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This page provides a description of how to load a new file into a new store within Atoti Market Risk. The techniques employed are generic examples that can be extended, adapted and repeated for any use case you encounter. In all cases, we make minimal changes to the MR application.

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Step 1 - Move data to the relevant directory

For this example, we want to bring any custom data to an appropriate folder inside of : /mr-application/src/main/resources/data within the /2023-09-26 folder and name our file Custom.csv.
AsOfDateRiskClassCustomProjected
2018-09-26Commodity-6640.633693
2018-09-26GIRR14020.37649
2018-09-26CSR Sec CTP8386.767854
2018-09-26CSR Sec non-CTP19218.3336
2018-09-26Commodity-2460.048584
2018-09-26Equity8274.302903
2018-09-26FX2150.845785
2018-09-26GIRR17537.8908
2018-09-26CSR non-Sec-25353.39868
2018-09-26DRC Sec non-CTP11319.08548
2018-09-26FX25977.18728
2018-09-26Commodity11714.89133
2018-09-26Equity-19844.11309
2018-09-26FX8906.302165
2018-09-26GIRR19617.16455
2018-09-26DRC non-Sec17134.37517

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Step 2 - Define the datastore and references

To add a new datastore, we will need to create a DatastoreConfiguratorConsumer bean that will be used by the addModifications() method inside the DatastoreConfiguratorSetup class. 
@Configuration
public class CustomDatastoreConfig {
    @Bean
    public DatastoreConfiguratorConsumer myCustomisations() {
        return Customisations::loadCustomisations;
    }

    public static void loadCustomisations(IDatastoreConfigurator configurator) {
        configurator.addStore(
                configurator.storeBuilder()
                        .withStoreName("CustomStore")
                        .withField(StoreFieldConstants.TRADE_KEY).asKeyField()
                        .withField("CustomField")
                        .withField("CustomValueField")
                        .build()
        );
        // Here we can also add a reference, if needed.
        configurator.addReference(
                configurator.referenceBuilder()
                        .fromStore(StoreConstants.TRADE_SENSITIVITIES_STORE_NAME)
                        .toStore("CustomStore")
                        .withName(DatastoreDescriptionUtils.joinName(StoreConstants.TRADE_SENSITIVITIES_STORE_NAME, "CustomStore"))
                        .withMapping(StoreFieldConstants.TRADE_KEY, StoreFieldConstants.TRADE_KEY)
                        .build()
        );
    }
}
See DatastoreHelper for more information.

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Step 3 - Create channel parameters for our data loading topic

The channel parameters for our store include store name, topic name, and file pattern. Ensure that a file pattern property is available in the application, either explicitly in a file or as a default in a Spring Boot ConfigurationProperties object. 
`mr.common.file-patterns.my-custom-file=**/*Custom*.csv`
The topic for the source can then be defined within a self-contained configuration class, by publishing a ChannelParametersHolderOperator bean: 
public class MyCustomSourceConfig {
    public static final String CUSTOM_STORE = "CustomStore";
    public static final List<String> ALIASES = List.of(DAILY_SENSI_ALIASES, ANY_TOPIC_ALIAS_NAME);

    @Bean
    @Qualifier(SP_QUALIFIER__COMMON_TOPIC_TO_STORE_AND_FILE_MAP)
    @Order(0)
    public ChannelParametersHolderOperator customSourceParameters(CustomFilePatternProperties filePatterns) {
        return patterns -> patterns.addTopic(CUSTOM_STORE, CUSTOM_STORE, filePatterns.getCustomFilePattern(), ALIASES);
    }
}
For more extensive customization, please refer to Configuring sources using Spring Beans.

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Step 4 - Include your custom configuration class in your application

You can include your new configuration class using the usual mechanisms: Spring auto-configuration or component scanning, explicit imports. If you want to import it into the standard Atoti Market Risk application, navigate to the MarketRiskConfig class (mr-application/src/main/java/com/activeviam/mr/application/main/MarketRiskConfig.java) and add the class to the @Import annotation: 
@Configuration
@Import(value = {
//...
        MyCustomSourceConfig.class
//...
})
public class MarketRiskConfig {
    //...
}

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When using DirectQuery

When using DirectQuery, we must perform Step 2 and configure our datastore correctly. Then we have to modify our remote database to include the new Table/Fields. When doing so, we must ensure we follow the naming convention of our Name Mapper. Our database only needs to contain the new fields and/or stores. When the application starts, the Datastore description is converted into a database description. The remote database needs to contain the modifications before we start the application.

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Adding a Field with DirectQuery

When adding a new field, we must add it to the datastore description as outlined in step 2 and also ensure the field exists in our database in the correct table. Then when the application starts, the datastore description (containing the custom field) will be converted into a DirectQuery database description and the field can be used for Hierarchies or treated the same as other DirectQuery fields.
When using custom fields with DirectQuery it is important to remember that datastore queries and getByKey queries are not recommended due to the performance overhead.

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Adding a new Table with DirectQuery

Stores that are part of the datastore star schema are automatically added as tables used with DirectQuery. If the remote table needs to be cached in memory, see paragraph [Registering the Table to Cache](/dev/dev-direct-query/caching-remote-table.html#Registering the Table to Cache)
The DirectQuery and in-memory Atoti servers must be configured identically. There must not be any hierarchies in the DirectQuery data node that do not exist in the in-memory one.

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Suggested Further Reading