the Data Explorer, open the Data Type whose documents you want to find and manage:

2. Enter the ID of the document you want to retrieve.

3. Click the Find button. The tab adjusts and the document is loaded:

4. Click to Delete the document if you want to remove it from your Data Type.

5. If you want to change the content of the document, click Edit. The Edit Document dialog appears.

6. Make the editing changes you want to the document:

7. If you want to perform a version check when you save your changes, select Use version check. If you select this, when you attempt to save your changes to the document, the save will fail if the document has been modified elsewhere since you loaded it using Find.

8. Click to Save your editing changes. The Edit Document dialog closes and the document has been updated on the Data Type tab:

Querying Data

If you have set up indexed fields for a Data Type, you can retrieve data from it by building a query using those indexed fields and submitting that query in the Data Explorer:

At the outset, it's important to note:

Using Query Builder

First, we’ll use the Query Builder to build a query using the indexed fields we've added to the Player Data Type:

1. In the Data Explorer, open the Data Type you want to query.

2. Select the Query action.

3. You can use the Builder to create the query you want to perform:

4. You can define a sorting for the results returned by the query using any of the indexed fields you’ve added to the Data Type:

5. Click the Query button:

Note: A Query returns up to a maximum of 100 results that satisfy the query.

6. Click to expand and view the details any of the documents returned by your query:

You can use two options here to manage your custom data:

7. You can refine your Query to get just the results you want:

Using Query JSON

As well as using the Builder to create a query, you can view and edit your query JSON directly:

Query Rules Using "in"

You can build query rules using the "in" operator by entering a comma-separated list of values for a field you are querying against. The query results will contain only those documents where the queried field value matches one of the values in the comma-separated list.

However, care is required when you use an "in" rule to build a query. Suppose we had inserted data into our PlayerOne and PlayerThree documents for the CLASS indexed fields of the Player Data Type - say Knight and Warrior respectively. We could then query the Data Type using this rule to return both documents:

But you must ensure that the comma-separated list of values you use for this type of query rule does not contain any white space characters. In this example, if we insert a white space before the second value: " Knight", the query will fail to return the PlayerOne document that satisfies "Knight":

Querying Arrays

When you build a query that will operate on a data array in a Data Type, then the query is performed against the last value in the array. Here's an example:

1. Open a Data Type and insert a data document that contains an array. We'll open TEAMS and insert TeamOne data:

2. For the purpose of the example, we'll add two more documents:

3. Now, before we try to query this Data Type, you can copy the JSON you've used to insert data for one of the TEAMS documents and go to the Game Data page and open the TEAMS Game Data Indexes.

4. Under Indexed Fields, click Index Advisor and paste in the JSON copied from the Insert. The JSON is scanned and candidate indexed fields for the Data Type are listed.

5. For this example, click to add the teamname and scores paths and give each indexed field a Short Code:

6. Click to Save and Close the Data Type indexing.

7. Go back to Data Explorer and build a simple query with a rule that uses the TEAMSCORE indexed field:

Building Complex Queries

You can use the Query Builder to build complex queries by using the Add Rule and Add Group options. However, you can only add two rules for each condition.

For example, suppose we develop the example from the previous section and add scores for each of our players, which is an indexed field for the Player Data Type:

If we now try to build a 3-rule condition to return only PlayerTwo and PlayerThree and submit the query, we'll get an error:

Instead, we have to add a second group and build the query in this way:

Exporting Query Results

You can export the results returned by a query against a Data Type directly to a local file:

Dropping Data Type

You can Drop a Data Type to remove all of its data. This will remove all of the documents in the Data Type. The Drop action can be useful in Preview because you might be developing and testing your game and want to clear out test data occasionally.

Important! There is no undo available for the Drop action, so you must be especially careful using in the Live stage of your game.

1. In Data Explorer, open a Data Type containing data that you want to remove.

2. Select Drop.

3. Click the red Drop button:

A warning/confirmation dialog appears:

4. Click OK to confirm the data drop. The dialog closes and a message confirms that the Data Type has been dropped:

It's important to note that:

Opening Other Data Types

You can create and open a Data Type directly from the Data Explorer. You can then:

To create, open, and query data for other Data Types:

1. Open the Data Explorer and on the Data Types panel, enter the name of the new Data Type in the Other type field:

2. Click Open. The new Data Type is created and opened in the Data Explorer.

3. Click Insert to load some data into the new Data Type:

4. Insert any other data documents you want for your Data Type:

5. If you refresh, the new TOURNAMENTS is added to the Data Types panel:

6. Go to Configurator>Game Data.

7. Add indexed fields for the new TOURNAMENTS Data Type using the same Short Code:

8. Click to Save and Close the new Data Type Index.

9. Return to the Data Explorer and re-open the TOURNAMENTS Data Type. Because we've added Data Type Indexing, the Query action is now available and we can query the data using any of the indexing fields:

Filtering Data Types

As you add Data Types to your game, the Data Types panel will automatically paginate the list into manageable pages of 10:

You can use the Filter field to quickly reduce the list and find the specific Data Type you want to work with:

Data Types in Preview and Live

When you have set up your Data Type Indexes in Preview for your game’s data persistence requirements against the platform, you can take a game configuration Snapshot. By publishing the game Snapshot, you make the Data Type Indexing available for the game’s Live stage. It’s important to note when publishing a game Snapshot to Live:

Re-Indexing and Publishing a Game

The updating of Data Type Indexes has a knock-on effect for the game publication process:

In the following example, five new Data Type Indexes have been added since the game was last published to Live. When the new game Snapshot is published from the Game Overview page, a status progress will show for the re-indexing operation:

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2020-03-03T11:08